Any Oscillator Underlay [TTF]We are proud to release a new indicator that has been a while in the making - the Any Oscillator Underlay (AOU) !
Note: There is a lot to discuss regarding this indicator, including its intent and some of how it operates, so please be sure to read this entire description before using this indicator to help ensure you understand both the intent and some limitations with this tool.
Our intent for building this indicator was to accomplish the following:
Combine all of the oscillators that we like to use into a single indicator
Take up a bit less screen space for the underlay indicators for strategies that utilize multiple oscillators
Provide a tool for newer traders to be able to leverage multiple oscillators in a single indicator
Features:
Includes 8 separate, fully-functional indicators combined into one
Ability to easily enable/disable and configure each included indicator independently
Clearly named plots to support user customization of color and styling, as well as manual creation of alerts
Ability to customize sub-indicator title position and color
Ability to customize sub-indicator divider lines style and color
Indicators that are included in this initial release:
TSI
2x RSIs (dubbed the Twin RSI )
Stochastic RSI
Stochastic
Ultimate Oscillator
Awesome Oscillator
MACD
Outback RSI (Color-coding only)
Quick note on OB/OS:
Before we get into covering each included indicator, we first need to cover a core concept for how we're defining OB and OS levels. To help illustrate this, we will use the TSI as an example.
The TSI by default has a mid-point of 0 and a range of -100 to 100. As a result, a common practice is to place lines on the -30 and +30 levels to represent OS and OB zones, respectively. Most people tend to view these levels as distance from the edges/outer bounds or as absolute levels, but we feel a more way to frame the OB/OS concept is to instead define it as distance ("offset") from the mid-line. In keeping with the -30 and +30 levels in our example, the offset in this case would be "30".
Taking this a step further, let's say we decided we wanted an offset of 25. Since the mid-point is 0, we'd then calculate the OB level as 0 + 25 (+25), and the OS level as 0 - 25 (-25).
Now that we've covered the concept of how we approach defining OB and OS levels (based on offset/distance from the mid-line), and since we did apply some transformations, rescaling, and/or repositioning to all of the indicators noted above, we are going to discuss each component indicator to detail both how it was modified from the original to fit the stacked-indicator model, as well as the various major components that the indicator contains.
TSI:
This indicator contains the following major elements:
TSI and TSI Signal Line
Color-coded fill for the TSI/TSI Signal lines
Moving Average for the TSI
TSI Histogram
Mid-line and OB/OS lines
Default TSI fill color coding:
Green : TSI is above the signal line
Red : TSI is below the signal line
Note: The TSI traditionally has a range of -100 to +100 with a mid-point of 0 (range of 200). To fit into our stacking model, we first shrunk the range to 100 (-50 to +50 - cut it in half), then repositioned it to have a mid-point of 50. Since this is the "bottom" of our indicator-stack, no additional repositioning is necessary.
Twin RSI:
This indicator contains the following major elements:
Fast RSI (useful if you want to leverage 2x RSIs as it makes it easier to see the overlaps and crosses - can be disabled if desired)
Slow RSI (primary RSI)
Color-coded fill for the Fast/Slow RSI lines (if Fast RSI is enabled and configured)
Moving Average for the Slow RSI
Mid-line and OB/OS lines
Default Twin RSI fill color coding:
Dark Red : Fast RSI below Slow RSI and Slow RSI below Slow RSI MA
Light Red : Fast RSI below Slow RSI and Slow RSI above Slow RSI MA
Dark Green : Fast RSI above Slow RSI and Slow RSI below Slow RSI MA
Light Green : Fast RSI above Slow RSI and Slow RSI above Slow RSI MA
Note: The RSI naturally has a range of 0 to 100 with a mid-point of 50, so no rescaling or transformation is done on this indicator. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Stochastic and Stochastic RSI:
These indicators contain the following major elements:
Configurable lengths for the RSI (for the Stochastic RSI only), K, and D values
Configurable base price source
Mid-line and OB/OS lines
Note: The Stochastic and Stochastic RSI both have a normal range of 0 to 100 with a mid-point of 50, so no rescaling or transformations are done on either of these indicators. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Ultimate Oscillator (UO):
This indicator contains the following major elements:
Configurable lengths for the Fast, Middle, and Slow BP/TR components
Mid-line and OB/OS lines
Moving Average for the UO
Color-coded fill for the UO/UO MA lines (if UO MA is enabled and configured)
Default UO fill color coding:
Green : UO is above the moving average line
Red : UO is below the moving average line
Note: The UO naturally has a range of 0 to 100 with a mid-point of 50, so no rescaling or transformation is done on this indicator. The only manipulation done is to properly position it in the indicator-stack based on which other indicators are also enabled.
Awesome Oscillator (AO):
This indicator contains the following major elements:
Configurable lengths for the Fast and Slow moving averages used in the AO calculation
Configurable price source for the moving averages used in the AO calculation
Mid-line
Option to display the AO as a line or pseudo-histogram
Moving Average for the AO
Color-coded fill for the AO/AO MA lines (if AO MA is enabled and configured)
Default AO fill color coding (Note: Fill was disabled in the image above to improve clarity):
Green : AO is above the moving average line
Red : AO is below the moving average line
Note: The AO is technically has an infinite (unbound) range - -∞ to ∞ - and the effective range is bound to the underlying security price (e.g. BTC will have a wider range than SP500, and SP500 will have a wider range than EUR/USD). We employed some special techniques to rescale this indicator into our desired range of 100 (-50 to 50), and then repositioned it to have a midpoint of 50 (range of 0 to 100) to meet the constraints of our stacking model. We then do one final repositioning to place it in the correct position the indicator-stack based on which other indicators are also enabled. For more details on how we accomplished this, read our section "Binding Infinity" below.
MACD:
This indicator contains the following major elements:
Configurable lengths for the Fast and Slow moving averages used in the MACD calculation
Configurable price source for the moving averages used in the MACD calculation
Configurable length and calculation method for the MACD Signal Line calculation
Mid-line
Note: Like the AO, the MACD also technically has an infinite (unbound) range. We employed the same principles here as we did with the AO to rescale and reposition this indicator as well. For more details on how we accomplished this, read our section "Binding Infinity" below.
Outback RSI (ORSI):
This is a stripped-down version of the Outback RSI indicator (linked above) that only includes the color-coding background (suffice it to say that it was not technically feasible to attempt to rescale the other components in a way that could consistently be clearly seen on-chart). As this component is a bit of a niche/special-purpose sub-indicator, it is disabled by default, and we suggest it remain disabled unless you have some pre-defined strategy that leverages the color-coding element of the Outback RSI that you wish to use.
Binding Infinity - How We Incorporated the AO and MACD (Warning - Math Talk Ahead!)
Note: This applies only to the AO and MACD at time of original publication. If any other indicators are added in the future that also fall into the category of "binding an infinite-range oscillator", we will make that clear in the release notes when that new addition is published.
To help set the stage for this discussion, it's important to note that the broader challenge of "equalizing inputs" is nothing new. In fact, it's a key element in many of the most popular fields of data science, such as AI and Machine Learning. They need to take a diverse set of inputs with a wide variety of ranges and seemingly-random inputs (referred to as "features"), and build a mathematical or computational model in order to work. But, when the raw inputs can vary significantly from one another, there is an inherent need to do some pre-processing to those inputs so that one doesn't overwhelm another simply due to the difference in raw values between them. This is where feature scaling comes into play.
With this in mind, we implemented 2 of the most common methods of Feature Scaling - Min-Max Normalization (which we call "Normalization" in our settings), and Z-Score Normalization (which we call "Standardization" in our settings). Let's take a look at each of those methods as they have been implemented in this script.
Min-Max Normalization (Normalization)
This is one of the most common - and most basic - methods of feature scaling. The basic formula is: y = (x - min)/(max - min) - where x is the current data sample, min is the lowest value in the dataset, and max is the highest value in the dataset. In this transformation, the max would evaluate to 1, and the min would evaluate to 0, and any value in between the min and the max would evaluate somewhere between 0 and 1.
The key benefits of this method are:
It can be used to transform datasets of any range into a new dataset with a consistent and known range (0 to 1).
It has no dependency on the "shape" of the raw input dataset (i.e. does not assume the input dataset can be approximated to a normal distribution).
But there are a couple of "gotchas" with this technique...
First, it assumes the input dataset is complete, or an accurate representation of the population via random sampling. While in most situations this is a valid assumption, in trading indicators we don't really have that luxury as we're often limited in what sample data we can access (i.e. number of historical bars available).
Second, this method is highly sensitive to outliers. Since the crux of this transformation is based on the max-min to define the initial range, a single significant outlier can result in skewing the post-transformation dataset (i.e. major price movement as a reaction to a significant news event).
You can potentially mitigate those 2 "gotchas" by using a mechanism or technique to find and discard outliers (e.g. calculate the mean and standard deviation of the input dataset and discard any raw values more than 5 standard deviations from the mean), but if your most recent datapoint is an "outlier" as defined by that algorithm, processing it using the "scrubbed" dataset would result in that new datapoint being outside the intended range of 0 to 1 (e.g. if the new datapoint is greater than the "scrubbed" max, it's post-transformation value would be greater than 1). Even though this is a bit of an edge-case scenario, it is still sure to happen in live markets processing live data, so it's not an ideal solution in our opinion (which is why we chose not to attempt to discard outliers in this manner).
Z-Score Normalization (Standardization)
This method of rescaling is a bit more complex than the Min-Max Normalization method noted above, but it is also a widely used process. The basic formula is: y = (x – μ) / σ - where x is the current data sample, μ is the mean (average) of the input dataset, and σ is the standard deviation of the input dataset. While this transformation still results in a technically-infinite possible range, the output of this transformation has a 2 very significant properties - the mean (average) of the output dataset has a mean (μ) of 0 and a standard deviation (σ) of 1.
The key benefits of this method are:
As it's based on normalizing the mean and standard deviation of the input dataset instead of a linear range conversion, it is far less susceptible to outliers significantly affecting the result (and in fact has the effect of "squishing" outliers).
It can be used to accurately transform disparate sets of data into a similar range regardless of the original dataset's raw/actual range.
But there are a couple of "gotchas" with this technique as well...
First, it still technically does not do any form of range-binding, so it is still technically unbounded (range -∞ to ∞ with a mid-point of 0).
Second, it implicitly assumes that the raw input dataset to be transformed is normally distributed, which won't always be the case in financial markets.
The first "gotcha" is a bit of an annoyance, but isn't a huge issue as we can apply principles of normal distribution to conceptually limit the range by defining a fixed number of standard deviations from the mean. While this doesn't totally solve the "infinite range" problem (a strong enough sudden move can still break out of our "conceptual range" boundaries), the amount of movement needed to achieve that kind of impact will generally be pretty rare.
The bigger challenge is how to deal with the assumption of the input dataset being normally distributed. While most financial markets (and indicators) do tend towards a normal distribution, they are almost never going to match that distribution exactly. So let's dig a bit deeper into distributions are defined and how things like trending markets can affect them.
Skew (skewness): This is a measure of asymmetry of the bell curve, or put another way, how and in what way the bell curve is disfigured when comparing the 2 halves. The easiest way to visualize this is to draw an imaginary vertical line through the apex of the bell curve, then fold the curve in half along that line. If both halves are exactly the same, the skew is 0 (no skew/perfectly symmetrical) - which is what a normal distribution has (skew = 0). Most financial markets tend to have short, medium, and long-term trends, and these trends will cause the distribution curve to skew in one direction or another. Bullish markets tend to skew to the right (positive), and bearish markets to the left (negative).
Kurtosis: This is a measure of the "tail size" of the bell curve. Another way to state this could be how "flat" or "steep" the bell-shape is. If the bell is steep with a strong drop from the apex (like a steep cliff), it has low kurtosis. If the bell has a shallow, more sweeping drop from the apex (like a tall hill), is has high kurtosis. Translating this to financial markets, kurtosis is generally a metric of volatility as the bell shape is largely defined by the strength and frequency of outliers. This is effectively a measure of volatility - volatile markets tend to have a high level of kurtosis (>3), and stable/consolidating markets tend to have a low level of kurtosis (<3). A normal distribution (our reference), has a kurtosis value of 3.
So to try and bring all that back together, here's a quick recap of the Standardization rescaling method:
The Standardization method has an assumption of a normal distribution of input data by using the mean (average) and standard deviation to handle the transformation
Most financial markets do NOT have a normal distribution (as discussed above), and will have varying degrees of skew and kurtosis
Q: Why are we still favoring the Standardization method over the Normalization method, and how are we accounting for the innate skew and/or kurtosis inherent in most financial markets?
A: Well, since we're only trying to rescale oscillators that by-definition have a midpoint of 0, kurtosis isn't a major concern beyond the affect it has on the post-transformation scaling (specifically, the number of standard deviations from the mean we need to include in our "artificially-bound" range definition).
Q: So that answers the question about kurtosis, but what about skew?
A: So - for skew, the answer is in the formula - specifically the mean (average) element. The standard mean calculation assumes a complete dataset and therefore uses a standard (i.e. simple) average, but we're limited by the data history available to us. So we adapted the transformation formula to leverage a moving average that included a weighting element to it so that it favored recent datapoints more heavily than older ones. By making the average component more adaptive, we gained the effect of reducing the skew element by having the average itself be more responsive to recent movements, which significantly reduces the effect historical outliers have on the dataset as a whole. While this is certainly not a perfect solution, we've found that it serves the purpose of rescaling the MACD and AO to a far more well-defined range while still preserving the oscillator behavior and mid-line exceptionally well.
The most difficult parts to compensate for are periods where markets have low volatility for an extended period of time - to the point where the oscillators are hovering around the 0/midline (in the case of the AO), or when the oscillator and signal lines converge and remain close to each other (in the case of the MACD). It's during these periods where even our best attempt at ensuring accurate mirrored-behavior when compared to the original can still occasionally lead or lag by a candle.
Note: If this is a make-or-break situation for you or your strategy, then we recommend you do not use any of the included indicators that leverage this kind of bounding technique (the AO and MACD at time of publication) and instead use the Trandingview built-in versions!
We know this is a lot to read and digest, so please take your time and feel free to ask questions - we will do our best to answer! And as always, constructive feedback is always welcome!
Cerca negli script per "富时中国50期指"
On Balance Volume Scaled - OBV ScaledThe main idea of this oscillator is to place the OBV oscillator and its oscillation around the range of 0 and around -50 to +50 and for this scaling of the "On Balance Volume" oscillator, I have used Min-max normalization.
Since this oscillator does not have a specific minimum and maximum, just setting the maximum and minimum does not seem the best thing to do. As in this case, we will constantly observe sudden changes and we will have problems such as volatility. On the one hand, we will constantly deal with sudden changes and problems such as volatility. Also on the other hand, the continuous collisions of the high/low(+50 & -50) and index and returning from that is another thing that we are going to deal with.
Therefore, to solve these problems and create more flexible maximum and minimum ranges, another similar method has been used. Choosing the maximum of our normalization to the size of the moving average of 100 candles of the index maximum and choosing the minimum of normalization to the size of the moving average of 100 candles of the minimums of the OBV index, and then normalizing the OBV index with the Min-max method with those ranges, is the recommended method ,which has been used to eliminate problems. In this case, we will not have any problem hitting 50 and returning or hitting -50 and returning. Also, our scaled OBV index will have the ability to touch and cross 50 and -50 and can fluctuate without problems.
RSI - colour fillThis script showcases the new (overload) feature regarding the fill() function! 🥳
2 plots could be filled before, but with just 1 colour per bar, now the colour can be a gradient type.
In this example we have 2 plots
- rsiPlot , which plots the rsi value
- centerPlot, which plots the value 50 ('centre line')
Explanation of colour fill in the zone 50-80
Default when rsi > 50
- a bottom value is set at 50 (associated with colour aqua)
- and a top value is set at 80 (associated with colour red)
This zone (bottom -> top value) is filled with a gradient colour (50 - aqua -> 80 - red)
When rsi is towards 80, you see a red coloured zone at the rsi value,
while when rsi is around 50, you'll only see the colour aqua
The same principle is applied in the zone 20-50 when rsi < 50
Cheers!
RSI band with Signal alert//th/en
//th
สวัสดีครับท่านสมาชิก
ก่อนอื่นต้องขอเกริ่นก่อนเลยว่า Indicator ตัวนี้ถูกสร้างขึ้นมาบนพื้นฐานของ RSI จริง เพียงแต่ใช้ค่า EMA27 ในการสร้าง เนื่องจากผมยังไม่สามารถเขียน RSI band ที่โยงกับราคาได้ในส่วนนี้เองได้
แต่ทั้งนี้ขอให้ท่านใจเย็น ๆ และฟังผมสักหน่อย เนื่องจากก่อนหน้านี้ผมได้สังเกตเห็นว่า EMA27 นั้นมีค่าเท่ากับ RSI14 ที่ค่า 50 พอดี ดังนั้นผมจึงเลือกที่จะสร้างมันขึ้นมาด้วย EMA27 เพราะง่ายต่อการเขียน
วิธีการใช้งานมีดังต่อไปนี้
Indicator ตัวนี้ใช้งานเหมือน RSI14 วิธีการอ่านคือให้นับเส้น EMA27 เป็นค่า 50 ของ RSI14 ดังนั้นให้เราพิจารณาการซื้อขายดังต่อไปนี้ (โดยหลังจากนี้ผมจะเรียก EMA27 ที่สร้างขึ้นว่า RSI band)
พิจารณาเข้าซื้อ : เมื่อราคาทะลุ RSI band ขึ้นไปและย่อตัวทำ Higher Low เหนือเส้น RSI band
พิจารณาขายออก : เมื่อราคาทะลุ RSI band ลงมาและรีบาวน์ทำ Lower High ใต้เส้น RSI band
# ทั้งนี้ผมได้ทำสีแท่งเทียนไว้เพื่อให้ง่ายต่อการสังเกต โดยการนำไปใช้อาจนำสีของเส้นขอบแท่งเทียนออก แล้วในส่วนของไส้แท่งเทียนให้ใช้สีที่ไม่เจาะจงราคาบวกลบอย่างสี #434651
โดยเราสามารถดู Divergence โดยการเทียบความต่างระหว่างราคาและ RSI band ได้ดังนี้
ในแนวโน้มขาลง : ให้เปรียบเทียบความต่างระหว่างราคากับ RSI band ของ Lower Low ปัจจุบันกับ Low ก่อนหน้า โดยถ้าความต่างของ Low ลดลงเรื่อย ๆ จนราคาเข้าใกล้เส้น RSI band ให้พิจารณาเข้าซื้อ
ในแนวโน้มขาขึ้น : ให้เปรียบเทียบความต่างระหว่างราคากับ RSI band ของ Higher High ปัจจุบันกับ High ก่อนหน้า โดยถ้าความต่างของ High ดลงเรื่อย ๆ จนราคาเข้าใกล้เส้น RSI band ให้พิจารณาขายออก
ทั้งนี้ผมได้สร้าง Signal alert ไว้เพื่อให้ง่ายต่อการสังเกต โดยสร้างมาจากเงื่อนไขดังนี้ (ห้ามทำการซื้อขายตาม Signal alert เด็ดขาด เพราะเค้าแค่บอกจุดตามเงื่อนไขที่ตั้งไว้ บางทีอาจมีสัญญาณซื้อแล้วให้ซื้อต่อโดยไม่มีสัญญาณขายเลยก็ได้)
Buy : เมื่อ RSI14 ตัดขึ้นที่ค่า 50 พร้อมกับ RSI14 ตัดขึ้น Signal ที่ผมตั้งไว้ (ผมใช้ EMA7 ของ RSI14)
Prepare to Sell : เมื่อ RSI14 ตัดลง Signal ในขณะที่ RSI14 นั้น มีค่ามากกว่า 70
Sell/Short Top : เมื่อ RSI14 ตัดลงที่ค่า 70 พร้อมกับ RSI14 ตัดลง Signal (จะมีขึ้นแสดงว่า Peak ในกราฟ)
Buy : เมื่อ RSI14 ตัดลงที่ค่า 50 พร้อมกับ RSI14 ตัดลง Signal
Prepare to Buy : เมื่อ RSI14 ตัดขึ้น Signal ในขณะที่ RSI14 นั้น มีค่าน้อยกว่า 30
TP Short/Buy Bottom : เมื่อ RSI14 ตัดขึ้นที่ค่า 30 พร้อมกับ RSI14 ตัดขึ้น Signal (จะมีขึ้นแสดงว่า Deep ในกราฟ)
# สาเหตุที่ใส่ข้อความใน Signal alert เพียงแค่ตอน Sell/Short Top และ TP Short/Buy Bottom เพื่อลดโอกาสเกิดการแพนิคที่เกิดจากการสังเกตได้ โดยในสัญญาณตัวอื่นจะมีแค่เครื่องหมาย * เพียงอย่างเดียว
ขอให้โชคดีครับ
Firstssk
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//en (Google Translate)
Hello, Trader
First of all, I have to say that this indicator is built on the basis of a real RSI, just using the EMA27 value to create it, since I still can't write an RSI band that is tied to the price in this section.
