Fair Value Gap - FVG - HistogramThis indicator uses a histogram to represent "fair value gaps" ("FVG"). FVG is a popular pattern among modern traders.
This document describes the purpose of the script and discusses the conceptual meaning of "fair value," as well as the connotations attached to it.
█🚀 Based on the previous script - improved clarity
This indicator is a modified version of the "Three Bar Gap (Simple Price Action - with 1 line plot)" indicator, which is also available as open source and can be applied to a chart as a complementary tool along with this indicator.
Differences:
The previous version introduced a "Threshold filter" to reduce the number of lines plotted on charts. This filter introduced two additional parameters for users to consider (ATR length and multiplier). These parameters made the indicator more complicated than intended.
To address this issue of having too many lines in the former version, I proposed a spin-off on this version: It's to consider plotting the magnitude of the FVGs on a histogram instead of using lines on a price chart. In my opinion, a histogram is more suitable for decision-making because it lays out data points side-by-side as bins, which makes comparisons much clearer.
Minor FVGs are expected to have smaller bins compared to their neighboring bins, and in extreme cases, the bins will become seemingly invisible due to the auto-adjusted scale of the y-axis. Therefore, there is no need to filter out any data, and all FVGs can be included in this spin-off version.
█🚀 Candlestick patterns - revisited
This script calculates the displacement of highs and lows over three consecutive bars.
A) Down move: When the high of the recent-confirmed bar is lower than the low of the previous-previous candle.
B) Up move: When the low of the recently-confirmed bar is higher than the high of the previous-previous candle.
█🚀 Parameters
Core Functionality
The purpose of this indicator is to generate bins representing the magnitude of FVGs in the form of a histogram to facilitate the visualization of price movements.
The act of "finding FVGs" does not require any inputs, but users can still customize the colors of the bins to indicate the direction of movement.
Auxiliary functionality: “Key level finder” by searching for large FVGs
The following inputs are optional, in fact, the entire feature can be toggled on/off.
In this example, setting the lookback at 20 means the script will generate a signal if the current histogram bin is taller than all previous bins over the past 20 bars.
█🚀 Applications
Tall histogram bins = key levels .
Traders should observe key levels for entry or exit opportunities.
It is important to note that this indicator was designed for standard time-based charts.
On a separate note, FVGs will not appear in Renko charts with fixed-size bricks. This is because the bricks align with their neighboring bricks. When the bricks are fixed, any displacement between highs and lows within less than or equal to three bars will be zero.
The concept of a "gap" is used to illustrate that price follows a jump-diffusion process, and time intervals can be assigned arbitrarily on the x-axis without needing fixed intervals. This idea was briefly discussed in the previous script's write-up.
█🚀 FAQ: Does it repaint?
No. And please continue reading.
Bins are plotted with a one-bar delay. It only takes one bar for the FVG to become confirmed. Lag is beneficial because it clarifies the need for traders to wait for the bar to close and for the signals to become confirmed before entering or exiting a trade. Experienced traders know that prices tend to retrace, so there is no need to chase. An added bar of delay proves to be useful.
█🚀 Opinion: The term “fair value” can be misleading
Those who come from traditional finance may find the term "fair value gap" somewhat insulting. When encountering the phrase, it can feel like a group of aliens from "Planet Technical Analysis" have intrusively landed on your planet and assertively redefined what "fair value" is supposed to mean.
So, what does "fair value" mean in the realm of technical analysis?
In the world of corporate finance, "fair value" is a subjective estimate of what buyers and sellers are hypothetically willing to pay or accept. Buy-side and sell-side analysts use their own methodologies to determine what constitutes "fair value". These approaches may be based on income, asset, or market comparables. Regardless of the approach used, subjectivity is inherent, and results depend on fundamental data provided by the numbers on financial statements. Valuations are unrelated to candlestick patterns .
When dealing with financial statements, finance professionals who are non-market-participants, such as those working in group reporting practices for reporting issuers, or those hired as external auditors, as required by regulators, may also question what constitutes "fair value". The main concerns always revolve around the assumptions used in valuation models; these are inputs that ultimately require management's judgment, and if not critically questioned, valuations as reported in the statements could end up becoming materially bogus. Both IFRS and U.S. GAAP define "fair value" with the same intended meaning in terms of definitions. We will not delve into the details here. The main point is that "fair value" from a financial reporting perspective has nothing to do with candlesticks .
If a price is already quoted in an actively traded market, you can refer to it to obtain what is known as "mark-to-market". This involves simply referring to the bid or ask price on the reporting date, and you're done - there's no need to read candlesticks !
"Fair value" is a neutral term used by finance professionals in all domains. It is not meant to imply that something is actually "fair." Paying the "fair value" for an asset can still result in overpaying or underpaying for what the asset is worth, depending on different model assumptions. The point is, candlesticks are irrelevant to the analysis of what is considered "fair value" in the realm of traditional finance.
That being said, there is no definitive answer as to why people refer to this pattern as a "fair value gap". It's like one of those oddball interview questions asking you to explain why tennis balls are fuzzy. Whatever answer you give, it's important to note that the subject itself is trivial.
Emphasis of matter on why "fair value" can be misleading
The previous paragraphs were not intended to attack ideas from the realm of technical analysis, nor to assert the true meaning, or lack of meaning, of the term "fair value". Words are constantly evolving. If the term "fair value gap" becomes more widely used to describe the displacement of highs and lows over three bars, then let's call it a "fair value gap".
To be clear, I argue that the term "fair value gap" should not be given a positive connotation. Traders should interpret the word "fair" neutrally. Although these signals occur frequently, if you trade every time there is a signal, you will overtrade and incur astronomical transaction costs over the long run, which can lead to losses.
█🚀 Conclusion:
In the end, what matters is how you apply FVG to trading. As mentioned in the "Applications" section above, traders should look for large FVGs - indicated by tall histogram bins - to identify key levels.
Cerca negli script per "bar"
MARS - Moving Average Relative StrengthThe original idea from this script is from the script " Percentage Relative Strength " by dman103 . The original script compared a symbol to an index by their everyday percentage change. The symbol percentage was subtracted from percentage change of the index, & the results were then smoothed by moving averages.
Instead of daily percentage changes, this script directly calculates relative strength via a moving average. We call this simpler approach as MARS (Moving Average Relative Strength) .
MARS compares a symbol to the index by making use of the price's distance from a moving average. By default, we compare the distance from the 50-day simple moving average of the stock vs that of the index. Both the type & the length of the moving average is customisable.
Background color indicates the index being above or below its moving average.
Blue background: index is above its moving average
Pink background: index is below its moving average
The histogram indicates whether the stock is under-performing or out-performing the index.
Up-bars : stock is out-performing the index i.e. between the stock & the index, the difference between the distance to/from the 50-day moving average is a positive value.
Down-bars : stock is under-performing the index i.e. between the stock & the index, the difference between the distance to/from the 50-day moving average is a negative value.
The color of the histogram indicates the type of out-performance or under-performance. There can be a total of 6 such colors:
Relative out-performance : both index & stock are bearish, but stock is less bearish. The script prints light green up-bars on a pink background.
Gross out-performance : both index & stock are bullish, but stock is more bullish. The script prints green up-bars on a blue background.
Absolute out-performance : index is bearish, but stock is bullish! The script prints blue up-bars on a pink background.
Relative under-performance : both index & stock are bullish, but stock is less bullish. The script prints light red bars on a blue background.
Gross under-performance : both index & stock are bearish, but stock is more bearish. The script prints dark red bars on a pink background.
Absolute under-performance : index is bullish, but stock is bearish! The script prints black down-bars on a blue background.
Additional customisation options:
Paint bars option changes the bar colors to mirror the histogram colors.
Easy colors option just changes the histogram colors to either blue or pink, indicating out-performance or under-performance, respectively. This is when the trader does not wish to demarcate between the above-mentioned 6 conditions.
RedK EVEREX - Effort Versus Results ExplorerRedK EVEREX is an experimental indicator that explores "Volume Price Analysis" basic concepts and Wyckoff law "Effort versus Result" - by inspecting the relative volume (effort) and the associated (relative) price action (result) for each bar - showing the analysis as an easy to read "stacked bands" visual. From that analysis, we calculate a "Relative Rate of Flow" - an easy to use +100/-100 oscilator that can be used to trigger a signal when a bullish or bearish mode is detected for a certain user-selected length of bars.
Basic Concepts of VPA
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(The topics of VPA & Wyckoff Effort vs Results law are too comprehensive to cover here - So here's just a very basic summary - please review these topics in detail in various sources available here in TradingView or on the web)
* Volume Price Analysis (VPA) is the examination of the number of shares or contracts of a security that have been traded in a given period, and the associated price movement. By analyzing trends in volume in conjunction with price movements, traders can determine the significance of changes in price and what may unfold in the near future.
* Oftentimes, high volumes of trading can infer a lot about investors’ outlook on a market or security. A significant price increase along with a significant volume increase, for example, could be a credible sign of a continued bullish trend or a bullish reversal. Adversely, a significant price decrease with a significant volume increase can point to a continued bearish trend or a bearish trend reversal.
* Incorporating volume into a trading decision can help an investor to have a more balanced view of all the broad market factors that could be influencing a security’s price, which helps an investor to make a more informed decision.
* Wyckoff's law "Effort versus results" dictates that large effort is expected to be accompanied with big results - which means that we should expect to see a big price move (result) associated with a large relative volume (effort) for a certain trading period (bar).
* The way traders use this concept in chart analysis is to mainly look for imbalances or invalidation. for example, when we observe a large relative volume that is associated with very limited price change - that should trigger an early flag/warning sign that the current price trend is facing challenges and may be an early sign of "reversal" - this applies in both bearish and bullish conditions. on the other hand, when price starts to trend in a certain direction and that's associated with increasing volume, that can act as kind of validation, or a confirmation that the market supports that move.
How does EVEREX work
---------------------------------
* EVEREX inspects each bar and calculates a relative value for volume (effort) and "strength of price movement" (result) compared to a specified lookback period. The results are then visualized as stacked bands - the lower band represents the relative volume, the upper band represents the relative price strength - with clear color coding for easier analysis.
* The scale of the band is initially set to 100 (each band can occupy up to 50) - and that can be changed in the settings to 200 or 400 - mainly to allow a "zoom in" on the bands.
* Reading the resulting stacked bands makes it easier to see "balanced" volume/price action (where both bands are either equally strong, or equally weak), or when there's imbalance between volume and price (for example, a compression bar will show with high volume band and very small/tiny price action band) - another favorite pattern in VPA is the "Ease of Move", which will show as a relatively small volume band associated with a large "price action band" (either bullish or bearish) .. and so on.
* a bit of a techie piece: why the use of a custom "Normalize()" function to calculate "relative" values in EVEREX?
When we evaluate a certain value against an average (for example, volume) we need a mechanism to deal with "super high" values that largely exceed that average - I also needed a mechanism that mimics how a trader looks at a volume bar and decides that this volume value is super low, low, average, above average, high or super high -- the issue with using a stoch() function, which is the usual technique for comparing a data point against a lookback average, is that this function will produce a "zero" for low values, and cause a large distortion of the next few "ratios" when super large values occur in the data series - i researched multiple techniques here and decided to use the custom Normalize() function - and what i found is, as long as we're applying the same formula consistently to the data series, since it's all relative to itself, we can confidently use the result. Please feel free to play around with this part further if you like - the code is commented for those who would like to research this further.
