seasonThis script is meant to help verify the existence of a seasonal effect in asset returns, using a Z-test. There are three steps:
1. Think of a way to identify a season. The available methods are: by month, by week of the year, by day of the month, by day of the week, by hour of the day, and by minute of the hour.
2. Set the chart to the unit of your season. For example, if you want to check whether a crop commodity's harvest season has a seasonal implication, select "month". If you want to investigate the exchange's opening or close, select "hour".
3. Using the inputs, select the unit (e.g. "month", "dayofweek", "hour", etc.) and the range that identifies the season. The example natural gas chart has set "start" to 8 and "end" to 12 for September through December.
The test logic is as follows:
The "season" you select has a fixed length; for example, months eight through twelve has a length of four. This length is used to compute a sample mean, which is the mean return of all September-December periods in the chart. It is also used to calculate the mean/stdev of every other four-month period in the chart history. The latter is considered the "population." Using a Z-test, the script scores the difference between the sample returns and the population returns, and displays the results at two levels of significance (P = 0.05 and P = 0.01). The null hypothesis is "there is no difference between the seasonal periods and the population of ordinary periods". If the Z-score is sufficiently large or small, we can reject the null hypothesis and say that there is a seasonal effect at the given level of confidence. The output table will show green for a rejection of the null hypothesis (meaning there is a seasonal effect) or red of acceptance (there is no seasonal effect).
The seasonal periods that you have defined will be highlighted on the chart, so you can make sure they are correct. Additionally, the output table shows the mean, median, standard deviation, and top and bottom percentiles for both the seasonal and population samples.
Many news sites, twitter feeds, influences, etc. enjoy posting statistics about past returns, like "the stock market has gone up on this day 85 out of the past 100 years" and so on. Unfortunately, these posts don't tell you that many of these statistics are meaningless, as even totally random price fluctuations will cause many such interesting figures to occur. This script provides a limited means of testing some such seasonal effects so you can see if they are probably just random, or if they may have some meaning.
Note that Tradingview seems to use 1-based indexing for daily or higher timeframes, and 0-based indexing for intraday timeframes:
Months: 1-12
Weeks: 1-52
Days (of month): 1-31
Days (of week): 1-7
Hours (of day): 0-23
Minutes (of hour): 0-59
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S&P 500 Earnings Yield SpreadThis indicator compares the attractiveness of equities relative to the risk-free rate of return, by comparing the earnings yields of S&P 500 companies to the 10Y treasury yields. "Earnings yield" refers to the net income attributable to shareholders divided by the stock's price - effectively the inverse of the PE ratio. The tangible meaning of this metric is "the annual income received by (attributable to) shareholders as a percent of the price paid to receive said income." Therefore, earnings yield is comparable to bond yields, which are "the annual income received by bond holders as a percent of the price paid to receive said income."
This indicator subtracts the earnings yield of S&P 500 companies from the current 10-year treasury bond yield, creating a "spread" between the yields that determines whether equities are currently an attractive investment relative to bonds. That is, if the S&P 500 earnings yield exceeds the 10Y treasury yield, then equity investors are receiving more attributable income per dollar paid than bondholders, which could be an indication that equities are an attractive purchase relative to the risk-free rate. The same applies vice-versa; if the 10Y treasury yield exceeds that of the S&P 500 earnings yield, then equities may not be an attractive investment relative to the risk-free rate.
Since data on S&P 500 companies' earnings yields are pulled on a monthly basis, this indicator should be used on a monthly timeframe or longer. Historical data has shown that the critical zones for the indicator are at -4% and +3%, i.e. when equities are trading with a 4% greater yield than 10Y T-bonds and when equities are trading with a 3% lower yield than 10Y T-bonds, respectively. In the "Oversold" case (-4%), equities are trading at a steep discount to the risk-free rate and has often represented a strong buying opportunity. In the "Overbought" case (+3%), equities are trading at a premium to the risk-free rate, which may be an indication that caution should be exercised within the stock market. When the indicator first crosses into "Oversold" territory, this has historically been near a the bottom of a crash on the S&P 500. When the indicator first crosses into the "Overbought" territory, this has often precipitated a correction of 15% on the S&P 500.
Some notable "misses," crashes that this indicator missed, include the 1973 stock market crash and the 2008 global recession. However, both of these cases were largely precipitated by unprecedented economic events, as opposed to stocks simply being "Overbought" relative to treasury yields. Nonetheless, this indicator should form only a small portion of your fundamental analysis, as there are many macroeconomic factors that could lead to major corrections besides the impact of treasury yields. Furthermore, it should also be noted that since markets are "forward looking," future earnings growth or interest rate hikes may become "priced into" both the stock and bond markets, affecting the outputs of this indicator. However, since both the stock and bond markets should account for these factors simultaneously, the impact has historically been minimized.
I hope you find this indicator to be beneficial to your strategies. Stay safe, and happy trading.
PSv5 Color Magic and Chart Theme SimulatorKEEP YOUR COINS FOLKS! I DON'T NEED THEM, DON'T WANT THEM. Many other talented authors on TV deserve them.
INTRODUCTION:
This is my "PSv5 Color Magic and Chart Theme Simulator" displayed using Pine Script version 5.0. The purpose of this PSv5 colorcator is to show vivid colors that are most suitable in my opinion for modifying or developing Pine scripts. Whether you are new to Pine or an experienced Pine poet, this should aid you in developing indicators with stunning color from the provided color list that is easily copied and pasted into any novel script you should possess. Whichever colors you choose, and how, is up to your imagination's capacity.
COMMENTARY:
I have a thesis. Pine essentially is a gigantor calculator with a lot of programmable bells and whistles to perform intense analytics. Zillions of numbers per day are blended up into another cornucopia of numbers to analyze. The thing is, ALL of those numbers are moot unless we can informatively portray them in various colorized forms with unique methods to point out significant numeric events. By graphically displaying them with specific modes of operation, only then do these numbers truly make any sense to us and become quantitatively beneficial.
I have to admit... I hate numbers. I never really liked them, even before I knew what an ema() was. Some days I almost can't stand them, and on occasion I feel they deserve to be flushed down the toilet at times. However, I'm a stickler for a proper gauge of measurements. Numbers are a mental burden, but they do have "purpose and meaning". That's where COLOR comes in! By applying color in specific ways in varying dynamic forms, we can generate smarter visual aids from these numerics. Numbers can be "transformed" into something colorful it wasn't before, into a tool, like a hammer. But we don't need a hammer, we need an impressive jack hammer for BIG problem solving that we could never achieve in the not to distant past.
As time goes on, we analytically measure more, and more, and more each year. It's necessary to our continual evolution. That's one significant difference between us and cave men, and the pertinent reason why we are quickly evolving as a species, while animals haven't. Humankind is gifted to enumerate very well AND blessed to see in color. We use it for innumerable things in the technological present for purpose and pleasure. Day in and day out, we take color for granted, because it's every where we can look. The fact is, color is the most important apparatus in humankind's existence EVER. We wouldn't have survived this far without it.
By utilizing color to it's grand potential, greater advancements can be attained while simultaneously being enjoyed visually. Once color is transformed from it's numeric origins into applicable tools, we can enjoy the style, elegance, and QUALITATIVE nature of the indication that can be forged. Quantities can't reveal all. Color on the other hand has a handy "quality" factor to it, often revealing things we can't ordinarily recognize. When high quality tools provide us with obtained goals, that's when we will realize how magical color truly is, always has been, and shall always be.
The future emerging economies and future financial vessels of people around the globe are going to be dependent on the secured construction of intelligent applications with a rock solid color foundation, not just math alone. I have no doubt about that. I can envision that with my eyes closed. To make an informed choice, it should be charted or graphed somehow prior to a final executive decision to trade. Going back to abysmal black and white with double decimal points placed next to cartoons within extinction doomed newspapers is not a viable option any more.
OBSERVATIONS AND UTILITY:
One thing you will notice is the code is very dense. Looks almost hideous right? Well, the variable naming is lengthy, but it's purpose is to be self explanatory, even for those who don't know how to program, YET. I'm simply not a notation enthusiast. My main intention was to provide clearly identifiable variables from their origin of assignment to their intended destination of use, clearly visible for anyone visiting. The empowerment of well versed words that are easier to understand, is a close rival to the prominent influence color has.
Secondly, I'm displaying hline() and label.new() as prime candidates to exemplify by demonstration how the "Power of Color" can be embraced with the "Power of Pine". Color in Pine has been extensively upgraded to serve novel purposes to accomplish next generation indicators that do and WILL come to exist. New functions included with PSv5 are color.rgb(), color.from_gradient(), color.r(), color.g(), color.b(), and color.t() to accompany color.new() in our mutual TV adventures. Keep in mind, the extreme agility of color also extends to line.new(), the "entirely new" linefill.new(), table.new(), bgcolor() and every other function that may utilize color.
There's a wide range of adjustability in Settings to make selections to see how they perform on different backgrounds, with their size and form. As you curiously toy with those, you're going to notice how some jump out like laser beams while others don't. Things that aren't visually appealing, still have very viable purposes, even if they don't stand out in the crowd. Often, that's preferable. The important thing is that when pertinent information relative to indication is crucial, you can program it with distinction from an assortment of a potential 1.67 million colors that can be created in Pine. "These" are my chosen favorite few, and I hope you adopt them.
PURPOSES:
For those of you who are new to Pine Script, this also may help you understand color hex/rgb and how it is utilized in Pine in a most effective manner. The most skilled of programmers can garner perks as well. There is countless examples of code diversity present here that are applicable in other scripts with adequate mutation. Any member has the freedom use any of this code in this script any way they see fit. It's specifically intended for all. There is absolutely no need for accreditation for any of this code reuse ever, in the present case. Don't worry about, I'm not.
The color_tostring() will be most valuable in troubleshooting color when using color.rgb() and becoming adept with it. I'm not going to be able to use color.rgb() without it. Chameleon indicators of the polychromatic variety are most likely going to be fine tuned with color_tostring() divulging it's results to label.new() or even table.new() maybe. One the best virtues of this script in chart, is when you hover over the generated labels, there's a hidden gift for those who truly wish to learn the intricate mechanics of diverse color in Pine. Settings has informative tooltips too.
AFTERTHOUGHTS:
Colors are most vibrant on the "Black Chart" which is the default, but it doesn't currently exist as a chart theme. With the extreme luminous intensity of LCDs in millicandela( mcd ), you may notice "Light" charts may saturate the colors making charts challenging to analyze. Because of this, I personally use "Dark Charts" and design my indicators specifically for these. I hope this provides inspiration for the future developers who are contemplating the creation of next generation indicators and how color may enhance their usefulness.
When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members , I may implement more ideas when they present themselves as worthy additions. Have a profitable future everyone!
Reverse Cutlers Relative Strength Index On ChartIntroduction
The Reverse Cutlers Relative Strength Index (RCRSI) OC is an indicator which tells the user what price is required to give a particular Cutlers Relative Strength Index ( RSI ) value, or cross its Moving Average (MA) signal line.
Overview
Background & Credits:
The relative strength index ( RSI ) is a momentum indicator used in technical analysis that was originally developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, “New Concepts in Technical Trading Systems.”.
Cutler created a variation of the RSI known as “Cutlers RSI” using a different formulation to avoid an inherent accuracy problem which arises when using Wilders method of smoothing.
Further developments in the use, and more nuanced interpretations of the RSI have been developed by Cardwell, and also by well-known chartered market technician, Constance Brown C.M.T., in her acclaimed book "Technical Analysis for the Trading Professional” 1999 where she described the idea of bull and bear market ranges for RSI , and while she did not actually reveal the formulas, she introduced the concept of “reverse engineering” the RSI to give price level outputs.
Renowned financial software developer, co-author of academic books on finance, and scientific fellow to the Department of Finance and Insurance at the Technological Educational Institute of Crete, Giorgos Siligardos PHD . brought a new perspective to Wilder’s RSI when he published his excellent and well-received articles "Reverse Engineering RSI " and "Reverse Engineering RSI II " in the June 2003, and August 2003 issues of Stocks & Commodities magazine, where he described his methods of reverse engineering Wilders RSI .
Several excellent Implementations of the Reverse Wilders Relative Strength Index have been published here on Tradingview and elsewhere.
My utmost respect, and all due credits to authors of related prior works.
Introduction
It is worth noting that while the general RSI formula, and the logic dictating the UpMove and DownMove data series has remained the same as the Wilders original formulation, it has been interpreted in a different way by using a different method of averaging the upward, and downward moves.
Cutler recognized the issue of data length dependency when using wilders smoothing method of calculating RSI which means that wilders standard RSI will have a potential initialization error which reduces with every new data point calculated meaning early results should be regarded as unreliable until enough calculation iterations have occurred for convergence.
Hence Cutler proposed using Simple Moving Averaging for gain and loss data which this Indicator is based on.
Having "Reverse engineered" prices for any oscillator makes the planning, and execution of strategies around that oscillator far simpler, more timely and effective.
Introducing the Reverse Cutlers RSI which consists of plotted lines on a scale of 0 to 100, and an optional infobox.
The RSI scale is divided into zones:
• Scale high (100)
• Bull critical zone (80 - 100)
• Bull control zone (62 - 80)
• Scale midline (50)
• Bear control zone (20 - 38)
• Bear critical zone (0 - 20)
• Scale low (0)
The RSI plots which graphically display output closing price levels where Cutlers RSI value will crossover:
• RSI (eq) (previous RSI value)
• RSI MA signal line
• RSI Test price
• Alert level high
• Alert level low
The info box displays output closing price levels where Cutlers RSI value will crossover:
• Its previous value. ( RSI )
• Bull critical zone.
• Bull control zone.
• Mid-Line.
• Bear control zone.
• Bear critical zone.
• RSI MA signal line
• Alert level High
• Alert level low
And also displays the resultant RSI for a user defined closing price:
• Test price RSI
The infobox outputs can be shown for the current bar close, or the next bar close.
The user can easily select which information they want in the infobox from the setttings
Importantly:
All info box price levels for the current bar are calculated immediately upon the current bar closing and a new bar opening, they will not change until the current bar closes.
All info box price levels for the next bar are projections which are continually recalculated as the current price changes, and therefore fluctuate as the current price changes.
Understanding the Relative Strength Index
At its simplest the RSI is a measure of how quickly traders are bidding the price of an asset up or down.
It does this by calculating the difference in magnitude of price gains and losses over a specific lookback period to evaluate market conditions.
The RSI is displayed as an oscillator (a line graph that can move between two extremes) and outputs a value limited between 0 and 100.
It is typically accompanied by a moving average signal line.
Traditional interpretations
Overbought and oversold:
An RSI value of 70 or above indicates that an asset is becoming overbought (overvalued condition), and may be may be ready for a trend reversal or corrective pullback in price.
An RSI value of 30 or below indicates that an asset is becoming oversold (undervalued condition), and may be may be primed for a trend reversal or corrective pullback in price.
Midline Crossovers:
When the RSI crosses above its midline ( RSI > 50%) a bullish bias signal is generated. (only take long trades)
When the RSI crosses below its midline ( RSI < 50%) a bearish bias signal is generated. (only take short trades)
Bullish and bearish moving average signal Line crossovers:
When the RSI line crosses above its signal line, a bullish buy signal is generated
When the RSI line crosses below its signal line, a bearish sell signal is generated.
Swing Failures and classic rejection patterns:
If the RSI makes a lower high, and then follows with a downside move below the previous low, a Top Swing Failure has occurred.
If the RSI makes a higher low, and then follows with an upside move above the previous high, a Bottom Swing Failure has occurred.
Examples of classic swing rejection patterns
Bullish swing rejection pattern:
The RSI moves into oversold zone (below 30%).
The RSI rejects back out of the oversold zone (above 30%)
The RSI forms another dip without crossing back into oversold zone.
The RSI then continues the bounce to break up above the previous high.
Bearish swing rejection pattern:
The RSI moves into overbought zone (above 70%).
The RSI rejects back out of the overbought zone (below 70%)
The RSI forms another peak without crossing back into overbought zone.
The RSI then continues to break down below the previous low.
Divergences:
A regular bullish RSI divergence is when the price makes lower lows in a downtrend and the RSI indicator makes higher lows.