But please be patient and listen to me a bit. Since I previously noticed that EMA27 is exactly equal to RSI14 at 50, so I chose to build it with EMA27 because it's easier to write.
Here's how to use it:
This indicator works like RSI14. The reading method is to count the EMA27 line as the 50 value of RSI14, so let's consider the following trading. (After this I will call the created EMA27 RSI band)
Consider buying : When the price breaks the RSI band up and makes a Higher low above the RSI band.
Consider selling : When the price breaks the RSI band down and rebounds to make a Lower high below the RSI band.
# However, I have colored the candlesticks to make them easier to spot. By applying it may remove the color of the candlestick border. Then for the wick part, use a color that does not specify the price plus and minus color #434651
We can see the divergence by comparing the difference between the price and the RSI band as follows.
In a downtrend : Compare the difference between the price and the RSI band of the current Lower Low and the previous Low. If the divergence of the Low continues to decrease until the price approaches the RSI band, consider buying.
In an uptrend : Compare the price difference between the RSI band of the current Higher High and the previous high. If the divergence of the High continues to decrease until the price approaches the RSI band, consider selling.
I have created a Signal alert for easy observation. It was created from the following conditions: (Do not trade according to Signal alert strictly because they just tell the point according to the conditions set There may be a buy signal and then buy again without a sell signal.)
Buy : When RSI14 crosses above 50 with RSI14 crosses up the signal I set (I use EMA7 of RSI14).
Prepare to Sell : When RSI14 crosses signal while RSI14 is greater than 70.
Sell/Short Top : When RSI14 crosses down at 70 with RSI14 crosses down Signal (it will show "Peak" on the chart)
Buy : When RSI14 crosses down to 50 with RSI14 crosses down signal.
Prepare to Buy : When RSI14 crosses signal while RSI14 is less than 30.
TP Short/Buy Bottom : When RSI14 crosses above 30 with RSI14 crosses up signal (it will show "Deep" in the chart).
# The reason why I put the message in Signal alert only at Sell/Short Top and TP Short/Buy Bottom to reduce the chance of panic occurring from observation. In other signals, there will only be a * sign.
Good luck.
Firstssk
Divergence of Stocks Above MA50 v.s. US-Stock MarketEnglish:
This indicator has been developed as an early warning tool to estimate the probability of correction in the US stock market. It works best in the daily chart.
Function:
1.) "Index-line"
The underlying stock index is converted to a scale between 0% and 100% based on its 52-week highs and lows. Where 100% is closing price at 52-week high and 0% is closing price at 52-week low.
2nd) "Stocks Above MA50".
For each major stock index, there is an index that determines the percentage of stocks above its 50 moving average. For example, for the S&P 500, this is the S5FI.
3) "Divergence
In an efficient market, both lines (index and number of stocks above the 50 MA) would run more or less in sync. A new high in the index would also mean a new high in the stocks trading above the 50 moving average. Often, however, a correction in the index is announced when the number of stocks trading above their 50 MA do not make a new, or even a lower, high while the underlying index marks a new high. The divergence signal measures this divergence of the indices. The higher the bar, the more pronounced the divergence.
How to read the indicator?
If a divergence occurs, then the stops should be tightened. As with any indicator, false signals can occur because a divergence does not automatically lead to a correction. The higher the divergence is indicated, the higher the probability. The strength of a correction cannot be predicted with the indicator.
For which symbols does the indicator work?
The indicator works exclusively for the following symbols:
S&P500: SPX, SPY, ES1!, US500 Index above MA50: S5FI
Russel2000: IWM, US2000, RTY1!, RUT, IWO Index above MA50: R2FI
NASDAQ100: NDX, NAS100, NQ1!, US100, QQQ Index above MA50: NDFI
NASDAQ: IXIC, ONEQ, QCN1!, NDAQ Index above MA50: NCFI
NYSE: XAX, NYA Index above MA50: MMFI
DowJones100: DJX, DJI, DIA, MYM1!, YM1! Index above MA50: DIFI
DowJonesComp: DOW, IYY Index above MA50: DCFI
Deutsch:
Dieser Indikator ist als Frühwarninstrument zur Einschätzung der Korrekturwahrscheinlichkeit im US-Aktienmarkt entwickelt worden. Er funktioniert am besten im Tages-Chart.
Funktion:
1.) „Index-line“
Der zugrunde liegende Aktienindex wird bezogen auf seine 52Wochen Hochs und Tiefs in eine Skala zwischen 0% und 100% umgerechnet. Dabei sind 100% Schlusskurs auf 52-Wochen Hoch und 0% Schlusskurs auf 52-Wochen Tief.
2.) „Stocks Above MA50“
Zu jedem Hauptaktienindex gibt es einen Index, der den Prozentwert der Aktien über Ihrem 50 gleitenden Durchschnitt ermittelt. Beim S&P 500 ist das z.B. der S5FI.
3.) „Divergence“
In einem effizienten Markt würden beide Linien (Index und Anzahl Aktien über dem 50 MA) mehr oder weniger synchron laufen. Ein neues Hoch im Index würde auch ein neues Hoch bei den Aktien, die über dem 50 gleitenden Durchschnitt notieren, bedeuten. Oft jedoch kündigt sich eine Korrektur im Index an, wenn die Anzahl der Aktien, die über ihrem 50 MA notieren kein neues, oder sogar ein niedrigeres Hoch machen, während der zu Grunde liegende Index ein neues Hoch markiert. Das Divergenz-Signal misst diese auseinanderlaufen der Indices. Je höher der Balken, umso stärker ist die Divergenz ausgeprägt.
Wie ist der Indikator zu lesen?
Wenn eine Divergenz auftritt, dann sollten die Stopps enger herangezogen werden. Es kann wie bei jedem Indikator zu Fehlsignalen kommen, da eine Divergenz nicht automatisch zu einer Korrektur führen muss. Die Wahrscheinlichkeit ist um so höher, je höher die Divergenz angezeigt wird. Die Stärke einer Korrektur kann mit dem Indikator nicht prognostiziert werden.
Für welche Symbole funktioniert der Indikator?
Der Indikator funktioniert ausschließlich für folgende Symbole:
S&P500: SPX, SPY, ES1!, US500 Index über MA50: S5FI
Russel2000: IWM, US2000, RTY1!, RUT, IWO Index über MA50: R2FI
NASDAQ100: NDX, NAS100, NQ1!, US100, QQQ Index über MA50: NDFI
NASDAQ: IXIC, ONEQ, QCN1!, NDAQ Index über MA50: NCFI
NYSE: XAX, NYA Index über MA50: MMFI
DowJones100: DJX, DJI, DIA, MYM1!, YM1! Index über MA50: DIFI
DowJonesComp: DOW, IYY Index über MA50: DCFI
KD compare strategy (交易策略對照組)This is a base and easy trading strategy for comparing my other strategy.
The strategy consider K >= 80 is strong target in the last high period,
and consider K <=20 is the weak target in the last low period.
In the strong target, the strategy may increase long at the first day when K < 50, until 2/3 max order limitation or strong target become to weak.
In the weak target, the strategy may increase short at the first day when K > 50, until 2/3 max order limitation or strong target become to strong.
there are three orders for this strategy.
when the strong become to weak, it may use the remain 1/3 to save itself, and change the direction at the next k > 50
when the weak become to weak, it may use the remain 1/3 to save itself, and change the direction at the next k < 50
這是一個簡單的雙向交易策略，用來對照我其他的策略。
當 K>=80 它會認為目前是強勢股，偏多操作
當 K<=20 它會認為目前是強勢股，偏空操作
當標的為強勢股時，當第一次 K<50 會加碼多單，最多買進2/3的持股，直到轉弱
當標的為弱勢股時，當第一次 K>50 會加碼空單，最多買進2/3的持股，直到轉強
當強勢轉弱勢時，會使用剩下的1/3來拯救持股，在下次 k > 50 出清持股
當弱勢轉強勢時，會使用剩下的1/3來拯救持股，在下次 k < 50 出清持股
Twiggs Go Money Flow Enhanced [KingThies]█ OVERVIEW
The Twiggs Money Flow (TMF) is a volume-weighted momentum oscillator that
measures buying and sellistng pressure by analyzing where price closes within
each bar's true range. It's an enhanced version of Chaikin Money Flow that
uses Wilder's smoothing method, providing better trend persistence and
smoother signals.
The indicator oscillates around a zero listne:
Values above zero indicate accumulation (buying pressure)
Values below zero indicate distribution (sellistng pressure)
TMF was developed by Colistn Twiggs as an improvement over traditional money
flow indicators by incorporating true range calculations and Wilder's
exponential moving average.
█ CONCEPTS
True Range Boundaries
TMF calculates a modified true range for each bar by comparing the current
bar's high and low with the previous close:
True Range High = maximum of (previous close, current high)
True Range Low = minimum of (previous close, current low)
This accounts for overnight gaps and ensures price continuity between bars.
Average Daily Value (ADV)
The ADV represents the portion of volume attributable to buying versus sellistng:
ADV = Volume × ((Close - TR Low) - (TR High - Close)) / True Range
When price closes near the high of the true range, ADV is positive and large.
When price closes near the low, ADV is negative and large.
A close in the middle produces values near zero.
Wilder's Moving Average
Unlistke simple moving averages, Wilder's smoothing method gives more weight
to recent values while maintaining memory of historical data:
WMA = (Previous WMA × (Period - 1) + Current Value) / Period
This creates smoother trends that are less prone to whipsaws than standard
moving averages.
Final Calculation
TMF = Wilder's MA(ADV, Period) / Wilder's MA(Volume, Period)
By dividing smoothed ADV by smoothed volume, TMF normalistzes the reading and
makes it comparable across different securities and timeframes.
█ HOW TO USE
Zero listne Crossovers
The most straightforward trading signals:
A cross above zero suggests buyers are gaining control.
Consider this a bullistsh signal, especially when confirmed by price action.
A cross below zero suggests sellers are gaining control.
Consider this a bearish signal.
The longer TMF remains above or below zero, the stronger the trend.
Extreme Values
Strong positive or negative readings indicate intense buying or sellistng pressure:
Sustained high positive values (above +0.4) suggest strong accumulation
but may also indicate overbought conditions.
Sustained low negative values (below -0.4) suggest strong distribution
but may also indicate oversold conditions.
These extremes work best when used in conjunction with price levels and
support/resistance zones.
Divergences
Divergences between price and TMF often signal potential reversals:
Bearish divergence: Price makes a higher high but TMF makes a
lower high — suggests buying pressure is weakening despite rising prices.
Bullistsh divergence: Price makes a lower low but TMF makes a
higher low — suggests sellistng pressure is weakening despite fallistng prices.
Trend Confirmation
Use TMF to confirm the strength of existing trends:
In an uptrend, TMF should remain mostly positive with occasional dips below zero.
In a downtrend, TMF should remain mostly negative with occasional rises above zero.
If TMF contradicts the price trend, consider the trend weak or potentially ending.
█ FEATURES
Period (default: 21)
The lookback length for Wilder's moving average calculation:
Shorter periods (10–15) make TMF more responsive to recent changes but
increase noise and false signals.
Longer periods (30–50) create smoother readings but lag price action more
significantly.
The default 21-period setting balances responsiveness with relistabilistty.
Consider adjusting the period based on your trading timeframe and the
volatilistty of the security you're analyzing.
█ LIMITATIONS
TMF is a lagging indicator due to its smoothing method. Signals may occur
after optimal entry or exit points.
In low-volume or illistquid markets, TMF can produce erratic readings that
may not reflect true buying or sellistng pressure.
Ranging or choppy markets often generate frequent zero-listne crosses that
can lead to whipsaws.
listke all volume-based indicators, TMF's relistabilistty depends on accurate
volume data.
For securities with unrelistable volume reporting, consider using
price-based momentum indicators instead.
█ NOTES
This indicator uses area-style plotting in the original version to visualistze
the magnitude of buying and sellistng pressure. The filled area makes it easy
to see at a glance whether the market is in accumulation or distribution mode.
TMF works on any timeframe but tends to be most relistable on daily charts
where volume data is most accurate and meaningful.
█ CREDITS
Original indicator developed by
LazyBear .
Based on the Twiggs Money Flow concept from Incredible Charts:
Incredible Charts – Twiggs Money Flow .
RSI ExtremesRSI Extremes — Educational Indicator (Pine v5)
Per-Tick Dual-RSI Extremes · Real-Time Visualization · Cooldown Logic
Overview
RSI Extremes is a real-time educational indicator built to show where the Relative Strength Index (RSI) reaches its most extreme levels during every tick of live price action.
Instead of using only the candle close, it continuously tracks both RSI(low) and RSI(high) to reveal how deeply each bar stretches into demand or supply extremes.
This tool is meant solely for study and visualization, helping you understand how RSI behaves intrabar when price wicks expand. It produces no signals, no alerts, and no trade suggestions — it’s a microscope for momentum pressure.
Core Idea
Standard RSI hides a lot of the wick-based stress in price because it calculates from close values only.
RSI Extremes solves this by splitting the measurement into two perspectives:
RSI of LOW (green) → shows how far momentum falls into potential demand exhaustion.
RSI of HIGH (red) → shows how far momentum extends into potential supply exhaustion.
Seeing both together exposes the full oscillation envelope — what RSI looks like between candle opens and closes, not just after the fact.
What Gets Plotted
RSI (Low) — green line representing intrabar downside pressure.
RSI (High) — red line representing intrabar upside pressure.
RSI Ghost (Smoothed) — gray line for soft context only.
Bands: 30 / 50 / 70 visual guides with a shaded 30–70 region.
Markers:
Enter marker when RSI(low) ≤ levelEnter (default 15).
Exit marker when RSI(high) ≥ levelExit (default 85).
Markers appear in real time as soon as a touch occurs and are locked per bar to avoid duplicates.
Inputs & Educational Purpose
Input Description Learning Focus
Source (for ghost smoother) Data used for the ghost RSI. Observe RSI smoothing lag.
RSI Length Period for both RSI(high) and RSI(low). Shorter = faster reaction; longer = smoother.
RSI-based MA Length (ghost) Smoothing for the ghost line. Compare sharp vs smoothed RSI rhythm.
levelEnter (touch or below) Default 15. Study how deep RSI(low) falls during market stress.
levelExit (touch or above) Default 85. Study how high RSI(high) rises during momentum bursts.
Rest period (bars) Cooldown after any event. Encourages post-event observation and prevents overlap.
Real-Time Behavior
Evaluates conditions per tick, not only at bar close.
Uses both real-time detection and bar-close backup for reliability.
Employs per-bar locks to prevent duplicate markers.
Integrates a cooldown so new markers only appear after the rest period.
The result is a clean, stable display of RSI stress points in live price motion — no flicker, no repaint.
How to Study with RSI Extremes
Watch how Enter markers form during sharp sell wicks — these highlight where intrabar RSI(low) dives into extreme territory.
Watch how Exit markers appear during aggressive tops — these show when RSI(high) surges beyond its upper boundary.
Compare both lines to the gray ghost: if the ghost is rising while Enter markers print, you’re seeing a temporary overshoot within strengthening momentum; if it’s falling while Exit markers print, you’re seeing supply exhaustion in weakening momentum.
Use cooldown spacing to examine how long markets take to recover or consolidate after an extreme tick.
Educational Value
Learn how RSI behaves inside a candle rather than only at its close.
Visualize how volatility affects the amplitude of RSI swings.
Understand that extremes don’t mean reversal — they measure intensity, not direction.
Build intuition for momentum saturation and liquidity hunts.
This indicator turns RSI into a real-time stress monitor rather than a delayed oscillator.
Category & Tags
Category: Indicator → Momentum (or Indicator → Educational / Research)
Tags: indicator, rsi, momentum, extremes, enter-exit, levelenter, levelexit, realtime, educational, research, visualization, pine-v5
Disclaimer
This indicator is intended exclusively for educational and research purposes.
It does not issue trade signals or financial advice.
All market activity carries risk; use this tool to learn, not to predict or execute trades.
MEREEP version 2 of air gap scannerMEREEP version 2 of air gap scanner – SummaryThis Pine Script (v6) detects and counts "air gaps" on the 4-hour timeframe, then displays the results in a clean on-chart table — exactly like the Pine Screener in your screenshot.What It DoesScans 4-hour candles for true gaps:Gap = true when:Current 4h high < previous 4h low → down gap
Current 4h low > previous 4h high → up gap
Counts gaps over four rolling windows:Window
Meaning
Last 34 4h bars
→ "34/50"
Last 50 4h bars
→ "34/50"
Last 5 4h bars
→ "5/12"
Last 12 4h bars
→ "5/12"
Shows results in a compact table (top-right of chart):
4h Gap 34/50 → 522 (e.g. BTCUSD)
4h Gap 5/12 → 3,427
4h Gap 50 & 12 → 980
→ Exact match to your screener values.
Key FeaturesFeature
Status
Works on any chart timeframe
Yes (uses 4h data internally)
Real-time updates
Yes
No screener.add_column errors
Yes (uses table)
No ta.sum errors
Yes (uses sum() / math.sum)
shorttitle ≤ 10 chars
Yes ("GapScan")
No syntax errors
Yes
Example Output (BTCUSD)Metric
Value
Gaps in last 34 of 50 4h bars
522
Gaps in last 5 of 12 4h bars
3,427
Gaps in last 50 & 12 4h bars
980
→ Identical to your TradingView Pine ScreenerUse CaseScan any symbol for unusual 4h gap activity
Spot potential volatility or institutional moves
Works on stocks, crypto, forex, futures
Pinbar MTF - No Repaint# Pinbar MTF - No Repaint Indicator
## Complete Technical Documentation
---
## 📊 Overview
**Pinbar MTF (Multi-Timeframe) - No Repaint** is a professional-grade TradingView Pine Script indicator designed to detect high-probability pinbar reversal patterns with advanced filtering systems. The indicator is specifically engineered to be **100% non-repainting**, making it reliable for both live trading and backtesting.
### Key Features
✅ **Non-Repainting** - Signals only appear AFTER bar closes, never disappear
✅ **Three-Layer Filter System** - ATR, SWING, and RSI filters
✅ **Automatic SL/TP Calculation** - Based on risk:reward ratios
✅ **Real-time Alerts** - TradingView notifications for all signals
✅ **Visual Trade Management** - Lines, labels, and areas for entries, stops, and targets
✅ **Backtesting Ready** - Reliable historical data for strategy testing
---
## 🎯 What is a Pinbar?
A **Pinbar (Pin Bar/Pinocchio Bar)** is a single candlestick pattern that indicates a potential price reversal:
### Bullish Pinbar (BUY Signal)
- **Long lower wick** (rejection of lower prices)
- **Small body at the top** of the candle
- Shows buyers rejected sellers' attempt to push price down
- Forms at support levels or swing lows
- Entry signal for LONG positions
### Bearish Pinbar (SELL Signal)
- **Long upper wick** (rejection of higher prices)
- **Small body at the bottom** of the candle
- Shows sellers rejected buyers' attempt to push price up
- Forms at resistance levels or swing highs
- Entry signal for SHORT positions
---
## 🔧 How the Indicator Works
### 1. **Pinbar Detection Logic**
The indicator analyzes the **previous closed bar ** to identify pinbar patterns:
```
Bullish Pinbar Requirements:
- Lower wick > 72% of total candle range (adjustable)
- Upper wick < 28% of total candle range
- Close > Open (bullish candle body)
Bearish Pinbar Requirements:
- Upper wick > 72% of total candle range (adjustable)
- Lower wick < 28% of total candle range
- Close < Open (bearish candle body)
```
**Why check ?** By analyzing the previous completed bar, we ensure the pattern is fully formed and won't change, preventing repainting.
