Trend Correlation HeatmapHello everyone!
I am excited to release my trend correlation heatmap, or trend heatmap for short.
Per usual, I think its important to explain the theory before we get into the use of the indicator, so let's get into the theory!
The theory:
So what is a correlation?
Correlation is the relationship one variable has to another. Correlations are the basis of everything I do as a quantitative trader. From the correlation between the same variables (i.e. autocorrelation), the correlation between other variables (i.e. VIX and SPY, SPY High and SPY Low, DXY and ES1! close, etc.) and, as well, the correlation between price and time (time series correlation).
This may sound very familiar to you, especially if you are a user, observer or follower of my ideas and/or indicators. Ninety-five percent of my indicators are a function of one of those three things. Whether it be a time series based indicator (i.e.my time series indicator), whether it be autocorrelation (my autoregressive cloud indicator or my autocorrelation oscillator) or whether it be regressive in nature (i.e. my SPY Volume weighted close, or even my expected move which uses averages in lieu of regressive approaches but is foundational in regression principles. Or even my VIX oscillator which relies on the premise of correlations between tickers.) So correlation is extremely important to me and while its true I am more of a regression trader than anything, I would argue that I am more of a correlation trader, because correlations are the backbone of how I develop math models of stocks.
What I am trying to stress here is the importance of correlations. They really truly are foundational to any type of quantitative analysis for stocks. And as such, understanding the current relationship a stock has to time is pivotal for any meaningful analysis to be conducted.
So what is correlation to time and what does it tell us?
Correlation to time, otherwise known and commonly referred to as "Time Series", is the relationship a ticker's price has to the passing of time. It is displayed in the traditional Pearson Correlation Coefficient or R value and can be any value from -1 (strong negative relationship, i.e. a strong downtrend) to + 1 (i.e. a strong positive relationship, i.e. a strong uptrend). The higher or lower the value the stronger the up or downtrend is.
As such, correlation to time tells us two very important things. These are:
a) The direction of the stock; and
b) The strength of the trend.
Let's take a look at an example:
Above we have a chart of QQQ. We can see a trendline that seems to fit well. The questions we ask as traders are:
1. What is the likelihood QQQ breaks down from this trendline?
2. What is the likelihood QQQ continues up?
3. What is the likelihood QQQ does a false breakdown?
There are numerous mathematical approaches we can take to answer these questions. For example, 1 and 2 can be answered by use of a Cumulative Distribution Density analysis (CDDA) or even a linear or loglinear regression analysis and 3 can be answered, more or less, with a linear regression analysis and standard error ascertainment, or even just a general comparison using a data science approach (such as cosine similarity or Manhattan distance).
But, the reality is, all 3 of these questions can be visualized, at least in some way, by simply looking at the correlation to time. Let's look at this chart again, this time with the correlation heatmap applied:
If we look at the indicator we can see some pivotal things. These are:
1. We have 4, very strong uptrends that span both higher AND lower timeframes. We have a strong uptrend of 0.96 on the 5 minute, 50 candle period. We have a strong uptrend at the 300 candle lookback period on the 1 minute, we have a strong uptrend on the 100 day lookback on the daily timeframe period and we have a strong uptrend on the 5 minute on the 500 candle lookback period.
2. By comparison, we have 3 downtrends, all of which have correlations less than the 4 uptrends. All of the downtrends have a correlation above -0.8 (which we would want lower than -0.8 to be very strong), and all of the uptrends are greater than + 0.80.
3. We can also see that the uptrends are not confined to the smaller timeframes. We have multiple uptrends on multiple timeframes and both short term (50 to 100 candles) and long term (up to 500 candles).
4. The overall trend is strengthening to the upside manifested by a positive Max Change and a Positive Min change (to be discussed later more in-depth).
With this, we can see that QQQ is actually very strong and likely will continue at least some upside. If we let this play out:
We continued up, had one test and then bounced.
Now, I want to specify, this indicator is not a panacea for all trading. And in relation to the 3 questions posed, they are best answered, at least quantitatively, not only by correlation but also by the aforementioned methods (CDDA, etc.) but correlation will help you get a feel for the strength or weakness present with a stock.
What are some tangible applications of the indicator?
For me, this indicator is used in many ways. Let me outline some ways I generally apply this indicator in my day and swing trading:
1. Gauging the strength of the stock: The indictor tells you the most prevalent behavior of the stock. Are there more downtrends than uptrends present? Are the downtrends present on the larger timeframes vs uptrends on the shorter indicating a possible bullish reversal? or vice versa? Are the trends strengthening or weakening? All of these things can be visualized with the indicator.
2. Setting parameters for other indicators: If you trade EMAs or SMAs, you may have a "one size fits all" approach. However, its actually better to adjust your EMA or SMA length to the actual trend itself. Take a look at this:
This is QQQ on the 1 hour with the 200 EMA with 200 standard deviation bands added. If we look at the heatmap, we can see, yes indeed 200 has a fairly strong uptrend correlation of 0.70. But the strongest hourly uptrend is actually at 400 candles, with a correlation of 0.91. So what happens if we change the EMA length and standard deviation to 400? This:
The exact areas are circled and colour coded. You can see, the 400 offers more of a better reference point of supports and resistances as well as a better overall trend fit. And this is why I never advocate for getting married to a specific EMA. If you are an EMA 200 lover or 21 or 51, know that these are not always the best depending on the trend and situation.
Components of the indicator:
Ah okay, now for the boring stuff. Let's go over the functionality of the indicator. I tried to keep it simple, so it is pretty straight forward. If we open the menu here are our options:
We have the ability to toggle whichever timeframes we want. We also have the ability to toggle on or off the legend that displays the colour codes and the Max and Min highest change.
Max and Min highest change: The max and min highest change simply display the change in correlation over the previous 14 candles. An increasing Max change means that the Max trend is strengthening. If we see an increasing Max change and an increasing Min change (the Min correlation is moving up), this means the stock is bullish. Why? Because the min (i.e. ideally a big negative number) is going up closer to the positives. Therefore, the downtrend is weakening.
If we see both the Max and Min declining (red), that means the uptrend is weakening and downtrend is strengthening. Here are some examples:
Final Thoughts:
And that is the indicator and the theory behind the indicator.
In a nutshell, to summarize, the indicator simply tracks the correlation of a ticker to time on multiple timeframes. This will allow you to make judgements about strength, sentiment and also help you adjust which tools and timeframes you are using to perform your analyses.
As well, to make the indicator more user friendly, I tried to make the colours distinctively different. I was going to do different shades but it was a little difficult to visualize. As such, I have included a toggle-able legend with a breakdown of the colour codes!
That's it my friends, I hope you find it useful!
Safe trades and leave your questions, comments and feedback below!
Cerca negli script per "港股央企红利etf"
Autocorrelation OscillatorReleasing the autocorrelation oscillator.