A regular bearish RSI divergence is when the price makes higher highs in an uptrend and the RSI indicator makes lower highs.
A hidden bullish RSI divergence is when the price makes higher lows in an uptrend and the RSI indicator makes lower lows.
A hidden bearish RSI divergence is when the price makes lower highs in a downtrend and the RSI indicator makes higher highs.
Regular divergences can signal a reversal of the trending direction.
Hidden divergences can signal a continuation in the direction of the trend.
Chart Patterns:
RSI regularly forms classic chart patterns that may not show on the underlying price chart, such as ascending and descending triangles & wedges , double tops, bottoms and trend lines etc.
Support and Resistance:
It is very often easier to define support or resistance levels on the RSI itself rather than the price chart.
Modern interpretations in trending markets:
Modern interpretations of the RSI stress the context of the greater trend when using RSI signals such as crossovers, overbought/oversold conditions, divergences and patterns.
Constance Brown, CMT , was one of the first who promoted the idea that an oversold reading on the RSI in an uptrend is likely much higher than 30%, and that an overbought reading on the RSI during a downtrend is much lower than the 70% level.
In an uptrend or bull market, the RSI tends to remain in the 40 to 90 range, with the 40-50 zone acting as support.
During a downtrend or bear market, the RSI tends to stay between the 10 to 60 range, with the 50-60 zone acting as resistance.
For ease of executing more modern and nuanced interpretations of RSI it is very useful to break the RSI scale into bull and bear control and critical zones.
These ranges will vary depending on the RSI settings and the strength of the specific market’s underlying trend.
Limitations of the RSI
Like most technical indicators, its signals are most reliable when they conform to the long-term trend.
True trend reversal signals are rare, and can be difficult to separate from false signals.
False signals or “fake-outs”, e.g. a bullish crossover, followed by a sudden decline in price, are common.
Since the indicator displays momentum, it can stay overbought or oversold for a long time when an asset has significant sustained momentum in either direction.
Data Length Dependency when using wilders smoothing method of calculating RSI means that wilders standard RSI will have a potential initialization error which reduces with every new data point calculated meaning early results should be regarded as unreliable until calculation iterations have occurred for convergence.
Reverse Cutlers Relative Strength IndexIntroduction
The Reverse Cutlers Relative Strength Index (RCRSI) is an indicator which tells the user what price is required to give a particular Cutlers Relative Strength Index (RSI) value, or cross its Moving Average (MA) signal line.
Overview
Background & Credits:
The relative strength index (RSI) is a momentum indicator used in technical analysis that was originally developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, “New Concepts in Technical Trading Systems.”.
Cutler created a variation of the RSI known as “Cutlers RSI” using a different formulation to avoid an inherent accuracy problem which arises when using Wilders method of smoothing.
Further developments in the use, and more nuanced interpretations of the RSI have been developed by Cardwell, and also by well-known chartered market technician, Constance Brown C.M.T., in her acclaimed book "Technical Analysis for the Trading Professional” 1999 where she described the idea of bull and bear market ranges for RSI, and while she did not actually reveal the formulas, she introduced the concept of “reverse engineering” the RSI to give price level outputs.
Renowned financial software developer, co-author of academic books on finance, and scientific fellow to the Department of Finance and Insurance at the Technological Educational Institute of Crete, Giorgos Siligardos PHD. brought a new perspective to Wilder’s RSI when he published his excellent and well-received articles "Reverse Engineering RSI " and "Reverse Engineering RSI II " in the June 2003, and August 2003 issues of Stocks & Commodities magazine, where he described his methods of reverse engineering Wilders RSI.
Several excellent Implementations of the Reverse Wilders Relative Strength Index have been published here on Tradingview and elsewhere.
My utmost respect, and all due credits to authors of related prior works.
Introduction
It is worth noting that while the general RSI formula, and the logic dictating the UpMove and DownMove data series as described above has remained the same as the Wilders original formulation, it has been interpreted in a different way by using a different method of averaging the upward, and downward moves.
Cutler recognized the issue of data length dependency when using wilders smoothing method of calculating RSI which means that wilders standard RSI will have a potential initialization error which reduces with every new data point calculated meaning early results should be regarded as unreliable until enough calculation iterations have occurred for convergence.
Hence Cutler proposed using Simple Moving Averaging for gain and loss data which this Indicator is based on.
Having "Reverse engineered" prices for any oscillator makes the planning, and execution of strategies around that oscillator far simpler, more timely and effective.
Introducing the Reverse Cutlers RSI which consists of plotted lines on a scale of 0 to 100, and an optional infobox.
The RSI scale is divided into zones:
• Scale high (100)
• Bull critical zone (80 - 100)
• Bull control zone (62 - 80)
• Scale midline (50)
• Bear critical zone (20 - 38)
• Bear control zone (0 - 20)
• Scale low (0)
The RSI plots are:
• Cutlers RSI
• RSI MA signal line
• Test price RSI
• Alert level high
• Alert level low
The info box displays output closing price levels where Cutlers RSI value will crossover:
• Its previous value. (RSI )
• Bull critical zone.
• Bull control zone.
• Mid-Line.
• Bear control zone.
• Bear critical zone.
• RSI MA signal line
• Alert level High
• Alert level low
And also displays the resultant RSI for a user defined closing price:
• Test price RSI
The infobox outputs can be shown for the current bar close, or the next bar close.
The user can easily select which information they want in the infobox from the setttings
Importantly:
All info box price levels for the current bar are calculated immediately upon the current bar closing and a new bar opening, they will not change until the current bar closes.
All info box price levels for the next bar are projections which are continually recalculated as the current price changes, and therefore fluctuate as the current price changes.
Understanding the Relative Strength Index
At its simplest the RSI is a measure of how quickly traders are bidding the price of an asset up or down.
It does this by calculating the difference in magnitude of price gains and losses over a specific lookback period to evaluate market conditions.
The RSI is displayed as an oscillator (a line graph that can move between two extremes) and outputs a value limited between 0 and 100.
It is typically accompanied by a moving average signal line.
Traditional interpretations
Overbought and oversold:
An RSI value of 70 or above indicates that an asset is becoming overbought (overvalued condition), and may be may be ready for a trend reversal or corrective pullback in price.
An RSI value of 30 or below indicates that an asset is becoming oversold (undervalued condition), and may be may be primed for a trend reversal or corrective pullback in price.
Midline Crossovers:
When the RSI crosses above its midline (RSI > 50%) a bullish bias signal is generated. (only take long trades)
When the RSI crosses below its midline (RSI < 50%) a bearish bias signal is generated. (only take short trades)
Bullish and bearish moving average signal Line crossovers:
When the RSI line crosses above its signal line, a bullish buy signal is generated
When the RSI line crosses below its signal line, a bearish sell signal is generated.
Swing Failures and classic rejection patterns:
If the RSI makes a lower high, and then follows with a downside move below the previous low, a Top Swing Failure has occurred.
If the RSI makes a higher low, and then follows with an upside move above the previous high, a Bottom Swing Failure has occurred.
Examples of classic swing rejection patterns
Bullish swing rejection pattern:
The RSI moves into oversold zone (below 30%).
The RSI rejects back out of the oversold zone (above 30%)
The RSI forms another dip without crossing back into oversold zone.
The RSI then continues the bounce to break up above the previous high.
Bearish swing rejection pattern:
The RSI moves into overbought zone (above 70%).
The RSI rejects back out of the overbought zone (below 70%)
The RSI forms another peak without crossing back into overbought zone.
The RSI then continues to break down below the previous low.
Divergences:
A regular bullish RSI divergence is when the price makes lower lows in a downtrend and the RSI indicator makes higher lows.
A regular bearish RSI divergence is when the price makes higher highs in an uptrend and the RSI indicator makes lower highs.
A hidden bullish RSI divergence is when the price makes higher lows in an uptrend and the RSI indicator makes lower lows.
A hidden bearish RSI divergence is when the price makes lower highs in a downtrend and the RSI indicator makes higher highs.
Regular divergences can signal a reversal of the trending direction.
Hidden divergences can signal a continuation in the direction of the trend.
Chart Patterns:
RSI regularly forms classic chart patterns that may not show on the underlying price chart, such as ascending and descending triangles & wedges, double tops, bottoms and trend lines etc.
Support and Resistance:
It is very often easier to define support or resistance levels on the RSI itself rather than the price chart.
Modern interpretations in trending markets:
Modern interpretations of the RSI stress the context of the greater trend when using RSI signals such as crossovers, overbought/oversold conditions, divergences and patterns.
Constance Brown, CMT, was one of the first who promoted the idea that an oversold reading on the RSI in an uptrend is likely much higher than 30%, and that an overbought reading on the RSI during a downtrend is much lower than the 70% level.
In an uptrend or bull market, the RSI tends to remain in the 40 to 90 range, with the 40-50 zone acting as support.
During a downtrend or bear market, the RSI tends to stay between the 10 to 60 range, with the 50-60 zone acting as resistance.
For ease of executing more modern and nuanced interpretations of RSI it is very useful to break the RSI scale into bull and bear control and critical zones.
These ranges will vary depending on the RSI settings and the strength of the specific market’s underlying trend.
Limitations of the RSI
Like most technical indicators, its signals are most reliable when they conform to the long-term trend.
True trend reversal signals are rare, and can be difficult to separate from false signals.
False signals or “fake-outs”, e.g. a bullish crossover, followed by a sudden decline in price, are common.
Since the indicator displays momentum, it can stay overbought or oversold for a long time when an asset has significant sustained momentum in either direction.
Data Length Dependency when using wilders smoothing method of calculating RSI means that wilders standard RSI will have a potential initialization error which reduces with every new data point calculated meaning early results should be regarded as unreliable until calculation iterations have occurred for convergence.
[blackcat] L1 Buff AverageLevel: 1
Background
This indicator buffs up your moving averages using the volume-weighting method presented in Buff Dormeier's article in 2001, "Buff Up Your Moving Averages." The weighting formula has been created as a function in pine script so that it can be referenced from any analysis technique or strategy. In addition, a simple two-line volume-weighted average indicator that references the function has also been included.
Function
The name of the volume-weighted average function is "BuffAverage()." The function has two inputs, price and length. The price input represents the price value upon which the average calculation is based. The length input represents the number of bars that are used in the calculation of the average. The two-line volume-weighted average indicator is presented. This indicator has three inputs. The price input represents the price value upon which the average calculation is based. The FastAvg input represents the number of bars to use in the fast volume-weighted average calculation. The SlowAvg input represents the number of bars to use in the slow volume-weighted average calculation. A simple alert criteria has also been included to provide an alert when the two lines cross.
Key Signal
FastBuff Line --> fast line in yellow;
SlowBuff Line --> slow line in fuchsia.
Remarks
This is a Level 1 free and open source indicator.
Feedbacks are appreciated.
Doji Hunter█ OVERVIEW
This script is built to search for 8 different Doji candlestick patterns in markets and makes them appear on screen with bar coloring and creating color-coded labels/shapes. It will identify the following variants based upon user input for various rules to abide by:
Gapping Up
Gapping Down
Gravestone
Dragonfly
Long-Legged
Rickshaw Man
Northern (Doji in uptrend)
Southern (Doji in downtrend)
Note: for the remainder of this description, the types for inputs will be marked by italic text.
█ OPTIONS
This script features a wide range of options available to the user to modify how it functions. The first set of inputs dictate how the trend analysis is done with moving averages. The second and third sets of inputs dictate specific rules for how Doji candles are analyzed and the colors used for when they appear.
█ INPUTS (short)
1 — Moving Average Rules:
The Northern and Southern Doji variants require some trend analysis which will be done by Moving Averages. The inputs in this section change various things about the moving average(s) to be used. In the second section of inputs, there is one boolean option that will nullify the need for trend detection and consolidates the Northern and Southern Doji variants into one.
2/3 — Doji Rules and Colors:
The next two sections of inputs correspond to the various rules that dictate how various doji variants will be analyzed, as well as the colors that correspond to each variant. The colors will also apply to each of the labels/shapes used.
4 — Diagnostics:
The last boolean will allow the user to see extra detail with regards to how and when dojis are detected. Note: This is not a part of any prior section and is simply included as a last functional item to the list of all inputs.
An example of multiple labels being shown on screen for various types of Dojis (DJI 1D chart):
█ INPUTS (extended)
1 — Moving Average Rules:
This section consists of 10 different inputs specific to the rules on how the moving average functions for trend analysis.
"Trend Rule" ( string list) determines which Moving Average will be used for trend detection. It has 3 options: "MA 1", "MA 2", or "BOTH". The second input "Trend Source" determines which OHLC (or combination) value to use in comparison to either MA 1 or MA 2 (EX: Trend Rule -> "MA 1" and Trend Source -> "close": if close > MA 1 -> uptrend, downtrend otherwise). If "BOTH" is selected then "Trend Source" is ignored and added nuance in the script ensures that the shorter MA being above the longer MA yields an uptrend (downtrend otherwise).
The next 8 inputs focus on 4 different parts of both MA 1 and 2.
Length ( integer(s) )
Color
Switch between SMA/EMA ( boolean(s) )
Source for MA
Note: Additional attention to detail has been made here as trend direction is ignored if "BOTH" is selected for the MA Rules and the lengths of both Moving Averages are set to be the same.
2/3 — Doji Rules and Colors:
The next two sections include 19 inputs that are related to how this script will analyze and identify the different variants of Doji candles.
"Identify Pattern On Close" ( boolean ) modifies which candles are to be used for determining when Doji candles are recognized. This changes an offset used for historical reference on some global variables which will force the script to only identify patterns after the current candle has closed.
"Doji Body Tolerance" ( float ) tells the script the maximum % the candle body may be of the high-low range to be considered a Doji candle.
"Doji Wick Sample" ( integer ) defines how many prior candles to sample from in calculating the current average upper and lower wick sizes.
"Simplify Northern/Southern Dojis" ( boolean ) makes this script ignore trend direction for Doji detection and consolidates Northern and Southern Dojis into being recognized as the same. This has an added effect of removing the plotted moving averages from the screen.
"Northern/Southern Display" ( string list ) that has multiple options for how Northern and Southern Dojis will be displayed on screen. Because of how labels may be extremely taxing on TradingView's servers to display, the default setting is "shapes" where Northern and Southern (N/S) Dojis will be marked with a colored triangle at the top of the candle. If "Simplify Northern/Southern Dojis" is true, all N/S Dojis will be marked with an x-cross instead. Other options include "labels" which enables the use of labels accompanied by their respective tooltip and color, or "none" where N/S Dojis will be only noticeable by their changed barcolor.
"Allow Gravestone/Dragonfly Shadows" ( boolean ) allows a bit of additional nuance to the definition of Gravestone or Dragonfly Dojis with small shadows.
"Gravestone/Dragonfly Shadow Tolerance" ( float ) defines the maximum % that the lower wick/upper wick (respectively) may be relative to the high-low range for Gravestone or Dragonfly Dojis to still be considered valid.
"Doji Long Wick Setting" ( string list) is a list of settings for three different ways of confirming if a Doji is Long-Legged. The settings are "one", "two", and "average". These define how many wick lengths of a candle need to exceed the calculated average wick lengths (EX: "both" -> upper wick length > upper wick average and lower wick length > lower wick average). The "average" setting will combine the lengths of both wicks and both prior wick averages, divide both of these sums by 2 and compare them instead.
"Doji Long Wick Tolerance" ( float ) defines how large compared to the averages that wick lengths need to be in order for them to be considered "Long-Legged" (EX: 1.50 -> upper/lower wick needs to exceed 150% the average of previous upper/lower wicks).
"Rickshaw Man Body Placement Tolerance" ( float ) defines how close to the high-low range's midpoint the candle body's midpoint needs to be in order for it to be considered a Rickshaw Man Doji candle instead.
The remaining 9 inputs define the colors to use for differentiating between all Doji variants this script will recognize.
█ USAGE
My hope for this script is that users find this easy to use/understand and will tinker with the input values to better identify Doji candlesticks across a wide range of markets.
Suggestions for changes in the future are welcome.
Squeeze Momentum [Plus]The "Momentum" in this indicator is smoothed out using linear regression. The Momentum is what is displayed on the indicator as a histogram, its purpose is obvious (to show momentum).