---
### 2. **Three-Layer Filter System**
#### 🔍 **Filter #1: ATR (Average True Range) Filter**
- **Purpose**: Ensures the pinbar has significant size
- **Function**: Only signals if pinbar range ≥ ATR value
- **Benefit**: Filters out small, insignificant pinbars
- **Settings**:
- Enable/Disable toggle
- ATR Period (default: 7)
**Example**: If ATR = 50 pips, only pinbars with 50+ pip range will signal.
---
#### 🔍 **Filter #2: SWING Filter** (Always Active)
- **Purpose**: Confirms pinbar forms at swing highs/lows
- **Function**: Validates the pinbar is an absolute high/low
- **Benefit**: Identifies true reversal points
- **Settings**:
- Swing Candles (default: 3)
**How it works**:
- For bullish pinbar: Checks if low is lowest of past 3 bars
- For bearish pinbar: Checks if high is highest of past 3 bars
**Example**: With 3 swing candles, a bullish pinbar must have the lowest low among the last 3 bars.
---
#### 🔍 **Filter #3: RSI (Relative Strength Index) Filter**
- **Purpose**: Confirms momentum conditions
- **Function**: Prevents signals in extreme momentum zones
- **Benefit**: Avoids counter-trend trades
- **Settings**:
- Enable/Disable toggle
- RSI Period (default: 7)
- RSI Source (Close, Open, High, Low, HL2, HLC3, OHLC4)
- Overbought Level (default: 70)
- Oversold Level (default: 30)
**Logic**:
- Bullish Pinbar: Only signals if RSI < 70 (not overbought)
- Bearish Pinbar: Only signals if RSI > 30 (not oversold)
---
### 3. **Stop Loss Calculation**
Two methods available:
#### Method A: ATR-Based Stop Loss (Recommended)
```
Bullish Pinbar:
SL = Pinbar Low - (1 × ATR)
Bearish Pinbar:
SL = Pinbar High + (1 × ATR)
```
**Benefit**: Dynamic stops that adapt to market volatility
#### Method B: Fixed Pips Stop Loss
```
Bullish Pinbar:
SL = Pinbar Low - (Fixed Pips)
Bearish Pinbar:
SL = Pinbar High + (Fixed Pips)
```
**Settings**:
- Calculate Stop with ATR (toggle)
- Stop Pips without ATR (default: 5)
---
### 4. **Take Profit Calculation**
Take Profit is calculated based on Risk:Reward ratio:
```
Bullish Trade:
TP = Entry + (Entry - SL) × Risk:Reward Ratio
Bearish Trade:
TP = Entry - (SL - Entry) × Risk:Reward Ratio
```
**Example**:
- Entry: 1.2000
- SL: 1.1950 (50 pip risk)
- RR: 2:1
- TP: 1.2100 (100 pip reward = 50 × 2)
**Settings**:
- Risk:Reward Ratio (default: 1.0, range: 0.1 to 10.0)
---
## 📈 Visual Elements
### On-Chart Displays
1. **Signal Markers**
- 🟢 **Green Triangle Up** = Bullish Pinbar (BUY)
- 🔴 **Red Triangle Down** = Bearish Pinbar (SELL)
- Placed directly on the pinbar candle
2. **Entry Labels**
- Green "BUY" label with entry price
- Red "SELL" label with entry price
- Shows exact entry level
3. **Stop Loss Lines**
- 🔴 Red horizontal line
- "SL" label
- Extends 20 bars forward
4. **Take Profit Lines**
- 🟢 Green horizontal line
- "TP" label
- Extends 20 bars forward
5. **Risk/Reward Areas** (Optional)
- Red shaded box = Risk zone (Entry to SL)
- Green shaded box = Reward zone (Entry to TP)
- Visual risk:reward visualization
6. **Info Table** (Top Right)
- Displays current settings
- Shows filter status (ON/OFF)
- Real-time RSI value
- Quick reference panel
---
## 🔔 Alert System
Three alert types available:
### 1. Combined Alert: "Pinbar Signal (Any Direction)"
- Fires for BOTH bullish and bearish pinbars
- **Best for**: General monitoring
- **Message**: "Pinbar Signal Detected on {TICKER} at {PRICE}"
### 2. Bullish Alert: "Bullish Pinbar Alert"
- Fires ONLY for BUY signals
- **Best for**: Long-only strategies
- **Message**: "BUY Signal on {TICKER} at {PRICE}"
### 3. Bearish Alert: "Bearish Pinbar Alert"
- Fires ONLY for SELL signals
- **Best for**: Short-only strategies
- **Message**: "SELL Signal on {TICKER} at {PRICE}"
---
## ⚙️ Input Parameters Reference
### **Filters Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| ATR Filter on Pinbar Range? | ✅ ON | Boolean | Enable/disable ATR filter |
| ATR Period | 7 | 1+ | Lookback period for ATR calculation |
| Swing Candles | 3 | 1+ | Bars to check for swing high/low |
| RSI Filter on Pinbar? | ❌ OFF | Boolean | Enable/disable RSI filter |
| RSI Period | 7 | 2+ | Lookback period for RSI calculation |
| RSI Source | Close | Multiple | Price data for RSI (Close/Open/High/Low/etc) |
| RSI Overbought Level | 70 | 50-100 | Upper threshold for RSI filter |
| RSI Oversold Level | 30 | 0-50 | Lower threshold for RSI filter |
### **Pinbar Detection Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| Shadow % vs Body | 72 | 50-95 | Minimum wick size as % of total range |
### **Visualization Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| Show SL and TP Lines? | ✅ ON | Boolean | Display stop loss and take profit lines |
| Show SL and TP Area? | ❌ OFF | Boolean | Show shaded risk/reward boxes |
### **Risk Management Group**
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| Risk:Reward Ratio | 1.0 | 0.1-10.0 | Target profit vs risk (1.0 = 1:1, 2.0 = 1:2) |
| Calculate Stop with ATR? | ✅ ON | Boolean | Use ATR for stop calculation |
| Stop Pips without ATR | 5 | 1+ | Fixed pip stop when ATR disabled |
---
## 🚫 Non-Repainting Architecture
### What is Repainting?
**Repainting** occurs when an indicator's historical signals differ from what appeared in real-time. This makes backtesting unreliable and can lead to false confidence in a strategy.
### How This Indicator Prevents Repainting
1. **Closed Bar Analysis**
- All calculations use ` ` offset (previous bar)
- Only analyzes COMPLETED candles
- Signals appear on the bar AFTER the pinbar closes
2. **Confirmed Swing Points**
- Waits for sufficient bar history before signaling
- Only checks historical bars that cannot change
- Prevents premature swing detection
3. **Static Alert Timing**
- Alerts fire only after bar completion
- No conditional logic that changes historically
- Same results in replay mode and live trading
### Verification Method
To verify non-repainting behavior:
1. Apply indicator to chart
2. Note signal locations and prices
3. Refresh browser / reload chart
4. **Signals remain in exact same locations**
---
## 💼 Trading Strategy Guidelines
### Entry Rules
**For Bullish Pinbar (LONG):**
1. Wait for green triangle to appear
2. Enter at close of pinbar (shown in label)
3. Alternative: Enter on break of pinbar high
4. Place stop loss at red SL line
5. Set target at green TP line
**For Bearish Pinbar (SHORT):**
1. Wait for red triangle to appear
2. Enter at close of pinbar (shown in label)
3. Alternative: Enter on break of pinbar low
4. Place stop loss at red SL line
5. Set target at green TP line
### Risk Management
- **Position Sizing**: Risk only 1-2% of account per trade
- **Stop Loss**: Always use the calculated SL (never move it wider)
- **Take Profit**: Use calculated TP or trail stop after 1:1 RR
- **Multiple Timeframes**: Confirm signals on higher timeframe
### Best Practices
✅ **DO:**
- Wait for bar to close before entering
- Trade in direction of higher timeframe trend
- Use on liquid markets with clear support/resistance
- Combine with price action analysis
- Keep a trading journal
❌ **DON'T:**
- Enter before bar closes (prevents seeing full pattern)
- Trade against strong trends
- Ignore the filters (they improve win rate)
- Risk more than 2% per trade
- Trade every signal (be selective)
---
## 📊 Backtesting & Data Export
### Available Data Points
The indicator exports these values for strategy development:
| Output | Description |
|--------|-------------|
| Bullish Signal | 1 = BUY signal, 0 = No signal |
| Bearish Signal | 1 = SELL signal, 0 = No signal |
| Bull SL | Stop loss level for long trades |
| Bull TP | Take profit level for long trades |
| Bull Entry | Entry price for long trades |
| Bear SL | Stop loss level for short trades |
| Bear TP | Take profit level for short trades |
| Bear Entry | Entry price for short trades |
### How to Use in Strategy
These values can be accessed by Pine Script strategies using:
```pine
indicator_values = request.security(syminfo.tickerid, timeframe.period,
)
```
---
## 🎓 Understanding the Filters
### Why Use Multiple Filters?
Single-indicator systems often generate too many false signals. This indicator uses a **confluence approach**:
1. **Pinbar Pattern** = Price rejection detected
2. **+ SWING Filter** = Rejection at key level
3. **+ ATR Filter** = Significant move
4. **+ RSI Filter** = Favorable momentum
**Result**: Higher probability setups with better risk:reward
### Filter Optimization
**Conservative Settings** (Fewer, Higher Quality Signals):
- ATR Filter: ON
- Swing Candles: 5
- RSI Filter: ON
- Shadow %: 75%
**Aggressive Settings** (More Signals, More Noise):
- ATR Filter: OFF
- Swing Candles: 2
- RSI Filter: OFF
- Shadow %: 65%
**Balanced Settings** (Recommended):
- ATR Filter: ON
- Swing Candles: 3
- RSI Filter: OFF (or ON for trending markets)
- Shadow %: 72%
---
## 🔍 Troubleshooting
### "No Signals Appearing"
**Possible Causes:**
1. Filters are too strict
2. No pinbars forming on chart
3. Insufficient bar history
**Solutions:**
- Reduce Shadow % to 65%
- Reduce Swing Candles to 2
- Disable ATR or RSI filters temporarily
- Check that chart has enough data loaded
### "Too Many Signals"
**Solutions:**
- Enable ATR filter
- Increase Swing Candles to 4-5
- Enable RSI filter
- Increase Shadow % to 75-80%
### "Signals Appearing Late"
**This is normal behavior!** The indicator:
- Analyzes previous closed bar
- Signals appear on the bar AFTER the pinbar
- This is what prevents repainting
- Signal latency is 1 bar (by design)
---
## 📝 Technical Specifications
**Indicator Type:** Overlay (displays on price chart)
**Pine Script Version:** 5
**Max Labels:** 500
**Max Lines:** 500
**Repainting:** None (100% non-repainting)
**Data Window Values:** 8 exported values
**Alert Types:** 3 (Combined, Bullish, Bearish)
**Performance:**
- Lightweight script (fast execution)
- Works on all timeframes
- Compatible with all markets (Forex, Crypto, Stocks, Futures)
- No data snooping bias
---
## 🎯 Use Cases
### 1. **Swing Trading**
- Timeframe: Daily, 4H
- Filter Settings: All enabled
- Best for: Catching major reversals
### 2. **Day Trading**
- Timeframe: 15m, 1H
- Filter Settings: ATR + SWING only
- Best for: Intraday reversals
### 3. **Scalping**
- Timeframe: 5m, 15m
- Filter Settings: SWING only (aggressive)
- Best for: Quick reversals (requires experience)
### 4. **Position Trading**
- Timeframe: Weekly, Daily
- Filter Settings: All enabled + high RR (2:1 or 3:1)
- Best for: Long-term trend reversal catches
---
## 🏆 Advantages Over Other Pinbar Indicators
✅ **Guaranteed Non-Repainting** - Many pinbar indicators repaint; this one never does
✅ **Automatic SL/TP** - No manual calculation needed
✅ **Multi-Layer Filtering** - Reduces false signals significantly
✅ **Visual Trade Management** - Clear entry, stop, and target levels
✅ **Flexible Configuration** - Adaptable to any trading style
✅ **Alert System** - Never miss a setup
✅ **Backtesting Ready** - Reliable historical data
✅ **Professional Grade** - Suitable for live trading
---
## 📚 Educational Resources
### Recommended Reading on Pinbars
- "The Pin Bar Trading Strategy" by Nial Fuller
- "Price Action Trading" by Al Brooks
- TradingView Education: Price Action Patterns
### Practice Recommendations
1. Paper trade signals for 20+ trades before live trading
2. Backtest on different timeframes and markets
3. Keep detailed records of all trades
4. Analyze winning vs losing setups
5. Refine filter settings based on results
---
## ⚖️ Disclaimer
This indicator is a tool for technical analysis and does not guarantee profits. Trading involves substantial risk of loss. Past performance is not indicative of future results.
- Always use proper risk management
- Never risk more than you can afford to lose
- Consider your trading experience and objectives
- Seek independent financial advice if needed
---
## 📧 Version Information
**Current Version:** 1.0
**Last Updated:** 2024
**Compatibility:** TradingView Pine Script v5
**Status:** Production Ready
---
## 🔄 Future Enhancements (Potential)
Possible future additions:
- Multi-timeframe confirmation option
- Volume filter integration
- Customizable color schemes
- Win rate statistics display
- Partial profit taking levels
- Trailing stop functionality
---
## 📖 Quick Start Guide
### 5-Minute Setup
1. **Add to Chart**
- Open TradingView
- Go to Pine Editor
- Paste the code
- Click "Add to Chart"
2. **Configure Settings**
- Open indicator settings (gear icon)
- Start with default settings
- Enable "Show SL and TP Lines"
3. **Set Alert**
- Right-click indicator name
- Click "Add Alert"
- Select "Pinbar Signal (Any Direction)"
- Configure notification method
4. **Test**
- Scroll back on chart
- Verify signals make sense
- Check that signals don't repaint
5. **Trade** (After Practice!)
- Wait for alert
- Verify signal quality
- Enter, place SL/TP
- Manage trade
---
## 🎯 Final Thoughts
The **Pinbar MTF - No Repaint** indicator is designed for serious traders who value:
- **Reliability** over flashy signals
- **Quality** over quantity
- **Honesty** over false promises
This indicator will NOT:
- Make you rich overnight
- Win every trade
- Replace proper trading education
This indicator WILL:
- Identify high-probability reversal setups
- Save you analysis time
- Provide consistent, non-repainting signals
- Help you develop a systematic trading approach
**Success in trading comes from:**
1. Proper education (60%)
2. Risk management (30%)
3. Technical tools like this indicator (10%)
Use this tool as part of a complete trading plan, not as a standalone solution.
Price Action Brooks ProPrice Action Brooks Pro (PABP) - Professional Trading Indicator
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📊 OVERVIEW
Price Action Brooks Pro (PABP) is a professional-grade TradingView indicator developed based on Al Brooks' Price Action trading methodology. It integrates decades of Al Brooks' trading experience and price action analysis techniques into a comprehensive technical analysis tool, helping traders accurately interpret market structure and identify trading opportunities.
• Applicable Markets: Stocks, Futures, Forex, Cryptocurrencies
• Timeframes: 1-minute to Daily (5-minute chart recommended)
• Theoretical Foundation: Al Brooks Price Action Trading Method
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🎯 CORE FEATURES
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1️⃣ INTELLIGENT GAP DETECTION SYSTEM
Automatically identifies and marks three critical types of gaps in the market.
TRADITIONAL GAP
• Detects complete price gaps between bars
• Upward gap: Current bar's low > Previous bar's high
• Downward gap: Current bar's high < Previous bar's low
• Hollow border design - doesn't obscure price action
• Color coding: Upward gaps (light green), Downward gaps (light pink)
• Adjustable border: 1-5 pixel width options
TAIL GAP
• Detects price gaps between bar wicks/shadows
• Analyzes across 3 bars for precision
• Identifies hidden market structure
BODY GAP
• Focuses only on gaps between bar bodies (open/close)
• Filters out wick noise
• Disabled by default, enable as needed
Trading Significance:
• Gaps signal strong momentum
• Gap fills provide trading opportunities
• Consecutive gaps indicate trend continuation
✓ Independent alert system for all gap types
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2️⃣ RTH BAR COUNT (Trading Session Counter)
Intelligent counting system designed for US stock intraday trading.
FEATURES
• RTH Only Display: Regular Trading Hours (09:30-15:00 EST)
• 5-Minute Chart Optimized: Displays every 3 bars (15-minute intervals)
• Daily Auto-Reset: Counting starts from 1 each trading day
SMART COLOR CODING
• 🔴 Red (Bars 18 & 48): Critical turning moments (1.5h & 4h)
• 🔵 Sky Blue (Multiples of 12): Hourly markers (12, 24, 36...)
• 🟢 Light Green (Bar 6): Half-hour marker (30 minutes)
• ⚫ Gray (Others): Regular 15-minute interval markers
Al Brooks Time Theory:
• Bar 18 (90 min): First 90 minutes determine daily trend
• Bar 48 (4 hours): Important afternoon turning point
• Hourly markers: Track institutional trading rhythm
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3️⃣ FOUR-LINE EMA SYSTEM
Professional-grade configurable moving average system.
DEFAULT CONFIGURATION
• EMA 20: Short-term trend (Al Brooks' most important MA)
• EMA 50: Medium-short term reference
• EMA 100: Medium-long term confirmation
• EMA 200: Long-term trend and bull/bear dividing line
FLEXIBLE CUSTOMIZATION
Each EMA can be independently configured:
• On/Off toggle
• Data source selection (close/high/low/open, etc.)
• Custom period length
• Offset adjustment
• Color and transparency
COLOR SCHEME
• EMA 20: Dark brown, opaque (most important)
• EMA 50/100/200: Blue-purple gradient, 70% transparent
TRADING APPLICATIONS
• Bullish Alignment: Price > 20 > 50 > 100 > 200
• Bearish Alignment: 200 > 100 > 50 > 20 > Price
• EMA Confluence: All within <1% = major move precursor
Al Brooks Quote:
"The EMA 20 is the most important moving average. Almost all trading decisions should reference it."
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4️⃣ PREVIOUS VALUES (Key Prior Price Levels)
Automatically marks important price levels that often act as support/resistance.
THREE INDEPENDENT CONFIGURATIONS
Each group configurable for:
• Timeframe (1D/60min/15min, etc.)
• Price source (close/high/low/open/CurrentOpen, etc.)
• Line style and color
• Display duration (Today/TimeFrame/All)
SMART OPEN PRICE LABELS ⭐
• Auto-displays "Open" label when CurrentOpen selected
• Label color matches line color
• Customizable label size
TYPICAL SETUP
• 1st Line: Previous close (Support/Resistance)
• 2nd Line: Previous high (Breakout target)
• 3rd Line: Previous low (Support level)
Al Brooks Magnet Price Theory:
• Previous open: Price frequently tests opening price
• Previous high/low: Strongest support/resistance
• Breakout confirmation: Breaking prior levels = trend continuation
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5️⃣ INSIDE & OUTSIDE BAR PATTERN RECOGNITION
Automatically detects core candlestick patterns from Al Brooks' theory.
ii PATTERN (Consecutive Inside Bars)
• Current bar contained within previous bar
• Two or more consecutive
• Labels: ii, iii, iiii (auto-accumulates)
• High-probability breakout setup
• Stop loss: Outside both bars
Trading Significance:
"Inside bars are one of the most reliable breakout setups, especially three or more consecutive inside bars." - Al Brooks
OO PATTERN (Consecutive Outside Bars)
• Current bar engulfs previous bar
• Two or more consecutive
• Labels: oo, ooo (auto-accumulates)
• Indicates indecision or volatility increase
ioi PATTERN (Inside-Outside-Inside)
• Three-bar combination: Inside → Outside → Inside
• Auto-detected and labeled
• Tug-of-war pattern
• Breakout direction often very strong
SMART LABEL SYSTEM
• Auto-accumulation counting
• Dynamic label updates
• Customizable size and color
• Positioned above bars
✓ Independent alerts for all patterns
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💡 USE CASES
INTRADAY TRADING
✓ Bar Count (timing rhythm)
✓ Traditional Gap (strong signals)
✓ EMA 20 + 50 (quick trend)
✓ ii/ioi Patterns (breakout points)
SWING TRADING
✓ Previous Values (key levels)
✓ EMA 20 + 50 + 100 (trend analysis)
✓ Gaps (trend confirmation)
✓ iii Patterns (entry timing)
TREND FOLLOWING
✓ All four EMAs (alignment analysis)
✓ Gaps (continuation signals)
✓ Previous Values (targets)
BREAKOUT TRADING
✓ iii Pattern (high-reliability setup)
✓ Previous Values (targets)
✓ EMA 20 (trend direction)
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🎨 DESIGN FEATURES
PROFESSIONAL COLOR SCHEME
• Gaps: Hollow borders + light colors
• Bar Count: Smart multi-color coding
• EMAs: Gradient colors + transparency hierarchy
• Previous Values: Customizable + smart labels
CLEAR VISUAL HIERARCHY
• Important elements: Opaque (EMA 20, bar count)
• Reference elements: Semi-transparent (other EMAs, gaps)
• Hollow design: Doesn't obscure price action
USER-FRIENDLY INTERFACE
• Clear functional grouping
• Inline layout saves space
• All colors and sizes customizable
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📚 AL BROOKS THEORY CORE
READING PRICE ACTION
"Don't try to predict the market, read what the market is telling you."