NOTE! Please be sure to read the description. This is a theoretical indicator and its important to understand the theory behind its use.
About the indicator:
Before getting into the indicator and its functionality, its important to discuss the theoretical underpinnings of the indicator.
The autocorrelation oscillator operates on two theories of market behaviour that go hand in hand. Those theories are the market efficiency theory and the random walk theory (or hypothesis ).
Market efficiency theory: The market efficiency theory or "Efficient Market Hypothesis (EMH)" postulates that all available information is reflected in a ticker's price almost instantaneously and thus it is impossible for an investor or trader to get ahead of the market because we cannot respond to the speed that the market responds. Of course, there are many holes in this theory, the most notable being that the market is a function of humans. Absent humans and their technological integrations into the market, the market would cease to react at all. But that's besides the point. This is a widely accepted theory and one in which I can mathematically observe through statistical tests. The truth behind this theory is the market is efficient for responding to evolving economic and financial information, likely owning to huge amounts of computer and algorithmic integration into trading, and thus the market is more efficient than the average person is capable (absent computerized algorithms and integration) of ascertaining nuanced financial and economic circumstances. By the time we the people can appraise information, the market has already acted on it. And that is the main premise of the EMH.
The next theory is the Random Walk Theory or Hypothesis (RWH). This builds on the EMH and essentially postulates that the market reacts so quickly to price in current circumstances that it is too random for people to truly exploit and benefit from.
The result of these two theories is two-fold and can be summarized as such:
a) The market behaves in a chaotic fashion that is seemingly random and is incapable of being predicted effectively; and
b) The market is more efficient than a person in incorporating key fundamental information, contributing to the high degree of seemingly random behaviour.
So, how does this help us?
It is said, because of the EMH and the RWH, the only way to truly exploit the market for profit is by:
a) Buying and holding and investing under the bias that stocks will eventually rise in value; or
b) For short term trading, exploiting the pricing anomalies within the data.
So how do we exploit pricing anomalies within the data?
Well, in my own research on market efficiency and behaviour, I have identified many ways of figuring out some anomalies. One of the most effective ways is by looking at simple correlation of lagged values, or autocorrelation for short.
What is autocorrelation and how to use it in relation to EMH and RWH?
Autocorrelation refers to the correlative relationship among the values in a series. Put simply, its the relationship of the same variable over time. For example, if we wanted to look at the auto-correlation of a ticker's high price, we would take, say, 5 to 7 previous high prices and correlate them with the current high price in a series dataset. If the EMH and RWH are true, the correlation among all the variables should have an average less than 0.5 or greater than -0.5. This would indicate true randomness in the dataset and thus an efficient market.
However, if the average of all of the sum's of these correlations are greater than or equal to 0.5 or less than or equal to -0.5, that indicates there is a high degree of autocorrelation and thus the EMH ad RWH is being invalidated as the market is not operating efficiently. This is an anomaly and this anomaly can be exploited.
So how do we exploit it?
Well, when the EMH and RWH hypothesis is being invalidated, we can expect what I coin as a "Regression to Chaos" i.e. the market will revert back to an efficient equilibrium state. So if we have a high correlation of the lagged variables and a strong uptrend or downtrend correlation, we can expect an inefficient market to correct back to an efficient market (i.e. have a reversal from the current trend).
So how does the indicator work?
The indicator measures the lagged correlation of the previous 5 highs and lows of a ticker. A high correlation among all of the highs and lows that exceeds 0.8 would be an invalidation of the EMH and RWH and thus signal a correction to come (i.e. a Regression to Chaos).
The indicator will display this by changing colour. Red for a bearish reversal and green for a bullish. Let's take a look below using the ticker MSFT:
Above we can see the indicator identifying observed inefficiencies within the MSFT ticker on the 1 minute timeframe. The green vertical lines correspond to potential bullish reversals as a result of bearish inefficiencies, the red correspond to bearish reversals as a result of bullish inefficiencies.
You can see these lead to reversals within the ticker.
Components of the indicator:
In the chart above we see the following that are being indicated by arrows:
Red Arrows: Show the identified inefficiencies. Red for bullish inefficiencies (i.e. bearish reversal), green for bearish inefficiencies (i.e. bullish reversal)
Yellow Arrow: The lagged variable chart. This will display the current correlation among all the lagged variables the indicator is assessing.
Teal arrow: Displays the current strength of the trend by correlating the trend to time. A strong negative value (i.e. a value less than or equal to -0.5) indicates a strong downtrend, a strong positive value indicates the inverse.
You can unselect the data-tables in the settings menu if you just want to view the correlation line itself. This part of the indicator is customizable. You can also define the lookback period; however, it is strongly recommended to leave it at 14 as this maintains the use of this indicator as an oscillator.
And that is the indicator! Let me know your comments, questions and feedback below.
Safe trades everyone!
Anchored VWAP (Auto High & Low)OVERVIEW
This script plots, and auto-updates, 3 separate VWAPs: a traditional VWAP, a VWAP anchored to a trends high, and another anchored to a trends low.
VWAP and Anchored VWAPs are commonly used by institutions responsible for the majority of market volume on a given day. Citadel Trading, for example, accounts for approximately 35% of all U.S. listed retail volume , largely executed through program trades over the course of a day, week, or month.
Because VWAP is a prominent market maker tool for executing large trades, day traders can use it to better anticipate trends, mean reversion, and breakouts.
This is most useful on charts with intraday time frames (1 minute, 5 minute etc.) commonly used for day trading. This is not ideal for larger time frames (1 hour or greater) commonly used for swing trading or identifying larger trends.
INPUTS
You can configure:
The size, color, and visibility of 6 different plots (VWAP, High Anchor, Low Anchor, Average of Anchors, Quarter Values, Interim Bands)
How smooth the average displays
INSPIRATION
1. "How To Measure Anything" by Douglas W. Hubbard
2. "Maximum Trading Gains With Anchored VWAP" by Brian Shannon
Better understanding probability and how to analyze risk (first book), as well as the tools market makers use (second book), has completely reframed how I approach day trading.
Trendilo LSMA Band ExampleThe "Trendilo LSMA Example" indicator is a technical analysis tool that combines two moving averages, the Linear Regression Moving Average (LSMA) and the Hull Moving Average (HMA), to provide insights into market trends.
The indicator plots a line on the price chart, which represents the combined values of the LSMA and HMA. This line changes color based on the direction of the trend. When the line is green, it suggests an upward trend, indicating that prices may continue to rise. Conversely, when the line is red, it suggests a downward trend, indicating that prices may continue to fall. If the line is yellow, it suggests a neutral or sideways trend, indicating that prices may be moving within a range without a clear trend.
Traders can customize the indicator by adjusting the input parameters. The "LSMAlen" parameter determines the length of the LSMA, the "LSMA Offset" parameter sets the offset for the LSMA, and the "LSMA Smoother" parameter controls the smoothing factor. Additionally, the "HMAlen" parameter determines the length of the HMA.