What is a Squeeze? A squeeze occurs when Bollinger Bands tighten up enough to slip inside of Keltner Channels .
This is interpreted as price is compressing and building up energy before releasing it and making a big move.
Traditionally, John Carter's version uses 20 period SMAs as the basis lines on both the BB and the KC.
In this version, I've given the freedom to change this and try out different types of moving averages.
The original squeeze indicator had only one Squeeze setting, though this new one has three.
The gray dot Squeeze, call it a "low squeeze" or an "early squeeze" - this is the easiest Squeeze to form based on its settings.
The orange dot Squeeze is the original from the first Squeeze indicator.
And finally, the yellow dot squeeze, call it a "high squeeze" or "power squeeze" - is the most difficult to form and suggests price is under extreme levels of compression.
Now to explain the parameters:
Squeeze Input - This is just the source for the Squeeze to use, default value is closing price.
Length - This is the length of time used to calculate the Bollinger Bands and Keltner Channels .
Bollinger Bands Calculation Type - Selects the type of moving average used to create the Bollinger Bands .
Keltner Channel Calculation Type - Selects the type of moving average used to create the Keltner Channel.
Color Format - you to choose one of 5 different color schemes.
Draw Divergence - Self explanatory here, this will auto-draw divergence on the indicator.
Gray Background for Dark Mode - to make them more visually appealing.
Added ADX (Average Directional Index) that measure a trend’s strength. The higher the ADX value, the stronger the trend. The ADX line is white when it has a positive slope, otherwise it is gray. When the ADX has a very large dispersion with respect to the momentum histogram, increase the scale number.
Added "H (Hull Moving Average) Signal". Hull is a extremely responsive and smooth moving average created by Alan Hull in 2005. Have option to chose between 3 Hull variations.
Added "Williams Vix Fix" signal. The Vix is one of the most reliable indicators in history for finding market bottoms. The Williams Vix Fix is simply a code from Larry Williams creating almost identical results for creating the same ability the Vix has to all assets.
The VIX has always been much better at signaling bottoms than tops. Simple reason is when market falls retail traders panic and increase volatility, and professionals come in and capitalize on the situation. At market tops there is no one panicking... just liquidity drying up.
The FE green triangles are "Filtered Entries"
The AE green triangles are "Aggressive Filtered Entries"
WaveTrend MultiEMAThis is a modification of LazyBear's WaveTrend. The SMA trend has been removed and a shorter time frame EMA has been added in black. The idea is to buy when the shorter time frame starts to curl up and the longer time frame, green, has started to either flatten out or curl up too. Sell when the shorter time frame has started down and green has either flattened or bottomed out as well. The black line will generate some noise so the key is to use the two in combination. My final goal would be to have the green line looking at daily candles and the black line looking at a 2 or 4 hour candle, but I haven't figured out how to do that.
Tenkansen&Kijunsen LinesYou can see 2 sections on this script
1. Kijunsen Lines Section
Basicly calculated by adding the highest high and the lowest low over the past 26 periods and dividing the result by two.
Kijunsen Lines section has 4 lines
a. 60 Minutes Kijunsen
b. 240 Minutes Kijunsen
c. 1 Day Kijunsen
d. 1 Week Kijunsen
You can see all 4 kijunsen at all periods.
2. Tenkansen Lines Section
Basicly calculated by adding the highest high and the highest low over the past nine periods and then dividing the result by two
Tenkansen Lines section has 4 lines
a. 60 Minutes Tenkansen
b. 240 Minutes Tenkansen
c. 1 Day Tenkansen
d. 1 Week Tenkansen
You can see all 4 tenkansen at all periods.
With this you can see 4 kijunsen and 4 tenkansen lines without changing periods. (May have some calculating problems. Because of different candle systems.)
This indicator has 2 functions
A. Support Function
All kijunsen and all tenkansen lines has support function.
B. Resistance Function
All kijunsen and all tenkansen lines has resistance function.
RSI-VWAP Indicator %█ OVERALL
Simple and effective script that, as you already know, uses vwap as source of the rsi, and with good results as long as the market has no long-term downtrend.
RsiVwap = rsi (vwap (close), Length)
The default settings are for BTC in a 30 minute time frame. For other pairs and time frames you just have to play with the settings.
█ FEATURES
• The option to start trading from a certain date has been added.
• To make the profit more progressive, a percentage of your equity is used for entries and a percentage of your position is used for closings.
• The option to trade in Spot mode has been added, since, for the TradingView backtest, the money is infinite and if you do not limit it somehow,
it would offer you much better profits than the live trading.
QuantityOnLong = Spot ? (EquityPercent / 100) * ((strategy.equity / close) - strategy.position_size) : (EquityPercent / 100) * (strategy.equity / close)
• The option to stop the system when the drawdown exceeds the fixed limit has been added.
Drawdown, as you already know, is a very important measure of risk in trading systems.
The maximum drawdown will tell us what the maximum loss of a trading system has been during a period. This maximum loss is determined by:
strategy.risk.max_drawdown(Risk, strategy.percent_of_equity)
• Leverage plotted on labels added.
█ ALERTS
To enjoy the benefits of automatic trading, TradingView alerts can be used as direct buy-sell orders on spot, or long-close orders with leverage.
Currently there are Chrome extensions that act as a bridge between TradingView and your Exchange or Broker.
This is an example of syntax for this type of extensions. Copy and paste a message like this into the alert window:
{{strategy.order.action}} @ {{strategy.order.price}} | e = {{exchange}} a = account s = {{ticker}} b = {{strategy.order.action}} {{strategy.order.alert_message}}
█ NOTE
Certain Risks of Live Algorithmic Trading You Should Know:
• Backtesting cannot assure actual results.
• The relevant market might fail or behave unexpectedly.
• Your broker may experience failures in its infrastructure, fail to execute your orders in a correct or timely fashion or reject your orders.
• The system you use for generating trading orders, communicating those orders to your broker, and receiving queries and trading results from your broker may fail.
• Time lag at various point in live trading might cause unexpected behavior.
• The systems of third parties in addition to those of the provider from which we obtain various services, your broker, and the applicable securities market may fail or malfunction.
█ THANKS
Thanks to TradingView, its Pine code, its community and especially those Pine wizards who post their ideas that helps us to learn.
If the world is heading toward a equitable new world economic order, let's get rich first ...
Happy trading!
Price Action - Support & Resistance by DGTSᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ , is undoubtedly one of the key concepts of technical analysis
█ Sᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ Dᴇꜰɪɴɪᴛɪᴏɴ
Support and Resistance terms are used by traders to refer to price levels on charts that tend to act as barriers, preventing the price of an financial instrument from getting pushed in a certain direction.
A support level is a price level where buyers are more aggressive than sellers. This means that the price is more likely to "bounce" off this level rather than break through it. However, once the price has breached this level it is likely to continue falling until meeting another support level.
A resistance level is the opposite of a support level. It is where the price tends to find resistance as it rises. Again, this means that the price is more likely to "bounce" off this level rather than break through it. However, once the price has breached this level it is likely to continue rising until meeting another resistance level.
A previous support level will sometimes become a resistance level when the price attempts to move back up, and conversely, a resistance level will become a support level as the price temporarily falls back.
█ Iᴅᴇɴᴛɪꜰʏɪɴɢ Sᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ
Support and resistance can come in various forms, and the concept is more difficult to master than it first appears. Identification of key support and resistance levels is an essential ingredient to successful technical analysis.
If the price stalls and reverses in the same price area on minimum of two different occasions, then a horizontal line is drawn to show that the market is struggling to move past that area. Those areas are static barriers, one of the most popular forms of support/resistance and are highlighted with horizontal lines.
Repeated test , the more often a support/resistance level is "tested" over an extended period of time (touched and bounced off by price), the more significance is given to that specific level
High volume , the more buying and selling that has occurred at a particular price level, the stronger the support or resistance level is likely to be
Market psychology , plays a major role as traders and investors remember the past and react to changing conditions to anticipate future market movement.
Psychological levels , is a price level that significantly affects the price of an underlying financial instrument. Typically, near round numbers often serve as support and resistance
The following support and resistance related topics are beyond the scope of this study, so they will be mentioned roughly only as a reference for support and resistance concept
Trendlines , Support and resistance levels in trends are dynamic. Throughout an uptrend, levels of support tend to look like a trendline, usually clustering around higher lows. As the price rises, the price where buyers consider the stock to be “too cheap” also changes, which creates new support levels on the way up. The same is also true for resistance levels. In an uptrend, a stock is continuously breaking through perceived resistance levels and making new highs
Moving Averages , is a constantly changing line that smooths out past price data while also allowing the trader to identify support and resistance. In the example Notice how the price of the asset finds support at the moving average when the trend is up, and how it acts as resistance when the trend is down
The Fibonacci Retracement/Extension tool , is a favorite among many short-term traders because it clearly identifies levels of potential support and resistance
Pivot Point Calculations , is another common technical analysis technique, where pivot point is calculated based on the high, low, and closing prices of previous trading session/day and support & resistance levels are projected based on the pivot point, different calculation techniques are available, as presented in this example of an pivot point indicator : PVTvX by DGT
█ Tʀᴀᴅɪɴɢ Bᴀꜱᴇᴅ ᴏɴ Sᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ
Once an area or "zone" of support or resistance has been identified, those price levels can serve as potential entry or exit points because, as a price reaches a point of support or resistance, it will do one of two things—bounce back away from the support or resistance level (trading ranges), or violate the price level and continue in its direction (trading breakouts) —until it hits the next support or resistance level
The basic trading method for using support and resistance is to buy near support in uptrends or the parts of ranges or chart patterns where prices are moving up and to sell/sell short near resistance in downtrends or the parts of ranges and chart patterns where prices are moving down. Buying near support or selling near resistance can pay off, but there is no assurance that the support or resistance will hold. Therefore, consider waiting for some confirmation that the market is still respecting that area
Trading breakouts, a breakout is a potential trading opportunity that occurs when an asset's price moves above a resistance level or moves below a support level on increasing volume. The first step in trading breakouts is to identify current price trend patterns along with support and resistance levels in order to plan possible entry and exit points. Once the asset trades beyond the price barrier, volatility tends to increase and prices usually trend in the breakout's direction. Breakouts are such an important trading strategy since these setups are the starting point for future volatility increases, large price swings and, in many circumstances, major price trends. When trading breakouts, it is important to consider the underlying asset's support and resistance levels. The more times an asset price has touched these areas, the more valid these levels are and the more important they become. At the same time, the longer these support and resistance levels have been in play, the better the outcome when the asset price finally breaks out. Asset prices will often move slightly further than we expect them to. This doesn't happen all the time, but when it does it is called a false breakout. Therefore it is important to consider waiting for some confirmation while trading breakouts. It’s also popular for traders to sell 50% of their positions at the resistance level, and hold the rest in anticipation of a breakout above resistance
█ Pʀɪᴄᴇ Aᴄᴛɪᴏɴ - Sᴜᴘᴘᴏʀᴛ & Rᴇꜱɪꜱᴛᴀɴᴄᴇ ʙʏ DGT Sᴛᴜᴅʏ
This experimental study attempts to identify the support and resistance levels. Assumes a simple logic to discover moments where the price is rising or falling consecutively for minimum 3 bars with the condition volume increases on each bar and the last bar’s volume should be bigger than the long term volume moving average. A line will be drawn at the end of the move (highest or lowest, depending on the move direction), the line will be drawn at minimum on the 3rd bar and if condition holds for other consecutive bars the line will switch to 4th, 5th etc bar.
Lines will not be deleted so the historical ones will remain and will emphasis the levels significance when they overlap in feature. Strong levels are more likely to hold and cause the price to move in the other direction, whereas the minor levels may only cause the price to pause and keep moving in the same direction. Determining future levels of support and resistance can drastically improve the returns of a short-term investing strategy
Bar colors will be painted based on the volume of the specific bar to its long term volume moving average. This will help identifying the support and resistance levels significance and emphasis the sings of breakouts
Finally, Volume spikes will be marked on top of the price chart. A high volume usually indicates more interest in the security and the presence of institutional traders. However, a rapidly rising price in an uptrend accompanied by a huge volume may be a sign of exhaustion. Traders usually look for breaks of support and resistance to enter positions. When security break critical levels without volume , you should consider the breakout suspect and prime for a reversal off the highs/lows. Volume spikes are often the result of news-driven events. Volume spike will often lead to sharp reversals since the moves are unsustainable due to the imbalance of supply and demand
A good example with many support and resistance concepts observed on a stock chart and detected by the study
Settings:
Length of volume moving average, where volume moving average is used to detect support and resistance levels, is used as reference to compare with threshold values for volume spikes and colors of the bars
Hint, to get more historical lines scrolling chart to left will enable visualization of them. Please note they may appear to much all 500 line limit is used 😉
Special thanks to @HEMANT Telegram user, for his observations and suggestions
Disclaimer:
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
MrBS:Directional Movement Index [Trend Friend Strategy]This goes with my MrBS:DMI+ indicator. I originally combined them into one, but then you cannot set alerts based on what the ADX and DMI is doing, only strategy alerts, so separate ones have more flexibility and uses.
Indicator Version is found under "MrBS:Directional Movement Index " ()
//// THE IDEA
The majority of profits made in the market come from trending markets. Of course there are strategies that would say otherwise but for the majority of people, THE TREND IS YOUR FRIEND (until the end). The idea is to follow the trend, entering once it has established its self and exiting positions when the trend weakens. This strategy gives a rough idea of the returns produced from following purely the ADX signals. At first Heikin Ashi values were used for the calculation but the results show it's not that effective. The functionality to switch between calculation types has been left in, so we can uses HA candle data to generate signals from while looking at an OHLC chart, if we want to experiment. Due to the way strategies work, we are unable to get reliable results when running the strategy on the HA chart even if we are calculating the signals from the real OHLC values. It is best to always run strategies on standard charts.
When using this strategy, I look for confirmation of the signal based on stochastic (14:3:6) direction, reversal level of stochastic, and divergance, to add confidence and adjust position size accordingly. I am going to try and code some version of that in future updates, if anyone can help or has suggestions please drop me a message.
//// INDICATOR DETAILS
- The default settings are for optimized Daily charts, for 4 hour I would suggest a smoothing of 2.
- The default values used for calculation are the Real OHLC, we can change this to Heikin Ashi in the menu.
- The strategy enters a position when ADX crosses the threshold level, and closes the position when ADX starts to fall.
- There is a signal filter in the form of a 377 period Hull Moving Average, which the price must be above or bellow for long and short positions respectively.
- The strategy closes the position when a cross-under of the ADX and its 4 period EMA. This is an attempt to stay into positions longer as sometimes the ADX will fall for 1 bar and then keep rising, while the overall trend is strong. The downside to this is that we exit trades later and this affects our max drawdown.
Ruckard TradingLatinoThis strategy tries to mimic TradingLatino strategy.
The current implementation is beta.
Si hablas castellano o espanyol por favor consulta MENSAJE EN CASTELLANO más abajo.
It's aimed at BTCUSDT pair and 4h timeframe.
STRATEGY DEFAULT SETTINGS EXPLANATION
max_bars_back=5000 : This is a random number of bars so that the strategy test lasts for one or two years
calc_on_order_fills=false : To wait for the 4h closing is too much. Try to check if it's worth entering a position after closing one. I finally decided not to recheck if it's worth entering after an order is closed. So it is false.
calc_on_every_tick=false
pyramiding=0 : We only want one entry allowed in the same direction. And we don't want the order to scale by error.
initial_capital=1000 : These are 1000 USDT. By using 1% maximum loss per trade and 7% as a default stop loss by using 1000 USDT at 12000 USDT per BTC price you would entry with around 142 USDT which are converted into: 0.010 BTC . The maximum number of decimal for contracts on this BTCUSDT market is 3 decimals. E.g. the minimum might be: 0.001 BTC . So, this minimal 1000 amount ensures us not to entry with less than 0.001 entries which might have happened when using 100 USDT as an initial capital.
slippage=1 : Binance BTCUSDT mintick is: 0.01. Binance slippage: 0.1 % (Let's assume). TV has an integer slippage. It does not have a percentage based slippage. If we assume a 1000 initial capital, the recommended equity is 142 which at 11996 USDT per BTC price means: 0.011 BTC. The 0.1% slippage of: 0.011 BTC would be: 0.000011 . This is way smaller than the mintick. So our slippage is going to be 1. E.g. 1 (slippage) * 0.01 (mintick)
commission_type=strategy.commission.percent and commission_value=0.1 : According to: binance . com / en / fee / schedule in VIP 0 level both maker and taker fees are: 0.1 %.