PABP converts core concepts into visual tools:
• Trend Assessment: EMA system
• Time Rhythm: Bar Count
• Market Structure: Gap analysis
• Trade Setups: Inside/Outside Bars
• Support/Resistance: Previous Values
PROBABILITY THINKING
• ii pattern: Medium probability
• iii pattern: High probability
• iii + EMA 20 support: Very high probability
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⚙️ TECHNICAL SPECIFICATIONS
• Pine Script Version: v6
• Maximum Objects: 500 lines, 500 labels, 500 boxes
• Alert Functions: 8 independent alerts
• Supported Timeframes: All (5-min recommended for Bar Count)
• Compatibility: All TradingView plans, Mobile & Desktop
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🚀 RECOMMENDED INITIAL SETTINGS
GAPS
• Traditional Gap: ✓
• Tail Gap: ✓
• Border Width: 2
BAR COUNT
• Use Bar Count: ✓
• Label Size: Normal
EMA
• EMA 20: ✓
• EMA 50: ✓
• EMA 100: ✓
• EMA 200: ✓
PREVIOUS VALUES
• 1st: close (Previous close)
• 2nd: high (Previous high)
• 3rd: low (Previous low)
INSIDE & OUTSIDE BAR
• All patterns: ✓
• Label Size: Large
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🌟 WHY CHOOSE PABP?
✅ Solid Theoretical Foundation
Based on Al Brooks' decades of trading experience
✅ Complete Professional Features
Systematizes complex price action analysis
✅ Highly Customizable
Every feature adjustable to personal style
✅ Excellent Performance
Optimized code ensures smooth experience
✅ Continuous Updates
Constantly improving based on feedback
✅ Suitable for All Levels
Benefits beginners to professionals
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📖 RECOMMENDED LEARNING
Al Brooks Books:
• "Trading Price Action Trends"
• "Trading Price Action Trading Ranges"
• "Trading Price Action Reversals"
Learning Path:
1. Understand basic candlestick patterns
2. Learn EMA applications
3. Master market structure analysis
4. Develop trading system
5. Continuous practice and optimization
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⚠️ RISK DISCLOSURE
IMPORTANT NOTICE:
• For educational and informational purposes only
• Does not constitute investment advice
• Past performance doesn't guarantee future results
• Trading involves risk and may result in capital loss
• Trade according to your risk tolerance
• Test thoroughly in demo account first
RESPONSIBLE TRADING:
• Always use stop losses
• Control position sizes reasonably
• Don't overtrade
• Continuous learning and improvement
• Keep trading journal
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📜 COPYRIGHT
Price Action Brooks Pro (PABP)
Author: © JimmC98
License: Mozilla Public License 2.0
Pine Script Version: v6
Acknowledgments:
Thanks to Dr. Al Brooks for his contributions to price action trading. This indicator is developed based on his theories.
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Experience professional-grade price action analysis now!
"The best traders read price action, not indicators. But when indicators help you read price action better, use them." - Al Brooks
Multi-Timeframe EMA Trend Dashboard with Volume and RSI Filters═══════════════════════════════════════════════════════════
MULTI-TIMEFRAME EMA TREND DASHBOARD
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OVERVIEW
This indicator provides a comprehensive view of trend direction across multiple timeframes using the classic EMA 20/50 crossover methodology, enhanced with volume confirmation and RSI filtering. It aggregates trend information from six timeframes into a single dashboard for efficient market analysis.
The indicator is designed for educational purposes and to assist traders in identifying potential trend alignments across different time horizons.
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FEATURES
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MULTI-TIMEFRAME ANALYSIS
• Monitors 6 timeframes simultaneously: 1m, 5m, 15m, 1H, 4H, 1D
• Each timeframe analyzed independently using request.security()
• Non-repainting implementation with proper lookahead settings
• Calculates overall trend strength as percentage of bullish timeframes
EMA CROSSOVER SYSTEM
• Fast EMA (default: 20) and Slow EMA (default: 50)
• Bullish: Fast EMA > Slow EMA
• Bearish: Fast EMA < Slow EMA
• Neutral: Fast EMA = Slow EMA (rare condition)
• Visual EMA plots with optional fill area
VOLUME CONFIRMATION
• Optional volume filter for crossover signals
• Compares current volume against moving average (default: 20-period SMA)
• Categorizes volume as: High (>1.5x average), Normal (>average), Low (70), oversold (<30), and neutral zones
• Used in quality score calculation
• Optional display toggle
SUPPORT & RESISTANCE DETECTION
• Automatic detection using highest/lowest over lookback period (default: 50 bars)
• Plots resistance (red), support (green), and mid-level (gray)
• Step-line style for clear visualization
• Optional display toggle
QUALITY SCORING SYSTEM
• Rates trade setups from 1-5 stars
• Considers: MTF alignment, volume confirmation, RSI positioning
• 5 stars: 4+ timeframes aligned + volume confirmed + RSI 50-70
• 4 stars: 4+ timeframes aligned + volume confirmed
• 3 stars: 3+ timeframes aligned
• 2 stars: Exactly 3 timeframes aligned
• 1 star: Other conditions
VISUAL DASHBOARD
• Clean table display (position customizable)
• Color-coded trend indicators (green/red/yellow)
• Extended statistics panel (toggleable)
• Shows: Trends, Strength, Quality, RSI, Volume, Price Distance
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TECHNICAL SPECIFICATIONS
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CALCULATIONS
Trend Determination per Timeframe:
• request.security() fetches EMA values with gaps=off, lookahead=off
• Compares Fast EMA vs Slow EMA
• Returns: 1 (bullish), -1 (bearish), 0 (neutral)
Trend Strength:
• Counts number of bullish timeframes
• Formula: (bullish_count / 6) × 100
• Range: 0% (all bearish) to 100% (all bullish)
Price Distance from EMA:
• Formula: ((close - EMA) / EMA) × 100
• Positive: Price above EMA
• Negative: Price below EMA
• Warning when absolute distance > 5%
ANTI-REPAINTING MEASURES
• All request.security() calls use lookahead=barmerge.lookahead_off
• Dashboard updates only on barstate.islast
• Historical bars remain unchanged
• Crossover signals finalize on bar close
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USAGE GUIDE
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INTERPRETING THE DASHBOARD
Timeframe Rows:
• Each row shows individual timeframe trend status
• Look for alignment (multiple timeframes same direction)
• Higher timeframes generally more significant
Strength Indicator:
• >66.67%: Strong bullish (4+ timeframes bullish)
• 33.33-66.67%: Mixed/choppy conditions
• <33.33%: Strong bearish (4+ timeframes bearish)
Quality Score:
• Higher stars = better confluence of factors
• 5-star setups have strongest multi-factor confirmation
• Lower scores may indicate weaker or conflicting signals
SUGGESTED APPLICATIONS
Trend Confirmation:
• Check if multiple timeframes confirm current chart trend
• Higher agreement = stronger trend confidence
• Use for position sizing decisions
Entry Timing:
• Wait for EMA crossover on chart timeframe
• Confirm with higher timeframe alignment
• Volume above average preferred
• RSI not in extreme zones
Divergence Detection:
• When lower timeframes diverge from higher
• May indicate trend exhaustion or reversal
• Requires additional confirmation
CUSTOMIZATION
EMA Settings:
• Adjust Fast/Slow lengths for different sensitivities
• Shorter periods = more responsive, more signals
• Longer periods = smoother, fewer signals
• Common alternatives: 10/30, 12/26, 50/200
Volume Filter:
• Enable for higher-quality signals (fewer false positives)
• Disable in always-liquid markets or for more signals
• Adjust MA length based on typical volume patterns
Display Options:
• Toggle EMAs, S/R levels, extended stats as needed
• Choose dashboard position to avoid chart overlap
• Adjust colors for visibility preferences
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ALERTS
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AVAILABLE ALERT CONDITIONS
1. Bullish EMA Cross (Volume Confirmed)
2. Bearish EMA Cross (Volume Confirmed)
3. Strong Bullish Alignment (4+ timeframes)
4. Strong Bearish Alignment (4+ timeframes)
5. Trend Strength Increasing (>16.67% jump)
6. Trend Strength Decreasing (>16.67% drop)
7. Excellent Trade Setup (5-star rating)
Alert messages use standard placeholders:
• {{ticker}} - Symbol name
• {{close}} - Current close price
• {{time}} - Bar timestamp
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LIMITATIONS & CONSIDERATIONS
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KNOWN LIMITATIONS
• Lower timeframe data may not be available on all symbols
• 1-minute data typically limited to recent history
• request.security() subject to TradingView data limits
• Dashboard requires screen space (may overlap on small screens)
• More complex calculations may affect load time on slower devices
NOT SUITABLE FOR
• Highly volatile/illiquid instruments (many false signals)
• News-driven markets during announcements
• Automated trading without additional filters
• Markets where EMA strategies don't perform well
DOES NOT PROVIDE
• Exact entry/exit prices
• Stop-loss or take-profit levels
• Position sizing recommendations
• Guaranteed profit signals
• Market predictions
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BEST PRACTICES
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RECOMMENDED USAGE
✓ Combine with price action analysis
✓ Use appropriate risk management
✓ Backtest on historical data before live use
✓ Adjust settings for specific market characteristics
✓ Wait for higher-quality setups in important trades
✓ Consider overall market context and fundamentals
NOT RECOMMENDED
✗ Using as standalone trading system without confirmation
✗ Trading every signal without discretion
✗ Ignoring risk management principles
✗ Trading without understanding the methodology
✗ Applying to unsuitable markets/timeframes
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EDUCATIONAL BACKGROUND
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EMA CROSSOVER STRATEGY
The Exponential Moving Average crossover is a classical trend-following technique:
• Golden Cross: Fast EMA crosses above Slow EMA (bullish signal)
• Death Cross: Fast EMA crosses below Slow EMA (bearish signal)
• Widely used since the 1970s in various markets
• More responsive than SMA due to exponential weighting
MULTI-TIMEFRAME ANALYSIS
Analyzing multiple timeframes helps traders:
• Identify alignment between short and long-term trends
• Reduce false signals from single-timeframe noise
• Understand market context across different horizons
• Make informed decisions about trade duration
VOLUME ANALYSIS
Volume confirmation adds reliability:
• High volume suggests institutional participation
• Low volume signals may indicate false breakouts
• Volume precedes price in many market theories
• Helps distinguish genuine moves from noise
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TECHNICAL IMPLEMENTATION
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CODE STRUCTURE
• Organized in clear sections with proper commenting
• Uses explicit type declarations (int, float, bool, color, string)
• Constants defined at top (BULLISH=1, BEARISH=-1, etc.)
• Functions documented with @function, @param, @returns
• Follows PineCoders naming conventions (camelCase variables)
PERFORMANCE OPTIMIZATION
• var keyword for table (created once, not every bar)
• Calculations cached where possible
• Dashboard updates only on last bar
• Minimal redundant security() calls
SECURITY IMPLEMENTATION
• Proper gaps and lookahead parameters
• No future data leakage
• Signals finalize on bar close
• Historical bars remain static
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VERSION INFORMATION
═══════════════════════════════════════════════════════════
Current Version: 2.0
Pine Script Version: 5
Last Updated: 2024
Developed by: Zakaria Safri
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SETTINGS REFERENCE
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EMA SETTINGS
• Fast EMA Length: 1-500 (default: 20)
• Slow EMA Length: 1-500 (default: 50)
VOLUME & MOMENTUM
• Use Volume Confirmation: true/false (default: true)
• Volume MA Length: 1-500 (default: 20)
• Show RSI Levels: true/false (default: true)
• RSI Length: 1-500 (default: 14)
PRICE ACTION FEATURES
• Show Price Distance: true/false (default: true)
• Show Key Levels: true/false (default: true)
• S/R Lookback Period: 10-500 (default: 50)
DISPLAY SETTINGS
• Show EMAs on Chart: true/false (default: true)
• Fast EMA Color: customizable (default: cyan)
• Slow EMA Color: customizable (default: orange)
• EMA Line Width: 1-5 (default: 2)
• Show Fill Between EMAs: true/false (default: true)
• Show Crossover Signals: true/false (default: true)
DASHBOARD SETTINGS
• Position: Top Left/Right, Bottom Left/Right
• Show Extended Statistics: true/false (default: true)
ALERT SETTINGS
• Alert on Multi-TF Alignment: true/false (default: true)
• Alert on Trend Strength Change: true/false (default: true)
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RISK DISCLAIMER
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This indicator is provided for educational and informational purposes only. It should not be considered financial advice or a recommendation to buy or sell any security.
IMPORTANT NOTICES:
• Past performance does not indicate future results
• All trading involves risk of capital loss
• No indicator guarantees profitable trades
• Always conduct independent research and analysis
• Use proper risk management and position sizing
• Consult a qualified financial advisor before trading
• The developer assumes no liability for trading losses
By using this indicator, you acknowledge that you understand these risks and accept full responsibility for your trading decisions.
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SUPPORT & CONTRIBUTIONS
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FEEDBACK WELCOME
• Constructive comments appreciated
• Bug reports help improve the indicator
• Feature suggestions considered for future versions
• Share your experience to help other users
OPEN SOURCE
This code is published as open source for the TradingView community to:
• Learn from the implementation
• Modify for personal use
• Understand multi-timeframe analysis techniques
If you find this indicator useful, please consider:
• Leaving a thoughtful review
• Sharing with other traders who might benefit
• Following for future updates and releases
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ADDITIONAL RESOURCES
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RECOMMENDED READING
• TradingView Pine Script documentation
• PineCoders community resources
• Technical analysis textbooks on moving averages
• Multi-timeframe trading strategy guides
• Risk management principles
RELATED CONCEPTS
• Trend following strategies
• Moving average convergence/divergence
• Multiple timeframe analysis
• Volume-price relationships
• Momentum indicators
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Thank you for using this indicator. Trade responsibly and continue learning!
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Triple Stochastic RSITriple Stochastic RSI (TSRSI)
The Triple Stochastic RSI is a momentum visualization tool designed to help identify potential market tops and bottoms with greater clarity. This indicator stacks three layers of smoothed StochRSI — Fast , Slow , and Slowest — each derived from increasingly longer RSI and Stochastic periods.
By analyzing how these layers interact, especially when the Slow (purple) and Slowest (orange) lines converge or cross near overbought or oversold zones, traders can spot high-probability reversal points. These moments often precede price turning points, and the signals gain strength when confirmed by divergences between price and indicator movement.
Key features include:
Triple StochRSI smoothing to capture short- to long-term momentum shifts.
Dynamic overbought/oversold signals with visual cross markers.
Built-in trend sentiment and average streak statistics.
Alerts for crossovers, trend shifts, and extended over/underperformance streaks.
Use it as a standalone momentum framework or as a supporting layer for divergence detection and market exhaustion analysis.
The stats table in your script provides insight into how long each Stochastic line (%K) typically stays above or below the 50 midline, and how the current streak compares to that average.
1. "Current" Column
This shows how many consecutive bars the %K has been:
Above 50 (▲)
OR Below 50 (▼)
It updates in real time on the last bar.
2. "Avg ▲ / Avg ▼" Column
These are historical averages based on your lookbackPeriod (default 1000 bars). It shows:
The average length of time %K stays above 50 (bullish bias)
The average time it stays below 50 (bearish bias)
Example Breakdown:
Let’s say the "Slow" row shows:
Current: 7 ▼
Avg ▲ / Avg ▼: 6 / 5
This means:
%K on the Slow lane has been below 50 for 7 bars
Historically, it only stays below 50 for about 5 bars on average
So, this bearish streak is already longer than usual
How to Use This Information:
A longer-than-average streak could imply a maturing move, potentially near exhaustion.
If current ▲ or ▼ streak is nearing or exceeding its average, it may warn of an upcoming shift.
Good for contextualizing trends and avoiding late entries.
Mythical EMAs + Dynamic VWAP BandThis indicator titled "Mythical EMAs + Dynamic VWAP Band." It overlays several volatility-adjusted Exponential Moving Averages (EMAs) on the chart, along with a Volume Weighted Average Price (VWAP) line and a dynamic band around it.
Additionally, it uses background coloring (clouds) to visualize bullish or bearish trends, with intensity modulated by the price's position relative to the VWAP.
The EMAs are themed with mythical names (e.g., Hermes for the 9-period EMA), but this is just stylistic flavoring and doesn't affect functionality.
I'll break it down section by section, explaining what each part does, how it works, and its purpose in the context of technical analysis. This indicator is designed for traders to identify trends, momentum, and price fairness relative to volume-weighted averages, with volatility adjustments to make the EMAs more responsive in volatile markets.
### 1. **Volatility Calculation (ATR)**
```pine
atrLength = 14
volatility = ta.atr(atrLength)
```
- **What it does**: Calculates the Average True Range (ATR) over 14 periods (a common default). ATR measures market volatility by averaging the true range (the greatest of: high-low, |high-previous close|, |low-previous close|).
- **Purpose**: This volatility value is used later to dynamically adjust the EMAs, making them more sensitive in high-volatility conditions (e.g., during market swings) and smoother in low-volatility periods. It helps the indicator adapt to changing market environments rather than using static EMAs.
### 2. **Custom Mythical EMA Function**
```pine
mythical_ema(src, length, base_alpha, vol_factor) =>
alpha = (2 / (length + 1)) * base_alpha * (1 + vol_factor * (volatility / src))
ema = 0.0
ema := na(ema ) ? src : alpha * src + (1 - alpha) * ema
ema
```
- **What it does**: Defines a custom function to compute a modified EMA.
- It starts with the standard EMA smoothing factor formula: `2 / (length + 1)`.
- Multiplies it by a `base_alpha` (a user-defined multiplier to tweak responsiveness).
- Adjusts further for volatility: Adds a term `(1 + vol_factor * (volatility / src))`, where `vol_factor` scales the impact, and `volatility / src` normalizes ATR relative to the source price (making it scale-invariant).
- The EMA is then calculated recursively: If the previous EMA is NA (e.g., at the start), it uses the current source value; otherwise, it weights the current source by `alpha` and the prior EMA by `(1 - alpha)`.
- **Purpose**: This creates "adaptive" EMAs that react faster in volatile markets (higher alpha when volatility is high relative to price) without overreacting in calm periods. It's an enhancement over standard EMAs, which use fixed alphas and can lag in choppy conditions. The mythical theme is just naming—functionally, it's a volatility-weighted EMA.
### 3. **Calculating the EMAs**
```pine
ema9 = mythical_ema(close, 9, 1.2, 0.5) // Hermes - quick & nimble
ema20 = mythical_ema(close, 20, 1.0, 0.3) // Apollo - short-term foresight
ema50 = mythical_ema(close, 50, 0.9, 0.2) // Athena - wise strategist
ema100 = mythical_ema(close, 100, 0.8, 0.1) // Zeus - powerful oversight
ema200 = mythical_ema(close, 200, 0.7, 0.05) // Kronos - long-term patience
```
- **What it does**: Applies the custom EMA function to the close price with varying lengths (9, 20, 50, 100, 200 periods), base alphas (decreasing from 1.2 to 0.7 for longer periods to make shorter ones more responsive), and volatility factors (decreasing from 0.5 to 0.05 to reduce volatility influence on longer-term EMAs).