* Overall, the hope is to make the bar-by-bar analysis easier and faster for traders who apply VPA concepts in their trading
What is RROF?
--------------------------
* Once we have the values of relative volume and relative price strength, it's easy from there to combine these values into a moving index that can be used to track overall strength and detect reversals in market direction - if you think about it this a very similar concept to a volume-weighted RSI. I call that index the "Relative Rate of Flow" - or RROF (cause we're not using the direct volume and price values in the calculation, but rather relative values that we calculated with the proprietary "Normalize" function in the script.
* You can show RROF as a single or double-period - and you can customize it in terms of smoothing, and signal line - and also utilize the basic alerts to get notified when a change in strength from one side to the other (bullish vs bearish) is detected
* In the chart above, you can see how the RROF was able to detect change in market condition from Bearsh to Bullish - then from Bullish to Bearish for TSLA with good accuracy.
Other Usage Options in EVEREX
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* I wrote EVEREX with a lot of flexibility and utilization in mind, while focusing on a clean and easy to use visual - EVEREX should work with any time frame and any instrument - in instruments with no volume data, only price data will be used.
* You can completely hide the "EVEREX bands" and use EVEREX as a single or dual period strength indicator (by exposing the Bias/Sentiment plot which is hidden by default) -
here's how this setup would look like - in this mode, you will basically be using EVEREX the same way you're using a volume-weighted RSI
* or you can hide the bias/sentiment, and expose the Bulls & Bears plots (using the indicator's "Style" tab), and trade it like a Bull/Bear Pressure Index like this
* you can choose Moving Average type for most plot elements in EVEREX, including how to deal with the Lookback averaging
* you can set EVEREX to a different time frame than the chart
* did i mention basic alerts in this v1.0 ?? There's room to add more VPA-specific alerts in future version (for example, when Ease-of-Move or Compression bars are detected...etc) - let me know if the comments what you want to see
Final Thoughts
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* EVEREX can be used for bar-by-bar VPA analysis - There are so much literature out there about VPA and it's highly recommended that traders read more about what VPA is and how it works - as it adds an interesting (and critical) dimension to technical analysis and will improve decision making
* RROF is a "strength indicator" - it does not track price values (levels) or momentum - as you will see when you use it, the price can be moving up, while the RROF signal line starts moving down, reflecting decreasing strength (or otherwise, increasing bear strength) - So if you incorporate EVEREX in your trading you will need to use it alongside other momentum and price value indicators (like MACD, MA's, Trend Channels, Support & Resistance Lines, Fib / Donchian..etc) - to use for trade confirmation
Diamonds✋ Experimental script where a diamond shape is created by making 4 lines around each bar which touches the edge of the bar.
𒀸 Example of how it works:
Create the left upper line:
A) Calculate middle of the bar
B) Calculate which one is highest -> close or open
'Draw' imaginary line from A to B (A starts 1 bar back)
Adjust height of A by adding 2/3 of the difference between A & B
𒓕 That's it!
𒀸 This technique can be developed further by anyone who's inspired.
• For now, I've just added an option where you can extend 2 lines of 1 specific bar
𒓕 Settings ➺ extend lines ➺ toggle on/off ➺ type ➺ which bar back
𒀸 X bars back sets the max bars in history
• Since this script uses line.new() , this results in maximum 500 lines to be drawn.
Each Diamand Bar contains 4 lines, resulting in maximum 125 Diamond Bars .
𒀸 Standard Candles ~ Diamond Bars
Cheers!
Ehlers Two-Pole Predictor [Loxx]Ehlers Two-Pole Predictor is a new indicator by John Ehlers . The translation of this indicator into PineScript™ is a collaborative effort between @cheatcountry and I.
The following is an excerpt from "PREDICTION" , by John Ehlers
Niels Bohr said “Prediction is very difficult, especially if it’s about the future.”. Actually, prediction is pretty easy in the context of technical analysis . All you have to do is to assume the market will behave in the immediate future just as it has behaved in the immediate past. In this article we will explore several different techniques that put the philosophy into practice.
LINEAR EXTRAPOLATION
Linear extrapolation takes the philosophical approach quite literally. Linear extrapolation simply takes the difference of the last two bars and adds that difference to the value of the last bar to form the prediction for the next bar. The prediction is extended further into the future by taking the last predicted value as real data and repeating the process of adding the most recent difference to it. The process can be repeated over and over to extend the prediction even further.
Linear extrapolation is an FIR filter, meaning it depends only on the data input rather than on a previously computed value. Since the output of an FIR filter depends only on delayed input data, the resulting lag is somewhat like the delay of water coming out the end of a hose after it supplied at the input. Linear extrapolation has a negative group delay at the longer cycle periods of the spectrum, which means water comes out the end of the hose before it is applied at the input. Of course the analogy breaks down, but it is fun to think of it that way. As shown in Figure 1, the actual group delay varies across the spectrum. For frequency components less than .167 (i.e. a period of 6 bars) the group delay is negative, meaning the filter is predictive. However, the filter has a positive group delay for cycle components whose periods are shorter than 6 bars.
Figure 1
Here’s the practical ramification of the group delay: Suppose we are projecting the prediction 5 bars into the future. This is fine as long as the market is continued to trend up in the same direction. But, when we get a reversal, the prediction continues upward for 5 bars after the reversal. That is, the prediction fails just when you need it the most. An interesting phenomenon is that, regardless of how far the extrapolation extends into the future, the prediction will always cross the signal at the same spot along the time axis. The result is that the prediction will have an overshoot. The amplitude of the overshoot is a function of how far the extrapolation has been carried into the future.
But the overshoot gives us an opportunity to make a useful prediction at the cyclic turning point of band limited signals (i.e. oscillators having a zero mean). If we reduce the overshoot by reducing the gain of the prediction, we then also move the crossing of the prediction and the original signal into the future. Since the group delay varies across the spectrum, the effect will be less effective for the shorter cycles in the data. Nonetheless, the technique is effective for both discretionary trading and automated trading in the majority of cases.
EXPLORING THE CODE
Before we predict, we need to create a band limited indicator from which to make the prediction. I have selected a “roofing filter” consisting of a High Pass Filter followed by a Low Pass Filter. The tunable parameter of the High Pass Filter is HPPeriod. Think of it as a “stone wall filter” where cycle period components longer than HPPeriod are completely rejected and cycle period components shorter than HPPeriod are passed without attenuation. If HPPeriod is set to be a large number (e.g. 250) the indicator will tend to look more like a trending indicator. If HPPeriod is set to be a smaller number (e.g. 20) the indicator will look more like a cycling indicator. The Low Pass Filter is a Hann Windowed FIR filter whose tunable parameter is LPPeriod. Think of it as a “stone wall filter” where cycle period components shorter than LPPeriod are completely rejected and cycle period components longer than LPPeriod are passed without attenuation. The purpose of the Low Pass filter is to smooth the signal. Thus, the combination of these two filters forms a “roofing filter”, named Filt, that passes spectrum components between LPPeriod and HPPeriod.
Since working into the future is not allowed in EasyLanguage variables, we need to convert the Filt variable to the data array XX. The data array is first filled with real data out to “Length”. I selected Length = 10 simply to have a convenient starting point for the prediction. The next block of code is the prediction into the future. It is easiest to understand if we consider the case where count = 0. Then, in English, the next value of the data array is equal to the current value of the data array plus the difference between the current value and the previous value. That makes the prediction one bar into the future. The process is repeated for each value of count until predictions up to 10 bars in the future are contained in the data array. Next, the selected prediction is converted from the data array to the variable “Prediction”. Filt is plotted in Red and Prediction is plotted in yellow.
The Predict Extrapolation indicator is shown below for the Emini S&P Futures contract using the default input parameters. Filt is plotted in red and Predict is plotted in yellow. The crossings of the Predict and Filt lines provide reliable buy and sell timing signals. There is some overshoot for the shorter cycle periods, for example in February and March 2021, but the only effect is a late timing signal. Further reducing the gain and/or reducing the BarsFwd inputs would provide better timing signals during this period.
Figure 2. Predict Extrapolation Provides Reliable Timing Signals
I have experimented with other FIR filters for predictions, but found none that had a significant advantage over linear extrapolation.
MESA
MESA is an acronym for Maximum Entropy Spectral Analysis. Conceptually, it removes spectral components until the residual is left with maximum entropy. It does this by forming an all-pole filter whose order is determined by the selected number of coefficients. It maximally addresses the data within the selected window and ignores all other data. Its resolution is determined only by the number of filter coefficients selected. Since the resulting filter is an IIR filter, a prediction can be formed simply by convolving the filter coefficients with the data. MESA is one of the few, if not the only way to practically determine the coefficients of a higher order IIR filter. Discussion of MESA is beyond the scope of this article.
TWO POLE IIR FILTER
While the coefficients of a higher order IIR filter are difficult to compute without MESA, it is a relatively simple matter to compute the coefficients of a two pole IIR filter.
(Skip this paragraph if you don’t care about DSP) We can locate the conjugate pole positions parametrically in the Z plane in polar coordinates. Let the radius be QQ and the principal angle be 360 / P2Period. The first order component is 2*QQ*Cosine(360 / P2Period) and the second order component is just QQ2. Therefore, the transfer response becomes:
H(z) = 1 / (1 - 2*QQ*Cosine(360 / P2Period)*Z-1 + QQ2*Z-2)
By mixing notation we can easily convert the transfer response to code.
Output / Input = 1 / (1 - 2*QQ*Cosine(360 / P2Period)* + QQ2* )
Output - 2*QQ*Cosine(360 / P2Period)*Output + QQ2*Output = Input
Output = Input + 2*QQ*Cosine(360 / P2Period)*Output - QQ2*Output
The Two Pole Predictor starts by computing the same “roofing filter” design as described for the Linear Extrapolation Predictor. The HPPeriod and LPPeriod inputs adjust the roofing filter to obtain the desired appearance of an indicator. Since EasyLanguage variables cannot be extended into the future, the prediction process starts by loading the XX data array with indicator data up to the value of Length. I selected Length = 10 simply to have a convenient place from which to start the prediction. The coefficients are computed parametrically from the conjugate pole positions and are normalized to their sum so the IIR filter will have unity gain at zero frequency.
The prediction is formed by convolving the IIR filter coefficients with the historical data. It is easiest to see for the case where count = 0. This is the initial prediction. In this case the new value of the XX array is formed by successively summing the product of each filter coefficient with its respective historical data sample. This process is significantly different from linear extrapolation because second order curvature is introduced into the prediction rather than being strictly linear. Further, the prediction is adaptive to market conditions because the degree of curvature depends on recent historical data. The prediction in the data array is converted to a variable by selecting the BarsFwd value. The prediction is then plotted in yellow, and is compared to the indicator plotted in red.
The Predict 2 Pole indicator is shown above being applied to the Emini S&P Futures contract for most of 2021. The default parameters for the roofing filter and predictor were used. By comparison to the Linear Extrapolation prediction of Figure 2, the Predict 2 Pole indicator has a more consistent prediction. For example, there is little or no overshoot in February or March while still giving good predictions in April and May.