BACKGROUND
Jaime Merino is a well known Youtuber focused on crypto trading
His channel TradingLatino
features monday to friday videos where he explains his strategy.
JAIME MERINO STANCE ON BOTS
Jaime Merino stance on bots (taken from memory out of a 2020 June video from him):
'~
You know. They can program you a bot and it might work.
But, there are some special situations that the bot would not be able to handle.
And, I, as a human, I would handle it. And the bot wouldn't do it.
~'
My long term target with this strategy script is add as many
special situations as I can to the script
so that it can match Jaime Merino behaviour even in non normal circumstances.
My alternate target is learn Pine script
and enjoy programming with it.
WARNING
This script might be bigger than other TradingView scripts.
However, please, do not be confused because the current status is beta.
This script has not been tested with real money.
This is NOT an official strategy from Jaime Merino.
This is NOT an official strategy from TradingLatino . net .
HOW IT WORKS
It basically uses ADX slope and LazyBear's Squeeze Momentum Indicator
to make its buy and sell decisions.
Fast paced EMA being bigger than slow paced EMA
(on higher timeframe) advices going long.
Fast paced EMA being smaller than slow paced EMA
(on higher timeframe) advices going short.
It finally add many substrats that TradingLatino uses.
SETTINGS
__ SETTINGS - Basics
____ SETTINGS - Basics - ADX
(ADX) Smoothing {14}
(ADX) DI Length {14}
(ADX) key level {23}
____ SETTINGS - Basics - LazyBear Squeeze Momentum
(SQZMOM) BB Length {20}
(SQZMOM) BB MultFactor {2.0}
(SQZMOM) KC Length {20}
(SQZMOM) KC MultFactor {1.5}
(SQZMOM) Use TrueRange (KC) {True}
____ SETTINGS - Basics - EMAs
(EMAS) EMA10 - Length {10}
(EMAS) EMA10 - Source {close}
(EMAS) EMA55 - Length {55}
(EMAS) EMA55 - Source {close}
____ SETTINGS - Volume Profile
Lowest and highest VPoC from last three days
is used to know if an entry has a support
VPVR of last 100 4h bars
is also taken into account
(VP) Use number of bars (not VP timeframe): Uses 'Number of bars {100}' setting instead of 'Volume Profile timeframe' setting for calculating session VPoC
(VP) Show tick difference from current price {False}: BETA . Might be useful for actions some day.
(VP) Number of bars {100}: If 'Use number of bars (not VP timeframe)' is turned on this setting is used to calculate session VPoC.
(VP) Volume Profile timeframe {1 day}: If 'Use number of bars (not VP timeframe)' is turned off this setting is used to calculate session VPoC.
(VP) Row width multiplier {0.6}: Adjust how the extra Volume Profile bars are shown in the chart.
(VP) Resistances prices number of decimal digits : Round Volume Profile bars label numbers so that they don't have so many decimals.
(VP) Number of bars for bottom VPOC {18}: 18 bars equals 3 days in suggested timeframe of 4 hours. It's used to calculate lowest session VPoC from previous three days. It's also used as a top VPOC for sells.
(VP) Ignore VPOC bottom advice on long {False}: If turned on it ignores bottom VPOC (or top VPOC on sells) when evaluating if a buy entry is worth it.
(VP) Number of bars for VPVR VPOC {100}: Number of bars to calculate the VPVR VPoC. We use 100 as Jaime once used. When the price bounces back to the EMA55 it might just bounce to this VPVR VPoC if its price it's lower than the EMA55 (Sells have inverse algorithm).
____ SETTINGS - ADX Slope
ADX Slope
help us to understand if ADX
has a positive slope, negative slope
or it is rather still.
(ADXSLOPE) ADX cut {23}: If ADX value is greater than this cut (23) then ADX has strength
(ADXSLOPE) ADX minimum steepness entry {45}: ADX slope needs to be 45 degrees to be considered as a positive one.
(ADXSLOPE) ADX minimum steepness exit {45}: ADX slope needs to be -45 degrees to be considered as a negative one.
(ADXSLOPE) ADX steepness periods {3}: In order to avoid false detection the slope is calculated along 3 periods.
____ SETTINGS - Next to EMA55
(NEXTEMA55) EMA10 to EMA55 bounce back percentage {80}: EMA10 might bounce back to EMA55 or maybe to 80% of its complete way to EMA55
(NEXTEMA55) Next to EMA55 percentage {15}: How much next to the EMA55 you need to be to consider it's going to bounce back upwards again.
____ SETTINGS - Stop Loss and Take Profit
You can set a default stop loss or a default take profit.
(STOPTAKE) Stop Loss % {7.0}
(STOPTAKE) Take Profit % {2.0}
____ SETTINGS - Trailing Take Profit
You can customize the default trailing take profit values
(TRAILING) Trailing Take Profit (%) {1.0}: Trailing take profit offset in percentage
(TRAILING) Trailing Take Profit Trigger (%) {2.0}: When 2.0% of benefit is reached then activate the trailing take profit.
____ SETTINGS - MAIN TURN ON/OFF OPTIONS
(EMAS) Ignore advice based on emas {false}.
(EMAS) Ignore advice based on emas (On closing long signal) {False}: Ignore advice based on emas but only when deciding to close a buy entry.
(SQZMOM) Ignore advice based on SQZMOM {false}: Ignores advice based on SQZMOM indicator.
(ADXSLOPE) Ignore advice based on ADX positive slope {false}
(ADXSLOPE) Ignore advice based on ADX cut (23) {true}
(STOPTAKE) Take Profit? {false}: Enables simple Take Profit.
(STOPTAKE) Stop Loss? {True}: Enables simple Stop Loss.
(TRAILING) Enable Trailing Take Profit (%) {True}: Enables Trailing Take Profit.
____ SETTINGS - Strategy mode
(STRAT) Type Strategy: 'Long and Short', 'Long Only' or 'Short Only'. Default: 'Long and Short'.
____ SETTINGS - Risk Management
(RISKM) Risk Management Type: 'Safe', 'Somewhat safe compound' or 'Unsafe compound'. ' Safe ': Calculations are always done with the initial capital (1000) in mind. The maximum losses per trade/day/week/month are taken into account. ' Somewhat safe compound ': Calculations are done with initial capital (1000) or a higher capital if it increases. The maximum losses per trade/day/week/month are taken into account. ' Unsafe compound ': In each order all the current capital is gambled and only the default stop loss per order is taken into account. That means that the maximum losses per trade/day/week/month are not taken into account. Default : 'Somewhat safe compound'.
(RISKM) Maximum loss per trade % {1.0}.
(RISKM) Maximum loss per day % {6.0}.
(RISKM) Maximum loss per week % {8.0}.
(RISKM) Maximum loss per month % {10.0}.
____ SETTINGS - Decimals
(DECIMAL) Maximum number of decimal for contracts {3}: How small (3 decimals means 0.001) an entry position might be in your exchange.
EXTRA 1 - PRICE IS IN RANGE indicator
(PRANGE) Print price is in range {False}: Enable a bottom label that indicates if the price is in range or not.
(PRANGE) Price range periods {5}: How many previous periods are used to calculate the medians
(PRANGE) Price range maximum desviation (%) {0.6} ( > 0 ): Maximum positive desviation for range detection
(PRANGE) Price range minimum desviation (%) {0.6} ( > 0 ): Mininum negative desviation for range detection
EXTRA 2 - SQUEEZE MOMENTUM Desviation indicator
(SQZDIVER) Show degrees {False}: Show degrees of each Squeeze Momentum Divergence lines to the x-axis.
(SQZDIVER) Show desviation labels {False}: Whether to show or not desviation labels for the Squeeze Momentum Divergences.
(SQZDIVER) Show desviation lines {False}: Whether to show or not desviation lines for the Squeeze Momentum Divergences.
EXTRA 3 - VOLUME PROFILE indicator
WARNING: This indicator works not on current bar but on previous bar. So in the worst case it might be VP from 4 hours ago. Don't worry, inside the strategy calculus the correct values are used. It's just that I cannot show the most recent one in the chart.
(VP) Print recent profile {False}: Show Volume Profile indicator
(VP) Avoid label price overlaps {False}: Avoid label prices to overlap on the chart.
EXTRA 4 - ZIGNALY SUPPORT
(ZIG) Zignaly Alert Type {Email}: 'Email', 'Webhook'. ' Email ': Prepare alert_message variable content to be compatible with zignaly expected email content format. ' Webhook ': Prepare alert_message variable content to be compatible with zignaly expected json content format.
EXTRA 5 - DEBUG
(DEBUG) Enable debug on order comments {False}: If set to true it prepares the order message to match the alert_message variable. It makes easier to debug what would have been sent by email or webhook on each of the times an order is triggered.
HOW TO USE THIS STRATEGY
BOT MODE: This is the default setting.
PROPER VOLUME PROFILE VIEWING: Click on this strategy settings. Properties tab. Make sure Recalculate 'each time the order was run' is turned off.
NEWBIE USER: (Check PROPER VOLUME PROFILE VIEWING above!) You might want to turn on the 'Print recent profile {False}' setting. Alternatively you can use my alternate realtime study: 'Resistances and supports based on simplified Volume Profile' but, be aware, it might consume one indicator.
ADVANCED USER 1: Turn on the 'Print price is in range {False}' setting and help us to debug this subindicator. Also help us to figure out how to include this value in the strategy.
ADVANCED USER 2: Turn on the all the (SQZDIVER) settings and help us to figure out how to include this value in the strategy.
ADVANCED USER 3: (Check PROPER VOLUME PROFILE VIEWING above!) Turn on the 'Print recent profile {False}' setting and report any problem with it.
JAIME MERINO: Just use the indicator as it comes by default. It should only show BUY signals, SELL signals and their associated closing signals. From time to time you might want to check 'ADVANCED USER 2' instructions to check that there's actually a divergence. Check also 'ADVANCED USER 1' instructions for your amusement.
EXTRA ADVICE
It's advised that you use this strategy in addition to these two other indicators:
* Squeeze Momentum Indicator
* ADX
so that your chart matches as close as possible to TradingLatino chart.
ZIGNALY INTEGRATION
This strategy supports Zignaly email integration by default. It also supports Zignaly Webhook integration.
ZIGNALY INTEGRATION - Email integration example
What you would write in your alert message:
||{{strategy.order.alert_message}}||key=MYSECRETKEY||
ZIGNALY INTEGRATION - Webhook integration example
What you would write in your alert message:
{ {{strategy.order.alert_message}} , "key" : "MYSECRETKEY" }
CREDITS
I have reused and adapted some code from
'Directional Movement Index + ADX & Keylevel Support' study
which it's from TradingView console user.
I have reused and adapted some code from
'3ema' study
which it's from TradingView hunganhnguyen1193 user.
I have reused and adapted some code from
'Squeeze Momentum Indicator ' study
which it's from TradingView LazyBear user.
I have reused and adapted some code from
'Strategy Tester EMA-SMA-RSI-MACD' study
which it's from TradingView fikira user.
I have reused and adapted some code from
'Support Resistance MTF' study
which it's from TradingView LonesomeTheBlue user.
I have reused and adapted some code from
'TF Segmented Linear Regression' study
which it's from TradingView alexgrover user.
I have reused and adapted some code from
"Poor man's volume profile" study
which it's from TradingView IldarAkhmetgaleev user.
FEEDBACK
Please check the strategy source code for more detailed information
where, among others, I explain all of the substrats
and if they are implemented or not.
Q1. Did I understand wrong any of the Jaime substrats (which I have implemented)?
Q2. The strategy yields quite profit when we should long (EMA10 from 1d timeframe is higher than EMA55 from 1d timeframe.
Why the strategy yields much less profit when we should short (EMA10 from 1d timeframe is lower than EMA55 from 1d timeframe)?
Any idea if you need to do something else rather than just reverse what Jaime does when longing?
FREQUENTLY ASKED QUESTIONS
FAQ1. Why are you giving this strategy for free?
TradingLatino and his fellow enthusiasts taught me this strategy. Now I'm giving back to them.
FAQ2. Seriously! Why are you giving this strategy for free?
I'm confident his strategy might be improved a lot. By keeping it to myself I would avoid other people contributions to improve it.
Now that everyone can contribute this is a win-win.
FAQ3. How can I connect this strategy to my Exchange account?
It seems that you can attach alerts to strategies.
You might want to combine it with a paying account which enable Webhook URLs to work.
I don't know how all of this works right now so I cannot give you advice on it.
You will have to do your own research on this subject. But, be careful. Automating trades, if not done properly,
might end on you automating losses.
FAQ4. I have just found that this strategy by default gives more than 3.97% of 'maximum series of losses'. That's unacceptable according to my risk management policy.
You might want to reduce default stop loss setting from 7% to something like 5% till you are ok with the 'maximum series of losses'.
FAQ5. Where can I learn more about your work on this strategy?
Check the source code. You might find unused strategies. Either because there's not a substantial increases on earnings. Or maybe because they have not been implemented yet.
FAQ6. How much leverage is applied in this strategy?
No leverage.
FAQ7. Any difference with original Jaime Merino strategy?
Most of the times Jaime defines an stop loss at the price entry. That's not the case here. The default stop loss is 7% (but, don't be confused it only means losing 1% of your investment thanks to risk management). There's also a trailing take profit that triggers at 2% profit with a 1% trailing.
FAQ8. Why this strategy return is so small?
The strategy should be improved a lot. And, well, backtesting in this platform is not guaranteed to return theoric results comparable to real-life returns. That's why I'm personally forward testing this strategy to verify it.
MENSAJE EN CASTELLANO
En primer lugar se agradece feedback para mejorar la estrategia.
Si eres un usuario avanzado y quieres colaborar en mejorar el script no dudes en comentar abajo.
Ten en cuenta que aunque toda esta descripción tenga que estar en inglés no es obligatorio que el comentario esté en inglés.
CHISTE - CASTELLANO
¡Pero Jaime!
¡400.000!
¡Tu da mun!
McGinley Dynamic (Improved) - John R. McGinley, Jr.For all the McGinley enthusiasts out there, this is my improved version of the "McGinley Dynamic", originally formulated and publicized in 1990 by John R. McGinley, Jr. Prior to this release, I recently had an encounter with a member request regarding the reliability and stability of the general algorithm. Years ago, I attempted to discover the root of it's inconsistency, but success was not possible until now. Being no stranger to a good old fashioned computational crisis, I revisited it with considerable contemplation.
I discovered a lack of constraints in the formulation that either caused the algorithm to implode to near zero and zero OR it could explosively enlarge to near infinite values during unusual price action volatility conditions, occurring on different time frames. A numeric E-notation in a moving average doesn't mean a stock just shot up in excess of a few quintillion in value from just "10ish" moments ago. Anyone experienced with the usual McGinley Dynamic, has probably encountered this with dynamically dramatic surprises in their chart, destroying it's usability.
Well, I believe I have found an answer to this dilemma of 'susceptibility to miscalculation', to provide what is most likely McGinley's whole hearted intention. It required upgrading the formulation with two constraints applied to it using min/max() functions. Let me explain why below.
When using base numbers with an exponent to the power of four, some miniature numbers smaller than one can numerically collapse to near 0 values, or even 0.0 itself. A denominator of zero will always give any computational device a horribly bad day, not to mention the developer. Let this be an EASY lesson in computational division, I often entertainingly express to others. You have heard the terminology "$#|T happens!🙂" right? In the programming realm, "AnyNumber/0.0 CAN happen!🤪" too, and it happens "A LOT" unexpectedly, even when it's highly improbable. On the other hand, numbers a bit larger than 2 with the power of four can tremendously expand rapidly to the numeric limits of 64-bit processing, generating ginormous spikes on a chart.