- **Purpose**: These form a multi-timeframe EMA ribbon:
- Shorter EMAs (e.g., 9 and 20) capture short-term momentum.
- Longer ones (e.g., 200) show long-term trends.
- Crossovers (e.g., short EMA crossing above long EMA) can signal buy/sell opportunities. The volatility adjustment makes them "mythical" by adding dynamism, potentially improving signal quality in real markets.
### 4. **VWAP Calculation**
```pine
vwap_val = ta.vwap(close) // VWAP based on close price
```
- **What it does**: Computes the Volume Weighted Average Price (VWAP) using the built-in `ta.vwap` function, anchored to the close price. VWAP is the average price weighted by volume over the session (resets daily by default in Pine Script).
- **Purpose**: VWAP acts as a benchmark for "fair value." Prices above VWAP suggest bullishness (buyers in control), below indicate bearishness (sellers dominant). It's commonly used by institutional traders to assess entry/exit points.
### 5. **Plotting EMAs and VWAP**
```pine
plot(ema9, color=color.fuchsia, title='EMA 9 (Hermes)')
plot(ema20, color=color.red, title='EMA 20 (Apollo)')
plot(ema50, color=color.orange, title='EMA 50 (Athena)')
plot(ema100, color=color.aqua, title='EMA 100 (Zeus)')
plot(ema200, color=color.blue, title='EMA 200 (Kronos)')
plot(vwap_val, color=color.yellow, linewidth=2, title='VWAP')
```
- **What it does**: Overlays the EMAs and VWAP on the chart with distinct colors and titles for easy identification in TradingView's legend.
- **Purpose**: Visualizes the EMA ribbon and VWAP line. Traders can watch for EMA alignments (e.g., all sloping up for uptrend) or price interactions with VWAP.
### 6. **Dynamic VWAP Band**
```pine
band_pct = 0.005
vwap_upper = vwap_val * (1 + band_pct)
vwap_lower = vwap_val * (1 - band_pct)
p1 = plot(vwap_upper, color=color.new(color.yellow, 0), title="VWAP Upper Band")
p2 = plot(vwap_lower, color=color.new(color.yellow, 0), title="VWAP Lower Band")
fill_color = close >= vwap_val ? color.new(color.green, 80) : color.new(color.red, 80)
fill(p1, p2, color=fill_color, title="Dynamic VWAP Band")
```
- **What it does**: Creates a band ±0.5% around the VWAP.
- Plots the upper/lower bands with full transparency (color opacity 0, so lines are invisible).
- Fills the area between them dynamically: Semi-transparent green (opacity 80) if close ≥ VWAP (bullish bias), red if below (bearish bias).
- **Purpose**: Highlights deviations from VWAP visually. The color change provides an at-a-glance sentiment indicator—green for "above fair value" (potential strength), red for "below" (potential weakness). The narrow band (0.5%) focuses on short-term fairness, and the fill makes it easier to spot than just the line.
### 7. **Trend Clouds with VWAP Interaction**
```pine
bullish = ema9 > ema20 and ema20 > ema50
bearish = ema9 < ema20 and ema20 < ema50
bullish_above_vwap = bullish and close > vwap_val
bullish_below_vwap = bullish and close <= vwap_val
bearish_below_vwap = bearish and close < vwap_val
bearish_above_vwap = bearish and close >= vwap_val
bgcolor(bullish_above_vwap ? color.new(color.green, 50) : na, title="Bullish Above VWAP")
bgcolor(bullish_below_vwap ? color.new(color.green, 80) : na, title="Bullish Below VWAP")
bgcolor(bearish_below_vwap ? color.new(color.red, 50) : na, title="Bearish Below VWAP")
bgcolor(bearish_above_vwap ? color.new(color.red, 80) : na, title="Bearish Above VWAP")
```
- **What it does**: Defines trend conditions based on EMA alignments:
- Bullish: Shorter EMAs stacked above longer ones (9 > 20 > 50, indicating upward momentum).
- Bearish: The opposite (downward momentum).
- Sub-conditions combine with VWAP: E.g., bullish_above_vwap is true only if bullish and price > VWAP.
- Applies background colors (bgcolor) to the entire chart pane:
- Strong bullish (above VWAP): Green with opacity 50 (less transparent, more intense).
- Weak bullish (below VWAP): Green with opacity 80 (more transparent, less intense).
- Strong bearish (below VWAP): Red with opacity 50.
- Weak bearish (above VWAP): Red with opacity 80.
- If no condition matches, no color (na).
- **Purpose**: Creates "clouds" for trend visualization, enhanced by VWAP context. This helps traders confirm trends—e.g., a strong bullish cloud (darker green) suggests a high-conviction uptrend when price is above VWAP. The varying opacity differentiates signal strength: Darker for aligned conditions (trend + VWAP agreement), lighter for misaligned (potential weakening or reversal).
### Overall Indicator Usage and Limitations
- **How to use it**: Add this to a TradingView chart (e.g., stocks, crypto, forex). Look for EMA crossovers, price bouncing off EMAs/VWAP, or cloud color changes as signals. Bullish clouds with price above VWAP might signal buys; bearish below for sells.
- **Strengths**: Combines momentum (EMAs), volume (VWAP), and volatility adaptation for a multi-layered view. Dynamic colors make it intuitive.
- **Limitations**:
- EMAs lag in ranging markets; volatility adjustment helps but doesn't eliminate whipsaws.
- VWAP resets daily (standard behavior), so it's best for intraday/session trading.
- No alerts or inputs for customization (e.g., changeable lengths)—it's hardcoded.
- Performance depends on the asset/timeframe; backtest before using.
- **License**: Mozilla Public License 2.0, so it's open-source and modifiable.
Retail Sentiment Indicator - Multi-Asset CFD & Fear/Greed IndexRetail Sentiment Indicator - Multi-Asset CFD & Fear/Greed Index
Overview
The Retail Sentiment Indicator provides real-time sentiment data for major financial instruments including stocks, forex, commodities, and cryptocurrencies. This indicator displays retail trader positioning and market sentiment using CFD data and fear/greed indices.
Methodology and Scale Calculation
This indicator operates on a **-50 to +50 scale** with zero representing perfect market equilibrium.
Scale Interpretation:
- **Zero (0)**: Market balance - exactly 50% of investors buying, 50% selling
- **Positive values**: Majority buying pressure
- Example: If 63% of investors are buying, the indicator shows +13 (63 - 50 = +13)
- **Negative values**: Majority selling pressure
- Example: If 92% of investors are selling, the indicator shows -42 (50 - 92 = -42)
BTC Fear & Greed Index Scaling:
The original `BTC FEAR&GREED` index is natively scaled from 0-100 by its creator. In our indicator, this data has been rescaled to also fit the -50 to +50 range for consistency with other sentiment data sources.
This unified scaling approach allows for direct comparison across all instruments and data sources within the indicator.
-Important Data Source Selection-
Bitcoin (BTC) Data Sources
When viewing Bitcoin charts, the indicator offers **two different data sources**:
1. **Default Auto-Mode**: `BTCUSD Retail CFD` - Retail CFD traders sentiment data (automatically loaded).
2. **Manual Selection**: `BTC FEAR&GREED` - Fear & Greed Index from website: alternative dot me
**To access BTC Fear & Greed Index**: Input settings -> disable checkbox "Auto-load Sentiment Data" -> manually select "BTC FEAR&GREED" from the dropdown menu.
US Stock Market Data Sources
For US stocks and indices (S&P 500, NASDAQ, Dow Jones), there are **two data source options**:
1. **Default Auto-Mode**: Individual retail CFD sentiment data for each instrument
2. **Manual Selection**: `SNN FEAR&GREED` - SNN's Fear & Greed Index covering the overall US market sentiment. SNN was used as the name to avoid any potential trademark infringement.
**To access SNN Fear & Greed Index**: When viewing US market charts, disable in input settings checkbox "Auto-load Sentiment Data" and manually select "SNN FEAR&GREED" from the dropdown menu.
This distinction allows traders to choose between **instrument-specific retail sentiment** (auto-mode) or **broader market sentiment indices** (manual selection).
Features
- **Auto-Detection**: Automatically loads sentiment data based on the current chart symbol
- **Manual Selection**: Choose from 40+ supported instruments when auto-detection is unavailable
- **Multiple Data Sources**: Combines retail CFD sentiment with Fear & Greed indices
- **Visual Zones**: Clear greed/fear zones with color-coded backgrounds
- **Real-time Updates**: Live sentiment data from merged data sources
Supported Instruments
Major Indices
- S&P 500, NASDAQ, Dow Jones 30, DAX
Forex Pairs
- Major pairs: EURUSD, GBPUSD, USDJPY, USDCHF, USDCAD
- Cross pairs: EURJPY, GBPJPY, AUDUSD, NZDUSD, and 20+ others
Commodities
- Precious metals: Gold (XAUUSD), Silver (XAGUSD)
- Energy: WTI Oil
- Agricultural: Wheat, Coffee
- Industrial: Copper
Cryptocurrencies
- Bitcoin (BTC) sentiment data
- BTC & SNN Fear & Greed indices
How to Use
1. **Auto Mode** (Default): Enable "Auto-load Sentiment Data" to automatically display sentiment for the current chart symbol
2. **Manual Mode**: Disable auto-load and select from the dropdown menu for specific instruments
3. **Interpretation**:
- Values above 0 (green) indicate retail greed/bullish sentiment
- Values below 0 (red) indicate retail fear/bearish sentiment
- Fear & Greed indices use 0-100 scale (50 is neutral)
Data Sources
This indicator uses curated sentiment data from retail CFD providers and established fear/greed indices. Data is updated regularly and sourced from reputable financial data providers.
Trading Strategy & Market Philosophy
Contrarian Trading Approach
The primary purpose of this indicator is based on the fundamental market principle that **the majority of retail investors are often wrong**, and markets typically move opposite to the positions held by the majority of market participants.
Key Strategy Guidelines:
- **Contrarian Signal**: When the majority of users are positioned on one side of the market, there is statistically greater market advantage in taking positions in the opposite direction
- **Trend Exhaustion Signal**: An interesting observed phenomenon occurs when, during a long-lasting trend where the majority of investors have consistently been on the wrong side, the Sentiment indicator suddenly shows that the majority has flipped and opened positions in the direction of that long-running trend. This is often a signal of fuel exhaustion for further movement in that direction
Interpretation Examples
- High greed readings (majority bullish) → Consider bearish opportunities
- High fear readings (majority bearish) → Consider bullish opportunities
- Sudden sentiment flip during established trends → Potential trend reversal signal
Technical Notes
- Built with PineScript v6
- Dynamic symbol detection with fallback options
- Optimized for performance with minimal resource usage
- Color-coded visualization with customizable zones
Data Sources & Expansion
Acknowledgments
We extend our gratitude to **TradingView** for enabling the use of custom data feeds based on GitHub repositories, making this comprehensive sentiment analysis possible.
Data Expansion Opportunities
As the operator of this indicator, I am **open to suggestions for new data sources** that could be integrated and published. If you have ideas for additional instruments or sentiment data:
How to Submit Suggestions:
1. Send a **private message** with your proposal
2. Include: **instrument/data type**, **source**, and **brief description**
3. If technically feasible, we will work to import and publish the data
Data Infrastructure Status
Current Data Upload Process:
Please note that sentiment data uploads may occasionally experience minor interruptions. However, this should not pose significant issues as sentiment data typically changes gradually rather than rapidly.
Infrastructure Development:
We are actively working on establishing permanent cloud-based infrastructure to ensure continuous, automated data collection and upload processes. This will provide more reliable and consistent data availability in the future.
Disclaimer
This indicator is for educational and informational purposes only. Sentiment data should be used as part of a comprehensive trading strategy and not as the sole basis for trading decisions. Past performance does not guarantee future results. The contrarian approach described is a market theory and may not always produce profitable results.
Volume-Weighted Money Flow [sgbpulse]Overview
The VWMF indicator is an advanced technical analysis tool that combines and summarizes five leading momentum and volume indicators (OBV, PVT, A/D, CMF, MFI) into one clear oscillator. The indicator helps to provide a clear picture of market sentiment by measuring the pressure from buyers and sellers. Unlike single indicators, VWMF provides a comprehensive view of market money flow by weighting existing indicators and presenting them in a uniform and understandable format.
Indicator Components
VWMF combines the following indicators, each normalized to a range of 0 to 100 before being weighted:
On-Balance Volume (OBV): A cumulative indicator that measures positive and negative volume flow.
Price-Volume Trend (PVT): Similar to OBV, but incorporates relative price change for a more precise measure.
Accumulation/Distribution Line (A/D): Used to identify whether an asset is being bought (accumulated) or sold (distributed).
Chaikin Money Flow (CMF): Measures the money flow over a period based on the close price's position relative to the candle's range.
Money Flow Index (MFI): A momentum oscillator that combines price and volume to measure buying and selling pressure.
Understanding the Normalized Oscillators
The indicator combines the five different momentum indicators by normalizing each one to a uniform range of 0 to 100 .
Why is Normalization Important?
Indicators like OBV, PVT, and the A/D Line are cumulative indicators whose values can become very large. To assess their trend, we use a Moving Average as a dynamic reference line . The Moving Average allows us to understand whether the indicator is currently trending up or down relative to its average behavior over time.
How Does Normalization Work?
Our normalization fully preserves the original trend of each indicator.
For Cumulative Indicators (OBV, PVT, A/D): We calculate the difference between the current indicator value and its Moving Average. This difference is then passed to the normalization process.
- If the indicator is above its Moving Average, the difference will be positive, and the normalized value will be above 50.
- If the indicator is below its Moving Average, the difference will be negative, and the normalized value will be below 50.
Handling Extreme Values: To overcome the issue of extreme values in indicators like OBV, PVT, and the A/D Line , the function calculates the highest absolute value over the selected period. This value is used to prevent sharp spikes or drops in a single indicator from compromising the accuracy of the normalization over time. It's a sophisticated method that ensures the oscillators remain relevant and accurate.
For Bounded Indicators (CMF, MFI): These indicators already operate within a known range (for example, CMF is between -1 and 1, and MFI is between 0 and 100), so they are normalized directly without an additional reference line.
Reference Line Settings:
Moving Average Type: Allows the user to choose between a Simple Moving Average (SMA) and an Exponential Moving Average (EMA).
Volume Flow MA Length: Allows the user to set the lookback period for the Moving Average, which affects the indicator's sensitivity.
The 50 line serves as the new "center line." This ensures that, even after normalization, the determination of whether a specific indicator supports a bullish or bearish trend remains clear.
Settings and Visual Tools
The indicator offers several customization options to provide a rich analysis experience:
VWMF Oscillator (Blue Line): Represents the weighted average of all five indicators. Values above 50 indicate bullish momentum, and values below 50 indicate bearish momentum.
Strength Metrics (Bullish/Bearish Strength %): Two metrics that appear on the status line, showing the percentage of indicators supporting the current trend. They range from 0% to 100%, providing a quick view of the strength of the consensus.
Dynamic Background Colors: The background color of the chart automatically changes to bullish (a blue shade by default) or bearish (a default brown-gray shade) based on the trend. The transparency of the color shows the consensus strength—the more opaque the background, the more indicators support the trend.
Advanced Settings:
- Background Color Logic: Allows the user to choose the trigger for the background color: Weighted Value (based on the combined oscillator) or Strength (based on the majority of individual indicators).
- Weights: Provides full control over the weight of each of the five indicators in the final oscillator.
Using the Data Window
TradingView provides a useful Data Window that allows you to see the exact numerical values of each normalized oscillator separately, in addition to the trend strength data.
You can use this window to:
Get more detailed information on each indicator: Viewing the precise numerical data of each of the five indicators can help in making trading decisions.
Calibrate weights: If you want to manually adjust the indicator weights (in the settings menu), you can do so while tracking the impact of each indicator on the weighted oscillator in the Data Window.
The indicator's default setting is an equal weight of 20% for each of the five indicators.
Alert Conditions
The indicator comes with a variety of built-in alerts that can be configured through the TradingView alerts menu:
VWMF Cross Above 50: An alert when the VWMF oscillator crosses above the 50 line, indicating a potential bullish momentum shift.
VWMF Cross Below 50: An alert when the VWMF oscillator crosses below the 50 line, indicating a potential bearish momentum shift.
Bullish Strength: High But Not Absolute Consensus: An alert when the bullish trend strength reaches 60% or more but is less than 100%, indicating a high but not absolute consensus.
Bullish Strength at 100%: An alert when all five indicators (MFI, OBV, PVT, A/D, CMF) show bullish strength, indicating a full and absolute consensus.
Bearish Strength: High But Not Absolute Consensus: An alert when the bearish trend strength reaches 60% or more but is less than 100%, indicating a high but not absolute consensus.
Bearish Strength at 100%: An alert when all five indicators (MFI, OBV, PVT, A/D, CMF) show bearish strength, indicating a full and absolute consensus.
Summary
The VWMF indicator is a powerful, all-in-one tool for analyzing market momentum, money flow, and sentiment. By combining and normalizing five different indicators into a single oscillator, it offers a holistic and accurate view of the market's underlying trend. Its dynamic visual features and customizable settings, including the ability to adjust indicator weights, provide a flexible experience for both novice and experienced traders. The built-in alerts for momentum shifts and trend consensus make it an effective tool for spotting trading opportunities with confidence. In essence, VWMF distills complex market data into clear, actionable signals.
Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
log.info() - 5 Exampleslog.info() is one of the most powerful tools in Pine Script that no one knows about. Whenever you code, you want to be able to debug, or find out why something isn’t working. The log.info() command will help you do that. Without it, creating more complex Pine Scripts becomes exponentially more difficult.
The first thing to note is that log.info() only displays strings. So, if you have a variable that is not a string, you must turn it into a string in order for log.info() to work. The way you do that is with the str.tostring() command. And remember, it's all lower case! You can throw in any numeric value (float, int, timestamp) into str.string() and it should work.
Next, in order to make your output intelligible, you may want to identify whatever value you are logging. For example, if an RSI value is 50, you don’t want a bunch of lines that just say “50”. You may want it to say “RSI = 50”.
To do that, you’ll have to use the concatenation operator. For example, if you have a variable called “rsi”, and its value is 50, then you would use the “+” concatenation symbol.
EXAMPLE 1
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
log.info(“RSI= ” + str.tostring(rsi))
Example Output =>
RSI= 50
Here, we use double quotes to create a string that contains the name of the variable, in this case “RSI = “, then we concatenate it with a stringified version of the variable, rsi.
Now that you know how to write a log, where do you view them? There isn’t a lot of documentation on it, and the link is not conveniently located.
Open up the “Pine Editor” tab at the bottom of any chart view, and you’ll see a “3 dot” button at the top right of the pane. Click that, and right above the “Help” menu item you’ll see “Pine logs”. Clicking that will open that to open a pane on the right of your browser - replacing whatever was in the right pane area before. This is where your log output will show up.
But, because you’re dealing with time series data, using the log.info() command without some type of condition will give you a fast moving stream of numbers that will be difficult to interpret. So, you may only want the output to show up once per bar, or only under specific conditions.
To have the output show up only after all computations have completed, you’ll need to use the barState.islast command. Remember, barState is camelCase, but islast is not!
EXAMPLE 2
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
if barState.islast
log.info("RSI=" + str.tostring(rsi))
plot(rsi)
However, this can be less than ideal, because you may want the value of the rsi variable on a particular bar, at a particular time, or under a specific chart condition. Let’s hit these one at a time.
In each of these cases, the built-in bar_index variable will come in handy. When debugging, I typically like to assign a variable “bix” to represent bar_index, and include it in the output.
So, if I want to see the rsi value when RSI crosses above 0.5, then I would have something like
EXAMPLE 3
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
bix = bar_index
rsiCrossedOver = ta.crossover(rsi,0.5)
if rsiCrossedOver
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
plot(rsi)
Example Output =>
bix=19964 - RSI=51.8449459867
bix=19972 - RSI=50.0975830828
bix=19983 - RSI=53.3529808079
bix=19985 - RSI=53.1595745146
bix=19999 - RSI=66.6466337654
bix=20001 - RSI=52.2191767466
Here, we see that the output only appears when the condition is met.