Input parameters can be varied to adjust the appearance of the prediction. You will find that the indicator is relatively insensitive to the BarsFwd input. The P2Period parameter primarily controls the gain of the prediction and the QQ parameter primarily controls the amount of prediction lead during trending sections of the indicator.
TAKEAWAYS
1. A more or less universal band limited “roofing filter” indicator was used to demonstrate the predictors. The HPPeriod input parameter is used to control whether the indicator looks more like a trend indicator or more like a cycle indicator. The LPPeriod input parameter is used to control the smoothness of the indicator.
2. A linear extrapolation predictor is formed by adding the difference of the two most recent data bars to the value of the last data bar. The result is considered to be a real data point and the process is repeated to extend the prediction into the future. This is an FIR filter having a one bar negative group delay at zero frequency, but the group delay is not constant across the spectrum. This variable group delay causes the linear extrapolation prediction to be inconsistent across a range of market conditions.
3. The degree of prediction by linear extrapolation can be controlled by varying the gain of the prediction to reduce the overshoot to be about the same amplitude as the peak swing of the indicator.
4. I was unable to experimentally derive a higher order FIR filter predictor that had advantages over the simple linear extrapolation predictor.
5. A Two Pole IIR predictor can be created by parametrically locating the conjugate pole positions.
6. The Two Pole predictor is a second order filter, which allows curvature into the prediction, thus mitigating overshoot. Further, the curvature is adaptive because the prediction depends on previously computed prediction values.
7. The Two Pole predictor is more consistent over a range of market conditions.
ADDITIONS
Loxx's Expanded source types:
Library for expanded source types:
Explanation for expanded source types:
Three different signal types: 1) Prediction/Filter crosses; 2) Prediction middle crosses; and, 3) Filter middle crosses.
Bar coloring to color trend.
Signals, both Long and Short.
Alerts, both Long and Short.
VonnyPublicLibraryLibrary "VonnyPublicLibrary"
A collection functions commonly used within my scripts
EntryBull(float, float)
Calculate when a bullish condition occurs. (When you have two variables)
Parameters:
float : Enter first variable
float : Enter second variable
Returns: True the first bar of your bullish condition
EntryBear(float, float)
Calculate when a bearish condition occurs. (When you have two variables)
Parameters:
float : Enter first variable
float : Enter second variable
Returns: True the first bar of your bearish condition
LowestPivot(bool, bool, bool, float, float)
Calculate the low of your bearish condition
Parameters:
bool : bullish condition
bool : bearish condition
bool : candle buffer to prevent the script from crashing. Since were working with a Dynamic Length
float : Enter what you want to see the low off? Low of the bar OR Close of the bar
float : Enter what you want to see the low off? Low of the bar OR Open of the bar..... might seem pointless but some times the Lowest open is lower then the Lowest Close
Returns: Lowest point of your sell condition when ever your buy condition is triggered
HighestPivot(bool, bool, bool, float, float)
Calculate the high of your bullish condition
Parameters:
bool : bullish condition
bool : bearish condition
bool : candle buffer to prevent the script from crashing. Since were working with a Dynamic Length
float : Enter what you want to see the high off? High of the bar OR Close of the bar
float : Enter what you want to see the high off? High of the bar OR Open of the bar..... might seem pointless but some times the Highest open is Higher then the Highest Close
Returns: Highest point of your buy condition when ever your sell condition is triggered
lookBack(bool, bool)
Calculate how many bars since your bullish condition and bearish condition.
Parameters:
bool : enter bullish condition
bool : enter bearish condition
Returns: How many bars elapsed since the most recent condition. Bullish or bearish
Fast v Slow Moving Averages Strategy (Variable) [divonn1994]This is a simple moving average based strategy that takes 2 moving averages, a Fast and a Slow one, plots them both, and then decides to enter a 'long' position or exit it based on whether the two lines have crossed each other. It goes 'long when the Fast Moving Average crosses above the Slow Moving Average. This could indicate upwards momentum in prices in the future. It then exits the position when the the Fast Moving Average crosses back below. This could indicate downwards momentum in prices in the future. This is only speculative, though, but sometimes it can be a very good indicator/strategy to predict future action.
I've tried some strategy settings and I found different promising strategies. Here are a few:
BTCUSD ( BitStamp ) 1 Day Timeframe : EMA, Fast length 25 bars, Slow length 62 bars => 28,792x net profit (default)
BTCUSD ( BitStamp ) 1 Day Timeframe : VWMA, Fast length 21 bars, Slow length 60 bars => 15,603x net profit
BTCUSD ( BitStamp ) 1 Day Timeframe : SMA, Fast length 18 bars, Slow length 51 bars => 19,507x net profit
BTCUSD ( BitStamp ) 1 Day Timeframe : RMA, Fast length 20 bars, Slow length 52 bars => 5,729x net profit
BTCUSD ( BitStamp ) 1 Day Timeframe : WMA, Fast length 29 bars, Slow length 60 bars => 19,869x net profit
Features:
-You can choose your preferred moving average: SMA , EMA , WMA , RMA & VWMA .
-You can change the length average for each moving average
-I made the background color Green when you're currently in a long position and Red when not. I made it so you can see when you'd be actively in a trade or not. The Red and Green background colors can be toggled on/off in order to see other indicators more clearly overlayed in the chart, or if you prefer a cleaner look on your charts.
-I also have a plot of the Fast moving average and Slow moving average together. The Opening moving average is Purple, the Closing moving average is White. White on top is a sign of a potential upswing and purple on top is a sign of a potential downswing. I've made this also able to be toggled on/off.
Let me know if you think I should change anything with my script, I'm always open to constructive criticism so feel free to comment below :)
Hodrick-Prescott Extrapolation of Price [Loxx]Hodrick-Prescott Extrapolation of Price is a Hodrick-Prescott filter used to extrapolate price.
The distinctive feature of the Hodrick-Prescott filter is that it does not delay. It is calculated by minimizing the objective function.
F = Sum((y(i) - x(i))^2,i=0..n-1) + lambda*Sum((y(i+1)+y(i-1)-2*y(i))^2,i=1..n-2)
where x() - prices, y() - filter values.
If the Hodrick-Prescott filter sees the future, then what future values does it suggest? To answer this question, we should find the digital low-frequency filter with the frequency parameter similar to the Hodrick-Prescott filter's one but with the values calculated directly using the past values of the "twin filter" itself, i.e.
y(i) = Sum(a(k)*x(i-k),k=0..nx-1) - FIR filter
or
y(i) = Sum(a(k)*x(i-k),k=0..nx-1) + Sum(b(k)*y(i-k),k=1..ny) - IIR filter
It is better to select the "twin filter" having the frequency-independent delay Тdel (constant group delay). IIR filters are not suitable. For FIR filters, the condition for a frequency-independent delay is as follows:
a(i) = +/-a(nx-1-i), i = 0..nx-1
The simplest FIR filter with constant delay is Simple Moving Average (SMA):
y(i) = Sum(x(i-k),k=0..nx-1)/nx
In case nx is an odd number, Тdel = (nx-1)/2. If we shift the values of SMA filter to the past by the amount of bars equal to Тdel, SMA values coincide with the Hodrick-Prescott filter ones. The exact math cannot be achieved due to the significant differences in the frequency parameters of the two filters.
To achieve the closest match between the filter values, I recommend their channel widths to be similar (for example, -6dB). The Hodrick-Prescott filter's channel width of -6dB is calculated as follows:
wc = 2*arcsin(0.5/lambda^0.25).
The channel width of -6dB for the SMA filter is calculated by numerical computing via the following equation:
|H(w)| = sin(nx*wc/2)/sin(wc/2)/nx = 0.5
Prediction algorithms:
The indicator features the two prediction methods:
Metod 1:
1. Set SMA length to 3 and shift it to the past by 1 bar. With such a length, the shifted SMA does not exist only for the last bar (Bar = 0), since it needs the value of the next future price Close(-1).
2. Calculate SMA filer's channel width. Equal it to the Hodrick-Prescott filter's one. Find lambda.
3. Calculate Hodrick-Prescott filter value at the last bar HP(0) and assume that SMA(0) with unknown Close(-1) gives the same value.
4. Find Close(-1) = 3*HP(0) - Close(0) - Close(1)
5. Increase the length of SMA to 5. Repeat all calculations and find Close(-2) = 5*HP(0) - Close(-1) - Close(0) - Close(1) - Close(2). Continue till the specified amount of future FutBars prices is calculated.
Method 2:
1. Set SMA length equal to 2*FutBars+1 and shift SMA to the past by FutBars
2. Calculate SMA filer's channel width. Equal it to the Hodrick-Prescott filter's one. Find lambda.
3. Calculate Hodrick-Prescott filter values at the last FutBars and assume that SMA behaves similarly when new prices appear.
4. Find Close(-1) = (2*FutBars+1)*HP(FutBars-1) - Sum(Close(i),i=0..2*FutBars-1), Close(-2) = (2*FutBars+1)*HP(FutBars-2) - Sum(Close(i),i=-1..2*FutBars-2), etc.
The indicator features the following inputs:
Method - prediction method
Last Bar - number of the last bar to check predictions on the existing prices (LastBar >= 0)
Past Bars - amount of previous bars the Hodrick-Prescott filter is calculated for (the more, the better, or at least PastBars>2*FutBars)
Future Bars - amount of predicted future values
The second method is more accurate but often has large spikes of the first predicted price. For our purposes here, this price has been filtered from being displayed in the chart. This is why method two starts its prediction 2 bars later than method 1. The described prediction method can be improved by searching for the FIR filter with the frequency parameter closer to the Hodrick-Prescott filter. For example, you may try Hanning, Blackman, Kaiser, and other filters with constant delay instead of SMA.
Related indicators
Itakura-Saito Autoregressive Extrapolation of Price
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Weighted Burg AR Spectral Estimate Extrapolation of Price
Levinson-Durbin Autocorrelation Extrapolation of Price
Fourier Extrapolator of Price w/ Projection Forecast
Hayden's Advanced Relative Strength Index (RSI)Preface: I'm just the bartender serving today's freshly blended concoction; I'd like to send a massive THANK YOU to @iFuSiiOnzZ, @Koalafied_3, @LonesomeTheBlue, @LazyBear, @dgtrd and the rest of the PineWizards for the locally-sourced ingredients. I am simply a code editor, not a code author. The book that inspired this indicator is a free download, plus all of the pieces I used were free code from the PineWizards; my hope is that any additional useful development of The Complete RSI trading system also is offered open-source to the community for collaboration.
Features: Fixed & Custom price targeting. Triple trend state detection. Advanced data ticker. Candles, bars, or line RSI . Stochastic of over 20 indicators for adjustable entry/exit signals. Customizable trader watermark. Trend lines for spotting wedges , triangles, pennants , etc. Divergences for spotting potential reversals and Momentum Discrepancy Reversal Point opportunities. RSI percent change and price pivot labels. Gradient bar coloring on-chart.
‼ IMPORTANT: Hover over labels for additional information. Google & read John Hayden's "The Complete RSI" pdf book for comprehensive instructions before attempting to trade with this indicator. Always keep an eye on higher/stronger timeframes.
⚠ DISCLAIMER: DYOR. Not financial advice. Not a trading system. I am not affiliated with TradingView or John Hayden; this is my own personally PineScripted presentation of a suitable RSI to use when trading according to Hayden's rules.