By using the Trendilo LSMA Example indicator, traders can get a visual representation of the market trend and use it to make informed trading decisions. Green indicates a potential buying opportunity, red suggests a potential selling opportunity, and yellow suggests a period of uncertainty where it may be prudent to wait for a clearer trend signal.
% Stocks Above MABreadth indicator showing % stocks above various moving averages. Histogram is positive (blue) when % stocks above selected MA is greater than 50%. Histogram is negative (red) when % of stocks above selected MA is less than 50%. Data manipulation causes the actual % value in y-axis to be incorrect but enhances visualization. Actual %'s are simply the displayed values + 50.
Improvements / suggestions welcome.
Trendilo (OPEN-SOURCE)The provided code is a custom indicator called "Trendilo" in TradingView. It helps traders identify trends in price data. The indicator calculates the percentage change of the chosen price source and applies smoothing to it. Then, it calculates the Arnaud Legoux Moving Average (ALMA) of the smoothed percentage change. The ALMA is compared to a root mean square (RMS) band, which represents the expected range of the ALMA values. Based on this comparison, the indicator determines whether the trend is up, down, or sideways. The indicator line is plotted in a color corresponding to the trend direction. The indicator also provides the option to fill the area between the indicator line and the RMS band. Additionally, users can choose to color the bars of the chart based on the trend direction. Overall, the "Trendilo" indicator helps traders visually identify trends and potential reversals in the price data.
Positive Volatility and Volume GaugeThis is my first published script. It is a real volatility gauge that allows the user to see the real volatility of a given candle on the 15-min time frame. It also has the SMA of real volatility and volume available.
It provides the user to identify high volatility points that can lead to reversals back to the mid-point of said high volatility.
You can change the threshold of the signal line. For the 15-min time frame, I suggest that the 1.5-2.5 threshold be used for the best view.
Good luck and let me know if you have any questions or suggestions. I'm always open to learning.
Thank you!
Fibonacci Levels on Any Indicator [By MUQWISHI]▋ INTRODUCTION :
A “Fibonacci Levels on Any Indicator” can be applied to any indicator to draw Fibonacci levels based on provided conditions of two price points to produce a sequence of horizontal line levels starting from 0% to 100% in addition to extension levels. The 0% level is measured as the start of retracement, while the 100% level is the beginning of the extension levels. This tool was developed to be easy to add to any indicator, and it could be valuable to some traders in terms of managing trades by setting targets and reducing risk in the trend direction.
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▋ USAGE:
➤ NEEDS TO IDENTIFY 4 ELEMENTS:
1. Starting Point. What’re the conditions / When will the drawing of the Fibonacci levels begin?
2. Ending Point. What’re the conditions / When will the drawing of the Fibonacci levels end?
3. High Point. What is the price for a 100% Fibonacci level (0% for the downside)?
4. Low Point. What is the price for a 0% Fibonacci level (100% for the downside)?
➤ STARTING & ENDING POINTS CONDITIONS:
Need to specify the condition when the drawing of Fibonacci levels starts and ends, and the indicator shows different prepared conditions.
New Phase: Import a value (plot) from an existing indicator, where its status changes from NaN to a real number.
Crosses Above/Below: Import a value(1) (plot) from an existing indicator, where it crosses above/below value(2).
Reversal Up/Down: Import a value(1) (plot) from an existing indicator, where it rises/decreases than the previous value(1).
First/Last Bar: Useful to draw stationary Fibonacci levels.
➤ UPPER & LOWER PIVOTS (0% & 100%):
Need to specify the two price points representing 0% & 100% Fibonacci levels to expose the sequence of Fibonacci lines.
Upper Pivot. By default, the ATR Upper Band. It’s possible to import a custom value from an existing indicator.
Lower Pivot. By default, the ATR Lower Band. It’s possible to import a custom value from an existing indicator.
➤ FIBONACCI STYLING OPTIONS:
Ability to customize line & label style, color, reverse, and hide/show levels.
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▋ IMPLEMENTATION:
Here are some examples of implementing the indicator.
Note: All presented examples below are for demonstration purposes, and they're not trading suggestions.
# Example 1: (Reversal Up/Down)
We want to implement Fibonacci levels on the Hull MA by mohamed982 . Our requirements are as follows:
Fibonacci levels start when the Hull MA reverses up.
Fibonacci levels end when the Hull MA reverses down.
Upper Pivot is the ATR Upper Band.
Lower Pivot is the ATR Lower Band.
After adding the required indicator (Hull MA), here’re the implementation and results
# Example 2: (Crosses Above/Below)
We want to implement Fibonacci Level on the Squeeze Momentum by LazyBear . Our requirements are as follows:
Fibonacci levels start when the Squeeze Momentum histogram crosses above 0.
Fibonacci levels end when the Squeeze Momentum histogram crosses below 0.
Upper Pivot is the Bollinger Upper Band.
Lower Pivot is the Bollinger Lower Band.
After adding the required indicators (Squeeze Momentum & Bollinger Band), here’re the implementation and results
# Example 3: (Crosses Above/Below)
We want to implement Fibonacci Level on the Crossing Moving Averages. Our requirements are as follows:
Fibonacci levels start when the 20-EMA crosses above 100-MA.
Fibonacci levels end when the 20-EMA crosses below 100-MA.
Upper Pivot is the ATR Upper Band.
Lower Pivot is the ATR Lower Band.
After adding the required indicators (20-EMA & 100-MA), here’re the implementation and results
# Example 4: (New Phase: When the previous value is NaN, and the current value is a real number.)
We want to implement Fibonacci Level on the Supertrend. Our requirements are as follows:
Fibonacci levels start when an up-Supertrend (green) line shows up.
Fibonacci levels end when a down-Supertrend (red) line shows up.
Upper Pivot is the down-Supertrend.
Lower Pivot is the up-Supertrend.
After adding the required indicator (Supertrend), here’re the implementation and results
# Example 5: (First/Last Bar)
We want to implement Fibonacci Level between two points, 330 & 300. Our requirements are as follows:
Fibonacci levels start at first bar on the chart.
Fibonacci levels end at last bar on the chart.
Upper Pivot is 330.
Lower Pivot is 300.
Here’re the implementation and results.
To customize the number of bars back (like 50 bars)
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▋ Final Comments:
The “Fibonacci Levels on Any Indicator” is made to apply on other indicators for planning Fibonacci Levels.
It can be implemented in different ways, along with presented examples.
This indicator does not work with plots that were developed by drawing classes.
Please let me know if you have any questions.
Thank you.
Visible Range Linear Regression Channel [vnhilton](OVERVIEW)
This indicator calculates the linear regression channel for the visible bars shown on the chart instead of the traditional fixed length linear regression channel TradingView provides (and is more accurate I believe). Inspired by TradingView's Linear Regression Channel and Visible Average Price indicator, and the DAS Trader linear regression indicator.