A useful thing to know is that if you want to limit the number of decimal places, then you would use the command str.tostring(rsi,”#.##”), which tells the interpreter that the format of the number should only be 2 decimal places. Or you could round the rsi variable with a command like rsi2 = math.round(rsi*100)/100 . In either case you’re output would look like:
bix=19964 - RSI=51.84
bix=19972 - RSI=50.1
bix=19983 - RSI=53.35
bix=19985 - RSI=53.16
bix=19999 - RSI=66.65
bix=20001 - RSI=52.22
This would decrease the amount of memory that’s being used to display your variable’s values, which can become a limitation for the log.info() command. It only allows 4096 characters per line, so when you get to trying to output arrays (which is another cool feature), you’ll have to keep that in mind.
Another thing to note is that log output is always preceded by a timestamp, but for the sake of brevity, I’m not including those in the output examples.
If you wanted to only output a value after the chart was fully loaded, that’s when barState.islast command comes in. Under this condition, only one line of output is created per tick update — AFTER the chart has finished loading. For example, if you only want to see what the the current bar_index and rsi values are, without filling up your log window with everything that happens before, then you could use the following code:
EXAMPLE 4
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
//@version=6
indicator("log.info()")
rsi = ta.rsi(close,14)
bix = bar_index
if barstate.islast
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
Example Output =>
bix=20203 - RSI=53.1103309071
This value would keep updating after every new bar tick.
The log.info() command is a huge help in creating new scripts, however, it does have its limitations. As mentioned earlier, only 4096 characters are allowed per line. So, although you can use log.info() to output arrays, you have to be aware of how many characters that array will use.
The following code DOES NOT WORK! And, the only way you can find out why will be the red exclamation point next to the name of the indicator. That, and nothing will show up on the chart, or in the logs.
// CODE DOESN’T WORK
//@version=6
indicator("MW - log.info()")
var array rsi_arr = array.new()
rsi = ta.rsi(close,14)
bix = bar_index
rsiCrossedOver = ta.crossover(rsi,50)
if rsiCrossedOver
array.push(rsi_arr, rsi)
if barstate.islast
log.info("rsi_arr:" + str.tostring(rsi_arr))
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
plot(rsi)
// No code errors, but will not compile because too much is being written to the logs.
However, after putting some time restrictions in with the i_startTime and i_endTime user input variables, and creating a dateFilter variable to use in the conditions, I can limit the size of the final array. So, the following code does work.
EXAMPLE 5
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
// CODE DOES WORK
//@version=6
indicator("MW - log.info()")
i_startTime = input.time(title="Start", defval=timestamp("01 Jan 2025 13:30 +0000"))
i_endTime = input.time(title="End", defval=timestamp("1 Jan 2099 19:30 +0000"))
var array rsi_arr = array.new()
dateFilter = time >= i_startTime and time <= i_endTime
rsi = ta.rsi(close,14)
bix = bar_index
rsiCrossedOver = ta.crossover(rsi,50) and dateFilter // <== The dateFilter condition keeps the array from getting too big
if rsiCrossedOver
array.push(rsi_arr, rsi)
if barstate.islast
log.info("rsi_arr:" + str.tostring(rsi_arr))
log.info("bix=" + str.tostring(bix) + " - RSI=" + str.tostring(rsi))
plot(rsi)
Example Output =>
rsi_arr:
bix=20210 - RSI=56.9030578034
Of course, if you restrict the decimal places by using the rounding the rsi value with something like rsiRounded = math.round(rsi * 100) / 100 , then you can further reduce the size of your array. In this case the output may look something like:
Example Output =>
rsi_arr:
bix=20210 - RSI=55.6947486019
This will give your code a little breathing room.
In a nutshell, I was coding for over a year trying to debug by pushing output to labels, tables, and using libraries that cluttered up my code. Once I was able to debug with log.info() it was a game changer. I was able to start building much more advanced scripts. Hopefully, this will help you on your journey as well.
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE)
## Advanced Multi-Dimensional Mathematical Analysis System
*Where Quantum Mathematics Meets Market Structure*
---
## 🎓 THEORETICAL FOUNDATION
The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry.
### 🌊 Multi-Dimensional Volatility with Jump Detection
**Hawkes Process Implementation:**
The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects.
**Mathematical Foundation:**
```
Intensity λ(t) = μ + Σ α(t - Tᵢ)
```
Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99).
**Mahalanobis Distance Calculation:**
The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions:
- **Dimension 1:** Price volatility (standard deviation of returns)
- **Dimension 2:** Volume volatility (normalized volume fluctuations)
- **Dimension 3:** Range volatility (high-low spread variations)
- **Dimension 4:** Correlation volatility (price-volume relationship changes)
- **Dimension 5:** Microstructure volatility (intrabar positioning analysis)
This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches.
### 📐 Hurst Exponent Regime Detection
**Fractal Market Hypothesis Integration:**
The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification:
- **H > 0.6:** Trending (persistent) markets - momentum strategies optimal
- **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal
- **H ≈ 0.5:** Random walk markets - breakout strategies preferred
**Adaptive R/S Analysis:**
Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions:
```
H = log(R/S) / log(n)
```
Where R is the range of cumulative deviations and S is the standard deviation over period n.
**Dynamic Regime Classification:**
The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods.
### 🔄 Transfer Entropy Analysis
**Information Flow Quantification:**
Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements:
```
TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log
```
**Causality Detection:**
- **Volume → Price:** Indicates accumulation/distribution phases
- **Price → Volume:** Suggests retail participation or momentum chasing
- **Balanced Flow:** Market equilibrium or transition periods
The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows.
---
## 🔧 COMPREHENSIVE INPUT SYSTEM
### Core Parameters Group
**Primary Analysis Window (10-100, Default: 50)**
The fundamental lookback period affecting all calculations. Optimization by timeframe:
- **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements)
- **15 minute-1 hour:** 30-50 (balanced responsiveness and stability)
- **4 hour-daily:** 50-100 (smooth signals, reduced noise)
- **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60
**Signal Sensitivity (0.1-2.0, Default: 0.7)**
Master control affecting all threshold calculations:
- **Conservative (0.3-0.6):** High-quality signals only, fewer false positives
- **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles
- **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering
**Signal Generation Mode:**
- **Aggressive:** Any component signals (highest frequency)
- **Confluence:** 2+ components agree (balanced approach)
- **Conservative:** All 3 components align (highest quality)
### Volatility Jump Detection Group
**Volatility Dimensions (2-5, Default: 3)**
Determines the mathematical space complexity:
- **2D:** Price + Volume volatility (suitable for clean markets)
- **3D:** + Range volatility (optimal for most conditions)
- **4D:** + Correlation volatility (advanced multi-asset analysis)
- **5D:** + Microstructure volatility (maximum sensitivity)
**Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)**
Standard deviations required for volatility jump classification:
- **Cryptocurrency:** 2.0-2.5σ (naturally volatile)
- **Stock Indices:** 2.5-3.0σ (moderate volatility)
- **Forex Major Pairs:** 3.0-3.5σ (typically stable)
- **Commodities:** 2.0-3.0σ (varies by commodity)
**Jump Clustering Decay (0.5-0.99, Default: 0.85)**
Hawkes process memory parameter:
- **0.5-0.7:** Fast decay (jumps treated as independent)
- **0.8-0.9:** Moderate clustering (realistic market behavior)
- **0.95-0.99:** Strong clustering (crisis/event-driven markets)
### Hurst Exponent Analysis Group
**Calculation Method Options:**
- **Classic R/S:** Original Rescaled Range (fast, simple)
- **Adaptive R/S:** Dynamic windowing (recommended for trading)
- **DFA:** Detrended Fluctuation Analysis (best for noisy data)
**Trending Threshold (0.55-0.8, Default: 0.60)**
Hurst value defining persistent market behavior:
- **0.55-0.60:** Weak trend persistence
- **0.65-0.70:** Clear trending behavior
- **0.75-0.80:** Strong momentum regimes
**Mean Reversion Threshold (0.2-0.45, Default: 0.40)**
Hurst value defining anti-persistent behavior:
- **0.35-0.45:** Weak mean reversion
- **0.25-0.35:** Clear ranging behavior
- **0.15-0.25:** Strong reversion tendency
### Transfer Entropy Parameters Group
**Information Flow Analysis:**
- **Price-Volume:** Classic flow analysis for accumulation/distribution
- **Price-Volatility:** Risk flow analysis for sentiment shifts
- **Multi-Timeframe:** Cross-timeframe causality detection
**Maximum Lag (2-20, Default: 5)**
Causality detection window:
- **2-5 bars:** Immediate causality (scalping)
- **5-10 bars:** Short-term flow (day trading)
- **10-20 bars:** Structural flow (swing trading)
**Significance Threshold (0.05-0.3, Default: 0.15)**
Minimum entropy for signal generation:
- **0.05-0.10:** Detect subtle information flows
- **0.10-0.20:** Clear causality only
- **0.20-0.30:** Very strong flows only
---
## 🎨 ADVANCED VISUAL SYSTEM
### Tensor Volatility Field Visualization
**Five-Layer Resonance Bands:**
The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength:
- **Core Layer (Purple):** Primary tensor field with highest intensity
- **Layer 2 (Neutral):** Secondary mathematical resonance
- **Layer 3 (Info Blue):** Tertiary harmonic frequencies
- **Layer 4 (Warning Gold):** Outer field boundaries
- **Layer 5 (Success Green):** Maximum field extension
**Field Strength Calculation:**
```
Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity)
```
The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility.
**Radiation Line Network:**
During active tensor states, the system projects directional radiation lines showing field energy distribution:
- **8 Directional Rays:** Complete angular coverage
- **Tapering Segments:** Progressive transparency for natural visual flow
- **Pulse Effects:** Enhanced visualization during volatility jumps
### Dimensional Portal System
**Portal Mathematics:**
Dimensional portals visualize regime transitions using category theory principles:
- **Green Portals (◉):** Trending regime detection (appear below price for support)
- **Red Portals (◎):** Mean-reverting regime (appear above price for resistance)
- **Yellow Portals (○):** Random walk regime (neutral positioning)
**Tensor Trail Effects:**
Each portal generates 8 trailing particles showing mathematical momentum:
- **Large Particles (●):** Strong mathematical signal
- **Medium Particles (◦):** Moderate signal strength
- **Small Particles (·):** Weak signal continuation
- **Micro Particles (˙):** Signal dissipation
### Information Flow Streams
**Particle Stream Visualization:**
Transfer entropy creates flowing particle streams indicating information direction:
- **Upward Streams:** Volume leading price (accumulation phases)
- **Downward Streams:** Price leading volume (distribution phases)
- **Stream Density:** Proportional to information flow strength
**15-Particle Evolution:**
Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent.
### Fractal Matrix Grid System
**Multi-Timeframe Fractal Levels:**
The system calculates and displays fractal highs/lows across five Fibonacci periods:
- **8-Period:** Short-term fractal structure
- **13-Period:** Intermediate-term patterns
- **21-Period:** Primary swing levels
- **34-Period:** Major structural levels
- **55-Period:** Long-term fractal boundaries
**Triple-Layer Visualization:**
Each fractal level uses three-layer rendering:
- **Shadow Layer:** Widest, darkest foundation (width 5)
- **Glow Layer:** Medium white core line (width 3)
- **Tensor Layer:** Dotted mathematical overlay (width 1)
**Intelligent Labeling System:**
Smart spacing prevents label overlap using ATR-based minimum distances. Labels include:
- **Fractal Period:** Time-based identification
- **Topological Class:** Mathematical complexity rating (0, I, II, III)
- **Price Level:** Exact fractal price
- **Mahalanobis Distance:** Current mathematical field strength
- **Hurst Exponent:** Current regime classification
- **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡)
### Wick Pressure Analysis
**Rejection Level Mathematics:**
The system analyzes candle wick patterns to project future pressure zones:
- **Upper Wick Analysis:** Identifies selling pressure and resistance zones
- **Lower Wick Analysis:** Identifies buying pressure and support zones
- **Pressure Projection:** Extends lines forward based on mathematical probability
**Multi-Layer Glow Effects:**
Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart.
### Enhanced Regime Background
**Dynamic Intensity Mapping:**
Background colors reflect mathematical regime strength:
- **Deep Transparency (98% alpha):** Subtle regime indication
- **Pulse Intensity:** Based on regime strength calculation
- **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random)
**Smoothing Integration:**
Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts.
### Color Scheme System
**Six Professional Themes:**
- **Dark (Default):** Professional trading environment optimization
- **Light:** High ambient light conditions
- **Classic:** Traditional technical analysis appearance
- **Neon:** High-contrast visibility for active trading
- **Neutral:** Minimal distraction focus
- **Bright:** Maximum visibility for complex setups
Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences.
---
## 📊 INSTITUTIONAL-GRADE DASHBOARD
### Tensor Field Status Section
**Field Strength Display:**
Real-time Mahalanobis distance calculation with dynamic emoji indicators:
- **⚡ (Lightning):** Extreme field strength (>1.5× threshold)
- **● (Solid Circle):** Strong field activity (>1.0× threshold)
- **○ (Open Circle):** Normal field state
**Signal Quality Rating:**
Democratic algorithm assessment:
- **ELITE:** All 3 components aligned (highest probability)
- **STRONG:** 2 components aligned (good probability)
- **GOOD:** 1 component active (moderate probability)
- **WEAK:** No clear component signals
**Threshold and Anomaly Monitoring:**
- **Threshold Display:** Current mathematical threshold setting
- **Anomaly Level (0-100%):** Combined volatility and volume spike measurement
- **>70%:** High anomaly (red warning)
- **30-70%:** Moderate anomaly (orange caution)
- **<30%:** Normal conditions (green confirmation)
### Tensor State Analysis Section
**Mathematical State Classification:**
- **↑ BULL (Tensor State +1):** Trending regime with bullish bias
- **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias
- **◈ SUPER (Tensor State 0):** Random walk regime (neutral)
**Visual State Gauge:**
Five-circle progression showing tensor field polarity:
- **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment
- **⚪⚪🟡⚪⚪:** Neutral/transitional state
- **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment
**Trend Direction and Phase Analysis:**
- **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification
- **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength)
- **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength)
- **😴 CALM:** Low information flow (<1.0 flow strength)
### Trading Signals Section
**Real-Time Signal Status:**
- **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability
- **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability
- **Components (X/3):** Active algorithmic components
- **Mode Display:** Current signal generation mode
**Signal Strength Visualization:**
Color-coded component count:
- **Green:** 3/3 components (maximum confidence)
- **Aqua:** 2/3 components (good confidence)
- **Orange:** 1/3 components (moderate confidence)
- **Gray:** 0/3 components (no signals)
### Performance Metrics Section
**Win Rate Monitoring:**
Estimated win rates based on signal quality with emoji indicators:
- **🔥 (Fire):** ≥60% estimated win rate
- **👍 (Thumbs Up):** 45-59% estimated win rate
- **⚠️ (Warning):** <45% estimated win rate
**Mathematical Metrics:**
- **Hurst Exponent:** Real-time fractal dimension (0.000-1.000)
- **Information Flow:** Volume/price leading indicators
- **📊 VOL:** Volume leading price (accumulation/distribution)
- **💰 PRICE:** Price leading volume (momentum/speculation)
- **➖ NONE:** Balanced information flow
- **Volatility Classification:**
- **🔥 HIGH:** Above 1.5× jump threshold
- **📊 NORM:** Normal volatility range
- **😴 LOW:** Below 0.5× jump threshold
### Market Structure Section (Large Dashboard)
**Regime Classification:**
- **📈 TREND:** Hurst >0.6, momentum strategies optimal
- **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal
- **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred
**Mathematical Field Analysis:**
- **Dimensions:** Current volatility space complexity (2D-5D)
- **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00)
- **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal)
### Settings Summary Section (Large Dashboard)
**Active Configuration Display:**
- **Sensitivity:** Current master sensitivity setting
- **Lookback:** Primary analysis window
- **Theme:** Active color scheme
- **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA)
**Dashboard Sizing Options:**
- **Small:** Essential metrics only (mobile/small screens)
- **Normal:** Balanced information density (standard desktop)
- **Large:** Maximum detail (multi-monitor setups)
**Position Options:**
- **Top Right:** Standard placement (avoids price action)
- **Top Left:** Wide chart optimization
- **Bottom Right:** Recent price focus (scalping)
- **Bottom Left:** Maximum price visibility (swing trading)
---
## 🎯 SIGNAL GENERATION LOGIC
### Multi-Component Convergence System
**Component Signal Architecture:**
The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing:
**Volatility Component:**
- **Jump Detection:** Mahalanobis distance threshold breach
- **Hawkes Intensity:** Self-exciting process activation (>0.2)
- **Multi-dimensional:** Considers all volatility dimensions simultaneously
**Hurst Regime Component:**
- **Trending Markets:** Price above SMA-20 with positive momentum
- **Mean-Reverting Markets:** Price at Bollinger Band extremes
- **Random Markets:** Bollinger squeeze breakouts with directional confirmation
**Transfer Entropy Component:**
- **Volume Leadership:** Information flow from volume to price
- **Volume Spike:** Volume 110%+ above 20-period average
- **Flow Significance:** Above entropy threshold with directional bias
### Democratic Signal Weighting
**Signal Mode Implementation:**
- **Aggressive Mode:** Any single component triggers signal
- **Confluence Mode:** Minimum 2 components must agree
- **Conservative Mode:** All 3 components must align
**Momentum Confirmation:**
All signals require momentum confirmation:
- **Long Signals:** RSI >50 AND price >EMA-9
- **Short Signals:** RSI <50 AND price 0.6):**
- **Increase Sensitivity:** Catch momentum continuation
- **Lower Mean Reversion Threshold:** Avoid counter-trend signals
- **Emphasize Volume Leadership:** Institutional accumulation/distribution
- **Tensor Field Focus:** Use expansion for trend continuation
- **Signal Mode:** Aggressive or Confluence for trend following
**Range-Bound Markets (Hurst <0.4):**
- **Decrease Sensitivity:** Avoid false breakouts
- **Lower Trending Threshold:** Quick regime recognition
- **Focus on Price Leadership:** Retail sentiment extremes
- **Fractal Grid Emphasis:** Support/resistance trading
- **Signal Mode:** Conservative for high-probability reversals
**Volatile Markets (High Jump Frequency):**
- **Increase Hawkes Decay:** Recognize event clustering
- **Higher Jump Threshold:** Avoid noise signals
- **Maximum Dimensions:** Capture full volatility complexity
- **Reduce Position Sizing:** Risk management adaptation
- **Enhanced Visuals:** Maximum information for rapid decisions
**Low Volatility Markets (Low Jump Frequency):**
- **Decrease Jump Threshold:** Capture subtle movements
- **Lower Hawkes Decay:** Treat moves as independent
- **Reduce Dimensions:** Simplify analysis
- **Increase Position Sizing:** Capitalize on compressed volatility
- **Minimal Visuals:** Reduce distraction in quiet markets
---
## 🚀 ADVANCED TRADING STRATEGIES
### The Mathematical Convergence Method
**Entry Protocol:**
1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels
2. **Tensor Field Confirmation:** Verify field expansion supporting direction
3. **Portal Signal:** Wait for dimensional portal appearance
4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals
5. **Component Consensus:** Confirm 2+ components agree in Confluence mode
**Example Implementation:**
- Price approaching 21-period fractal high
- Tensor field expanding upward (bullish mathematical alignment)
- Green portal appears below price (trending regime confirmation)
- ELITE quality signal with 3/3 components active
- Enter long position with stop below fractal level
**Risk Management:**
- **Stop Placement:** Below/above fractal level that generated signal
- **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size)
- **Profit Targets:** Next fractal level or tensor field resistance
### The Regime Transition Strategy
**Regime Change Detection:**
1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds
2. **Portal Color Change:** Regime transitions show different portal colors
3. **Background Intensity:** Increasing regime background intensity
4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis)
**Trading Implementation:**
- **Trending Transitions:** Trade momentum breakouts, follow trend
- **Mean Reversion Transitions:** Trade range boundaries, fade extremes
- **Random Transitions:** Trade breakouts with tight stops
**Advanced Techniques:**
- **Multi-Timeframe:** Confirm regime on higher timeframe
- **Early Entry:** Enter on regime transition rather than confirmation
- **Regime Strength:** Larger positions during strong regime signals
### The Information Flow Momentum Strategy
**Flow Detection Protocol:**
1. **Monitor Transfer Entropy:** Watch for significant information flow shifts
2. **Volume Leadership:** Strong edge when volume leads price
3. **Flow Acceleration:** Increasing flow strength indicates momentum
4. **Directional Confirmation:** Ensure flow aligns with intended trade direction
**Entry Signals:**
- **Volume → Price Flow:** Enter during accumulation/distribution phases
- **Price → Volume Flow:** Enter on momentum confirmation breaks
- **Flow Reversal:** Counter-trend entries when flow reverses
**Optimization:**
- **Scalping:** Use immediate flow detection (2-5 bar lag)
- **Swing Trading:** Use structural flow (10-20 bar lag)
- **Multi-Asset:** Compare flow between correlated assets
### The Tensor Field Expansion Strategy
**Field Mathematics:**
The tensor field expansion indicates mathematical pressure building in market structure:
**Expansion Phases:**
1. **Compression:** Field contracts, volatility decreases
2. **Tension Building:** Mathematical pressure accumulates
3. **Expansion:** Field expands rapidly with directional movement
4. **Resolution:** Field stabilizes at new equilibrium
**Trading Applications:**
- **Compression Trading:** Prepare for breakout during field contraction
- **Expansion Following:** Trade direction of field expansion
- **Reversion Trading:** Fade extreme field expansion
- **Multi-Dimensional:** Consider all field layers for confirmation
### The Hawkes Process Event Strategy
**Self-Exciting Jump Trading:**
Understanding that market shocks cluster and create follow-on opportunities:
**Jump Sequence Analysis:**
1. **Initial Jump:** First volatility jump detected
2. **Clustering Phase:** Hawkes intensity remains elevated
3. **Follow-On Opportunities:** Additional jumps more likely
4. **Decay Period:** Intensity gradually decreases
**Implementation:**
- **Jump Confirmation:** Wait for mathematical jump confirmation
- **Direction Assessment:** Use other components for direction
- **Clustering Trades:** Trade subsequent moves during high intensity
- **Decay Exit:** Exit positions as Hawkes intensity decays
### The Fractal Confluence System
**Multi-Timeframe Fractal Analysis:**
Combining fractal levels across different periods for high-probability zones:
**Confluence Zones:**
- **Double Confluence:** 2 fractal levels align
- **Triple Confluence:** 3+ fractal levels cluster
- **Mathematical Confirmation:** Tensor field supports the level
- **Information Flow:** Transfer entropy confirms direction
**Trading Protocol:**
1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR
2. **Mathematical Support:** Verify tensor field alignment
3. **Signal Quality:** Wait for STRONG or ELITE signal
4. **Risk Definition:** Use fractal level for stop placement
5. **Profit Targeting:** Next major fractal confluence zone
---
## ⚠️ COMPREHENSIVE RISK MANAGEMENT
### Mathematical Position Sizing
**Mahalanobis Distance Integration:**
Position size should inversely correlate with mathematical field strength:
```
Position Size = Base Size × (Threshold / Mahalanobis Distance)
```
**Risk Scaling Matrix:**
- **Low Field Strength (<2.0):** Standard position sizing
- **Moderate Field Strength (2.0-3.0):** 75% position sizing
- **High Field Strength (3.0-4.0):** 50% position sizing
- **Extreme Field Strength (>4.0):** 25% position sizing or no trade
### Signal Quality Risk Adjustment
**Quality-Based Position Sizing:**
- **ELITE Signals:** 100% of planned position size
- **STRONG Signals:** 75% of planned position size
- **GOOD Signals:** 50% of planned position size
- **WEAK Signals:** No position or paper trading only
**Component Agreement Scaling:**
- **3/3 Components:** Full position size
- **2/3 Components:** 75% position size
- **1/3 Components:** 50% position size or skip trade
### Regime-Adaptive Risk Management
**Trending Market Risk:**
- **Wider Stops:** Allow for trend continuation
- **Trend Following:** Trade with regime direction
- **Higher Position Size:** Trend probability advantage
- **Momentum Stops:** Trail stops based on momentum indicators
**Mean-Reverting Market Risk:**
- **Tighter Stops:** Quick exits on trend continuation
- **Contrarian Positioning:** Trade against extremes
- **Smaller Position Size:** Higher reversal failure rate
- **Level-Based Stops:** Use fractal levels for stops
**Random Market Risk:**
- **Breakout Focus:** Trade only clear breakouts
- **Tight Initial Stops:** Quick exit if breakout fails
- **Reduced Frequency:** Skip marginal setups
- **Range-Based Targets:** Profit targets at range boundaries
### Volatility-Adaptive Risk Controls
**High Volatility Periods:**
- **Reduced Position Size:** Account for wider price swings
- **Wider Stops:** Avoid noise-based exits
- **Lower Frequency:** Skip marginal setups
- **Faster Exits:** Take profits more quickly
**Low Volatility Periods:**
- **Standard Position Size:** Normal risk parameters
- **Tighter Stops:** Take advantage of compressed ranges
- **Higher Frequency:** Trade more setups
- **Extended Targets:** Allow for compressed volatility expansion
### Multi-Timeframe Risk Alignment
**Higher Timeframe Trend:**
- **With Trend:** Standard or increased position size
- **Against Trend:** Reduced position size or skip
- **Neutral Trend:** Standard position size with tight management
**Risk Hierarchy:**
1. **Primary:** Current timeframe signal quality
2. **Secondary:** Higher timeframe trend alignment
3. **Tertiary:** Mathematical field strength
4. **Quaternary:** Market regime classification
---
## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS
### Advanced Mathematical Concepts
**Tensor Analysis in Markets:**
The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture.