About the Editor: I am a former-FINRA Registered Representative, inventor/patent-holder, and self-taught PineScripter. I mostly code on a v3 Pinescript level so expect heavy scripts that could use some shortening with modern conventions.
Hayden's RSI Rules:
📈 An Uptrend is indicated when:
1. RSI is in the 80 to 40 range
2. The chart shows simple bearish divergence
3. The chart shows Hidden bullish divergence
4. The chart shows Momentum Discrepancy Reversal Up
5. Upside targets being hit
6. 9-bar simple MA is greater than the 45-bar EMA on RSI
7. Counter-trend declines do not exceed 50% of the previous rally
🔮 An Uptrend is in danger when:
1. Longer timeframe fading rally
2. a) Multiple long-term bearish divergences. b) Upside targets not being hit.
3. 9-bar simple MA is less than the 45-bar EMA on RSI
4. Hidden bearish divergence, or simple bullish divergence
5. Deep counter-trend retracements greater than 50%
📉 A Downtrend is indicated when:
1. RSI is in the 60 to 20 range
2. The chart shows simple bullish divergences.
3. The chart shows Hidden bearish divergence
4. The chart shows Momentum Discrepancy Reversal Down
5. Downside targets being hit
6. 9-bar simple MA is less than the 45-bar EMA on RSI
7. Counter-trend rallies do not exceed 50% of the previous decline
🔮 A Downtrend is in danger when:
1. Longer timeframe fading decline
2. a) Multiple long-term bullish divergences. b) Downside targets not being hit.
3. 9-bar simple MA is greater than the 45-bar EMA on RSI
4. Hidden bullish divergence , or simple bearish divergence
5. Steep counter-trend retracements greater than 50%
LabelsLibrary "Labels"
Functions to create labels, from simple to complex.
labelSimple()
Creates a label each time a condition is true. All label parameters can be customised.
_condition The condition which must evaluate true for the label to be printed.
_x The x location.
_y The y location.
_text The text to print on the label.
_color The colour of the label.
_textColor The colour of the text.
_style The style of the label.
_yloc The y location type.
Returns
An unnamed label object with the supplied characteristics. To give it a name, assign the output of the function to a label variable, as in the example below.
labelLast()
Creates a label each time a condition is true. All label parameters can be customised. + Option to keep only the most recent label. + Option to display the label a configurable number of bars ahead.
_offset How many bars ahead to draw the label.
_keepLast If true (the default), keeps only the most recent label. If false, prints labels up to the TradingView limit.
_condition The condition which must evaluate true for the label to be printed.
_y The y location.
_text The text to print on the label.
_color The colour of the label.
_textColor The colour of the text.
_style The style of the label.
_yloc The y location type.
Returns A named label object with the supplied characteristics.
labelTextAndFloat()
Creates a label each time a condition is true. All label parameters can be customised. Option to keep only the most recent label. Option to display the label a configurable number of bars ahead; otherwise the x location is fixed at the bar time. + Prints (optional) text and a floating-point number on the next line.
_offset How many bars ahead to draw the label.
_float The floating-point number that you want to display on the label.
_keepLast If true (the default), keeps only the most recent label. If false, prints labels up to the TradingView limit.
_condition The condition which must evaluate true for the label to be printed.
_y The y location.
_text The text to print on the label.
_color The colour of the label.
_textColor The colour of the text.
_style The style of the label.
_yloc The y location type.
Returns A named label object with the supplied characteristics.
labelTextAndFloatSigFig()
Creates a label each time a condition is true. All label parameters can be customised. Option to keep only the most recent label. Option to display the label a configurable number of bars ahead; otherwise the x location is fixed at the bar time. Prints (optional) text and a floating-point number on the next line + to a given number of significant figures.
_offset How many bars ahead to draw the label.
_sigNumFig The number of significant figures to display the floating-point number to.
_float The floating-point number that you want to display on the label.
_keepLast If true (the default), keeps only the most recent label. If false, prints labels up to the TradingView limit.
_condition The condition which must evaluate true for the label to be printed.
_y The y location.
_text The text to print on the label.
_color The colour of the label.
_textColor The colour of the text.
_style The style of the label.
_yloc The y location type.
Returns A named label object with the supplied characteristics.
labelTextAndFloatDecimals()
Creates a label each time a condition is true. All label parameters can be customised. Option to keep only the most recent label. Option to display the label a configurable number of bars ahead. Prints (optional) text and a floating-point number on the next line + to a given number of decimal places.
_offset How many bars ahead to draw the label.
_decimals The number of decimal places to display the floating-point number to.
_float The floating-point number that you want to display on the label.
_keepLast If true (the default), keeps only the most recent label. If false, prints labels up to the TradingView limit.
_condition The condition which must evaluate true for the label to be printed.
_y The y location.
_text The text to print on the label.
_color The colour of the label.
_textColor The colour of the text.
_style The style of the label.
_yloc The y location type.
Returns A named label object with the supplied characteristics.
SuperTrend+Based upon popular SuperTrend (AKA: ATR Trailing Stop) indicator with the following differences and improvements:
Defaults to using Volume-Adjusted WMA ( VAWMA ) for ATR. (Can still be configured to behave exactly like classic SuperTrend.)
Can use SMA, EMA, WMA, VWMA, and VAWMA instead of just SMA.
Confirmation close bars for avoiding false breaks.
Details:
If the confirmation closing bars value is greater than zero (default of two bars), the trend will only reverse if the price closes outside the boundary for that number of bars (does not need to be consecutive) or if the opposite side of the bar exceeds the boundary.
The confirmation bar count will reset if the trend has resumed (opposite boundary is broken).
Confirmation examples:
In a down-trend, but the previous two bars close above the boundary.
In a down-trend, but the low of the previous bar exceeds the boundary.
In a down-trend, but the high of the previous bar exceeds the boundary when confirmation bars are set to zero.
Portfolio Backtester Engine█ OVERVIEW
Portfolio Backtester Engine (PBTE). This tool will allow you to backtest strategies across multiple securities at once. Allowing you to easier understand if your strategy is robust. If you are familiar with the PineCoders backtesting engine , then you will find this indicator pleasant to work with as it is an adaptation based on that work. Much of the functionality has been kept the same, or enhanced, with some minor adjustments I made on the account of creating a more subjectively intuitive tool.
█ HISTORY
The original purpose of the backtesting engine (`BTE`) was to bridge the gap between strategies and studies . Previously, strategies did not contain the ability to send alerts, but were necessary for backtesting. Studies on the other hand were necessary for sending alerts, but could not provide backtesting results . Often, traders would have to manage two separate Pine scripts to take advantage of each feature, this was less than ideal.
The `BTE` published by PineCoders offered a solution to this issue by generating backtesting results under the context of a study(). This allowed traders to backtest their strategy and simultaneously generate alerts for automated trading, thus eliminating the need for a separate strategy() script (though, even converting the engine to a strategy was made simple by the PineCoders!).
Fast forward a couple years and PineScript evolved beyond these issues and alerts were introduced into strategies. The BTE was not quite as necessary anymore, but is still extremely useful as it contains extra features and data not found under the strategy() context. Below is an excerpt of features contained by the BTE:
"""
More than `40` built-in strategies,
Customizable components,
Coupling with your own external indicator,
Simple conversion from Study to Strategy modes,
Post-Exit analysis to search for alternate trade outcomes,
Use of the Data Window to show detailed bar by bar trade information and global statistics, including some not provided by TV backtesting,
Plotting of reminders and generation of alerts on in-trade events.
"""
Before I go any further, I want to be clear that the BTE is STILL a good tool and it is STILL very useful. The Portfolio Backtesting Engine I am introducing is only a tangental advancement and not to be confused as a replacement, this tool would not have been possible without the `BTE`.
█ THE PROBLEM
Most strategies built in Pine are limited by one thing. Data. Backtesting should be a rigorous process and researchers should examine the performance of their strategy across all market regimes; that includes, bullish and bearish markets, ranging markets, low volatility and high volatility. Depending on your TV subscription The Pine Engine is limited to 5k-20k historical bars available for backtesting, which can often leave the strategy results wanting. As a general rule of thumb, strategies should be tested across a quantity of historical bars which will allow for at least 100 trades. In many cases, the lack of historical bars available for backtesting and frequency of the strategy signals produces less than 100 trades, rendering your strategy results inconclusive.
█ THE SOLUTION
In order to be confident that we have a robust strategy we must test it across all market regimes and we must have over 100 trades. To do this effectively, researchers can use the Portfolio Backtesting Engine (PBTE).
By testing a strategy across a carefully selected portfolio of securities, researchers can now gather 5k-20k historical bars per security! Currently, the PTBE allows up to 5 securities, which amounts to 25k-100k historical bars.
█ HOW TO USE
1 — Add the indicator to your chart.
• Confirm inputs. These will be the most important initial values which you can change later by clicking the gear icon ⚙ and opening up the settings of the indicator.
2 — Select a portfolio.
• You will want to spend some time carefully selecting a portfolio of securities.
• Each security should be uncorrelated.
• The entire portfolio should contain a mix of different market regimes.
You should understand that strategies generally take advantage of one particular type of market regime. (trending, ranging, low/high volatility)
For example, the default RSI strategy is typically advantageous during ranging markets, whereas a typical moving average crossover strategy is advantageous in trending markets.
If you were to use the standard RSI strategy during a trending market, you might be selling when you should be buying.
Similarily, if you use an SMA crossover during a ranging market, you will find that the MA's may produce many false signals.
Even if you build a strategy that is designed to be used only in a trending market, it is still best to select a portfolio of all market regimes
as you will be able to test how your strategy will perform when the market does something unexpected.
3 — Test a built-in strategy or add your own.
• Navigate to gear icon ⚙ (settings) of strategy.
• Choose your options.
• Select a Main Entry Strat and Alternate Entry Strat .
• If you want to add your own strategy, you will need to modify the source code and follow the built-in example.
• You will only need to generate (buy 1 / sell -1/ neutral 0) signals.
• Select a Filter , by default these are all off.
• Select an Entry Stop - This will be your stop loss placed at the trade entry.
• Select Pyamiding - This will allow you to stack positions. By default this is off.
• Select Hard Exits - You can also think of these as Take Profits.
• Let the strategy run and take note of the display tables results.
• Portfolio - Shows each security.
• The strategy runs on each asset in your portfolio.
• The initial capital is equally distributed across each security.
So if you have 5 securities and a starting capital of 100,000$ then each security will run the strategy starting with 20,000$
The total row will aggregate the results on a bar by bar basis showing the total results of your initial capital.
• Net Profit (NP) - Shows profitability.
• Number of Trades (#T) - Shows # of trades taken during backtesting period.
• Typically will want to see this number greater than 100 on the "Total" row.
• Average Trade Length (ATL) - Shows average # of days in a trade.
• Maximum Drawdown (MD ) - Max peak-to-valley equity drawdown during backtesting period.
• This number defines the minimum amount of capital required to trade the system.
• Typically, this shouldn’t be lower than 34% and we will want to allow for at least 50% beyond this number.
• Maximum Loss (ML) - Shows largest loss experienced on a per-trade basis.
• Normally, don’t want to exceed more than 1-2 % of equity.
• Maximum Drawdown Duration (MDD) - The longest duration of a drawdown in equity prior to a new equity peak.