(FEATURES)
- Ability to extend lines to the right
- Show/hide individual lines
- Adjust standard deviation of bands
- Adjust line style and width of basis and band lines
- Change individual line colours and plot fills between the lines
(DIFFERENCES)
If you compare this indicator to TradingView's Linear Regression Channel, you will notice some differences (as of 11th June, 2023). Differences and reasons are:
1) The intercept is wrong. The formula TradingView uses to calculate the intercept includes the addition of the gradient, which I believe is incorrect. Difference #2 is also why the intercept is wrong. This indicator omits that addition. This was verified by comparing the gradient calculated in this indicator with the gradient determined by Excel with the same data.
2) The gradient is "wrong". In quotations as essentially TradingView's code attempts to find the line of best fit, with the y-axis on the most recent bar instead of the oldest bar. This leads to the gradient being the opposite to the gradient found in this indicator, which isn't wrong, but the later formula used to calculate the intercept doesn't take this into account, resulting in an incorrect intercept value. The gradient and intercept values in this indicator matches those found in Excel.
3) Standard deviation bands of both indicators. I believe the code TradingView uses to calculate standard deviation is incorrect (basing this just through visuals). This indicator uses the array.stdev function to find the correct value (verified with Excel numbers).
Z-Score Retracement Indicator Releasing the Z-Score Retracement Indicator
What it does:
The Z-Score retracement indicator operates similarly to Fibonacci retracements. It calculates the average, standard deviation and Z-Scores of a user defined period and will plot out the various Standard Deviation levels and price targets based on the period under analysis.
It will visually display the distance from the mean and which price targets correspond to which standard deviation. It is intended to aid traders in determining where the mean is and to calculate the probability of price targets and the probability of a regression to the mean.
How do you use it?
When you launch the indicator, it will ask you to identify the start period. I always try to identify periods where the most recent uptrend or downtrend has started, and then start the analysis from that point. When you plot it, the indicator will display the current strength of the trend in the same way that a regression or log-linear regression indicator would, by displaying the Pearson Correlation Coefficient:
Unlike with linear regression or log-linear regression, you don't necessarily need to have a strong up or downtrend to use the indicator, however it is ideal to find an area with a clear trend.
From there, you can clearly see the standard deviation zones:
The indicator will also display the current Standard Deviation of the last close price.
The centre line (a Z-Score of 0) corresponds to absolute neutrality and would be a regression to the mean. The price target for this area is also listed.
If you want to calculate the price of a specific Standard Deviation, you can! Launch the settings and select the input you would like:
Simply select whether you want to convert a Standard Deviation Z-Score to price or price to Z-Score. Then input the variable into the appropriate field. The indicator will then display the results in a table at the top right of the chart:
In the above image, you can see that a Z-Score of 0 (indicating absolute neutrality) on QQQ is equivalent to a price of 299.
Calculating Probability:
You can calculate probability by reference a Z-Score Table. I have discussed this in my previous Z-Score based indicators, but essentially, the rule of thumb is this:
Anything over + 2 standard deviations corresponds with roughly less than a 5 to 10% chance of continuation higher. I encourage you to check out the writeup on my Z-Score Probability Indicator for more information on the price use of Z-Score for probability determinations.
Concluding remarks:
And that is the indicator! Its pretty straight forward and its intended to be an added tool for regression and log-linear regression based traders to help visualize the actual distance from the mean a ticker is currently trading at.
Another thing to keep in mind is you can use this on the very small time frames as well. I have used this for day trading on the 5 and 1 minute timeframe to determine "regressions to the mean" on a much smaller level. Like here:
That's the indicator!
Hope you enjoy, leave your questions, comments and suggestions below, safe trades everyone!
Ultimate Customizable EMA/SMAI know, not another EMA indicator, but I promise, I will make it worth your while!
About this indicator:
This is an EMA indicator, plain and simple. But its ultimate! And its ultimate in the sense that I have made it vastly customizable.
I made this indicator as a boring, single line indicator that would allow me to toggle to whichever EMA / SMA I wanted on whatever timeframe I wanted, because with the currently available EMAs and SMAs (and there are tons of them), I could never seem to get one with the precise settings I wanted.
Then I realized, if I struggled with this, chances are other people may be struggling with this. And also chances are not everyone is great with coding things quickly and it may be out of reach for those to code something specific to their individual needs and desires.
So this indicator is meant for those who, like me, may have very specific tastes for their EMA indicator and want to be able to tailor it right down to a T of what they want, but maybe don't have the skills to code things specifically the way they would like it.
So what can I do with it?
Well, you can do really whatever you want. I have made absolutely everything possible customizable, right down to the size of the plotted line (you can adjust the width of the line to make it more or less visible). But let me give you a list of the functions permitted for this indicator:
1. Toggle between an EMA or SMA: The indicator will default to show the EMA. However, you can toggle between an EMA or SMA, depending on your preference.
2. Add 2 EMA's or SMAs: The indicator permits up to 2 EMA's to be added. Both of which can be either EMA or SMA and operate independently (you can have one as EMA and the other as SMA, both as SMA or whatever combination thereof).
3. Specify your timeframes: Each EMA/SMA can have an individual timeframe. If you want to plot 2, 200 EMA's on your chart, 1 on the 5 minute chart and the other on the 1 Day chart, you can do it! The indicator will permit you to individually select which timeframe you want for both of the available EMAs/SMAs. They can both be on separate timeframes.
4. Specify your sources: In addition to both being able to be on separate timeframes, both can also be on separate sources. You can have the 200 EMA of the close price as well as the 200 EMA of the high or low price. The indicator will permit you to specify your preferred sources.
5. Plot Standard Deviation bands: You can plot the standard deviation bands of the primary EMA/SMA (this is only available on the primary EMA/SMA and not both). You can also specify the length of the standard deviation bands that can operate independently of the primary EMA/SMA. So if you have the 50 EMA but want the 200 standard deviation bands, you can do so and specify this in the data inputs.
6. Customize your alerts: The indicator provides 6 pre-programmed condition alerts that are applied to both the primary, secondary and both EMAs. This way, you can customize various alerts based on various conditions you want to look for.
7. Plot crossover / crossunder arrows: The indicator will allow you to request it to plot triangles to signal crossovers and crossunders. This can be toggled on and off based on your visual preference.
8. Provides demographic information: The EMA will provide basic demographic information about the stock's behaviour around the EMA/SMA. This is displayed in a table at the top right of the chart. It will tell you the number of touches a stock has with its various EMA/SMAs, how many closes it has had above or below the EMA/SMA (for example, a bullish ticker should have more closes above an EMA than below it and inverse for bearish), how many times the close price has crossed over or crossed under the two EMA/SMAs and how many time the EMA/SMAs have crossed over and crossed under each other. This all gives an idea of the relative strength and sentiment of a stock in a quantitative way. The length of the lookback period is customizable individually for each EMA/SMA. If you want to look back 100, 200, 500 or just 75 candles, you can specify. You can also toggle on and off each or both tables as you desire.