**Information Theory Applications:**
Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior.
**Fractal Geometry in Trading:**
The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure.
**Stochastic Process Theory:**
The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects.
### Learning Progressive Complexity
**Beginner Mathematical Concepts:**
- **Volatility Dimensions:** Understanding multi-dimensional analysis
- **Regime Classification:** Learning market personality types
- **Signal Democracy:** Algorithmic consensus building
- **Visual Mathematics:** Interpreting mathematical concepts visually
**Intermediate Mathematical Applications:**
- **Mahalanobis Distance:** Statistical distance in multi-dimensional space
- **Rescaled Range Analysis:** Fractal dimension measurement
- **Information Entropy:** Quantifying uncertainty and causality
- **Field Theory:** Understanding mathematical fields in market context
**Advanced Mathematical Integration:**
- **Tensor Field Dynamics:** Multi-dimensional market force analysis
- **Stochastic Self-Excitation:** Event clustering and memory effects
- **Categorical Composition:** Mathematical signal combination theory
- **Topological Market Analysis:** Understanding market shape and connectivity
### Practical Mathematical Intuition
**Developing Market Mathematics Intuition:**
The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of:
- **How markets exhibit mathematical structure beneath apparent randomness**
- **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches**
- **How information flows through markets in measurable, predictable ways**
- **Why mathematical models provide probabilistic edges rather than certainties**
---
## 🔬 IMPLEMENTATION AND OPTIMIZATION
### Getting Started Protocol
**Phase 1: Observation (Week 1)**
1. **Apply with defaults:** Use standard settings on your primary trading timeframe
2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams
3. **Monitor dashboard:** Observe how metrics change with market conditions
4. **No trading:** Focus entirely on pattern recognition and understanding
**Phase 2: Pattern Recognition (Week 2-3)**
1. **Identify signal patterns:** Note what market conditions produce different signal qualities
2. **Regime correlation:** Observe how Hurst regimes affect signal performance
3. **Visual confirmation:** Learn to read tensor field expansion and portal signals
4. **Component analysis:** Understand which components drive signals in different markets
**Phase 3: Parameter Optimization (Week 4-5)**
1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument
2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe
3. **Sensitivity adjustment:** Balance signal frequency with quality
4. **Visual customization:** Optimize colors and intensity for your trading environment
**Phase 4: Live Implementation (Week 6+)**
1. **Paper trading:** Test signals with hypothetical trades
2. **Small position sizing:** Begin with minimal risk during learning phase
3. **Performance tracking:** Monitor actual vs. expected signal performance
4. **Continuous optimization:** Refine settings based on real performance data
### Performance Monitoring System
**Signal Quality Tracking:**
- **ELITE Signal Win Rate:** Track highest quality signals separately
- **Component Performance:** Monitor which components provide best signals
- **Regime Performance:** Analyze performance across different market regimes
- **Timeframe Analysis:** Compare performance across different session times
**Mathematical Metric Correlation:**
- **Field Strength vs. Performance:** Higher field strength should correlate with better performance
- **Component Agreement vs. Win Rate:** More component agreement should improve win rates
- **Regime Alignment vs. Success:** Trading with mathematical regime should outperform
### Continuous Optimization Process
**Monthly Review Protocol:**
1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown
2. **Parameter Assessment:** Evaluate if current settings remain optimal
3. **Market Adaptation:** Adjust for changes in market character or volatility
4. **Component Weighting:** Consider if certain components should receive more/less emphasis
**Quarterly Deep Analysis:**
1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid
2. **Regime Distribution:** Analyze time spent in different market regimes
3. **Signal Evolution:** Track how signal characteristics change over time
4. **Correlation Analysis:** Monitor correlations between different mathematical components
---
## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS
### Revolutionary Mathematical Integration
**First-Ever Implementations:**
1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility
2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes
3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation
4. **Democratic Component Voting:** First algorithmic consensus system for signal generation
5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels
### Advanced Visualization Innovations
**Mathematical Visualization Breakthroughs:**
- **Tensor Field Radiation:** Visual representation of mathematical field energy
- **Dimensional Portal System:** Category theory visualization for regime transitions
- **Information Flow Streams:** Real-time visual display of market information transfer
- **Multi-Layer Fractal Grid:** Intelligent spacing and projection system
- **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength
### Practical Trading Innovations
**Trading System Advances:**
- **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence
- **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality
- **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering
- **Component Performance Tracking:** Real-time monitoring of algorithmic component success
- **Field-Strength Position Sizing:** Mathematical volatility integration for risk management
---
## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS
### Mathematical Model Limitations
**Understanding Model Boundaries:**
While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations:
- **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements
- **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely
- **Model Risk:** Complex models can fail during unprecedented market conditions
- **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions
### Proper Implementation Guidelines
**Risk Management Requirements:**
- **Never Risk More Than 2% Per Trade:** Regardless of signal quality
- **Diversification Mandatory:** Don't rely solely on mathematical signals
- **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence
- **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters
**Realistic Expectations:**
- **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes
- **Learning Curve Required:** Complex mathematical concepts require time to master
- **Market Adaptation Necessary:** Parameters must evolve with changing market conditions
- **Continuous Education Important:** Understanding underlying mathematics improves application
### Ethical Trading Considerations
**Market Impact Awareness:**
- **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants
- **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure
- **Sharing Knowledge:** Consider educational contributions to trading community
- **Fair Market Participation:** Use mathematical advantages responsibly within market framework
### Professional Development Path
**Skill Development Sequence:**
1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application
2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals
3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights
4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution
---
## 🔮 CONCLUSION
The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability.
### Mathematical Innovation Legacy
This indicator establishes new paradigms in technical analysis:
- **Tensor analysis for market volatility understanding**
- **Stochastic self-excitation for event clustering prediction**
- **Information theory for causality-based trade generation**
- **Democratic algorithmic consensus for signal quality enhancement**
- **Mathematical field visualization for intuitive market understanding**
### Practical Trading Revolution
Beyond mathematical innovation, the TMAE transforms practical trading:
- **Quality-rated signals replace binary buy/sell decisions**
- **Regime-adaptive strategies automatically optimize for market personality**
- **Multi-dimensional risk management integrates mathematical volatility measures**
- **Visual mathematical concepts make complex analysis immediately interpretable**
- **Educational value creates lasting improvement in trading understanding**
### Future-Proof Design
The mathematical foundations ensure lasting relevance:
- **Universal mathematical principles transcend market evolution**
- **Multi-dimensional analysis adapts to new market structures**
- **Regime detection automatically adjusts to changing market personalities**
- **Component democracy allows for future algorithmic additions**
- **Mathematical visualization scales with increasing market complexity**
### Commitment to Excellence
The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value.
### Trading with Mathematical Precision
In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals.
By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics.
### Final Perspective
Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure.
Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior.
Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE.
*"In mathematics, you don't understand things. You just get used to them." - John von Neumann*
*With the TMAE, mathematical market understanding becomes not just possible, but intuitive.*
— Dskyz, Trade with insight. Trade with anticipation.
Percent Change of Range Candles - FullPercent Change of Range Candles – Full (PCR Full)
Description:
PCR Full is a custom momentum indicator that measures the percentage price change relative to a defined range, offering traders a unique way to evaluate strength, direction, and potential reversals in price movement.
How it works:
The main value (PCR) is calculated by comparing the price change over a selected number of candles (length) to the range between the highest high and lowest low in the same period.
This percentage change is normalized and visualized with dynamic candles on the subgraph.
Reference levels at +100, +50, 0, -50, and -100 serve as key zones to indicate potential overbought/oversold conditions, continuation, or neutrality.
How to read the indicator:
1. Trend continuation:
When PCR breaks above +50 and holds, it often confirms a strong bullish move.
Similarly, values below -50 and staying low signal a bearish continuation.
2. Wick behavior (volatility insight):
Long wicks on PCR candles suggest uncertainty or failed breakout attempts.
Short or no wicks with strong body color show stable momentum and conviction.
On the chart, multiple long wicks near -50 suggest bulls are attempting to push price upward, but lack the strength — until a confirmed breakout.
3. Polarity transition (Bearish to Bullish or vice versa):
A transition from negative PCR values to above zero shows that the market is possibly turning.
Especially if PCR climbs gradually and stabilizes above zero, it indicates a developing bullish phase.
Components:
Main PCR line: Color-coded (green for rising, red for falling).
Open Average (gray line): Smooths recent PCR values, indicating balance.
High/Low adaptive bands: Adjust dynamically to PCR polarity.
PCR Candles: Visualize OHLC of PCR data for enhanced interpretation.
Suggested use cases:
Enter trend trades when PCR crosses +50 or -50 with volume or price confirmation.
Watch for reversal signs near ±100 if PCR fails to break further.
Use 0 line as a neutral zone — markets hovering near 0 are often in consolidation.
Combine with price action or oscillators like RSI/MACD for additional signals.
Customization:
The length input allows users to define the range for PCR calculations, making it adjustable to various timeframes and strategies (scalping, intraday, swing).
Canuck Trading Projection IndicatorCanuck Trading Projection Indicator
Overview
The Canuck Trading Projection Indicator is a powerful PineScript v6 tool designed for TradingView to project potential bullish and bearish price trajectories based on historical price and volume movements. It provides traders with actionable insights by estimating future price targets and assigning confidence levels to each outlook, helping to identify probable market directions across any timeframe. Ideal for both short-term and long-term traders, this indicator combines momentum analysis, RSI filtering, support/resistance detection, and time-weighted trend analysis to deliver robust projections.
Features
Bullish and Bearish Projections: Forecasts price targets for upward (bullish) and downward (bearish) movements over a user-defined projection period (default 20 bars).
Confidence Levels: Assigns percentage confidence scores to each outlook, reflecting the likelihood of the projected price based on historical trends, volatility, and volume.
RSI Filter: Incorporates a 14-period Relative Strength Index (RSI) to validate trends, requiring RSI > 50 for bullish and RSI < 50 for bearish signals.
Support/Resistance Detection: Adjusts confidence levels when projections are near key swing highs/lows (within 2% of average price), boosting confidence by 5% for alignments.
Time-Based Weighting: Prioritizes recent price movements in trend analysis, giving more weight to newer bars for improved relevance.
Customizable Inputs: Allows users to tailor lookback period, projection bars, RSI period, confidence threshold, colors, and label positioning.
Forced Label Spacing: Prevents overlap of bullish and bearish text labels, even for tight projections, using fixed vertical slots when price differences are small (<2% of average price).
Timeframe Flexibility: Works seamlessly across all TradingView timeframes (e.g., 30-minute, hourly, daily, weekly, monthly), adapting projections to the chart’s resolution.
Clean Visualization: Displays projections as green (bullish) and red (bearish) dashed lines, with non-overlapping text labels at the projection endpoints showing price targets and confidence levels.
How It Works
The indicator analyzes historical price and volume data over a user-defined lookback period (default 50 bars) to calculate:
Momentum: Combines price changes and volume to assess trend strength, using a weighted moving average (WMA) for directional bias.
Trend Analysis: Counts bullish (price up, volume above average, RSI > 50) and bearish (price down, volume above average, RSI < 50) trends, weighting recent bars more heavily.
Projections:
Bullish Slope: Positive or flat when momentum is upward, scaled by price change and momentum intensity.
Bearish Slope: Negative or flat when momentum is downward, amplified by bearish confidence for stronger projections.
Projects prices forward by 20 bars (default) using current close plus slope times projection bars.
Confidence Levels:
Base confidence derived from the proportion of bullish/bearish trends, with a 5% minimum to avoid zero confidence.
Adjusted by volatility (lower volatility increases confidence), volume trends, and proximity to support/resistance levels.
Visualization:
Draws projection lines from the current close to the 20-bar future target.
Places text labels at line endpoints, showing price targets and confidence percentages, with forced spacing for readability.
Input Parameters
Lookback Period (default: 50): Number of bars for historical analysis (minimum 10).
Projection Bars (default: 20): Number of bars to project forward (minimum 5).
Confidence Threshold (default: 0.6): Minimum confidence for strong trend indication (0.1 to 1.0).
Bullish Projection Line Color (default: Green): Color for bullish projection line and label.
Bearish Projection Line Color (default: Red): Color for bearish projection line and label.
RSI Period (default: 14): Period for RSI momentum filter (minimum 5).
Label Vertical Offset (%) (default: 1.0): Base offset for labels as a percentage of price range (0.1% to 5.0%).
Minimum Label Spacing (%) (default: 2.0): Minimum vertical spacing between labels for tight projections (0.5% to 10.0%).
Usage Instructions
Add to Chart: Copy the script into TradingView’s Pine Editor, save, and add the indicator to your chart.
Select Timeframe: Apply to any timeframe (e.g., 30-minute, hourly, daily, weekly, monthly) to match your trading strategy.
Interpret Outputs:
Green Line/Label: Bullish price target and confidence (e.g., "Bullish: 414.37, Confidence: 35%").
Red Line/Label: Bearish price target and confidence (e.g., "Bearish: 279.08, Confidence: 41.3%").
Higher confidence indicates a stronger likelihood of the projected outcome.
Adjust Inputs:
Modify Lookback Period to focus on shorter/longer historical trends (e.g., 20 for short-term, 100 for long-term).
Change Projection Bars to adjust forecast horizon (e.g., 10 for shorter, 50 for longer).
Tweak RSI Period or Confidence Threshold for sensitivity to momentum or trend strength.
Customize Colors for visual preference.
Increase Minimum Label Spacing if labels overlap in volatile markets.
Combine with Analysis: Use alongside other indicators (e.g., moving averages, Bollinger Bands) or fundamental analysis to confirm signals, as projections are probabilistic.
Example: TSLA Across Timeframes
Using live TSLA data (close ~346.46 USD, May 31, 2025), the indicator produces:
30-Minute: Bullish 341.93 (13.3%), Bearish 327.96 (86.7%) – Strong bearish sentiment due to intraday volatility.
1-Hour: Bullish 342.00 (33.9%), Bearish 327.50 (62.3%) – Bearish but less intense, reflecting hourly swings.
4-Hour: Bullish 345.52 (73.4%), Bearish 344.44 (19.0%) – Flat outlook, indicating consolidation.
Daily: Bullish 391.26 (68.8%), Bearish 302.22 (31.2%) – Bullish bias from recent uptrend, bearish tempered by longer lookback.