The ephemeral presence of one OR both of those potentials now has a combined satisfactory remedy, AND you as TV members now have it, endowed with the ever evolving "Power of Pine". Oh yeah, this one plots from bar_index==0 too. It also has experimental settings tweaks to play with, that may reveal untapped potential of this formulation. This function now has gain of function capabilities, NOT to be confused with viral gain of function enhancements from reckless BSL-4 leaking laboratories that need to be eternally abolished from this planet. Although, I do have hopes this imd() function has the potential to go viral. I believe this improved function may have utility in the future by developers of the TradingView community. You have the source, and use it wisely...
I included an generic ema() plot for a basic comparison, ultimately unveiling some of this algorithm's unique characteristics differing on a variety of time frames. Also another unconstrained function is included to display some the disparities of having no limitations on a divisor in the calculation. I strongly advise against the use of umd() in any published script. There is simply just no reason to even ponder using it. I also included notes in the script to warn against this. It's funny now, but some folks don't always read/understand my advisories... You have been warned!
NOTICE: You have absolute freedom to use this source code any way you see fit within your new Pine projects, and that includes TV themselves. You don't have to ask for my permission to reuse this improved function in your published scripts, simply because I have better things to do than answer requests for the reuse of this simplistic imd() function. Sufficient accreditation regarding this script and compliance with "TV's House Rules" regarding code reuse, is as easy as copying the entire function as is. Fair enough? Good! I have a backlog of "computational crises" to contend with, including another one during the writing of this elaborate description.
When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members, I may implement more ideas when they present themselves as worthy additions. Have a profitable future everyone!
ETS MA Deviation ExtremesWhile trading, I noticed that emphasis is often placed on how far price has moved from the moving average (whichever a trader prefers). In these cases I also found that Bollinger Bands only sometimes played a factor in determining whether price had moved "too far" from the moving average to potentially result in a sharp move back to the average.
Because I wanted something more objective than a "gut feeling" that price has moved away from the average enough to make it move back, I decided to see what I could do to determine the standard deviation of how price action moved away from the average , in order to determine when it could potentially have a "rubber band effect" to jump back to the "norm". The result of that is the ETS MA Deviation Extremes indicator, and I hope that it will help you in your trading.
The indicator also has bar coloring included, which can be turned off, which gives a good on-chart visual to warn you that the price action might reverse. This has often helped me to be a bit more cautious before just jumping into a trade that might be on the brink of reversing and taking my position out, and it actually turned out to be a good indicator for a reversal trade strategy.
The histogram bars give an indication of how far the price has moved away from the average, and I look for a potential reversal as soon as the histograms move back inside the deviation lines after having been outside it. The bar coloration actually depend on more than one set of deviation lines, but putting all of that on the chart just makes it confusing, so I removed the ones that I felt were not essential to make it clearer.
I hope it helps you in your trading and makes it easier for you to trade successfully!
Efficient Trend Step ChannelIntroduction
The efficient trend-step indicator is a trend indicator that make use of the efficiency ratio in order to adapt to the market trend strength, this indicator originally aimed to remain static during ranging states while fitting the price only when large variations occur. The trend step indicator family unlike most moving averages has a boxy appearance and could therefore not be classified as smooth, this makes it an indicator relatively uninteresting to use as input for other non-trending indicators such as oscillators.
Today a channel indicator making use of the efficient trend-step is proposed, the indicator has an upper and a lower extremity who can be used for breakout or support and resistance methodologies, however we will see that the indicator is sometimes able to return accurate support and resistance levels.
The Indicator
The indicator has the same settings has the efficient trend step indicator, length control the period of the efficiency ratio, fast control the period of the rolling standard deviation used for trending states, slow control the period of the rolling standard deviation used for ranging states, fast should be lower than slow , if both are equal then the indicator is equal to the classical trend step indicator and length does no longer affect the indicator output. Lower values of fast/slow will make the indicator more reactive to small variations thus changing direction more often.
The color changes you can see on the indicator are changed depending on the prior direction took by the indicator output, if the indicator where higher than its precedent value, then the color will be blue until the indicator is lower than its precedent value. Those colors help you have an estimate of the current trend direction.
Channel Calculation And Role
The extremities made from the efficient trend step allow for more advanced trading rules, they can act as stop/target level and can also give a rough estimate of the current market volatility, with wider extremities indicating a more volatile market.
The extremities are made directly from the dev element used by the efficient trend-step, the upper extremity is made by summing the efficient trend step with the value of dev when the efficient trend step change, the lower extremity is made the same way but the value is subtracted instead.
Is it a weird choice ? It sure is strange to see such approach, the absolute rolling average error between the price and the efficient trend step could have been a logical measure but using dev instead is more efficient and also allow for a more adaptive approach which can benefit the support and resistance methodology, the last reason is because i didn't wanted to "denature" the trend-step signature of the indicator.
The figure above represent the measurement used for making the extremities (in green).
Since the previously described measure change only when the efficient trend step change, we can conclude that such measure is representative of a relatively large variation, since the efficient trend step aim to only change when a large variations appear.
We can see that the upper extremity acted as an accurate resistance in this upper variation of AMD,
Here as well, however like other bands indicators it is safer to take into account the current trend direction, a strong uptrend will have less difficulties crossing the upper extremity, therefore it might be better to rely on the support (lower extremity) on an up-trending market (indicator in blue), and on the resistance (upper extremity) on an down-trending market (indicator in orange).
The figure above show support and resistances signals, a cross represent a false signal, while green arrows represent correct ones with their respective direction.
Conclusion
The presented indicator add more possibilities to the interpretation of the efficient trend step, the extremities can act as stop/target level, however this use has to be controlled, and the level should be in accordance to your risk/reward ratio.
Showcasing another trend-step indicator was a real pleasure. Thanks for reading :)
TRIX Ribbon [ChuckBanger]This is a TRIX indicator. You can read more about it here: www.investopedia.com
The trix indicator is usually only trix and a signal line. This indicator has 5 signal lines. The TRIX line has the color blue. The first has the color aqua and then lime, orange, red and the last is the maroon line. The first signal line is an EMA of the TRIX line, the second signal line a double smoothed EMA of the trix line and the third is triple smoothed TRIX line and so on.
Interpretation
TRIX is similar to MACD. As both is a momentum indicators that fluctuate above and below the zero line. Both have signal lines based on some sort of moving average (usually EMA). In this indicator the trader can set what moving average the trader prefer. The biggest difference between TRIX and MACD is that TRIX is the smoother of the two and are less jagged and tend to turn a bit later.
The most common signal is signal line crossover in the same manner as the MACD and its signal line. But this indicator has 5 signal lines. If this was a typical TRIX indicator it should only has the blue and aqua line (the line closest to the blue line). How you trade it is up to you. But for example you go long when the blue line crosses the aqua line. And because the all the is based on the TRIX line you can use the other crossovers as an confirmation signal.
Seasonality Monte Carlo Forecaster [BackQuant]Seasonality Monte Carlo Forecaster
Plain-English overview
This tool projects a cone of plausible future prices by combining two ideas that traders already use intuitively: seasonality and uncertainty. It watches how your market typically behaves around this calendar date, turns that seasonal tendency into a small daily “drift,” then runs many randomized price paths forward to estimate where price could land tomorrow, next week, or a month from now. The result is a probability cone with a clear expected path, plus optional overlays that show how past years tended to move from this point on the calendar. It is a planning tool, not a crystal ball: the goal is to quantify ranges and odds so you can size, place stops, set targets, and time entries with more realism.
What Monte Carlo is and why quants rely on it
• Definition . Monte Carlo simulation is a way to answer “what might happen next?” when there is randomness in the system. Instead of producing a single forecast, it generates thousands of alternate futures by repeatedly sampling random shocks and adding them to a model of how prices evolve.
• Why it is used . Markets are noisy. A single point forecast hides risk. Monte Carlo gives a distribution of outcomes so you can reason in probabilities: the median path, the 68% band, the 95% band, tail risks, and the chance of hitting a specific level within a horizon.
• Core strengths in quant finance .
– Path-dependent questions : “What is the probability we touch a stop before a target?” “What is the expected drawdown on the way to my objective?”
– Pricing and risk : Useful for path-dependent options, Value-at-Risk (VaR), expected shortfall (CVaR), stress paths, and scenario analysis when closed-form formulas are unrealistic.
– Planning under uncertainty : Portfolio construction and rebalancing rules can be tested against a cloud of plausible futures rather than a single guess.
• Why it fits trading workflows . It turns gut feel like “seasonality is supportive here” into quantitative ranges: “median path suggests +X% with a 68% band of ±Y%; stop at Z has only ~16% odds of being tagged in N days.”
How this indicator builds its probability cone
1) Seasonal pattern discovery
The script builds two day-of-year maps as new data arrives:
• A return map where each calendar day stores an exponentially smoothed average of that day’s log return (yesterday→today). The smoothing (90% old, 10% new) behaves like an EWMA, letting older seasons matter while adapting to new information.
• A volatility map that tracks the typical absolute return for the same calendar day.
It calculates the day-of-year carefully (with leap-year adjustment) and indexes into a 365-slot seasonal array so “March 18” is compared with past March 18ths. This becomes the seasonal bias that gently nudges simulations up or down on each forecast day.
2) Choice of randomness engine
You can pick how the future shocks are generated:
• Daily mode uses a Gaussian draw with the seasonal bias as the mean and a volatility that comes from realized returns, scaled down to avoid over-fitting. It relies on the Box–Muller transform internally to turn two uniform random numbers into one normal shock.
• Weekly mode uses bootstrap sampling from the seasonal return history (resampling actual historical daily drifts and then blending in a fraction of the seasonal bias). Bootstrapping is robust when the empirical distribution has asymmetry or fatter tails than a normal distribution.
Both modes seed their random draws deterministically per path and day, which makes plots reproducible bar-to-bar and avoids flickering bands.
3) Volatility scaling to current conditions
Markets do not always live in average volatility. The engine computes a simple volatility factor from ATR(20)/price and scales the simulated shocks up or down within sensible bounds (clamped between 0.5× and 2.0×). When the current regime is quiet, the cone narrows; when ranges expand, the cone widens. This prevents the classic mistake of projecting calm markets into a storm or vice versa.
4) Many futures, summarized by percentiles
The model generates a matrix of price paths (capped at 100 runs for performance inside TradingView), each path stepping forward for your selected horizon. For each forecast day it sorts the simulated prices and pulls key percentiles:
• 5th and 95th → approximate 95% band (outer cone).
• 16th and 84th → approximate 68% band (inner cone).
• 50th → the median or “expected path.”
These are drawn as polylines so you can immediately see central tendency and dispersion.
5) A historical overlay (optional)
Turn on the overlay to sketch a dotted path of what a purely seasonal projection would look like for the next ~30 days using only the return map, no randomness. This is not a forecast; it is a visual reminder of the seasonal drift you are biasing toward.
Inputs you control and how to think about them
Monte Carlo Simulation
• Price Series for Calculation . The source series, typically close.
• Enable Probability Forecasts . Master switch for simulation and drawing.
• Simulation Iterations . Requested number of paths to run. Internally capped at 100 to protect performance, which is generally enough to estimate the percentiles for a trading chart. If you need ultra-smooth bands, shorten the horizon.
• Forecast Days Ahead . The length of the cone. Longer horizons dilute seasonal signal and widen uncertainty.
• Probability Bands . Draw all bands, just 95%, just 68%, or a custom level (display logic remains 68/95 internally; the custom number is for labeling and color choice).
• Pattern Resolution . Daily leans on day-of-year effects like “turn-of-month” or holiday patterns. Weekly biases toward day-of-week tendencies and bootstraps from history.
• Volatility Scaling . On by default so the cone respects today’s range context.
Plotting & UI
• Probability Cone . Plots the outer and inner percentile envelopes.
• Expected Path . Plots the median line through the cone.
• Historical Overlay . Dotted seasonal-only projection for context.
• Band Transparency/Colors . Customize primary (outer) and secondary (inner) band colors and the mean path color. Use higher transparency for cleaner charts.
What appears on your chart
• A cone starting at the most recent bar, fanning outward. The outer lines are the ~95% band; the inner lines are the ~68% band.
• A median path (default blue) running through the center of the cone.
• An info panel on the final historical bar that summarizes simulation count, forecast days, number of seasonal patterns learned, the current day-of-year, expected percentage return to the median, and the approximate 95% half-range in percent.
• Optional historical seasonal path drawn as dotted segments for the next 30 bars.
How to use it in trading
1) Position sizing and stop logic
The cone translates “volatility plus seasonality” into distances.
• Put stops outside the inner band if you want only ~16% odds of a stop-out due to noise before your thesis can play.
• Size positions so that a test of the inner band is survivable and a test of the outer band is rare but acceptable.
• If your target sits inside the 68% band at your horizon, the payoff is likely modest; outside the 68% but inside the 95% can justify “one-good-push” trades; beyond the 95% band is a low-probability flyer—consider scaling plans or optionality.
2) Entry timing with seasonal bias
When the median path slopes up from this calendar date and the cone is relatively narrow, a pullback toward the lower inner band can be a high-quality entry with a tight invalidation. If the median slopes down, fade rallies toward the upper band or step aside if it clashes with your system.
3) Target selection
Project your time horizon to N bars ahead, then pick targets around the median or the opposite inner band depending on your style. You can also anchor dynamic take-profits to the moving median as new bars arrive.
4) Scenario planning & “what-ifs”
Before events, glance at the cone: if the 95% band already spans a huge range, trade smaller, expect whips, and avoid placing stops at obvious band edges. If the cone is unusually tight, consider breakout tactics and be ready to add if volatility expands beyond the inner band with follow-through.
5) Options and vol tactics
• When the cone is tight : Prefer long gamma structures (debit spreads) only if you expect a regime shift; otherwise premium selling may dominate.
• When the cone is wide : Debit structures benefit from range; credit spreads need wider wings or smaller size. Align with your separate IV metrics.
Reading the probability cone like a pro
• Cone slope = seasonal drift. Upward slope means the calendar has historically favored positive drift from this date, downward slope the opposite.
• Cone width = regime volatility. A widening fan tells you that uncertainty grows fast; a narrow cone says the market typically stays contained.
• Mean vs. price gap . If spot trades well above the median path and the upper band, mean-reversion risk is high. If spot presses the lower inner band in an up-sloping cone, you are in the “buy fear” zone.
• Touches and pierces . Touching the inner band is common noise; piercing it with momentum signals potential regime change; the outer band should be rare and often brings snap-backs unless there is a structural catalyst.
Methodological notes (what the code actually does)
• Log returns are used for additivity and better statistical behavior: sim_ret is applied via exp(sim_ret) to evolve price.
• Seasonal arrays are updated online with EWMA (90/10) so the model keeps learning as each bar arrives.
• Leap years are handled; indexing still normalizes into a 365-slot map so the seasonal pattern remains stable.
• Gaussian engine (Daily mode) centers shocks on the seasonal bias with a conservative standard deviation.
• Bootstrap engine (Weekly mode) resamples from observed seasonal returns and adds a fraction of the bias, which captures skew and fat tails better.
• Volatility adjustment multiplies each daily shock by a factor derived from ATR(20)/price, clamped between 0.5 and 2.0 to avoid extreme cones.
• Performance guardrails : simulations are capped at 100 paths; the probability cone uses polylines (no heavy fills) and only draws on the last confirmed bar to keep charts responsive.
• Prerequisite data : at least ~30 seasonal entries are required before the model will draw a cone; otherwise it waits for more history.
Strengths and limitations
• Strengths :
– Probabilistic thinking replaces single-point guessing.
– Seasonality adds a small but meaningful directional bias that many markets exhibit.
– Volatility scaling adapts to the current regime so the cone stays realistic.
• Limitations :
– Seasonality can break around structural changes, policy shifts, or one-off events.
– The number of paths is performance-limited; percentile estimates are good for trading, not for academic precision.
– The model assumes tomorrow’s randomness resembles recent randomness; if regime shifts violently, the cone will lag until the EWMA adapts.
– Holidays and missing sessions can thin the seasonal sample for some assets; be cautious with very short histories.
Tuning guide
• Horizon : 10–20 bars for tactical trades; 30+ for swing planning when you care more about broad ranges than precise targets.
• Iterations : The default 100 is enough for stable 5/16/50/84/95 percentiles. If you crave smoother lines, shorten the horizon or run on higher timeframes.