• This number is important to help us psychologically understand how long we can expect to wait for a new peak in account equity.
• Maximum Consecutive Losses (MCL) - The max consecutive losses endured throughout the backtesting period.
• Another important metric for trader psychology, this will help you understand how many losses you should be prepared to handle.
• Profit to Maximum Drawdown (P:MD) - A ratio for the average profit to the maximum drawdown.
• The higher the ratio is, the better. Large profits and small losses contribute to a good PMD.
• This metric allows us to examine the profit with respect to risk.
• Profit Loss Ratio (P:L) - Average profit over the average loss.
• Typically this number should be higher in trend following systems.
• Mean reversion systems show lower values, but compensate with a better win %.
• Percent Winners (% W) - The percentage of winning trades.
• Trend systems will usually have lower win percentages, since statistically the market is only trending roughly 30% of the time.
• Mean reversion systems typically should have a high % W.
• Time Percentage (Time %) - The amount of time that the system has an open position.
• The more time you are in the market, the more you are exposed to market risk, not to mention you could be using that money for something else right?
• Return on Investment (ROI) - Your Net Profit over your initial investment, represented as a percentage.
• You want this number to be positive and high.
• Open Profit (OP) - If the strategy has any open positions, the floating value will be represented here.
• Trading Days (TD) - An important metric showing how many days the strategy was active.
• This is good to know and will be valuable in understanding how long you will need to run this strategy in order to achieve results.
█ FEATURES
These are additional features that extend the original `BTE` features.
- Portfolio backtesting.
- Color coded performance results.
- Circuit Breakers that will stop trading.
- Position reversals on exit. (Simulating the function of always in the market. Similar to strategy.entry functionality)
- Whipsaw Filter
- Moving Average Filter
- Minimum Change Filter
- % Gain Equity Exit
- Popular strategies, (MACD, MA cross, supertrend)
Below are features that were excluded from the original `BTE`
- 2 stage in-trade stops with kick-in rules (This was a subjective decision to remove. I found it to be complex and thwarted my use of the `BTE` for some time.)
- Simple conversion from Study to Strategy modes. (Not possible with multiple securities)
- Coupling with your own external indicator (Not really practical to use with multiple securities, but could be used if signals were generated based on some indicator which was not based on the current chart)
- Use of the Data Window to show detailed bar by bar trade information and global statistics.
- Post Exit Analysis.
- Plotting of reminders and generation of alerts on in-trade events.
- Alerts (These may be added in the future by request when I find the time.)
█ THANKS
The whole PineCoders team for all their shared knowledge and original publication of the BTE and Richard Weismann for his ideas on building robust strategies.
═════════════════════════════════════════════════════════════════════════
Relative Volume at Time█ OVERVIEW
This indicator calculates relative volume, which is the ratio of present volume over an average of past volume.
It offers two calculation modes, both using a time reference as an anchor.
█ CONCEPTS
Calculation modes
The simplest way to calculate relative volume is by using the ratio of a bar's volume over a simple moving average of the last n volume values.
This indicator uses one of two, more subtle ways to calculate both values of the relative volume ratio: current volume:past volume .
The two calculations modes are:
1 — Cumulate from Beginning of TF to Current Bar where:
current volume = the cumulative volume since the beginning of the timeframe unit, and
past volume = the mean of volume during that same relative period of time in the past n timeframe units.
2 — Point-to-Point Bars at Same Offset from Beginning of TF where:
current volume = the volume on a single chart bar, and
past volume = the mean of volume values from that same relative bar in time from the past n timeframe units.
Timeframe units
Timeframe units can be defined in three different ways:
1 — Using Auto-steps, where the timeframe unit automatically adjusts to the timeframe used on the chart:
— A 1 min timeframe unit will be used on 1sec charts,
— 1H will be used for charts at 1min and less,
— 1D will be used for other intraday chart timeframes,
— 1W will be used for 1D charts,
— 1M will be used for charts at less than 1M,
— 1Y will be used for charts at greater or equal than 1M.
2 — As a fixed timeframe that you define.
3 — By time of day (for intraday chart timeframes only), which you also define. If you use non-intraday chart timeframes in this mode, the indicator will switch to Auto-steps.
Relative Relativity
A relative volume value of 1.0 indicates that current volume is equal to the mean of past volume , but how can we determine what constitutes a high relative volume value?
The traditional way is to settle for an arbitrary threshold, with 2.0 often used to indicate that relative volume is worthy of attention.
We wanted to provide traders with a contextual method of calculating threshold values, so in addition to the conventional fixed threshold value,
this indicator includes two methods of calculating a threshold channel on past relative volume values:
1 — Using the standard deviation of relative volume over a fixed lookback.
2 — Using the highs/lows of relative volume over a variable lookback.
Channels calculated on relative volume provide meta-relativity, if you will, as they are relative values of relative volume.
█ FEATURES
Controls in the "Display" section of inputs determine what is visible in the indicator's pane. The next "Settings" section is where you configure the parameters used in the calculations. The "Column Coloring Conditions" section controls the color of the columns, which you will see in three of the five display modes available. Whether columns are plotted or not, the coloring conditions also determine when markers appear, if you have chosen to show the markers in the "Display" section. The presence of markers is what triggers the alerts configured on this indicator. Finally, the "Colors" section of inputs allows you to control the color of the indicator's visual components.
Display
Five display modes are available:
• Current Volume Columns : shows columns of current volume , with past volume displayed as an outlined column.
• Relative Volume Columns : shows relative volume as a column.
• Relative Volume Columns With Average : shows relative volume as a column, with the average of relative volume.
• Directional Relative Volume Average : shows a line calculated using the average of +/- values of relative volume.
The positive value of relative volume is used on up bars; its negative value on down bars.
• Relative Volume Average : shows the average of relative volume.
A Hull moving average is used to calculate the average used in the three last display modes.
You can also control the display of:
• The value or relative volume, when in the first three display modes. Only the last 500 values will be shown.
• Timeframe transitions, shown in the background.
• A reminder of the active timeframe unit, which appears to the right of the indicator's last bar.
• The threshold used, which can be a fixed value or a channel, as determined in the next "Settings" section of inputs.
• Up/Down markers, which appear on transitions of the color of the volume columns (determined by coloring conditions), which in turn control when alerts are triggered.
• Conditions of high volatility.
Settings
Use this section of inputs to change:
• Calculation mode : this is where you select one of this indicator's two calculation modes for current volume and past volume , as explained in the "Concepts" section.
• Past Volume Lookback in TF units : the quantity of timeframe units used in the calculation of past volume .
• Define Timeframes Units Using : the mode used to determine what one timeframe unit is. Note that when using a fixed timeframe, it must be higher than the chart's timeframe.
Also, note that time of day timeframe units only work on intraday chart timeframes.
• Threshold Mode : Five different modes can be selected:
— Fixed Value : You can define the value using the "Fixed Threshold" field below. The default value is 2.0.
— Standard Deviation Channel From Fixed Lookback : This is a channel calculated using the simple moving average of relative volume
(so not the Hull moving average used elsewhere in the indicator), plus/minus the standard deviation multiplied by a user-defined factor.
The lookback used is the value of the "Channel Lookback" field. Its default is 100.
— High/Low Channel From Beginning of TF : in this mode, the High/Low values reset at the beginning of each timeframe unit.
— High/Low Channel From Beginning of Past Volume Lookback : in this mode, the High/Low values start from the farthest point back where we are calculating past volume ,
which is determined by the combination of timeframe units and the "Past Volume Lookback in TF units" value.
— High/Low Channel From Fixed Lookback : In this mode the lookback is fixed. You can define the value using the "Channel Lookback" field. The default value is 100.
• Period of RelVol Moving Average : the period of the Hull moving average used in the "Directional Relative Volume Average" and the "Relative Volume Average".
• High Volatility is defined using fast and slow ATR periods, so this represents the volatility of price.
Volatility is considered to be high when the fast ATR value is greater than its slow value. Volatility can be used as a filter in the column coloring conditions.
Column Coloring Conditions
• Eight different conditions can be turned on or off to determine the color of the volume columns. All "ON" conditions must be met to determine a high/low state of relative volume,
or, in the case of directional relative volume, a bull/bear state.
• A volatility state can also be used to filter the conditions.
• When the coloring conditions and the filter do not allow for a high/low state to be determined, the neutral color is used.
• Transitions of the color of the volume columns determined by coloring conditions are used to plot the up/down markers, which in turn control when alerts are triggered.
Colors
• You can define your own colors for all of the oscillator's plots.
• The default colors will perform well on light or dark chart backgrounds.
Alerts
• An alert can be defined for the script. The alert will trigger whenever an up/down marker appears in the indicator's display.
The particular combination of coloring conditions and the display settings for up/down markers when you create the alert will determine which conditions trigger the alert.
After alerts are created, subsequent changes to the conditions controlling the display of markers will not affect existing alerts.
• By configuring the script's inputs in different ways before you create your alerts, you can create multiple, functionally distinct alerts from this script.
When creating multiple alerts, it is useful to include in the alert's message a reminder of the particular conditions you used for each alert.
• As is usually the case, alerts triggering "Once Per Bar Close" will prevent repainting.
Error messages
Error messages will appear at the end of the chart upon the following conditions:
• When the combination of the timeframe units used and the "Past Volume Lookback in TF units" value create a lookback that is greater than 5000 bars.
The lookback will then be recalculated to a value such that a runtime error does not occur.
• If the chart's timeframe is higher than the timeframe units. This error cannot occur when using Auto-steps to calculate timeframe units.
• If relative volume cannot be calculated, for example, when no volume data is available for the chart's symbol.
• When the threshold of relative volume is configured to be visible but the indicator's scale does not allow it to be visible (in "Current Volume Columns" display mode).
█ NOTES
For traders
The chart shown here uses the following display modes: "Current Volume Columns", "Relative Volume Columns With Average", "Directional Relative Volume Average" and "Relative Volume Average". The last one also shows the threshold channel in standard deviation mode, and the TF Unit reminder to the right, in red.
Volume, like price, is a value with a market-dependent scale. The only valid reference for volume being its past values, any improvement in the way past volume is calculated thus represents a potential opportunity to traders. Relative volume calculated as it is here can help traders extract useful information from markets in many circumstances, markets with cyclical volume such as Forex being one, obvious case. The relative nature of the values calculated by this indicator also make it a natural fit for cross-market and cross-sector analysis, or to identify behavioral changes in the different futures contracts of the same market. Relative volume can also be put to more exotic uses, such as in evaluating changes in the popularity of exchanges.
Relative volume alone has no directional bias. While higher relative volume values always indicate higher trading activity, that activity does not necessarily translate into significant price movement. In a tightly fought battle between buyers and sellers, you could theoretically have very large volume for many bars, with no change whatsoever in bid/ask prices. This of course, is unlikely to happen in reality, and so traders are justified in considering high relative volume values as indicating periods where more attention is required, because imbalances in the strength of buying/selling power during high-volume trading periods can amplify price variations, providing traders with the generally useful gift of volatility.
Be sure to give the "Directional Relative Volume Average" a try. Contrary to the always-positive ratio widely used in this indicator, the "Directional Relative Volume Average" produces a value able to determine a bullish/bearish bias for relative volume.