Final thoughts:
The indicator was meant to tailor to my general need to toggle between very specific EMAs and SMAs to gauge averages. I generally will look at various EMAs and SMAs to calculate various things and I never specifically rely on a single EMA and SMA. Its annoying having to switch between multiple indicators and I always ended up opening pinescript and coding in what exactly I wanted to look at. This was meant to stop me from having to constantly code something specifically each time I wanted very specific information and I felt like I should share it with the community, as if I find it helpful and useful, I hope others will, too!
Hopefully you find it helpful and useful and as always leave your suggestions below!
RSI-CCI Fusion StrategyRSI-CCI Fusion Strategy: Harnessing the Power of RSI and CCI
The "RSI-CCI Fusion Strategy" is a powerful trading approach that combines the strengths of the Relative Strength Index (RSI) and the Commodity Channel Index (CCI) to provide enhanced trading insights. This strategy is based on the popular "RSI & CCI Fusion + Alerts" indicator, which utilizes the RSI and CCI indicators from TradingView .
1. Overview of RSI and CCI:
The Relative Strength Index (RSI) is a widely used momentum oscillator that measures the speed and change of price movements. It helps traders identify overbought and oversold conditions in the market. On the other hand, the Commodity Channel Index (CCI) is a versatile indicator that identifies cyclical trends and provides insights into overbought and oversold levels.
2. The RSI-CCI Fusion Strategy:
The RSI-CCI Fusion Strategy harnesses the combined power of the RSI and CCI indicators to generate robust trading signals. By blending the RSI and CCI, this strategy captures both momentum and cyclical trend dynamics, offering a more comprehensive view of the market.
3. Utilizing the RSI-CCI Fusion Indicator + Alerts:
The "RSI & CCI Fusion + Alerts" indicator serves as the backbone of the RSI-CCI Fusion Strategy. It integrates the RSI and CCI indicators from TradingView, providing traders with a clear and actionable trading signal.
4. How it Works:
- The indicator calculates the RSI and CCI values, standardizes them using z-score, and combines them with a weighted fusion approach.
- The resulting RSI-CCI Fusion indicator is plotted on the chart, accompanied by dynamic upper and lower bands, which help identify potential overbought and oversold conditions.
- Traders can customize alerts based on their preferred thresholds and timeframes, enabling them to receive timely notifications for potential buy and sell signals.
5. Implementing the RSI-CCI Fusion Strategy:
Traders following the RSI-CCI Fusion Strategy can utilize the buy and sell signals generated by the RSI-CCI Fusion indicator. When the indicator crosses below the upper band, it may signal a potential selling opportunity. Conversely, when it crosses above the lower band, it may indicate a potential buying opportunity. Traders can also consider additional factors and technical analysis tools to validate the signals before making trading decisions.
Conclusion: The RSI-CCI Fusion Strategy provides traders with a robust approach to analyze the market and make well-informed trading decisions. By incorporating the RSI and CCI indicators through the "RSI & CCI Fusion + Alerts" indicator, traders can take advantage of the combined strengths of these indicators. However, it is important to remember that no strategy guarantees success, and traders should always practice risk management and conduct thorough analysis before executing trades using this strategy.
Disclaimer: Trading involves risks, and it is important to conduct your own research and consult with a financial advisor before making any investment decisions.
Note: The RSI-CCI Fusion Strategy serves as a general guide, and individual traders may have different preferences and trading styles.
RSI-CCI Fusion + AlertsThe "RSI-CCI Fusion" indicator combines the Relative Strength Index (RSI) and Commodity Channel Index (CCI) from TradingView.
RSI-CCI Fusion: Unlocking Synergies in Technical Analysis
Technical analysis plays a crucial role in understanding market dynamics and making informed trading decisions. I often rely on a combination of indicators to gain insights into price movements and identify potential trade opportunities. In the lines below, I will explore the "RSI-CCI Fusion" indicator, a powerful tool that combines the strengths of the Relative Strength Index (RSI) and the Commodity Channel Index (CCI) to provide enhanced trading insights.
1. Understanding the RSI and CCI Indicators
Before delving into the fusion of these indicators, let's briefly review their individual characteristics. The RSI is a widely used momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100, with readings above 70 indicating overbought conditions and readings below 30 indicating oversold conditions.
On the other hand, the CCI is a versatile indicator designed to identify cyclical trends in prices. It measures the distance between the price and its statistical average, thereby providing valuable insights into overbought and oversold levels.
2. The Concept of RSI-CCI Fusion
The RSI-CCI Fusion indicator is born out of my desire to harness the collective power of the RSI and CCI. By combining these indicators, I can benefit from a more comprehensive trading signal that captures both momentum and cyclical trend dynamics.
The fusion process involves assigning weights to the RSI and CCI, creating a blended indicator that reflects their relative importance. The weighted combination ensures that both indicators contribute meaningfully to the final result.
To maintain consistency, the RSI and CCI values are standardized using the z-score technique. This normalization process brings the values to a common scale, making them directly comparable. Rescaling is then applied to bring the combined indicator back to its original scale, facilitating intuitive interpretation.
3. Interpreting the RSI-CCI Fusion Indicator
When plotting the RSI-CCI Fusion indicator on a chart, I gain valuable insights into market dynamics and potential trading opportunities. The indicator's plot typically includes dynamic upper and lower bands, which are calculated based on the indicator's standard deviation. These bands provide boundaries for evaluating overbought and oversold conditions.
When the RSI-CCI Fusion indicator crosses above the lower band, it suggests oversold conditions and potential buying opportunities. Conversely, when the indicator crosses below the upper band, it indicates overbought conditions and potential selling opportunities. I also pay attention to the baseline, which represents the neutral level and may signal potential trend reversals.
4. Utilizing Alerts for Trading Decisions
The RSI-CCI Fusion indicator can be further enhanced by incorporating alerts. These alerts notify me when the indicator generates buy or sell signals, enabling me to take prompt action. I can customize the alerts based on my preferred thresholds and timeframes.
However, it is crucial to remember that the RSI-CCI Fusion indicator should not be relied upon in isolation. To increase the robustness of my trading decisions, it is recommended to combine the indicator with other analysis techniques such as trend lines, support and resistance levels, or additional indicators. This convergence of analysis methodologies enhances the overall accuracy of my trade signals.
Conclusion: The RSI-CCI Fusion indicator represents a compelling approach to technical analysis by synergizing the strengths of the RSI and CCI. By combining momentum and cyclical trend dynamics, I gain a more comprehensive view of market conditions. The fusion of these indicators, accompanied by timely alerts, equips me with valuable insights and facilitates well-informed trading decisions.