Weekly: Bullish 414.37 (35.0%), Bearish 279.08 (41.3%) – Wide range, reflecting annual volatility.
Monthly: Bullish 396.70 (54.9%), Bearish 296.93 (10.2%) – Long-term bullish optimism.
These results align with market dynamics: short-term intervals capture volatility, while longer intervals smooth trends, providing balanced outlooks.
Notes
Accuracy: Projections are estimates based on historical data and should be used with other analysis tools. Confidence levels indicate likelihood, not certainty.
Timeframe Sensitivity: Short-term intervals (e.g., 30-minute) show larger price swings and higher confidence due to volatility, while longer intervals (e.g., monthly) are more stable.
Customization: Adjust inputs to match your trading style (e.g., shorter lookback for day trading, longer for swing trading).
Performance: Tested on volatile stocks like TSLA, NVIDIA, and others, ensuring robust performance across markets.
Limitations: May produce conservative bearish projections in strong uptrends due to momentum weighting. Adjust lookback or projection_bars for sensitivity.
Feedback
If you encounter issues (e.g., label overlap, projection mismatches), please share your timeframe, settings, or a screenshot. Suggestions for enhancements (e.g., additional filters, visual tweaks) are welcome!
Disclaimer
The Canuck Trading Projection Indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves significant risks, and past performance is not indicative of future results. Always perform your own due diligence and consult a qualified financial advisor before making trading decisions.
Mandelbrot-Fibonacci Cascade Vortex (MFCV)Mandelbrot-Fibonacci Cascade Vortex (MFCV) - Where Chaos Theory Meets Sacred Geometry
A Revolutionary Synthesis of Fractal Mathematics and Golden Ratio Dynamics
What began as an exploration into Benoit Mandelbrot's fractal market hypothesis and the mysterious appearance of Fibonacci sequences in nature has culminated in a groundbreaking indicator that reveals the hidden mathematical structure underlying market movements. This indicator represents months of research into chaos theory, fractal geometry, and the golden ratio's manifestation in financial markets.
The Theoretical Foundation
Mandelbrot's Fractal Market Hypothesis Traditional efficient market theory assumes normal distributions and random walks. Mandelbrot proved markets are fractal - self-similar patterns repeating across all timeframes with power-law distributions. The MFCV implements this through:
Hurst Exponent Calculation: H = log(R/S) / log(n/2)
Where:
R = Range of cumulative deviations
S = Standard deviation
n = Period length
This measures market memory:
H > 0.5: Trending (persistent) behavior
H = 0.5: Random walk
H < 0.5: Mean-reverting (anti-persistent) behavior
Fractal Dimension: D = 2 - H
This quantifies market complexity, where higher dimensions indicate more chaotic behavior.
Fibonacci Vortex Theory Markets don't move linearly - they spiral. The MFCV reveals these spirals using Fibonacci sequences:
Vortex Calculation: Vortex(n) = Price + sin(bar_index × φ / Fn) × ATR(Fn) × Volume_Factor
Where:
φ = 0.618 (golden ratio)
Fn = Fibonacci number (8, 13, 21, 34, 55)
Volume_Factor = 1 + (Volume/SMA(Volume,50) - 1) × 0.5
This creates oscillating spirals that contract and expand with market energy.
The Volatility Cascade System
Markets exhibit volatility clustering - Mandelbrot's "Noah Effect." The MFCV captures this through cascading volatility bands:
Cascade Level Calculation: Level(i) = ATR(20) × φ^i
Each level represents a different fractal scale, creating a multi-dimensional view of market structure. The golden ratio spacing ensures harmonic resonance between levels.
Implementation Architecture
Core Components:
Fractal Analysis Engine
Calculates Hurst exponent over user-defined periods
Derives fractal dimension for complexity measurement
Identifies market regime (trending/ranging/chaotic)
Fibonacci Vortex Generator
Creates 5 independent spiral oscillators
Each spiral follows a Fibonacci period
Volume amplification creates dynamic response
Cascade Band System
Up to 8 volatility levels
Golden ratio expansion between levels
Dynamic coloring based on fractal state
Confluence Detection
Identifies convergence of vortex and cascade levels
Highlights high-probability reversal zones
Real-time confluence strength calculation
Signal Generation Logic
The MFCV generates two primary signal types:
Fractal Signals: Generated when:
Hurst > 0.65 (strong trend) AND volatility expanding
Hurst < 0.35 (mean reversion) AND RSI < 35
Trend strength > 0.4 AND vortex alignment
Cascade Signals: Triggered by:
RSI > 60 AND price > SMA(50) AND bearish vortex
RSI < 40 AND price < SMA(50) AND bullish vortex
Volatility expansion AND trend strength > 0.3
Both signals implement a 15-bar cooldown to prevent overtrading.
Advanced Input System
Mandelbrot Parameters:
Cascade Levels (3-8):
Controls number of volatility bands
Crypto: 5-7 (high volatility)
Indices: 4-5 (moderate volatility)
Forex: 3-4 (low volatility)
Hurst Period (20-200):
Lookback for fractal calculation
Scalping: 20-50
Day Trading: 50-100
Swing Trading: 100-150
Position Trading: 150-200
Cascade Ratio (1.0-3.0):
Band width multiplier
1.618: Golden ratio (default)
Higher values for trending markets
Lower values for ranging markets
Fractal Memory (21-233):
Fibonacci retracement lookback
Uses Fibonacci numbers for harmonic alignment
Fibonacci Vortex Settings:
Spiral Periods:
Comma-separated Fibonacci sequence
Fast: "5,8,13,21,34" (scalping)
Standard: "8,13,21,34,55" (balanced)
Extended: "13,21,34,55,89" (swing)
Rotation Speed (0.1-2.0):
Controls spiral oscillation frequency
0.618: Golden ratio (balanced)
Higher = more signals, more noise
Lower = smoother, fewer signals
Volume Amplification:
Enables dynamic spiral expansion
Essential for stocks and crypto
Disable for forex (no central volume)
Visual System Architecture
Cascade Bands:
Multi-level volatility envelopes
Gradient coloring from primary to secondary theme
Transparency increases with distance from price
Fill between bands shows fractal structure
Vortex Spirals:
5 Fibonacci-period oscillators
Blue above price (bullish pressure)
Red below price (bearish pressure)
Multiple display styles: Lines, Circles, Dots, Cross
Dynamic Fibonacci Levels:
Auto-updating retracement levels
Smart update logic prevents disruption near levels
Distance-based transparency (closer = more visible)
Updates every 50 bars or on volatility spikes
Confluence Zones:
Highlighted boxes where indicators converge
Stronger confluence = stronger support/resistance
Key areas for reversal trades
Professional Dashboard System
Main Fractal Dashboard: Displays real-time:
Hurst Exponent with market state
Fractal Dimension with complexity level
Volatility Cascade status
Vortex rotation impact
Market regime classification
Signal strength percentage
Active indicator levels
Vortex Metrics Panel: Shows:
Individual spiral deviations
Convergence/divergence metrics
Real-time vortex positioning
Fibonacci period performance
Fractal Metrics Display: Tracks:
Dimension D value
Market complexity rating
Self-similarity strength
Trend quality assessment
Theory Guide Panel: Educational reference showing:
Mandelbrot principles
Fibonacci vortex concepts
Dynamic trading suggestions
Trading Applications
Trend Following:
High Hurst (>0.65) indicates strong trends
Follow cascade band direction
Use vortex spirals for entry timing
Exit when Hurst drops below 0.5
Mean Reversion:
Low Hurst (<0.35) signals reversal potential
Trade toward vortex spiral convergence
Use Fibonacci levels as targets
Tighten stops in chaotic regimes
Breakout Trading:
Monitor cascade band compression
Watch for vortex spiral alignment
Volatility expansion confirms breakouts
Use confluence zones for targets
Risk Management:
Position size based on fractal dimension
Wider stops in high complexity markets
Tighter stops when Hurst is extreme
Scale out at Fibonacci levels
Market-Specific Optimization
Cryptocurrency:
Cascade Levels: 5-7
Hurst Period: 50-100
Rotation Speed: 0.786-1.2
Enable volume amplification
Stock Indices:
Cascade Levels: 4-5
Hurst Period: 80-120
Rotation Speed: 0.5-0.786
Moderate cascade ratio
Forex:
Cascade Levels: 3-4
Hurst Period: 100-150
Rotation Speed: 0.382-0.618
Disable volume amplification
Commodities:
Cascade Levels: 4-6
Hurst Period: 60-100
Rotation Speed: 0.5-1.0
Seasonal adjustment consideration
Innovation and Originality
The MFCV represents several breakthrough innovations:
First Integration of Mandelbrot Fractals with Fibonacci Vortex Theory
Unique synthesis of chaos theory and sacred geometry
Novel application of Hurst exponent to spiral dynamics
Dynamic Volatility Cascade System
Golden ratio-based band expansion
Multi-timeframe fractal analysis
Self-adjusting to market conditions
Volume-Amplified Vortex Spirals
Revolutionary spiral calculation method
Dynamic response to market participation
Multiple Fibonacci period integration
Intelligent Signal Generation
Cooldown system prevents overtrading
Multi-factor confirmation required
Regime-aware signal filtering
Professional Analytics Dashboard
Institutional-grade metrics display
Real-time fractal analysis
Educational integration
Development Journey
Creating the MFCV involved overcoming numerous challenges:
Mathematical Complexity: Implementing Hurst exponent calculations efficiently
Visual Clarity: Displaying multiple indicators without cluttering
Performance Optimization: Managing array operations and calculations
Signal Quality: Balancing sensitivity with reliability
User Experience: Making complex theory accessible
The result is an indicator that brings PhD-level mathematics to practical trading while maintaining visual elegance and usability.
Best Practices and Guidelines
Start Simple: Use default settings initially
Match Timeframe: Adjust parameters to your trading style
Confirm Signals: Never trade MFCV signals in isolation
Respect Regimes: Adapt strategy to market state
Manage Risk: Use fractal dimension for position sizing
Color Themes
Six professional themes included:
Fractal: Balanced blue/purple palette
Golden: Warm Fibonacci-inspired colors
Plasma: Vibrant modern aesthetics
Cosmic: Dark mode optimized
Matrix: Classic green terminal
Fire: Heat map visualization
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice. While the MFCV reveals deep market structure through advanced mathematics, markets remain inherently unpredictable. Past performance does not guarantee future results.
The integration of Mandelbrot's fractal theory with Fibonacci vortex dynamics provides unique market insights, but should be used as part of a comprehensive trading strategy. Always use proper risk management and never risk more than you can afford to lose.
Acknowledgments
Special thanks to Benoit Mandelbrot for revolutionizing our understanding of markets through fractal geometry, and to the ancient mathematicians who discovered the golden ratio's universal significance.
"The geometry of nature is fractal... Markets are fractal too." - Benoit Mandelbrot
Revealing the Hidden Order in Market Chaos Trade with Mathematical Precision. Trade with MFCV.
— Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Liquid Pulse Liquid Pulse by Dskyz (DAFE) Trading Systems
Liquid Pulse is a trading algo built by Dskyz (DAFE) Trading Systems for futures markets like NQ1!, designed to snag high-probability trades with tight risk control. it fuses a confluence system—VWAP, MACD, ADX, volume, and liquidity sweeps—with a trade scoring setup, daily limits, and VIX pauses to dodge wild volatility. visuals include simple signals, VWAP bands, and a dashboard with stats.
Core Components for Liquid Pulse
Volume Sensitivity (volumeSensitivity) controls how much volume spikes matter for entries. options: 'Low', 'Medium', 'High' default: 'High' (catches small spikes, good for active markets) tweak it: 'Low' for calm markets, 'High' for chaos.
MACD Speed (macdSpeed) sets the MACD’s pace for momentum. options: 'Fast', 'Medium', 'Slow' default: 'Medium' (solid balance) tweak it: 'Fast' for scalping, 'Slow' for swings.
Daily Trade Limit (dailyTradeLimit) caps trades per day to keep risk in check. range: 1 to 30 default: 20 tweak it: 5-10 for safety, 20-30 for action.
Number of Contracts (numContracts) sets position size. range: 1 to 20 default: 4 tweak it: up for big accounts, down for small.
VIX Pause Level (vixPauseLevel) stops trading if VIX gets too hot. range: 10 to 80 default: 39.0 tweak it: 30 to avoid volatility, 50 to ride it.
Min Confluence Conditions (minConditions) sets how many signals must align. range: 1 to 5 default: 2 tweak it: 3-4 for strict, 1-2 for more trades.
Min Trade Score (Longs/Shorts) (minTradeScoreLongs/minTradeScoreShorts) filters trade quality. longs range: 0 to 100 default: 73 shorts range: 0 to 100 default: 75 tweak it: 80-90 for quality, 60-70 for volume.
Liquidity Sweep Strength (sweepStrength) gauges breakouts. range: 0.1 to 1.0 default: 0.5 tweak it: 0.7-1.0 for strong moves, 0.3-0.5 for small.
ADX Trend Threshold (adxTrendThreshold) confirms trends. range: 10 to 100 default: 41 tweak it: 40-50 for trends, 30-35 for weak ones.
ADX Chop Threshold (adxChopThreshold) avoids chop. range: 5 to 50 default: 20 tweak it: 15-20 to dodge chop, 25-30 to loosen.
VWAP Timeframe (vwapTimeframe) sets VWAP period. options: '15', '30', '60', '240', 'D' default: '60' (1-hour) tweak it: 60 for day, 240 for swing, D for long.
Take Profit Ticks (Longs/Shorts) (takeProfitTicksLongs/takeProfitTicksShorts) sets profit targets. longs range: 5 to 100 default: 25.0 shorts range: 5 to 100 default: 20.0 tweak it: 30-50 for trends, 10-20 for chop.
Max Profit Ticks (maxProfitTicks) caps max gain. range: 10 to 200 default: 60.0 tweak it: 80-100 for big moves, 40-60 for tight.
Min Profit Ticks to Trail (minProfitTicksTrail) triggers trailing. range: 1 to 50 default: 7.0 tweak it: 10-15 for big gains, 5-7 for quick locks.
Trailing Stop Ticks (trailTicks) sets trail distance. range: 1 to 50 default: 5.0 tweak it: 8-10 for room, 3-5 for fast locks.
Trailing Offset Ticks (trailOffsetTicks) sets trail offset. range: 1 to 20 default: 2.0 tweak it: 1-2 for tight, 5-10 for loose.
ATR Period (atrPeriod) measures volatility. range: 5 to 50 default: 9 tweak it: 14-20 for smooth, 5-9 for reactive.
Hardcoded Settings volLookback: 30 ('Low'), 20 ('Medium'), 11 ('High') volThreshold: 1.5 ('Low'), 1.8 ('Medium'), 2 ('High') swingLen: 5
Execution Logic Overview trades trigger when confluence conditions align, entering long or short with set position sizes. exits use dynamic take-profits, trailing stops after a profit threshold, hard stops via ATR, and a time stop after 100 bars.
Features Multi-Signal Confluence: needs VWAP, MACD, volume, sweeps, and ADX to line up.
Risk Control: ATR-based stops (capped 15 ticks), take-profits (scaled by volatility), and trails.
Market Filters: VIX pause, ADX trend/chop checks, volatility gates. Dashboard: shows scores, VIX, ADX, P/L, win %, streak.
Visuals Simple signals (green up triangles for longs, red down for shorts) and VWAP bands with glow. info table (bottom right) with MACD momentum. dashboard (top right) with stats.
Chart and Backtest:
NQ1! futures, 5-minute chart. works best in trending, volatile conditions. tweak inputs for other markets—test thoroughly.
Backtesting: NQ1! Frame: Jan 19, 2025, 09:00 — May 02, 2025, 16:00 Slippage: 3 Commission: $4.60
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Disclaimer this is for education only. past results don’t predict future wins. trading’s risky—only use money you can lose. backtest and validate before going live. (expect moderators to nitpick some random chart symbol rule—i’ll fix and repost if they pull it.)
About the Author Dskyz (DAFE) Trading Systems crafts killer trading algos. Liquid Pulse is pure research and grit, built for smart, bold trading. Use it with discipline. Use it with clarity. Trade smarter. I’ll keep dropping badass strategies ‘til i build a brand or someone signs me up.
2025 Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
Fibonacci - RSI OscillatorIndicator Overview
The Fibonacci RSI Oscillator calculates the Relative Strength Index (RSI) based on a dynamically adjusting level derived from recent price action and a fixed Fibonacci ratio (0.236). This differs from standard RSI, which is calculated directly on the closing price. The objective is to measure momentum relative to a level that adapts to recent peaks and valleys.
Core Calculation Mechanism
Peak/Valley Tracking: The script identifies the highest high (state_peak) and lowest low (state_valley) since the last detected change in short-term directional bias (state_dir).
Dynamic Level Calculation: A level (state_dyn_level) is calculated using a fixed 0.236 Fibonacci ratio relative to the tracked peak and valley:
If bias is up: state_dyn_level = state_peak - (state_peak - state_valley) * 0.236
If bias is down: state_dyn_level = state_valley + (state_peak - state_valley) * 0.236
This level adjusts automatically when a new peak or valley is established in the current directional bias. If price crosses the dynamic level against the current bias, the bias flips, and the level recalculates.
Optional Source Smoothing: The calculated state_dyn_level can optionally be smoothed using a user-selected moving average (SMA, EMA, WMA, HMA, RMA) before the RSI calculation.
RSI Calculation: The standard RSI formula is applied to the (optionally smoothed) state_dyn_level series to produce the primary oscillator value (val_primary_osc).
Signal Line: A moving average (type and length configurable) is calculated on the val_primary_osc to generate the val_sig_line.
Key Features & Components
Dynamic Fibonacci Level: The core input for the RSI calculation, based on recent peaks/valleys and the 0.236 ratio.
Fibonacci Level RSI: The primary oscillator line representing the RSI of the dynamic level.
Signal Line: A moving average of the primary RSI line.
Overbought/Oversold Levels: User-defined threshold lines.
Optional Source Smoothing: Configurable MA smoothing applied to the dynamic level before RSI calculation.
Gradient RSI Color : Option to color the primary RSI line based on its value relative to OB/Mid/OS levels.
Zone & OB/OS Fills: Visual fills for the 0-50 / 50-100 zones and specific fills when the RSI enters OB/OS territory.
Background Gradient: Optional vertical background color gradient based on the RSI's position between 0 and 100.
Configurable Parameters: Inputs for lengths, MA types, OB/OS levels, colors, line widths, and feature toggles.
Visual Elements Explained
Fibonacci Level RSI Line: The main plotted oscillator (color/gradient/width configurable).
Signal Line: The moving average of the RSI line (color/width/MA type configurable).
OB/OS Lines: Horizontal lines plotted at the set OB/OS levels (color/width configurable).
Mid-Line (50): Horizontal line plotted at 50 (color/width configurable).
Zone Fills:
Background fill between 0-50 and 50-100 (colors configurable).
Conditional fill between the RSI line and the 50 line when RSI > OB level or RSI < OS level (colors configurable).
Background Gradient: Optional background coloring where transparency varies vertically with the RSI level (base colors and transparency range configurable).
Configuration Options
Users can adjust the following parameters in the indicator settings:
Smoothing: Enable/disable dynamic level smoothing; set length and MA type.
RSI: Set the RSI calculation length.
Signal Line: Set the signal line smoothing length and MA type.
Levels: Define Overbought and Oversold numeric thresholds.
Visuals: Configure colors and widths for the RSI line, signal line, OB/OS lines, mid-line, zone fills, and OB/OS fills.
Gradients: Enable/disable and configure colors for the RSI line gradient; enable/disable and configure colors/transparency for the background gradient.
Interpretation Notes
The oscillator reflects the momentum of the dynamic Fibonacci level, not directly the price. Divergences, OB/OS readings, and signal line crossovers should be interpreted in this context.
The behavior may differ from standard RSI, potentially offering a smoother output or highlighting different momentum patterns depending on market structure and volatility.
As with any indicator, signals should be used in conjunction with other analysis methods and risk management practices. It is not designed as a standalone trading system.
Risk Disclaimer:
Trading involves significant risk. This indicator is provided for analytical purposes only and does not constitute financial advice. Past performance is not indicative of future results. Use sound risk management practices and never trade with capital you cannot afford to lose.