Note that realtime bars must be complete for the relative volume value to be confirmed. Values calculated on historical or elapsed realtime bars will not recalculate unless historical volume data changes.
Finally, as with all indicators using volume information, keep in mind that some exchanges/brokers supply different feeds for intraday and daily data, and the volume data on both feeds can sometimes vary quite a bit.
For coders
Our script was written using the PineCoders Coding Conventions for Pine .
The description was formatted using the techniques explained in the How We Write and Format Script Descriptions PineCoders publication.
Bits and pieces of code were lifted from the MTF Selection Framework and the MTF Oscillator Framework , also by PineCoders.
█ THANKS
Thanks to dgtrd for suggesting to add the channel using standard deviation.
Thanks to adolgov for helpful suggestions on calculations and visuals.
Look first. Then leap.
Polynomial Regression Bands + Channel [DW]This is an experimental study designed to calculate polynomial regression for any order polynomial that TV is able to support.
This study aims to educate users on polynomial curve fitting, and the derivation process of Least Squares Moving Averages (LSMAs).
I also designed this study with the intent of showcasing some of the capabilities and potential applications of TV's fantastic new array functions.
Polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modeled as a polynomial of nth degree (order).
For clarification, linear regression can also be described as a first order polynomial regression. The process of deriving linear, quadratic, cubic, and higher order polynomial relationships is all the same.
In addition, although deriving a polynomial regression equation results in a nonlinear output, the process of solving for polynomials by least squares is actually a special case of multiple linear regression.
So, just like in multiple linear regression, polynomial regression can be solved in essentially the same way through a system of linear equations.
In this study, you are first given the option to smooth the input data using the 2 pole Super Smoother Filter from John Ehlers.
I chose this specific filter because I find it provides superior smoothing with low lag and fairly clean cutoff. You can, of course, implement your own filter functions to see how they compare if you feel like experimenting.
Filtering noise prior to regression calculation can be useful for providing a more stable estimation since least squares regression can be rather sensitive to noise.
This is especially true on lower sampling lengths and higher degree polynomials since the regression output becomes more "overfit" to the sample data.
Next, data arrays are populated for the x-axis and y-axis values. These are the main datasets utilized in the rest of the calculations.
To keep the calculations more numerically stable for higher periods and orders, the x array is filled with integers 1 through the sampling period rather than using current bar numbers.
This process can be thought of as shifting the origin of the x-axis as new data emerges.
This keeps the axis values significantly lower than the 10k+ bar values, thus maintaining more numerical stability at higher orders and sample lengths.
The data arrays are then used to create a pseudo 2D matrix of x power sums, and a vector of x power*y sums.
These matrices are a representation the system of equations that need to be solved in order to find the regression coefficients.
Below, you'll see some examples of the pattern of equations used to solve for our coefficients represented in augmented matrix form.
For example, the augmented matrix for the system equations required to solve a second order (quadratic) polynomial regression by least squares is formed like this:
(∑x^0 ∑x^1 ∑x^2 | ∑(x^0)y)
(∑x^1 ∑x^2 ∑x^3 | ∑(x^1)y)
(∑x^2 ∑x^3 ∑x^4 | ∑(x^2)y)
The augmented matrix for the third order (cubic) system is formed like this:
(∑x^0 ∑x^1 ∑x^2 ∑x^3 | ∑(x^0)y)
(∑x^1 ∑x^2 ∑x^3 ∑x^4 | ∑(x^1)y)
(∑x^2 ∑x^3 ∑x^4 ∑x^5 | ∑(x^2)y)
(∑x^3 ∑x^4 ∑x^5 ∑x^6 | ∑(x^3)y)
This pattern continues for any n ordered polynomial regression, in which the coefficient matrix is a n + 1 wide square matrix with the last term being ∑x^2n, and the last term of the result vector being ∑(x^n)y.
Thanks to this pattern, it's rather convenient to solve the for our regression coefficients of any nth degree polynomial by a number of different methods.
In this script, I utilize a process known as LU Decomposition to solve for the regression coefficients.
Lower-upper (LU) Decomposition is a neat form of matrix manipulation that expresses a 2D matrix as the product of lower and upper triangular matrices.
This decomposition method is incredibly handy for solving systems of equations, calculating determinants, and inverting matrices.
For a linear system Ax=b, where A is our coefficient matrix, x is our vector of unknowns, and b is our vector of results, LU Decomposition turns our system into LUx=b.
We can then factor this into two separate matrix equations and solve the system using these two simple steps:
1. Solve Ly=b for y, where y is a new vector of unknowns that satisfies the equation, using forward substitution.
2. Solve Ux=y for x using backward substitution. This gives us the values of our original unknowns - in this case, the coefficients for our regression equation.
After solving for the regression coefficients, the values are then plugged into our regression equation:
Y = a0 + a1*x + a1*x^2 + ... + an*x^n, where a() is the ()th coefficient in ascending order and n is the polynomial degree.
From here, an array of curve values for the period based on the current equation is populated, and standard deviation is added to and subtracted from the equation to calculate the channel high and low levels.
The calculated curve values can also be shifted to the left or right using the "Regression Offset" input
Changing the offset parameter will move the curve left for negative values, and right for positive values.
This offset parameter shifts the curve points within our window while using the same equation, allowing you to use offset datapoints on the regression curve to calculate the LSMA and bands.
The curve and channel's appearance is optionally approximated using Pine's v4 line tools to draw segments.
Since there is a limitation on how many lines can be displayed per script, each curve consists of 10 segments with lengths determined by a user defined step size. In total, there are 30 lines displayed at once when active.
By default, the step size is 10, meaning each segment is 10 bars long. This is because the default sampling period is 100, so this step size will show the approximate curve for the entire period.
When adjusting your sampling period, be sure to adjust your step size accordingly when curve drawing is active if you want to see the full approximate curve for the period.
Note that when you have a larger step size, you will see more seemingly "sharp" turning points on the polynomial curve, especially on higher degree polynomials.
The polynomial functions that are calculated are continuous and differentiable across all points. The perceived sharpness is simply due to our limitation on available lines to draw them.
The approximate channel drawings also come equipped with style inputs, so you can control the type, color, and width of the regression, channel high, and channel low curves.
I also included an input to determine if the curves are updated continuously, or only upon the closing of a bar for reduced runtime demands. More about why this is important in the notes below.
For additional reference, I also included the option to display the current regression equation.
This allows you to easily track the polynomial function you're using, and to confirm that the polynomial is properly supported within Pine.
There are some cases that aren't supported properly due to Pine's limitations. More about this in the notes on the bottom.
In addition, I included a line of text beneath the equation to indicate how many bars left or right the calculated curve data is currently shifted.
The display label comes equipped with style editing inputs, so you can control the size, background color, and text color of the equation display.
The Polynomial LSMA, high band, and low band in this script are generated by tracking the current endpoints of the regression, channel high, and channel low curves respectively.
The output of these bands is similar in nature to Bollinger Bands, but with an obviously different derivation process.
By displaying the LSMA and bands in tandem with the polynomial channel, it's easy to visualize how LSMAs are derived, and how the process that goes into them is drastically different from a typical moving average.
The main difference between LSMA and other MAs is that LSMA is showing the value of the regression curve on the current bar, which is the result of a modelled relationship between x and the expected value of y.
With other MA / filter types, they are typically just averaging or frequency filtering the samples. This is an important distinction in interpretation. However, both can be applied similarly when trading.
An important distinction with the LSMA in this script is that since we can model higher degree polynomial relationships, the LSMA here is not limited to only linear as it is in TV's built in LSMA.
Bar colors are also included in this script. The color scheme is based on disparity between source and the LSMA.
This script is a great study for educating yourself on the process that goes into polynomial regression, as well as one of the many processes computers utilize to solve systems of equations.
Also, the Polynomial LSMA and bands are great components to try implementing into your own analysis setup.
I hope you all enjoy it!
--------------------------------------------------------
NOTES:
- Even though the algorithm used in this script can be implemented to find any order polynomial relationship, TV has a limit on the significant figures for its floating point outputs.
This means that as you increase your sampling period and / or polynomial order, some higher order coefficients will be output as 0 due to floating point round-off.
There is currently no viable workaround for this issue since there isn't a way to calculate more significant figures than the limit.
However, in my humble opinion, fitting a polynomial higher than cubic to most time series data is "overkill" due to bias-variance tradeoff.
Although, this tradeoff is also dependent on the sampling period. Keep that in mind. A good rule of thumb is to aim for a nice "middle ground" between bias and variance.
If TV ever chooses to expand its significant figure limits, then it will be possible to accurately calculate even higher order polynomials and periods if you feel the desire to do so.
To test if your polynomial is properly supported within Pine's constraints, check the equation label.
If you see a coefficient value of 0 in front of any of the x values, reduce your period and / or polynomial order.
- Although this algorithm has less computational complexity than most other linear system solving methods, this script itself can still be rather demanding on runtime resources - especially when drawing the curves.
In the event you find your current configuration is throwing back an error saying that the calculation takes too long, there are a few things you can try:
-> Refresh your chart or hide and unhide the indicator.
The runtime environment on TV is very dynamic and the allocation of available memory varies with collective server usage.
By refreshing, you can often get it to process since you're basically just waiting for your allotment to increase. This method works well in a lot of cases.
-> Change the curve update frequency to "Close Only".
If you've tried refreshing multiple times and still have the error, your configuration may simply be too demanding of resources.
v4 drawing objects, most notably lines, can be highly taxing on the servers. That's why Pine has a limit on how many can be displayed in the first place.
By limiting the curve updates to only bar closes, this will significantly reduce the runtime needs of the lines since they will only be calculated once per bar.
Note that doing this will only limit the visual output of the curve segments. It has no impact on regression calculation, equation display, or LSMA and band displays.
-> Uncheck the display boxes for the drawing objects.
If you still have troubles after trying the above options, then simply stop displaying the curve - unless it's important to you.
As I mentioned, v4 drawing objects can be rather resource intensive. So a simple fix that often works when other things fail is to just stop them from being displayed.
-> Reduce sampling period, polynomial order, or curve drawing step size.
If you're having runtime errors and don't want to sacrifice the curve drawings, then you'll need to reduce the calculation complexity.
If you're using a large sampling period, or high order polynomial, the operational complexity becomes significantly higher than lower periods and orders.
When you have larger step sizes, more historical referencing is used for x-axis locations, which does have an impact as well.
By reducing these parameters, the runtime issue will often be solved.
Another important detail to note with this is that you may have configurations that work just fine in real time, but struggle to load properly in replay mode.
This is because the replay framework also requires its own allotment of runtime, so that must be taken into consideration as well.
- Please note that the line and label objects are reprinted as new data emerges. That's simply the nature of drawing objects vs standard plots.
I do not recommend or endorse basing your trading decisions based on the drawn curve. That component is merely to serve as a visual reference of the current polynomial relationship.
No repainting occurs with the Polynomial LSMA and bands though. Once the bar is closed, that bar's calculated values are set.
So when using the LSMA and bands for trading purposes, you can rest easy knowing that history won't change on you when you come back to view them.
- For those who intend on utilizing or modifying the functions and calculations in this script for their own scripts, I included debug dialogues in the script for all of the arrays to make the process easier.
To use the debugs, see the "Debugs" section at the bottom. All dialogues are commented out by default.
The debugs are displayed using label objects. By default, I have them all located to the right of current price.