As with any technical analysis tool, it is essential for me to backtest the RSI-CCI Fusion indicator to evaluate its performance across different market conditions and timeframes. Additionally, applying proper risk management strategies is crucial to ensure consistent and disciplined trading practices.
Ultimate Balance StrategyThe Ultimate Balance Oscillator Strategy harnesses the power of the Ultimate Balance Oscillator to deliver a comprehensive and disciplined approach to trading. By combining the insights of the Rate of Change (ROC), Relative Strength Index (RSI), Commodity Channel Index (CCI), Williams Percent Range, and Average Directional Index (ADX) from TradingView, this strategy offers traders a systematic way to navigate the markets with precision.
The core principle of this strategy lies in its ability to identify optimal entry and exit points based on the movement of the Ultimate Balance Oscillator. When the oscillator line crosses below the 0.75 level, a buy signal is generated, indicating a potential opportunity for a bullish trend reversal. Conversely, when the oscillator line crosses above the 0.25 level, it triggers an exit signal, suggesting a possible end to a bullish trend.
Key Features:
1. Objective Market Analysis: The Ultimate Balance Oscillator Strategy provides a disciplined and objective approach to market analysis. By relying on the quantified insights of multiple indicators, it helps traders cut through market noise and focus on key signals, improving decision-making and reducing emotional biases.
2. Enhanced Timing and Precision: This strategy's entry and exit signals are based on the specific thresholds of the Ultimate Balance Oscillator. By waiting for confirmation through the crossing of these levels, traders can potentially enter trades at opportune moments and exit with greater precision, maximizing profit potential and minimizing risk exposure.
3. Customizability and Adaptability: The strategy offers flexibility, allowing traders to customize the parameters to fit their preferred trading style and timeframes. Whether you're a short-term trader or a long-term investor, the Ultimate Balance Oscillator Strategy can be adjusted to suit your specific needs, making it adaptable to various market conditions.
4. Real-time Alerts: Stay informed and never miss a potential trade opportunity with the strategy's built-in alert system. Set personalized alerts for buy and exit signals to receive timely notifications, ensuring you're always aware of the latest developments in the market.
5. Backtesting and Optimization: Before applying the strategy to live trading, it's recommended to conduct thorough backtesting and optimization. By testing the strategy's performance over historical data and fine-tuning the parameters, you can gain insights into its strengths and weaknesses, enabling you to make informed adjustments and increase its effectiveness.
Trading involves risk. Use the Ultimate Balance Oscillator Strategy at your own discretion. Past performance is not indicative of future results.
Ultimate Balance OscillatorIntroducing the Ultimate Balance Oscillator: A Powerful Trading Indicator
Built upon the renowned Rate of Change (ROC), Relative Strength Index (RSI), Commodity Channel Index (CCI), Williams Percent Range, and Average Directional Index (ADX) from TradingView, this indicator equips traders with an unparalleled understanding of market dynamics.
What sets the Ultimate Balance Oscillator apart is its meticulous approach to weighting. Each component is assigned a weight that reflects its individual significance, while carefully mitigating the influence of highly correlated signals. This strategic weighting methodology ensures an unbiased and comprehensive representation of market sentiment, eliminating dominance by any single indicator.
Key Features and Benefits:
1. Comprehensive Market Analysis: The Ultimate Balance Oscillator provides a comprehensive view of market conditions, enabling traders to discern price trends, evaluate momentum shifts, identify overbought or oversold levels, and gauge the strength of prevailing trends. This holistic perspective empowers traders to make well-informed decisions based on a thorough understanding of the market.
2. Enhanced Signal Accuracy: With its refined weighting approach, the Ultimate Balance Oscillator filters out noise and emphasizes the most relevant information. This results in heightened signal accuracy, providing traders with a distinct advantage in identifying optimal entry and exit points. Say goodbye to unreliable signals and welcome a more precise and dependable trading experience.
3. Adaptability to Various Trading Scenarios: The Ultimate Balance Oscillator transcends the constraints of specific markets or timeframes. It seamlessly adapts to diverse trading scenarios, accommodating both short-term trades and long-term investments. Traders can customize this indicator to suit their preferred trading style and effortlessly navigate ever-changing market conditions.
4. Simplicity and Ease of Use: The Ultimate Balance Oscillator simplifies trading analysis by providing a single line on the chart. Its straightforward interpretation and seamless integration into trading strategies make decision-making effortless. By observing bullish or bearish crossovers with the moving average, recognizing overbought or oversold levels, and tracking the overall trend of the oscillator, traders can make well-informed decisions with confidence.
5. Real-time Alerts: Stay ahead of the game with the Ultimate Balance Oscillator's customizable alert system. Traders can set up personalized alerts for bullish or bearish crossovers, breaches of overbought or oversold thresholds, or any specific events that align with their trading strategy. Real-time notifications enable timely action, ensuring traders never miss lucrative trading opportunities.
The Ultimate Balance Oscillator is a robust trading companion, empowering traders to make shrewd and calculated decisions. Embrace its power and elevate your trading endeavors to new heights of precision and success. Discover the potential of the Ultimate Balance Oscillator and unlock a world of trading possibilities.
Williams %R Strategy
The Williams %R Strategy is a trading approach that is based on the Williams Percent Range indicator, available on the TradingView platform.
This strategy aims to identify potential overbought and oversold conditions in the market, providing clear buy and sell signals for entry and exit.
The strategy utilizes the Williams %R indicator, which measures the momentum of the market by comparing the current close price with the highest high and lowest low over a specified period. When the Williams %R crosses above the oversold level, a buy signal is generated, indicating a potential upward price movement. Conversely, when the indicator crosses below the overbought level, a sell signal is generated, suggesting a possible downward price movement.
Position management is straightforward with this strategy. Upon receiving a buy signal, a long position is initiated, and the position is closed when a sell signal is generated. This strategy allows traders to capture potential price reversals and take advantage of short-term market movements.
To manage risk, it is recommended to adjust the position size based on the available capital. In this strategy, the position size is set to 10% of the initial capital, ensuring proper risk allocation and capital preservation.
It is important to note that the Williams %R Strategy should be used in conjunction with other technical analysis tools and risk management techniques. Backtesting and paper trading can help evaluate the strategy's performance and fine-tune the parameters before deploying it with real funds.
Remember, trading involves risks, and past performance is not indicative of future results. It is always advised to do thorough research, seek professional advice, and carefully consider your financial goals and risk tolerance before making any investment decisions.
Relative Strength, not RSIThe Smoothed Relative Strength Indicator (not RSI) with Multi-Timeframe Support is a custom indicator that combines the concepts of Relative Strength (not RSI) and Money Flow Index (MFI) to create a smoothed trend-following tool. It works on any timeframe and adapts to different market conditions.