• Daily vs. Weekly : Daily for equities and crypto where month-end and turn-of-month effects matter; Weekly for futures and FX where day-of-week behavior is strong.
• Volatility scaling : Keep it on. Turn off only when you intentionally want a “pure seasonality” cone unaffected by current turbulence.
Workflow examples
• Swing continuation : Cone slopes up, price pulls into the lower inner band, your system fires. Enter near the band, stop just outside the outer line for the next 3–5 bars, target near the median or the opposite inner band.
• Fade extremes : Cone is flat or down, price gaps to the upper outer band on news, then stalls. Favor mean-reversion toward the median, size small if volatility scaling is elevated.
• Event play : Before CPI or earnings on a proxy index, check cone width. If the inner band is already wide, cut size or prefer options structures that benefit from range.
Good habits
• Pair the cone with your entry engine (breakout, pullback, order flow). Let Monte Carlo do range math; let your system do signal quality.
• Do not anchor blindly to the median; recalc after each bar. When the cone’s slope flips or width jumps, the plan should adapt.
• Validate seasonality for your symbol and timeframe; not every market has strong calendar effects.
Summary
The Seasonality Monte Carlo Forecaster wraps institutional risk planning into a single overlay: a data-driven seasonal drift, realistic volatility scaling, and a probabilistic cone that answers “where could we be, with what odds?” within your trading horizon. Use it to place stops where randomness is less likely to take you out, to set targets aligned with realistic travel, and to size positions with confidence born from distributions rather than hunches. It will not predict the future, but it will keep your decisions anchored to probabilities—the language markets actually speak.
Information-Geometric Market DynamicsInformation-Geometric Market Dynamics
The Information Field: A Geometric Approach to Market Dynamics
By: DskyzInvestments
Foreword: Beyond the Shadows on the Wall
If you have traded for any length of time, you know " the feeling ." It is the frustration of a perfect setup that fails, the whipsaw that stops you out just before the real move, the nagging sense that the chart is telling you only half the story. For decades, technical analysis has relied on interpreting the shadows—the patterns left behind by price. We draw lines on these shadows, apply indicators to them, and hope they reveal the future.
But what if we could stop looking at the shadows and, instead, analyze the object casting them?
This script introduces a new paradigm for market analysis: Information-Geometric Market Dynamics (IGMD) . The core premise of IGMD is that the price chart is merely a one-dimensional projection of a much richer, higher-dimensional reality—an " information field " generated by the collective actions and beliefs of all market participants.
This is not just another collection of indicators. It is a unified framework for measuring the geometry of the market's information field—its memory, its complexity, its uncertainty, its causal flows—and making high-probability decisions based on that deeper reality. By fusing advanced mathematical and informational concepts, IGMD provides a multi-faceted lens through which to view market behavior, moving beyond simple price action into the very structure of market information itself.
Prepare to move beyond the flatland of the price chart. Welcome to the information field.
The IGMD Framework: A Multi-Kernel Approach
What is a Kernel? The Heart of Transformation
In mathematics and data science, a kernel is a powerful and elegant concept. At its core, a kernel is a function that takes complex, often inscrutable data and transforms it into a more useful format. Think of it as a specialized lens or a mathematical "probe." You cannot directly measure abstract concepts like "market memory" or "trend quality" by looking at a price number. First, you must process the raw price data through a specific mathematical machine—a kernel—that is designed to output a measurement of that specific property. Kernels operate by performing a sort of "similarity test," projecting data into a higher-dimensional space where hidden patterns and relationships become visible and measurable.
Why do creators use them? We use kernels to extract features —meaningful pieces of information—that are not explicitly present in the raw data. They are the essential tools for moving beyond surface-level analysis into the very DNA of market behavior. A simple moving average can tell you the average price; a suite of well-chosen kernels can tell you about the character of the price action itself.
The Alchemist's Challenge: The Art of Fusion
Using a single kernel is a challenge. Using five distinct, computationally demanding mathematical engines in unison is an immense undertaking. The true difficulty—and artistry—lies not just in using one kernel, but in fusing the outputs of many . Each kernel provides a different perspective, and they can often give conflicting signals. One kernel might detect a strong trend, while another signals rising chaos and uncertainty. The IGMD script's greatest strength is its ability to act as this alchemist, synthesizing these disparate viewpoints through a weighted fusion process to produce a single, coherent picture of the market's state. It required countless hours of testing and calibration to balance the influence of these five distinct analytical engines so they work in harmony rather than cacophony.
The Five Kernels of Market Dynamics
The IGMD script is built upon a foundation of five distinct kernels, each chosen to probe a unique and critical dimension of the market's information field.
1. The Wavelet Kernel (The "Microscope")
What it is: The Wavelet Kernel is a signal processing function designed to decompose a signal into different frequency scales. Unlike a Fourier Transform that analyzes the entire signal at once, the wavelet slides across the data, providing information about both what frequencies are present and when they occurred.
The Kernels I Use:
Haar Kernel: The simplest wavelet, a square-wave shape defined by the coefficients . It excels at detecting sharp, sudden changes.
Daubechies 2 (db2) Kernel: A more complex and smoother wavelet shape that provides a better balance for analyzing the nuanced ebb and flow of typical market trends.
How it Works in the Script: This kernel is applied iteratively. It first separates the finest "noise" (detail d1) from the first level of trend (approximation a1). It then takes the trend a1 and repeats the process, extracting the next level of cycle (d2) and trend (a2), and so on. This hierarchical decomposition allows us to separate short-term noise from the long-term market "thesis."
2. The Hurst Exponent Kernel (The "Memory Gauge")
What it is: The Hurst Exponent is derived from a statistical analysis kernel that measures the "long-term memory" or persistence of a time series. It is the definitive measure of whether a series is trending (H > 0.5), mean-reverting (H < 0.5), or random (H = 0.5).
How it Works in the Script: The script employs a method based on Rescaled Range (R/S) analysis. It calculates the average range of price movements over increasingly larger time lags (m1, m2, m4, m8...). The slope of the line plotting log(range) vs. log(lag) is the Hurst Exponent. Applying this complex statistical analysis not to the raw price, but to the clean, wavelet-decomposed trend lines, is a key innovation of IGMD.
3. The Fractal Dimension Kernel (The "Complexity Compass")
What it is: This kernel measures the geometric complexity or "jaggedness" of a price path, based on the principles of fractal geometry. A straight line has a dimension of 1; a chaotic, space-filling line approaches a dimension of 2.
How it Works in the Script: We use a version based on Ehlers' Fractal Dimension Index (FDI). It calculates the rate of price change over a full lookback period (N3) and compares it to the sum of the rates of change over the two halves of that period (N1 + N2). The formula d = (log(N1 + N2) - log(N3)) / log(2) quantifies how much "longer" and more convoluted the price path was than a simple straight line. This kernel is our primary filter for tradeable (low complexity) vs. untradeable (high complexity) conditions.
4. The Shannon Entropy Kernel (The "Uncertainty Meter")
What it is: This kernel comes from Information Theory and provides the purest mathematical measure of information, surprise, or uncertainty within a system. It is not a measure of volatility; a market moving predictably up by 10 points every bar has high volatility but zero entropy .
How it Works in the Script: The script normalizes price returns by the ATR, categorizes them into a discrete number of "bins" over a lookback window, and forms a probability distribution. The Shannon Entropy H = -Σ(p_i * log(p_i)) is calculated from this distribution. A low H means returns are predictable. A high H means returns are chaotic. This kernel is our ultimate gauge of market conviction.
5. The Transfer Entropy Kernel (The "Causality Probe")
What it is: This is by far the most advanced and computationally intensive kernel in the script. Transfer Entropy is a non-parametric measure of directed information flow between two time series. It moves beyond correlation to ask: "Does knowing the past of Volume genuinely reduce our uncertainty about the future of Price?"
How it Works in the Script: To make this work, the script discretizes both price returns and the chosen "driver" (e.g., OBV) into three states: "up," "down," or "neutral." It then builds complex conditional probability tables to measure the flow of information in both directions. The Net Transfer Entropy (TE Driver→Price minus TE Price→Driver) gives us a direct measure of causality . A positive score means the driver is leading price, confirming the validity of the move. This is a profound leap beyond traditional indicator analysis.
Chapter 3: Fusion & Interpretation - The Field Score & Dashboard
Each kernel is a specialist providing a piece of the puzzle. The Field Score is where they are fused into a single, comprehensive reading. It's a weighted sum of the normalized scores from all five kernels, producing a single number from -1 (maximum bearish information field) to +1 (maximum bullish information field). This is the ultimate "at-a-glance" metric for the market's net state, and it is interpreted through the dashboard.
The Dashboard: Your Mission Control
Field Score & Regime: The master metric and its plain-English interpretation ("Uptrend Field", "Downtrend Field", "Transitional").
Kernel Readouts (Wave Align, H(w), FDI, etc.): The live scores of each individual kernel. This allows you to see why the Field Score is what it is. A high Field Score with all components in agreement (all green or red) is a state of High Coherence and represents a high-quality setup.
Market Context: Standard metrics like RSI and Volume for additional confluence.
Signals: The raw and adjusted confluence counts and the final, calculated probability scores for potential long and short entries.
Pattern: Shows the dominant candlestick pattern detected within the currently forming APEX range box and its calculated confidence percentage.
Chapter 4: Mastering the Controls - The Inputs Menu
Every parameter is a lever to fine-tune the IGMD engine.
📊 Wavelet Transform: Kernel ( Haar for sharp moves, db2 for smooth trends) and Scales (depth of analysis) let you tune the script's core microscope to your asset's personality.
📈 Hurst Exponent: The Window determines if you're assessing short-term or long-term market memory.
🔍 Fractal Dimension & ⚡ Entropy Volatility: Adjust the lookback windows to make these kernels more or less sensitive to recent price action. Always keep "Normalize by ATR" enabled for Entropy for consistent results.
🔄 Transfer Entropy: Driver lets you choose what causal force to measure (e.g., OBV, Volume, or even an external symbol like VIX). The throttle setting is a crucial performance tool, allowing you to balance precision with script speed.
⚡ Field Fusion • Weights: This is where you can customize the model's "brain." Increase the weights for the kernels that best align with your trading philosophy (e.g., w_hurst for trend followers, w_fdi for chop avoiders).
📊 Signal Engine: Mode offers presets from Conservative to Aggressive . Min Confluence sets your evidence threshold. Dynamic Confluence is a powerful feature that automatically adapts this threshold to the market regime.
🎨 Visuals & 📏 Support/Resistance: These inputs give you full control over the chart's appearance, allowing you to toggle every visual element for a setup that is as clean or as data-rich as you desire.
Chapter 5: Reading the Battlefield - On-Chart Visuals
Pattern Boxes (The Large Rectangles): These are not simple range boxes. They appear when the Field Score crosses a significance threshold, signaling a potential ignition point.
Color: The color reflects the dominant candlestick pattern that has occurred within that box's duration (e.g., green for Bull Engulf).
Label: Displays the dominant pattern, its duration in bars, and a calculated Confidence % based on field strength and pattern clarity.
Bar Pattern Boxes (The Small Boxes): If enabled, these highlight individual, significant candlestick patterns ( BE for Bull Engulf, H for Hammer) on a bar-by-bar basis.
Signal Markers (▲ and ▼): These appear only when the Signal Engine's criteria are all met. The number is the calculated Probability Score .
RR Rails (Dashed Lines): When a signal appears, these lines automatically plot the Entry, Stop Loss (based on ATR), and two Take Profit targets (based on Risk/Reward ratios). They dynamically break and disappear as price touches each level.
Support & Resistance Lines: Plots of the highest high ( Resistance ) and lowest low ( Support ) over a lookback, providing key structural levels.
Chapter 6: Development Philosophy & A Final Word
One single question: " What is the market really doing? " It represents a triumph of complexity, blending concepts from signal processing, chaos theory, and information theory into a cohesive framework. It is offered for educational and analytical purposes and does not constitute financial advice. Its goal is to elevate your analysis from interpreting flat shadows to measuring the rich, geometric reality of the market's information field.
As the great mathematician Benoit Mandelbrot , father of fractal geometry, noted:
"Clouds are not spheres, mountains are not cones, coastlines are not circles, and bark is not smooth, nor does lightning travel in a straight line."
Neither does the market. IGMD is a tool designed to navigate that beautiful, complex, and fractal reality.
— Dskyz, Trade with insight. Trade with anticipation.
OBV Breakout Screener (By Tarso)1. Purpose of the Indicator
The "Advanced OBV Breakout Screener" is a specialized tool designed to find a powerful bullish signal. It scans for assets where buying pressure is increasing significantly, even though the price has not yet broken out.
The core strategy is to identify assets where:
Volume is leading Price: The On-Balance Volume (OBV) has already broken its recent high.
Price is still contained: The asset's price has not yet broken its recent high.
This setup helps you find potential trading opportunities right before a possible upward move.
2. How to Set Up the Indicator
First, you need to add the script to your TradingView account.
Open any chart on TradingView.
Click on the "Pine Editor" tab at the bottom of the screen.
Delete any existing code and paste the entire "Advanced OBV Breakout Screener" script into the editor.
Click "Add to chart". The indicator will now appear in a separate panel below your main price chart.
3. How to Use it with the Pine Screener (Step-by-Step)
This is the main purpose of the indicator. The script does all the complex analysis and provides a simple "1" (Signal is ON) or "0" (Signal is OFF). You only need to set up one filter.
Open the Stock Screener (or Crypto/Forex Screener).
Click the Filters button to open the settings panel.
Ensure you are on the Pine Screener tab (this allows you to filter using custom indicators).
In the indicator selection menu (it might say "Select Indicator..."), find and choose Advanced OBV Breakout Screener from your list.
Now, configure the single filter condition as follows:
In the first box, select Advanced Breakout Signal.
In the second box, select Equal to.
In the third box, select Number and type 1.
Your filter setup should look clean and simple, like this:
That's it! The screener will now display a list of all assets that currently meet the "Advanced Breakout" criteria for the timeframe you have selected (e.g., Daily, 4h, 1h).
4. Configuring the Lookback Period
By default, the indicator analyzes the last 20 periods. If you want to change this (for example, to scan for breakouts over 50 days), you must adjust it in the indicator's settings on your chart.
Go back to your chart view.
Find the "Advanced OBV Breakout Screener" panel.
Click the Settings icon (⚙️) next to the indicator's name.
In the "Inputs" tab, change the "Lookback Period (days)" to your desired value.
Click "OK".
The Pine Screener will automatically use this new setting for its market scan.
5. Understanding the On-Chart Visuals
When you add the indicator to your chart, you will see:
Blue Line: This is the On-Balance Volume (OBV).
Red Stepped Line: This represents the highest value the OBV has reached during the lookback period. A breakout happens when the blue line moves above this red line.
Green Triangle (▲): This symbol appears below a price candle whenever the full "Advanced Breakout" condition (OBV breakout + Price containment) is met, giving you a clear visual confirmation.
thors_forex_factory_utilityLibrary "forex_factory_utility"
Supporting Utility Library for the Live Economic Calendar by toodegrees Indicator; responsible for data handling, and plotting news event data.
isLeapYear()
Finds if it's currently a leap year or not.
Returns: Returns True if the current year is a leap year.
daysMonth(M)
Provides the days in a given month of the year, adjusted during leap years.
Parameters:
M (int) : Month in numerical integer format (i.e. Jan=1).
Returns: Days in the provided month.
MMM(M)
Converts a month from a numerical integer format to a MMM format (i.e. 'Jan').
Parameters:
M (int) : Month in numerical integer format (i.e. Jan=1).
Returns: Month in MMM format (i.e. 'Jan').
dow(D)
Converts a numbered day of the week string in format to 'DDD' format (i.e. "1" = Sun).
Parameters:
D (string) : Numbered day of the week from 1 to 7, starting on Sunday.
Returns: Returns the day of the week in 'DDD' format (i.e. "Fri").
size(S, N)
Converts a size string into the corresponding Pine Script v5 format, or N times smaller/bigger.
Parameters:
S (string) : Size string: "Tiny", "Small", "Normal", "Large", or "Huge".
N (int) : Size variation, can be positive (larger than S), or negative (smaller than S).