If you wish to display multiple debugs at once, it will be up to you to decide on display locations at your leisure.
When using the debugs, I recommend commenting out the other drawing objects (or even all plots) in the script to prevent runtime issues and overlapping displays.
Volume ProfileThis is a Volume Profile based on pine script arrays.
The main idea behind this script is from the user @IldarAkhmetgaleev .
He created an awesome piece of code for free users on tradingview.
Here are some changes to the main script:
0. Used Pine Script Arrays for doing/storing calculations.
1. The bar labels are replaced with lines.
2. Added a POC line.
3. Bar growing directions changed from right to left.
4. Added an option to change bar width.
Inputs:
0. Volume Lookback Depth : Number of bars to look back for volume calculations.
1. Bar Length Multiplier : Bar length multiplier to make bar long or short.
2. Bar Horizontal Offset : Horizontal distance from the current bar in the right direction.
3. Bar Width : Width of the bars.
4. Show POC Line : Show or hide the POC line.
Happy trading.
VAMA Volume Adjusted Moving AverageRichard Arms' Volume Adjusted Moving Average
Settings:
• Inp Avg Vol: Input - Purist method but not intended for live analysis, to retroactively alter MA curve enter Avg Vol from value shown on label into Use Avg Vol field.
• Inp Avg Vol: Current - Live method using current volume , to retroactively alter past MA curve toggle any setting back and forth to force recalculation.
• Inp Avg Vol: Subset - Similar to Current, but uses a subset rather than all bars for avg vol.
• Use Avg Vol - Used for Inp Avg Vol: Input mode. Enter volume from Avg Vol label here after each new bar closes, label will turn green, else red.
• Subset Data - Lookback length used for Inp Avg Vol: Subset mode.
• VAMA Length - Specified number of volume ratio buckets to be reached.
• Volume Incr - Size of volume ratio buckets.
• VAMA Source - Price used for volume weighted calculations.
• VAMA Strict - Must meet desired volume requirements, even if N bars has to exceed VAMA Length to do it.
• Show Avg Vol Label - Displays label on chart of total chart volume.
Notes: VAMA was created by Richard Arms. It utilizes a period length that is based on volume increments rather than time. It is an unusual indicator in that it cannot be used in some platforms in realtime mode as Arms had originally intended. VAMA requires that the average volume first be calculated for the entire chart duration, then that average volume is used to derive the variable adaptive length of the moving average. The consequence of this is that with each new bar, the new average volume alters the moving average period for the entire history. Since Pine scripts evaluate all historical bars only once upon initial script execution, there is no way to automatically shift the previous moving average values retroactively once a new bar has formed. Thus the historical plot of the moving average cannot be updated in realtime, but instead can only plot through previous bar that existed upon load or reinitialization through changing some setting.
Setting Use Avg Vol to Input mode the average volume through previous bar shown in label can be entered (input) into the Inp Avg Vol setting after each new bar closes. Entering this total chart volume forces the script to reevaluate historical bars which in turn allows the historical moving average to update the plot. When using Input mode the color of the label is green when Inp Avg Vol value matches current label value, the label color red signifies Inp Avg Vol value has not been entered or is stale.
Setting Use Avg Vol to Current mode allows the script to correctly calculate and plot the correct moving average upon initial load and the realtime moving average moving forward, but can not retroactively alter the plot of the past moving average unless some change is made in the script settings, such as toggling the Use Avg Vol from Current to some other choice and then back to Current .
Setting Use Avg Vol to Subset mode uses a rolling window of volume data to calculate the average volume and can be used in realtime, but should be noted it is a deviation from Richard Arms' original specification.
VAMA info: "Trading Without Fear" by Richard W Arms, Jr, www.fidelity.com
NOTICE: This is an example script and not meant to be used as an actual strategy. By using this script or any portion thereof, you acknowledge that you have read and understood that this is for research purposes only and I am not responsible for any financial losses you may incur by using this script!
BO - CCI Arrow with AlertBO - CCI Arrow with Alert base on CCI indicator to get signal for trade Binary Option.
Rules of BO - CCI Arrow with Alert below:
A. Setup Menu
1. cciLength:
* Default CCI lenght = 14
2. Linear Regression Length:
* Periods to calculate Linear Regression of CCI,
* Default value = 5
3. Extreme Level:
* Default top extreme level = 100
* Default bottom extreme level = -100
4. Filter Length:
* Periods to define highest or lowest Linear Regression
* Default value = 6
B. Rule Of Alert Bar
1. Put Alert Bar
* Current Linear Regression Line created temporrary peak
* Peak of Linear Regression Line greater than Top Extreme Level (100)
* Previous Linear Regression is highest of Filter Length (6)
* Previous Linear Regression is greater than previous peak of Linear Regression Line
* Current price greater than previous low
* CCI(14) less than Linear Regression Line
2. Call Alert Bar
* Current Linear Regression Line created temporrary bottom
* Bottom of Linear Regression Line less than Bottom Extreme Level (-100)
* Previous Linear Regression is lowest of Filter Length (6)
* Previous Linear Regression is less than previous bottom of Linear Regression Line
* Current price less than previous lhigh
* CCI(14) greater than Linear Regression Line
B. Rule Of Entry Bar and Epiry.
1. Put Entry with expiry 3 bars:
* After Put Alert Bar close with signal confirmed, put Arrow appear, and after 3 bars, result label will appear to show win trade, loss trade or draw trade
2. Call Entry with expiry 3 bars:
* After Call Alert Bar close with signal confirmed, call Arrow appear, and after 3 bars, result label will appear to show win trade, loss trade or draw trade.
3. While 1 trade is opening no more any signal
C. Popup Alert/Mobile Alert
1. Signal alert: Put Alert or Call Alert will send to mobile or show popup on chart
2. Put Alert: only Put Alert will send to mobile or show popup on chart
3. Call Alert: only Call Alert will send to mobile or show popup on chart
TheStocksDoctor_WVF + ADX + CCIThis script is a modified version of CM Williams Vix Fix for which I have added an indicator that shows when ADX and CCI are both indicating positive momentum - highlighted by green bars. This is part of TheStocksDoctor Trading System.
Inputs are as follows:
Lookback period Standard Deviation High ---> 22
Bolinger Band Length ---> 20
Bollinger Band Standard Dev.. ---> 2
Lookback period percentile high ---> 50
Highest Percentile ---> 0.85
----Highlight bars Below... --->
Show Highlight bar if WVF WAS true is now False --->
Show highlight bar if WVF IS True --->
----Highlight bars Below Use Filtered... --->
Show highlight bar for filtered entry --->
Show highlight bar for AGGRESSIVE Filtered Entry? --->
Check below to Turn all Bars Gray --->
Check box to Turn Bars gray? --->
Long-term look back current bar has to close Below... ---> 40
Medium-term look back current bar has to close below... ---> 14
Entry price action strength --close... ---> 3
--------Turn On/Off Alerts below... --->
---To activate alerts you HAVE To Check... --->
---You can un Check the box BELOW... --->
Show Williams Vix Fix Histogram... --->
Show Alert WVF = True? --->
Show Alert WVF wa true now False? --->
Show Alert WVF Filtered? --->
Show Alert WVF AGGRESSIVE Filter? --->
ADX Smoothing ---> 17
DI Length ---> 17
Kawabunga Swing Failure Points Candles (SFP) by RRBKawabunga Swing Failure Points Candles (SFP) by RagingRocketBull 2019
Version 1.0
This indicator shows Swing Failure Points (SFP) and Swing Confirmation Points (SCP) as candles on a chart.
SFP/SCP candles are used by traders as signals for trend confirmation/possible reversal.
The signal is stronger on a higher volume/larger candle size.
A Swing Failure Point (SFP) candle is used to spot a reversal:
- up trend SFP is a failure to close above prev high after making a new higher high => implies reversal down
- down trend SFP is a failure to close below prev low after making a new lower low => implies reversal up
A Swing Confirmation Point (SCP) candle is just the opposite and is used to confirm the current trend:
- up trend SCP is a successful close above prev high after making a new higher high => confirms the trend and implies continuation up
- down trend SCP is a successful close below prev low after making a new lower low => confirms the trend and implies continuation down
Features:
- uses fractal pivots with optional filter
- show/hide SFP/SCP candles, pivots, zigzag, last min/max pivot bands
- dim lag zones/hide false signals introduced by lagging fractals or
- use unconfirmed pivots to eliminate fractal lag/false signals. 2 modes: fractals 1,1 and highest/lowest
- filter only SFP/SCP candles confirmed with volume/candle size
- SFP/SCP candles color highlighting, dim non-important bars
Usage:
- adjust fractal settings to get pivots that best match your data (lower values => more frequent pivots. 0,0 - each candle is a pivot)
- use one of the unconfirmed pivot modes to eliminate false signals or just ignore all signals in the gray lag zones
- optionally filter only SFP/SCP candles with large volume/candle size (volume % change relative to prev bar, abs candle body size value)
- up/down trend SCP (lime/fuchsia) => continuation up/down; up/down trend SFP (orange/aqua) => possible reversal down/up. lime/aqua => up; fuchsia/orange => down.
- when in doubt use show/hide pivots/unconfirmed pivots, min/max pivot bands to see which prev pivot and min/max value were used in comparisons to generate a signal on the following candle.
- disable offset to check on which bar the signal was generated
Notes:
Fractal Pivots:
- SFP/SCP candles depend on fractal pivots, you will get different signals with different pivot settings. Usually 4,4 or 2,2 settings are used to produce fractal pivots, but you can try custom values that fit your data best.
- fractal pivots are a mixed series of highs and lows in no particular order. Pivots must be filtered to produce a proper zigzag where ideally a high is followed by a low and another high in orderly fashion.
Fractal Lag/False Signals:
- only past fractal pivots can be processed on the current bar introducing a lag, therefore, pivots and min/max pivot bands are shown with offset=-rightBars to match their target bars. For unconfirmed pivots an offset=-1 is used with a lag of just 1 bar.
- new pivot is not a confirmed fractal and "does not exist yet" while the distance between it and the current bar is < rightBars => prev old fractal pivot in the same dir is used for comparisons => gives a false signal for that dir
- to show false signals enable lag zones. SFP/SCP candles in lag zones are false. New pivots will be eventually confirmed, but meanwhile you get a false signal because prev pivot in the same dir was used instead.
- to solve this problem you can either temporary hide false signals or completely eliminate them by using unconfirmed pivots of a smaller degree/lag.
- hiding false signals only works for history and should be used only temporary (left disabled). In realtime/replay mode it disables all signals altogether due to TradingView's bug (barcolor doesn't support negative offsets)
Unconfirmed Pivots:
- you have 2 methods to check for unconfirmed pivots: highest/lowest(rightBars) or fractals(1,1) with a min possible step. The first is essentially fractals(0,0) where each candle is a pivot. Both produce more frequent pivots (weaker signals).
- an unconfirmed pivot is used in comparisons to generate a valid signal only when it is a higher high (> max high) or a lower low (< min low) in the dir of a trend. Confirmed pivots of a higher degree are not affected. Zigzag is not affected.
- you can also manually disable the offset to check on which bar the pivot was confirmed. If the pivot just before an SCP/SFP suddenly jumps ahead of it - prev pivot was used, generating a false signal.