Key Features:
Multi-timeframe support: [ The script uses the request.security function to fetch data from other timeframes, allowing users to analyze the trend on different timeframes simultaneously.
Relative Strength calculation: The script calculates the Relative Strength (not RSI) by averaging the gains and losses over a user-defined period (len).
Money Flow Index calculation: The script calculates the Money Flow Index (MFI) by considering both price and volume data. The MFI is an oscillator that ranges between 0 and 100, and it helps identify overbought or oversold conditions in the market.
Combination of Relative Strength and MFI:The indicator calculates the average of Relative Strength and MFI values to create the Trend Reversal Strength (TRS) line.
Smoothing the TRS line: The TRS line is smoothed using a Simple Moving Average (SMA) with a user-defined smoothing length (smoothLen). This helps to reduce noise and make the trend more readable.
Trend color determination: The script determines the trend color based on the slope of the smoothed TRS line. If the current value of the smoothed TRS line is higher than the previous one, the line is colored green (uptrend). If the current value is lower than the previous one, the line is colored red (downtrend).
Visual representation of trend changes: The indicator plots small circles at points where the trend color changes, making it easier to identify potential trend reversal points.
Zero line: The script draws a horizontal line at the zero level to help users gauge the market's strength or weakness relative to this level.
Usage:
This indicator can be used as a trend-following tool to identify potential entry and exit points in the market. When the smoothed TRS line is green and rising, it suggests a bullish trend, and traders may consider entering long positions. Conversely, when the smoothed TRS line is red and falling, it indicates a bearish trend, and traders may consider short positions or exiting long trades.
Please note that this indicator should be used in conjunction with other technical analysis tools and proper risk management techniques to improve the accuracy of your trading decisions.
Key Levels (Open, Premarket, & Yesterday)OVERVIEW
This indicator automatically identifies and draws recent high-probability support and resistance levels (recent key levels). Specifically, yesterdays highs / lows, premarket highs / lows, as well as yesterdays end of day Volume Weighted Average Price and trader specified Moving Average.
This is most useful on charts with intraday time frames (1 minute, 5 minute etc.) commonly used for day trading. This is not ideal for larger time frames (greater than 1 hour) commonly used for swing trading or identifying larger trends.
INPUTS
You can configure:
Line size, style, and colors
Label colors
Which key levels you want to see
Moving Average Parameters
Market Hours and Time Zone
DEV NOTES
This script illustrates:
A method for iterative management of more complex data objects (not just discrete values) with loops and arrays.
Central Bank LiquidityCentral Bank Liquidity = Total value of the assets of all Federal Reserve Banks - Overnight Reverse Repurchase Agreements (RRP) - The Treasury General Account (TGA)
TradingView ticker arithmetic: FRED:WALCL-FRED:WTREGEN-FRED:RRPONTSYD
Dynamic Trendlines Multi-TimeframeThe Dynamic Trendlines indicator is a useful tool for traders to identify potential support and resistance levels in the market. By analyzing price volatility and drawing trendlines based on high volatility candles, it helps traders visualize key price levels that may influence future price action. This indicator uses the Average True Range (ATR) as a measure of price volatility to determine the threshold for high volatility candles. This indicator can be used on multiple time frames, so just choose which one works best for you!
The underlying concept of this indicator revolves around the calculation of the True Range and Average True Range. The True Range is the maximum value among the difference between the current high and low, the absolute value of the difference between the current high and previous close, and the absolute value of the difference between the current low and previous close. The ATR is then calculated as the simple moving average of the True Range over a user-defined period (default is 14). The threshold for high volatility candles is determined by multiplying the ATR by a user-defined multiplier (default is 1.5).
The indicator identifies high volatility candles when the closing price is greater than the previous closing price plus the threshold. Based on the price action, trendlines are drawn connecting the high or low of high volatility candles. The initial color and style of the trendline are determined by whether the price is moving up or down. Green solid lines represent upward price movement, while red solid lines represent downward price movement.
As the price crosses the trendlines, the indicator tracks the number of crosses and updates the line's style accordingly. If the price crosses a trendline twice, the line style is changed to dashed, indicating the potential weakening of the support or resistance level.
This indicator works best with trading methods that focus on capturing price breakouts or reversals. Traders can use the trendlines to identify potential entry or exit points, stop-loss levels, or take-profit targets. It's important to note that this indicator should be used in conjunction with other technical analysis tools and an understanding of the overall market context to make informed trading decisions.
When using the Dynamic Trendlines indicator on TradingView, users can customize the ATR length, threshold multiplier, and the number of recent trendlines displayed on the chart. Additionally, small triangles are plotted below high volatility candles, with their color based on the trendline it starts, providing a quick visual reference for traders.
In summary, the Dynamic Trendlines indicator is a valuable tool for identifying potential support and resistance levels in the market by analyzing price volatility and drawing trendlines based on high volatility candles. It is best suited for breakout and reversal trading strategies and should be used in conjunction with other technical analysis tools for optimal results.
EMA/SMA Cross with LevelsThe EMA/SMA Cross indicator is a valuable trading tool designed to assist traders in identifying potential trend reversals or entry and exit points in the market. By plotting two moving averages, one based on the Exponential Moving Average (EMA) and the other on the Simple Moving Average (SMA), this indicator highlights the points at which these averages cross, signaling a potential change in the market trend. This straightforward yet powerful indicator follows the core principles of technical analysis, allowing traders to visualize key price levels that may influence future price action.
The underlying concept of this indicator revolves around the calculation and comparison of the short-term EMA and the long-term SMA. The EMA is a type of weighted moving average that gives more importance to recent price data, making it more responsive to new information. In contrast, the SMA assigns equal weight to all data points within a specified period, providing a smoother representation of price trends. By comparing these two averages, traders can gain insights into potential shifts in market sentiment and momentum.
When the short-term EMA crosses above the long-term SMA, it signals a possible bullish trend reversal, indicating that the recent price momentum is gaining strength. Conversely, when the short-term EMA crosses below the long-term SMA, it suggests a bearish trend reversal, implying that the recent price momentum is weakening. Traders can use these crossing points as potential entry or exit signals, depending on their trading strategy and risk tolerance.
A unique feature of this indicator is its ability to plot the crossing levels on the chart. When the short-term EMA crosses the long-term SMA, a dashed line is drawn horizontally at the level of the cross, emphasizing the significance of the price level. This line serves as a reference point for traders, helping them to identify potential support or resistance levels that may influence future price movements.
By plotting the crossing levels, the EMA/SMA Cross indicator offers traders an additional layer of information that can be used in their decision-making process. These levels can act as crucial points for stop-loss or take-profit orders, depending on the trader's strategy and risk tolerance. Additionally, they can serve as a basis for further technical analysis, such as the identification of chart patterns or the application of other technical indicators.