Returns: Size string in Pine Script v5 format.
lineStyle(S)
Converts a line style string into the corresponding Pine Script v5 format.
Parameters:
S (string) : Line style string: "Dashed", "Dotted" or "Solid".
Returns: Line style string in Pine Script v5 format.
lineTrnsp(S)
Converts a transparency style string into the corresponding integer value.
Parameters:
S (string) : Line style string: "Light", "Medium" or "Heavy".
Returns: Transparency integer.
boxLoc(X, Y)
Converts position strings of X and Y into a table position in Pine Script v5 format.
Parameters:
X (string) : X-axis string: "Left", "Center", or "Right".
Y (string) : Y-axis string: "Top", "Middle", or "Bottom".
Returns: Table location string in Pine Script v5 format.
method bubbleSort_NewsTOD(N)
Performs bubble sort on a Forex Factory News array of all news from the same date, ordering them in ascending order based on the time of the day.
Namespace types: array
Parameters:
N (array) : Forex Factory News array.
Returns: void
bubbleSort_News(N)
Performs bubble sort on a Forex Factory News array, ordering them in ascending order based on the time of the day, and date.
Parameters:
N (array) : Forex Factory News array.
Returns: Sorted Forex Factory News array.
weekNews(N, C, I)
Creates a Forex Factory News array containing the current week's Forex Factory News.
Parameters:
N (array) : Forex Factory News array containing this week's unfiltered Forex Factory News.
C (array) : Currency filter array (string array).
I (array) : Impact filter array (color array).
Returns: Forex Factory News array containing the current week's Forex Factory News.
todayNews(W, D, M)
Creates a Forex Factory News array containing the current day's Forex Factory News.
Parameters:
W (array) : Forex Factory News array containing this week's Forex Factory News.
D (array) : Forex Factory News array for the current day's Forex Factory News.
M (bool) : Boolean that marks whether the current chart has a Day candle-switch at Midnight New York Time.
Returns: Forex Factory News array containing the current day's Forex Factory News.
adjustTimezone(N, TZH, TZM)
Transposes the Time of the Day, and Date, in the Forex Factory News Table to a custom Timezone.
Parameters:
N (array) : Forex Factory News array.
TZH (int) : Custom Timezone hour.
TZM (int) : Custom Timezone minute.
Returns: Reformatted Forex Factory News array.
NewsAMPM_TOD(N)
Reformats the Time of the Day in the Forex Factory News Table to AM/PM format.
Parameters:
N (array) : Forex Factory News array.
Returns: Reformatted Forex Factory News array.
impFilter(X, L, M, H)
Creates a filter array from the User's desired Forex Facory News to be shown based on Impact.
Parameters:
X (bool) : Boolean - if True Holidays listed on Forex Factory will be shown.
L (bool) : Boolean - if True Low Impact listed on Forex Factory News will be shown.
M (bool) : Boolean - if True Medium Impact listed on Forex Factory News will be shown.
H (bool) : Boolean - if True High Impact listed on Forex Factory News will be shown.
Returns: Color array with the colors corresponding to the Forex Factory News to be shown.
curFilter(A, C1, C2, C3, C4, C5, C6, C7, C8, C9)
Creates a filter array from the User's desired Forex Facory News to be shown based on Currency.
Parameters:
A (bool) : Boolean - if True News related to the current Chart's symbol listed on Forex Factory will be shown.
C1 (bool) : Boolean - if True News related to the Australian Dollar listed on Forex Factory will be shown.
C2 (bool) : Boolean - if True News related to the Canadian Dollar listed on Forex Factory will be shown.
C3 (bool) : Boolean - if True News related to the Swiss Franc listed on Forex Factory will be shown.
C4 (bool) : Boolean - if True News related to the Chinese Yuan listed on Forex Factory will be shown.
C5 (bool) : Boolean - if True News related to the Euro listed on Forex Factory will be shown.
C6 (bool) : Boolean - if True News related to the British Pound listed on Forex Factory will be shown.
C7 (bool) : Boolean - if True News related to the Japanese Yen listed on Forex Factory will be shown.
C8 (bool) : Boolean - if True News related to the New Zealand Dollar listed on Forex Factory will be shown.
C9 (bool) : Boolean - if True News related to the US Dollar listed on Forex Factory will be shown.
Returns: String array with the currencies corresponding to the Forex Factory News to be shown.
FF_OnChartLine(N, T, S)
Plots vertical lines where a Forex Factory News event will occur, or has already occurred.
Parameters:
N (array) : News-type array containing all the Forex Factory News.
T (int) : Transparency integer value (0-100) for the lines.
S (string) : Line style in Pine Script v5 format.
Returns: void
method updateStringMatrix(M, P, V)
Updates a string Matrix containing the tooltips for Forex Factory News Event information for a given candle.
Namespace types: matrix
Parameters:
M (matrix) : String matrix.
P (int) : Position (row) of the Matrix to update based on the impact.
V (string) : information to push to the Matrix.
Returns: void
FF_OnChartLabel(N, Y, S, O)
Plots labels where a Forex Factory News has already occurred based on its/their impact.
Parameters:
N (array) : News-type array containing all the Forex Factory News.
Y (string) : String that gives direction on where to plot the label (options= "Above", "Below", "Auto").
S (string) : Label size in Pine Script v5 format.
O (bool) : Show outline of labels?
Returns: void
historical(T, D, W, X)
Deletes Forex Factory News drawings which are ourside a specific Time window.
Parameters:
T (int) : Number of days input used for Forex Factory News drawings' history.
D (bool) : Boolean that when true will only display Forex Factory News drawings of the current day.
W (bool) : Boolean that when true will only display Forex Factory News drawings of the current week.
X (string) : String that gives direction on what lines to plot based on Time (options= "Future", "Both").
Returns: void
newTable(P, B)
Creates a new Table object with parameters tailored to the Forex Factory News Table.
Parameters:
P (string) : Position string for the Table, in Pine Script v5 format.
B (color) : Border and frame color for the News Table.
Returns: Empty Forex Factory News Table.
resetTable(P, S, headTextC, headBgC, B)
Resets a Table object with parameters and headers tailored to the Forex Factory News Table.
Parameters:
P (string) : Position string for the Table, in Pine Script v5 format.
S (string) : Size string for the Table's text, in Pine Script v5 format.
headTextC (color)
headBgC (color)
B (color) : Border and frame color for the News Table.
Returns: Empty Forex Factory News Table.
logNews(N, TBL, R, S, rowTextC, rowBgC)
Adds an event to the Forex Factory News Table.
Parameters:
N (News) : News-type object.
TBL (table) : Forex Factory News Table object to add the News to.
R (int) : Row to add the event to in the Forex Factory News Table.
S (string) : Size string for the event's text, in Pine Script v5 format.
rowTextC (color)
rowBgC (color)
Returns: void
FF_Table(N, P, S, headTextC, headBgC, rowTextC, rowBgC, B)
Creates the Forex Factory News Table.
Parameters:
N (array) : News-type array containing all the Forex Factory News.
P (string) : Position string for the Table, in Pine Script v5 format.
S (string) : Size string for the Table's text, in Pine Script v5 format.
headTextC (color)
headBgC (color)
rowTextC (color)
rowBgC (color)
B (color) : Border and frame color for the News Table.
Returns: Forex Factory News Table.
timeline(N, T, F, TZH, TZM, D)
Shades Forex Factory News events in the Forex Factory News Table after they occur.
Parameters:
N (array) : News-type array containing all the Forex Factory News.
T (table) : Forex Facory News table object.
F (color) : Color used as shading once the Forex Factory News has occurred.
TZH (int) : Custom Timezone hour, if any.
TZM (int) : Custom Timezone minute, if any.
D (bool) : Daily Forex Factory News flag.
Returns: Forex Factory News Table.
News
Custom News type which contains informatino about a Forex Factory News Event.
Fields:
dow (series string) : Day of the week, in DDD format (i.e. 'Mon').
dat (series string) : Date, in MMM D format (i.e. 'Jan 1').
_t (series int)
tod (series string) : Time of the day, in hh:mm 24-Hour format (i.e 17:10).
cur (series string) : Currency, in CCC format (i.e. "USD").
imp (series color) : Impact, the respective impact color for Forex Factory News Events.
ttl (series string) : Title, encoded in a custom number mapping (see the toodegrees/toodegrees_forex_factory library to learn more).
tmst (series int)
ln (series line)
SMC Structures and FVGสวัสดีครับ! ผมจะอธิบายอินดิเคเตอร์ "SMC Structures and FVG + MACD" ที่คุณให้มาอย่างละเอียดในแต่ละส่วน เพื่อให้คุณเข้าใจการทำงานของมันอย่างถ่องแท้ครับ
อินดิเคเตอร์นี้เป็นการผสมผสานแนวคิดของ Smart Money Concept (SMC) ซึ่งเน้นการวิเคราะห์โครงสร้างตลาด (Market Structure) และ Fair Value Gap (FVG) เข้ากับอินดิเคเตอร์ MACD เพื่อใช้เป็นตัวกรองหรือตัวยืนยันสัญญาณ Choch/BoS (Change of Character / Break of Structure)
1. ภาพรวมอินดิเคเตอร์ (Overall Purpose)
อินดิเคเตอร์นี้มีจุดประสงค์หลักคือ:
ระบุโครงสร้างตลาด: ตีเส้นและป้ายกำกับ Choch (Change of Character) และ BoS (Break of Structure) บนกราฟโดยอัตโนมัติ
ผสานการยืนยันด้วย MACD: สัญญาณ Choch/BoS จะถูกพิจารณาก็ต่อเมื่อ MACD Histogram เกิดการตัดขึ้นหรือลง (Zero Cross) ในทิศทางที่สอดคล้องกัน
แสดง Fair Value Gap (FVG): หากเปิดใช้งาน จะมีการตีกล่อง FVG บนกราฟ
แสดงระดับ Fibonacci: คำนวณและแสดงระดับ Fibonacci ที่สำคัญตามโครงสร้างตลาดปัจจุบัน
ปรับตาม Timeframe: การคำนวณและการแสดงผลทั้งหมดจะปรับตาม Timeframe ที่คุณกำลังใช้งานอยู่โดยอัตโนมัติ
2. ส่วนประกอบหลักของโค้ด (Code Breakdown)
โค้ดนี้สามารถแบ่งออกเป็นส่วนหลัก ๆ ได้ดังนี้:
2.1 Inputs (การตั้งค่า)
ส่วนนี้คือตัวแปรที่คุณสามารถปรับแต่งได้ในหน้าต่างการตั้งค่าของอินดิเคเตอร์ (คลิกที่รูปฟันเฟืองข้างชื่ออินดิเคเตอร์บนกราฟ)
MACD Settings (ตั้งค่า MACD):
fast_len: ความยาวของ Fast EMA สำหรับ MACD (ค่าเริ่มต้น 12)
slow_len: ความยาวของ Slow EMA สำหรับ MACD (ค่าเริ่มต้น 26)
signal_len: ความยาวของ Signal Line สำหรับ MACD (ค่าเริ่มต้น 9)
= ta.macd(close, fast_len, slow_len, signal_len): คำนวณค่า MACD Line, Signal Line และ Histogram โดยใช้ราคาปิด (close) และค่าความยาวที่กำหนด
is_bullish_macd_cross: ตรวจสอบว่า MACD Histogram ตัดขึ้นเหนือเส้น 0 (จากค่าลบเป็นบวก)
is_bearish_macd_cross: ตรวจสอบว่า MACD Histogram ตัดลงใต้เส้น 0 (จากค่าบวกเป็นลบ)
Fear Value Gap (FVG) Settings:
isFvgToShow: (Boolean) เปิด/ปิดการแสดง FVG บนกราฟ
bullishFvgColor: สีสำหรับ Bullish FVG
bearishFvgColor: สีสำหรับ Bearish FVG
mitigatedFvgColor: สีสำหรับ FVG ที่ถูก Mitigate (ลดทอน) แล้ว
fvgHistoryNbr: จำนวน FVG ย้อนหลังที่จะแสดง
isMitigatedFvgToReduce: (Boolean) เปิด/ปิดการลดขนาด FVG เมื่อถูก Mitigate
Structures (โครงสร้างตลาด) Settings:
isStructBodyCandleBreak: (Boolean) หากเป็น true การ Break จะต้องเกิดขึ้นด้วย เนื้อเทียน ที่ปิดเหนือ/ใต้ Swing High/Low หากเป็น false แค่ไส้เทียนทะลุก็ถือว่า Break
isCurrentStructToShow: (Boolean) เปิด/ปิดการแสดงเส้นโครงสร้างตลาดปัจจุบัน (เส้นสีน้ำเงินในภาพตัวอย่าง)
pivot_len: ความยาวของแท่งเทียนที่ใช้ในการมองหาจุด Pivot (Swing High/Low) ยิ่งค่าน้อยยิ่งจับ Swing เล็กๆ ได้, ยิ่งค่ามากยิ่งจับ Swing ใหญ่ๆ ได้
bullishBosColor, bearishBosColor: สีสำหรับเส้นและป้าย BOS ขาขึ้น/ขาลง
bosLineStyleOption, bosLineWidth: สไตล์ (Solid, Dotted, Dashed) และความหนาของเส้น BOS
bullishChochColor, bearishChochColor: สีสำหรับเส้นและป้าย CHoCH ขาขึ้น/ขาลง
chochLineStyleOption, chochLineWidth: สไตล์ (Solid, Dotted, Dashed) และความหนาของเส้น CHoCH
currentStructColor, currentStructLineStyleOption, currentStructLineWidth: สี, สไตล์ และความหนาของเส้นโครงสร้างตลาดปัจจุบัน
structHistoryNbr: จำนวนการ Break (Choch/BoS) ย้อนหลังที่จะแสดง
Structure Fibonacci (จากโค้ดต้นฉบับ):
เป็นชุด Input สำหรับเปิด/ปิด, กำหนดค่า, สี, สไตล์ และความหนาของเส้น Fibonacci Levels ต่างๆ (0.786, 0.705, 0.618, 0.5, 0.382) ที่จะถูกคำนวณจากโครงสร้างตลาดปัจจุบัน
2.2 Helper Functions (ฟังก์ชันช่วยทำงาน)
getLineStyle(lineOption): ฟังก์ชันนี้ใช้แปลงค่า String ที่เลือกจาก Input (เช่น "─", "┈", "╌") ให้เป็นรูปแบบ line.style_ ที่ Pine Script เข้าใจ
get_structure_highest_bar(lookback): ฟังก์ชันนี้พยายามหา Bar Index ของแท่งเทียนที่ทำ Swing High ภายในช่วง lookback ที่กำหนด
get_structure_lowest_bar(lookback): ฟังก์ชันนี้พยายามหา Bar Index ของแท่งเทียนที่ทำ Swing Low ภายในช่วง lookback ที่กำหนด
is_structure_high_broken(...): ฟังก์ชันนี้ตรวจสอบว่าราคาปัจจุบันได้ Break เหนือ _structureHigh (Swing High) หรือไม่ โดยพิจารณาจาก _highStructBreakPrice (ราคาปิดหรือราคา High ขึ้นอยู่กับการตั้งค่า isStructBodyCandleBreak)
FVGDraw(...): ฟังก์ชันนี้รับ Arrays ของ FVG Boxes, Types, Mitigation Status และ Labels มาประมวลผล เพื่ออัปเดตสถานะของ FVG (เช่น ถูก Mitigate หรือไม่) และปรับขนาด/ตำแหน่งของ FVG Box และ Label บนกราฟ
2.3 Global Variables (ตัวแปรทั่วทั้งอินดิเคเตอร์)
เป็นตัวแปรที่ประกาศด้วย var ซึ่งหมายความว่าค่าของมันจะถูกเก็บไว้และอัปเดตในแต่ละแท่งเทียน (persists across bars)
structureLines, structureLabels: Arrays สำหรับเก็บอ็อบเจกต์ line และ label ของเส้น Choch/BoS ที่วาดบนกราฟ
fvgBoxes, fvgTypes, fvgLabels, isFvgMitigated: Arrays สำหรับเก็บข้อมูลของ FVG Boxes และสถานะต่างๆ
structureHigh, structureLow: เก็บราคาของ Swing High/Low ที่สำคัญของโครงสร้างตลาดปัจจุบัน
structureHighStartIndex, structureLowStartIndex: เก็บ Bar Index ของจุดเริ่มต้นของ Swing High/Low ที่สำคัญ
structureDirection: เก็บสถานะของทิศทางโครงสร้างตลาด (1 = Bullish, 2 = Bearish, 0 = Undefined)
fiboXPrice, fiboXStartIndex, fiboXLine, fiboXLabel: ตัวแปรสำหรับเก็บข้อมูลและอ็อบเจกต์ของเส้น Fibonacci Levels