- last max high/min low bands can be used to check which value was used in candle comparison to generate a signal: min(pivot min_low, upivot min_low) and max(pivot max_high, upivot max_high) are used
- in the unconfirmed pivots mode the max high/min low pivot bands partially break because you can't have a variable offset to match the random pos of an unconfirmed pivot (anywhere in 0..rightBars from the current bar) to its target bar.
- in the unconfirmed pivots mode h (green) and l (red) pivots become H and L, and h (lime) and l (fuchsia) are used to show unconfirmed pivots of a smaller degree. Some of them will be confirmed later as H and L pivots of a higher degree.
Pivot Filter:
- pivot filter is used to produce a better looking zigzag. Essentially it keeps only higher highs/lower lows in the trend direction until it changes, skipping:
- after a new high: all subsequent lower highs until a new low
- after a new low: all subsequent higher lows until a new high
- you can't filter out all prev highs/lows to keep just the last min/max pivots of the current swing because they were already confirmed as pivots and you can't delete/change history
- alternatively you could just pick the first high following a low and the first low following a high in a sequence and ignore the rest of the pivots in the same dir, producing a crude looking zigzag where obvious max high/min lows are ignored.
- pivot filter affects SCP/SFP signals because it skips some pivots
- pivot filter is not applied to/not affected by the unconfirmed pivots
- zigzag is affected by pivot filter, but not by the unconfirmed pivots. You can't have both high/low on the same bar in a zigzag. High has priority over Low.
- keep same bar pivots option lets you choose which pivots to keep when there are both high/low pivots on the same bar (both kept by default)
SCP/SFP Filters:
- you can confirm/filter only SCP/SFP signals with volume % change/candle size larger than delta. Higher volume/larger candle means stronger signal.
- technically SCP/SFP is always the first matching candle, but it can be invalidated by the following signal in the opposite dir which in turn can be negated by the next signal.
- show first matching SCP/SFP = true - shows only the first signal candle (and any invalidations that follow) and hides further duplicate signals in the same dir, does not highlight the trend.
- show first matching SCP/SFP = false - produces a sequence of candles with duplicate signals, highlights the whole trend until its dir changes (new pivot).
Good Luck! Feel free to learn from/reuse the code to build your own indicators!
Volume Indicator VSidea take from Alexander Elder, author of: The New Trading for a Living: Psychology, Discipline, Trading Tools and Systems, Risk Control, Trade Management
Meaning of colouring:
- Green bar Volume: If we look back certain numbers of volume bars, higher close price and higher volume.
- Blue bar Volume: If we look back certain numbers of volume bars, higher close price and lower volume.
- Red bar Volume: If we look back certain numbers of volume bars, lower close price and higher volume.
- Orange bar Volume: If we look back certain numbers of volume bars, lower close prince and lower volume.
- Grey bar Volume: If we look back certain numbers of volume bars, same price and same volume.
Locomotive v1.0My new free indicator "Locomotive v1.0" ("Loco", "Parovozik").
For 1D, 1W, 1MN, any crypto-pair. Long only!
Pattern:
Red bar = close < open
Lime bar = open < close
bar №1 = any red bar
bar №2 = any red bar
bar №3 = any red bar
bar №4 = any lime bar
Very simple :) But it works!
_CM_BarRange_PercentileI know a Trader that went 18 months without a losing trade. This Trader averaged trading 700-800 contracts per month in the Futures markets.
The was not his only system but here were his rules.
He looked at the 60 minute bar and calculated the ranges of the bars over the last 3 months. IF the range of the Bar was Greater Than the 99th Percentile, He would Fade that move or take the trade in the opposite direction.
Thought process is If the Price Bar is Greater Than the 99th Percentile then typically the market reverses. This happens a lot of times at news events. If you’ve studied the markets long enough you know if a Nes based event causes a Huge Move, which we define as Greater than the 99th Percentile, the Market typically moves in the opposite direction.
***This is dependent on the Instrument your trading and the time frame your trading. Some Instruments and time frames this signals a continuation move.
I also added in the Low of the Range based on the 99th Percentile. Often times Low Range Bars…especially if they appear at the top of a swing move, or the bottom of a swing move…create a high probability entry once the High or Low of the bar is taken out in the opposite direction of the previous move…The Low Range bars show indecision after a strong move and create great reversal opportunities.
Works on All Time Frames…again depending on the instrument your trading.
On instruments that MOVE or have High Volatility like Crude and Oil you can get great signals on 1 minute bars.
***Code includes ability to pick ham many bars you want your Look Back Period To Be.
***You can change the percentages to use the 99th Percentile, or 95th percentile, etc…
***The Green Line is the Value of the High Range Percentile.
***The Red Line is the Value of the Low Range Percentile.
***Plots a Magenta Cross on the Red Line if the Range is Below the Low Range Percentile.
***Plots a yellow Cross on the Green Line if the Range is Greater Than the High Range Percentile.
***The Aqua line is the Midpoint of the Range. Or the Average Price Move.
***Colors the Price Bar Yellow if the Range exceeds the High Range Percentile.
***Colors The Bar Magenta if the Range is Less Than the Low Range Percentile
***All parameters can be turned on or off via Check Boxes in the Inputs Tab
(Mustang Algo) Stochastic RSI + Triple EMAStochastic RSI + Triple EMA (StochTEMA)
Overview
The Stochastic RSI + Triple EMA indicator combines the Stochastic RSI oscillator with a Triple Exponential Moving Average (TEMA) overlay to generate clear buy and sell signals on the price chart. By measuring RSI overbought/oversold conditions and confirming trend direction with TEMA, this tool helps traders identify high-probability entries and exits while filtering out noise in choppy markets.
Key Features
Stochastic RSI Calculation
Computes a standard RSI over a user-defined period (default 50).
Applies a Stochastic oscillator to the RSI values over a second user-defined period (default 50).
Smooths the %K line by taking an SMA over a third input (default 3), and %D is an SMA of %K over another input (default 3).
Defines oversold when both %K and %D are below 20, and overbought when both are above 80.
Triple EMA (TEMA)
Calculates three successive EMAs on the closing price with the same length (default 9).
Combines them using TEMA = 3×(EMA1 – EMA2) + EMA3, producing a fast-reacting trend line.
Bullish trend is identified when price > TEMA and TEMA is rising; bearish trend when price < TEMA and TEMA is falling; neutral/flat when TEMA change is minimal.
Signal Logic
Strong Buy: Previous bar’s Stoch RSI was oversold (both %K and %D < 20), %K crosses above %D, and TEMA is in a bullish trend.
Medium Buy: %K crosses above %D (without requiring oversold), TEMA is bullish, and previous %K < 50.
Weak Buy: Previous bar’s %K and %D were oversold, %K crosses above %D, TEMA is flat or bullish (not bearish).
Strong Sell: Previous bar’s Stoch RSI was overbought (both %K and %D > 80), %K crosses below %D, and TEMA is bearish.
Medium Sell: %K crosses below %D (without requiring overbought), TEMA is bearish, and previous %K > 50.
Weak Sell: Previous bar’s %K and %D were overbought, %K crosses below %D, TEMA is flat or bearish (not bullish).
Visual Elements on Chart
TEMA Line: Plotted in cyan (#00BCD4) with a medium-thick line for clear trend visualization.
Buy/Sell Markers:
BUY STRONG: Lime label below the candle
BUY MEDIUM: Green triangle below the candle
BUY WEAK: Semi-transparent green circle below the candle
SELL STRONG: Red label above the candle
SELL MEDIUM: Orange triangle above the candle
SELL WEAK: Semi-transparent orange circle above the candle
Candle & Background Coloring: When a strong buy or sell signal occurs, the candle body is tinted (semi-transparent lime/red) and the chart background briefly flashes light green (buy) or light red (sell).
Dynamic Support/Resistance:
On a strong buy signal, a green dot is plotted under that bar’s low as a temporary support marker.
On a strong sell signal, a red dot is plotted above that bar’s high as a temporary resistance marker.
Alerts
Strong Buy Alert: Triggered when Stoch RSI is oversold, %K crosses above %D, and TEMA is bullish.
Strong Sell Alert: Triggered when Stoch RSI is overbought, %K crosses below %D, and TEMA is bearish.
General Buy Alert: Triggered on any bullish crossover (%K > %D) when TEMA is not bearish.
General Sell Alert: Triggered on any bearish crossover (%K < %D) when TEMA is not bullish.
Inputs
Stochastic RSI Settings (group “Stochastic RSI”):
K (smoothK): Period length for smoothing the %K line (default 3, minimum 1)
D (smoothD): Period length for smoothing the %D line (default 3, minimum 1)
RSI Length (lengthRSI): Number of bars used for the RSI calculation (default 50, minimum 1)
Stochastic Length (lengthStoch): Number of bars for the Stochastic oscillator applied to RSI (default 50, minimum 1)
RSI Source (src): Price source for the RSI (default = close)
TEMA Settings (group “Triple EMA”):
TEMA Length (lengthTEMA): Number of bars used for each of the three EMAs (default 9, minimum 1)
How to Use
Add the Script
Copy and paste the indicator code into TradingView’s Pine Editor (version 6).
Save the script and add it to your chart as “Stochastic RSI + Triple EMA (StochTEMA).”
Adjust Inputs
Choose shorter lengths for lower timeframes (e.g., intraday scalping) and longer lengths for higher timeframes (e.g., swing trading).
Fine-tune the Stochastic RSI parameters (K, D, RSI Length, Stochastic Length) to suit the volatility of the instrument.
Modify TEMA Length if you prefer a faster or slower moving average response.
Interpret Signals
Primary Entries/Exits: Focus on “BUY STRONG” and “SELL STRONG” signals, as they require both oversold/overbought conditions and a confirming TEMA trend.
Confirmation Signals: Use “BUY MEDIUM”/“BUY WEAK” to confirm or add to an existing position when the market is trending. Similarly, “SELL MEDIUM”/“SELL WEAK” can be used to scale out or confirm bearish momentum.
Support/Resistance Dots: These help identify recent swing lows (green dots) and swing highs (red dots) that were tagged by strong signals—useful to place stop-loss or profit-target orders.
Set Alerts
Open the Alerts menu (bell icon) in TradingView, choose this script, and select the desired alert condition (e.g., “BUY Signal Strong”).
Configure notifications (popup, email, webhook) according to your trading workflow.
Notes & Best Practices
Filtering False Signals: By combining Stoch RSI crossovers with TEMA trend confirmation, most false breakouts during choppy price action are filtered out.
Timeframe Selection: This indicator works on all timeframes, but shorter timeframes may generate frequent signals—consider higher-timeframe confirmation when trading lower timeframes.
Risk Management: Always use proper position sizing and stop-loss placement. An “oversold” or “overbought” reading can remain extended for some time in strong trends.
Backtesting/Optimization: Before live trading, backtest different parameter combinations on historical data to find the optimal balance between sensitivity and reliability for your chosen instrument.
No Guarantee of Profits: As with any technical indicator, past performance does not guarantee future results. Use in conjunction with other forms of analysis (volume, price patterns, fundamentals).
Author: Your Name or Username
Version: 1.0 (Pine Script v6)
Published: June 2025
Feel free to customize input values and visual preferences. If you find bugs or have suggestions for improvements, open an issue or leave a comment below. Trade responsibly!