This indicator works best with trading methods that focus on capturing price reversals or breakouts. It is particularly useful for traders who employ trend-following or momentum-based strategies, as it helps them identify the optimal moments to enter or exit a trade. However, it's important to note that the EMA/SMA Cross indicator should be used in conjunction with other technical analysis tools and an understanding of the overall market context to make informed trading decisions.
When using the EMA/SMA Cross indicator on TradingView, users can customize the time frame, source, and length for both the short-term EMA and long-term SMA, as well as the number of recent crossing lines displayed on the chart. This flexibility allows traders to tailor the indicator to their specific trading style and preferences.
In summary, the EMA/SMA Cross indicator is an essential tool for traders looking to identify potential trend reversals or entry and exit points in the market. By comparing the short-term EMA and long-term SMA, this indicator provides valuable insights into shifts in market sentiment and momentum. It is best suited for trend-following and momentum-based trading strategies and should be used in combination with other technical analysis tools for optimal results.
Z-Score Probability IndicatorThis is the Z-Score Probability indicator. As many people like my original Z-Score indicator and have expressed more interest in the powers of the Z, I decided to make this indicator which shows additional powers of the Z-Score.
Z-Score is not only useful for measuring a ticker or any other variable’s distance from the mean, it is also useful to calculate general probability in a normal distribution set. Not only can it calculate probability in a dataset, but it can also calculate the variables within said dataset by using the Standard Deviation and the Mean of the dataset.
Using these 2 aspects of the Z-Score, you can, In principle, have an indicator that operates similar to Fibonacci retracement levels with the added bonus of being able to actually ascertain the realistic probability of said retracement.
Let’s take a look at an example:
This is a chart showing SPY on the daily timeframe. If we look at the current Z-Score level, we can see that SPY is pushing into the 2 to 3 Z-Score range. We can see two things from this:
1. We can see that a retracement to a Z-Score of 2 would correspond to a price of 425.26 based on the current dataset. And
2. We can see that the probability that SPY retraces to a Z-Score of 2 is around 0.9800 or 98%.
To take it one step further, we can look at the various other variables in the distribution. If we were to bet on SPY retracing back to -1 SDs, that would correspond to a price of around 397.15, with a probability of around 0.1600 or 16% (see image below):
Let’s say, we thought SPY would go to $440. Well, we can see that the probability SPY goes to 434.64 currently is pretty low. How do we know? Because the Z-Score table shows us the probability of values falling BELOW that Z-score level in the current distribution. So if we look at this example below:
We can see that 0.9998 or roughly 99% of values in the current SPY distribution will fall below 434.64. Thus, it may be unrealistic, at this point in time, to target said value.
So what is a Z-Score Table?
Well, I need to disclose/clarify that the Z-Score Table being displayed in this indicator does Z-Score probability a HUGE injustice. However, with the constraints what is realistic to fit into an indicator, I had to make it far more succinct. Let’s take a look at an actual Z-Score Table below:
Above is a look an the actual Z-Score table. How it works is you first identify you’re Z-Score and then find the corresponding value that relates to your score. The number displayed in the dataset represents the number of variables in the dataset/density distribution that fall BELOW that particular Z-score.
So, for example, if we have a Z-Score of -2.31, we can consult that table, go to the -2.3 then scroll across to the 0.01 to represent -2.31. We would see that this Z-Score corresponds to a 0.0104 probability zone (or essentially 1%) indicating that the majority of the variables in the distribution fall below that mean Z-score. In terms of tickers and stocks, that would mean it would theoretically be “overbought”.
So what does the indicator Z-Table tell us?
I have averaged out the data for the purposes of this indicator. However, you can also reference a manual Z-Table to get the exact probability for the current precise Z-Score. However, the reality is it doesn’t necessarily matter to be exact when it comes to tickers. The reason being, ticker’s are in constant flux, and by the time you identify that probability, the ticker will already be at a different level. So generalizations are okay in these circumstances, you just need to get the “gist” of where the distribution lies.
So how do I use the indicator?
Using the indicator is pretty straightforward. Once launched, you will see the current Z-Score of the ticker, the current levels based on the distribution and the summarized Z-Table.
The Z-Table will turn gray to indicate the zone the ticker is currently in. In this case, we can see that SPY currently is in the 2 SD Zone, meaning that 0.98 or 98% of the current dataset being shown falls below the price we are at:
When we launch the settings, we can see a few inputs.
Lookback Length: This determines the number of candles back we want to calculate the distribution for. It is defaulted to 75, but you can adjust it to whichever length you want.
SMA Length: The SMA is optional but defaults to on. If you want to see the smoothed trend of the Z-Score, this will do the trick. It does not need to be set to the same
length as the Z-Score lookback. Thus, if you want a more or less responsive SMA with, say, a larger dataset, then you can reduce the SMA length yourself.
Distribution Probability Fills: This simply colour codes the distribution zones / probability zones on the indicator.
Show Z-Table: This will display the summarized Z-Table.
Show SMA: As I indicated, the SMA is optional, you can toggle it on or off to see the overall Z-Score trend.
Concluding Remarks:
And that my friends is the Z-Score Probability Indicator.
I hope you all enjoy it and find it helpful. As always leave your comments, questions and suggestions below.
Safe trades to all and take care!
Cumulative TICK [Pt]Cumulative TICK Indicator, shown as the bottom indicator, is a robust tool designed to provide traders with insights into market trends using TICK data. This indicator visualizes the cumulative TICK trend in the form of colored columns on a separate chart below the main price chart.
Here's an overview of the key features of the Cumulative TICK Indicator:
1. Selectable TICK Source 🔄: The indicator allows users to choose from four different TICK data sources, namely USI:TICK , USI:TICKQ , USI:TICKI , and $USI:TICKA.
2. TICK Data Type Selection 🎚️: Users can select the type of TICK data to be used. The options include: Close, Open, hl2, ohlc4, hlc3.
3. Optional Simple Moving Average (SMA) 📊: The indicator offers an option to apply an SMA to the Cumulative TICK values, with a customizable length.
4. After-hour Background Color 🌙: The background color changes during after-hours to provide a clear distinction between regular and after-hour trading sessions.
🛠️ How it Works:
The Cumulative TICK Indicator uses TICK data accumulated during the regular market hours (9:30-16:00) as per the New York time zone. At the start of a new session or at the end of the regular session, this cumulative TICK value is reset.
The calculated Cumulative TICK is plotted in a column-style graph. If the SMA is applied, the SMA values are used for the column plots instead. The columns are colored green when the Cumulative TICK is positive and red when it is negative. The shades of green and red vary based on whether the Cumulative TICK is increasing or decreasing compared to the previous value.
This is a simple yet powerful tool to track market sentiment throughout the day using TICK data. Please note that this indicator is intended to be used as part of a comprehensive trading strategy. Always ensure you are managing risk appropriately and consulting various data sources to make informed trading decisions.