isBOSAlert, isCHOCHAlert: (Boolean) ใช้สำหรับส่งสัญญาณ Alert (หากมีการตั้งค่า Alert ไว้)
2.4 FVG Processing (การประมวลผล FVG)
ส่วนนี้จะตรวจสอบเงื่อนไขการเกิด FVG (Bullish FVG: high < low , Bearish FVG: low > high )
หากเกิด FVG และ isFvgToShow เป็น true จะมีการสร้าง box และ label ใหม่เพื่อแสดง FVG บนกราฟ
มีการจัดการ fvgBoxes และ fvgLabels เพื่อจำกัดจำนวน FVG ที่แสดงตาม fvgHistoryNbr และลบ FVG เก่าออก
ฟังก์ชัน FVGDraw จะถูกเรียกเพื่ออัปเดตสถานะของ FVG (เช่น การถูก Mitigate) และปรับการแสดงผล
2.5 Structures Processing (การประมวลผลโครงสร้างตลาด)
Initialization: ที่ bar_index == 0 (แท่งเทียนแรกของกราฟ) จะมีการกำหนดค่าเริ่มต้นให้กับ structureHigh, structureLow, structureHighStartIndex, structureLowStartIndex
Finding Current High/Low: highest, highestBar, lowest, lowestBar ถูกใช้เพื่อหา High/Low ที่สุดและ Bar Index ของมันใน 10 แท่งล่าสุด (หรือทั้งหมดหากกราฟสั้นกว่า 10 แท่ง)
Calculating Structure Max/Min Bar: structureMaxBar และ structureMinBar ใช้ฟังก์ชัน get_structure_highest_bar และ get_structure_lowest_bar เพื่อหา Bar Index ของ Swing High/Low ที่แท้จริง (ไม่ใช่แค่ High/Low ที่สุดใน lookback แต่เป็นจุด Pivot ที่สมบูรณ์)
Break Price: lowStructBreakPrice และ highStructBreakPrice จะเป็นราคาปิด (close) หรือราคา Low/High ขึ้นอยู่กับ isStructBodyCandleBreak
isStuctureLowBroken / isStructureHighBroken: เงื่อนไขเหล่านี้ตรวจสอบว่าราคาได้ทำลาย structureLow หรือ structureHigh หรือไม่ โดยพิจารณาจากราคา Break, ราคาแท่งก่อนหน้า และ Bar Index ของจุดเริ่มต้นโครงสร้าง
Choch/BoS Logic (ส่วนสำคัญที่ถูกผสานกับ MACD):
if(isStuctureLowBroken and is_bearish_macd_cross): นี่คือจุดที่ MACD เข้ามามีบทบาท หากราคาทำลาย structureLow (สัญญาณขาลง) และ MACD Histogram เกิด Bearish Zero Cross (is_bearish_macd_cross เป็น true) อินดิเคเตอร์จะพิจารณาว่าเป็น Choch หรือ BoS
หาก structureDirection == 1 (เดิมเป็นขาขึ้น) หรือ 0 (ยังไม่กำหนด) จะตีเป็น "CHoCH" (เปลี่ยนทิศทางโครงสร้างเป็นขาลง)
หาก structureDirection == 2 (เดิมเป็นขาลง) จะตีเป็น "BOS" (ยืนยันโครงสร้างขาลง)
มีการสร้าง line.new และ label.new เพื่อวาดเส้นและป้ายกำกับ
structureDirection จะถูกอัปเดตเป็น 1 (Bullish)
structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow จะถูกอัปเดตเพื่อกำหนดโครงสร้างใหม่
else if(isStructureHighBroken and is_bullish_macd_cross): เช่นกันสำหรับขาขึ้น หากราคาทำลาย structureHigh (สัญญาณขาขึ้น) และ MACD Histogram เกิด Bullish Zero Cross (is_bullish_macd_cross เป็น true) อินดิเคเตอร์จะพิจารณาว่าเป็น Choch หรือ BoS
หาก structureDirection == 2 (เดิมเป็นขาลง) หรือ 0 (ยังไม่กำหนด) จะตีเป็น "CHoCH" (เปลี่ยนทิศทางโครงสร้างเป็นขาขึ้น)
หาก structureDirection == 1 (เดิมเป็นขาขึ้น) จะตีเป็น "BOS" (ยืนยันโครงสร้างขาขึ้น)
มีการสร้าง line.new และ label.new เพื่อวาดเส้นและป้ายกำกับ
structureDirection จะถูกอัปเดตเป็น 2 (Bearish)
structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow จะถูกอัปเดตเพื่อกำหนดโครงสร้างใหม่
การลบเส้นเก่า: d.delete_line (หากไลบรารีทำงาน) จะถูกเรียกเพื่อลบเส้นและป้ายกำกับเก่าออกเมื่อจำนวนเกิน structHistoryNbr
Updating Structure High/Low (else block): หากไม่มีการ Break เกิดขึ้น แต่ราคาปัจจุบันสูงกว่า structureHigh หรือต่ำกว่า structureLow ในทิศทางที่สอดคล้องกัน (เช่น ยังคงเป็นขาขึ้นและทำ High ใหม่) structureHigh หรือ structureLow จะถูกอัปเดตเพื่อติดตาม High/Low ที่สุดของโครงสร้างปัจจุบัน
Current Structure Display:
หาก isCurrentStructToShow เป็น true อินดิเคเตอร์จะวาดเส้น structureHighLine และ structureLowLine เพื่อแสดงขอบเขตของโครงสร้างตลาดปัจจุบัน
Fibonacci Display:
หาก isFiboXToShow เป็น true อินดิเคเตอร์จะคำนวณและวาดเส้น Fibonacci Levels ต่างๆ (0.786, 0.705, 0.618, 0.5, 0.382) โดยอิงจาก structureHigh และ structureLow ของโครงสร้างตลาดปัจจุบัน
Alerts:
alertcondition: ใช้สำหรับตั้งค่า Alert ใน TradingView เมื่อเกิดสัญญาณ BOS หรือ CHOCH
plot(na):
plot(na) เป็นคำสั่งที่สำคัญในอินดิเคเตอร์ที่ไม่ได้ต้องการพล็อต Series ของข้อมูลบนกราฟ (เช่น ไม่ได้พล็อตเส้น EMA หรือ RSI) แต่ใช้วาดอ็อบเจกต์ (Line, Label, Box) โดยตรง
การมี plot(na) ช่วยให้ Pine Script รู้ว่าอินดิเคเตอร์นี้มีเอาต์พุตที่แสดงผลบนกราฟ แม้ว่าจะไม่ได้เป็น Series ที่พล็อตตามปกติก็ตาม
3. วิธีใช้งาน
คัดลอกโค้ดทั้งหมด ที่อยู่ในบล็อก immersive ด้านบน
ไปที่ TradingView และเปิดกราฟที่คุณต้องการ
คลิกที่เมนู "Pine Editor" ที่อยู่ด้านล่างของหน้าจอ
ลบโค้ดเดิมที่มีอยู่ และ วางโค้ดที่คัดลอกมา ลงไปแทน
คลิกที่ปุ่ม "Add to Chart"
อินดิเคเตอร์จะถูกเพิ่มลงในกราฟของคุณโดยอัตโนมัติ คุณสามารถคลิกที่รูปฟันเฟืองข้างชื่ออินดิเคเตอร์บนกราฟเพื่อเข้าถึงหน้าต่างการตั้งค่าและปรับแต่งตามความต้องการของคุณได้
Hello! I will explain the "SMC Structures and FVG + MACD" indicator you provided in detail, section by section, so you can fully understand how it works.This indicator combines the concepts of Smart Money Concept (SMC), which focuses on analyzing Market Structure and Fair Value Gaps (FVG), with the MACD indicator to serve as a filter or confirmation for Choch (Change of Character) and BoS (Break of Structure) signals.1. Overall PurposeThe main purposes of this indicator are:Identify Market Structure: Automatically draw lines and label Choch (Change of Character) and BoS (Break of Structure) on the chart.Integrate MACD Confirmation: Choch/BoS signals will only be considered when the MACD Histogram performs a cross (Zero Cross) in the corresponding direction.Display Fair Value Gap (FVG): If enabled, FVG boxes will be drawn on the chart.Display Fibonacci Levels: Calculate and display important Fibonacci levels based on the current market structure.Adapt to Timeframe: All calculations and displays will automatically adjust to the timeframe you are currently using.2. Code BreakdownThis code can be divided into the following main sections:2.1 Inputs (Settings)This section contains variables that you can adjust in the indicator's settings window (click the gear icon next to the indicator's name on the chart).MACD Settings:fast_len: Length of the Fast EMA for MACD (default 12)slow_len: Length of the Slow EMA for MACD (default 26)signal_len: Length of the Signal Line for MACD (default 9) = ta.macd(close, fast_len, slow_len, signal_len): Calculates the MACD Line, Signal Line, and Histogram using the closing price (close) and the specified lengths.is_bullish_macd_cross: Checks if the MACD Histogram crosses above the 0 line (from negative to positive).is_bearish_macd_cross: Checks if the MACD Histogram crosses below the 0 line (from positive to negative).Fear Value Gap (FVG) Settings:isFvgToShow: (Boolean) Enables/disables the display of FVG on the chart.bullishFvgColor: Color for Bullish FVG.bearishFvgColor: Color for Bearish FVG.mitigatedFvgColor: Color for FVG that has been mitigated.fvgHistoryNbr: Number of historical FVG to display.isMitigatedFvgToReduce: (Boolean) Enables/disables reducing the size of FVG when mitigated.Structures (โครงสร้างตลาด) Settings:isStructBodyCandleBreak: (Boolean) If true, the break must occur with the candle body closing above/below the Swing High/Low. If false, a wick break is sufficient.isCurrentStructToShow: (Boolean) Enables/disables the display of the current market structure lines (blue lines in the example image).pivot_len: Lookback length for identifying Pivot points (Swing High/Low). A smaller value captures smaller, more frequent swings; a larger value captures larger, more significant swings.bullishBosColor, bearishBosColor: Colors for bullish/bearish BOS lines and labels.bosLineStyleOption, bosLineWidth: Style (Solid, Dotted, Dashed) and width of BOS lines.bullishChochColor, bearishChochColor: Colors for bullish/bearish CHoCH lines and labels.chochLineStyleOption, chochLineWidth: Style (Solid, Dotted, Dashed) and width of CHoCH lines.currentStructColor, currentStructLineStyleOption, currentStructLineWidth: Color, style, and width of the current market structure lines.structHistoryNbr: Number of historical breaks (Choch/BoS) to display.Structure Fibonacci (from original code):A set of inputs to enable/disable, define values, colors, styles, and widths for various Fibonacci Levels (0.786, 0.705, 0.618, 0.5, 0.382) that will be calculated from the current market structure.2.2 Helper FunctionsgetLineStyle(lineOption): This function converts the selected string input (e.g., "─", "┈", "╌") into a line.style_ format understood by Pine Script.get_structure_highest_bar(lookback): This function attempts to find the Bar Index of the Swing High within the specified lookback period.get_structure_lowest_bar(lookback): This function attempts to find the Bar Index of the Swing Low within the specified lookback period.is_structure_high_broken(...): This function checks if the current price has broken above _structureHigh (Swing High), considering _highStructBreakPrice (closing price or high price depending on isStructBodyCandleBreak setting).FVGDraw(...): This function takes arrays of FVG Boxes, Types, Mitigation Status, and Labels to process and update the status of FVG (e.g., whether it's mitigated) and adjust the size/position of FVG Boxes and Labels on the chart.2.3 Global VariablesThese are variables declared with var, meaning their values are stored and updated on each bar (persists across bars).structureLines, structureLabels: Arrays to store line and label objects for Choch/BoS lines drawn on the chart.fvgBoxes, fvgTypes, fvgLabels, isFvgMitigated: Arrays to store FVG box data and their respective statuses.structureHigh, structureLow: Stores the price of the significant Swing High/Low of the current market structure.structureHighStartIndex, structureLowStartIndex: Stores the Bar Index of the start point of the significant Swing High/Low.structureDirection: Stores the status of the market structure direction (1 = Bullish, 2 = Bearish, 0 = Undefined).fiboXPrice, fiboXStartIndex, fiboXLine, fiboXLabel: Variables to store data and objects for Fibonacci Levels.isBOSAlert, isCHOCHAlert: (Boolean) Used to trigger alerts in TradingView (if alerts are configured).2.4 FVG ProcessingThis section checks the conditions for FVG formation (Bullish FVG: high < low , Bearish FVG: low > high ).If FVG occurs and isFvgToShow is true, a new box and label are created to display the FVG on the chart.fvgBoxes and fvgLabels are managed to limit the number of FVG displayed according to fvgHistoryNbr and remove older FVG.The FVGDraw function is called to update the FVG status (e.g., whether it's mitigated) and adjust its display.2.5 Structures ProcessingInitialization: At bar_index == 0 (the first bar of the chart), structureHigh, structureLow, structureHighStartIndex, and structureLowStartIndex are initialized.Finding Current High/Low: highest, highestBar, lowest, lowestBar are used to find the highest/lowest price and its Bar Index of it in the last 10 bars (or all bars if the chart is shorter than 10 bars).Calculating Structure Max/Min Bar: structureMaxBar and structureMinBar use get_structure_highest_bar and get_structure_lowest_bar functions to find the Bar Index of the true Swing High/Low (not just the highest/lowest in the lookback but a complete Pivot point).Break Price: lowStructBreakPrice and highStructBreakPrice will be the closing price (close) or the Low/High price, depending on the isStructBodyCandleBreak setting.isStuctureLowBroken / isStructureHighBroken: These conditions check if the price has broken structureLow or structureHigh, considering the break price, previous bar prices, and the Bar Index of the structure's starting point.Choch/BoS Logic (Key Integration with MACD):if(isStuctureLowBroken and is_bearish_macd_cross): This is where MACD plays a role. If the price breaks structureLow (bearish signal) AND the MACD Histogram performs a Bearish Zero Cross (is_bearish_macd_cross is true), the indicator will consider it a Choch or BoS.If structureDirection == 1 (previously bullish) or 0 (undefined), it will be labeled "CHoCH" (changing structure direction to bearish).If structureDirection == 2 (already bearish), it will be labeled "BOS" (confirming bearish structure).line.new and label.new are used to draw the line and label.structureDirection will be updated to 1 (Bullish).structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow will be updated to define the new structure.else if(isStructureHighBroken and is_bullish_macd_cross): Similarly for bullish breaks. If the price breaks structureHigh (bullish signal) AND the MACD Histogram performs a Bullish Zero Cross (is_bullish_macd_cross is true), the indicator will consider it a Choch or BoS.If structureDirection == 2 (previously bearish) or 0 (undefined), it will be labeled "CHoCH" (changing structure direction to bullish).If structureDirection == 1 (already bullish), it will be labeled "BOS" (confirming bullish structure).line.new and label.new are used to draw the line and label.structureDirection will be updated to 2 (Bearish).structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow will be updated to define the new structure.Deleting Old Lines: d.delete_line (if the library works) will be called to delete old lines and labels when their number exceeds structHistoryNbr.Updating Structure High/Low (else block): If no break occurs, but the current price is higher than structureHigh or lower than structureLow in the corresponding direction (e.g., still bullish and making a new high), structureHigh or structureLow will be updated to track the highest/lowest point of the current structure.Current Structure Display:If isCurrentStructToShow is true, the indicator draws structureHighLine and structureLowLine to show the boundaries of the current market structure.Fibonacci Display:If isFiboXToShow is true, the indicator calculates and draws various Fibonacci Levels (0.786, 0.705, 0.618, 0.5, 0.382) based on the structureHigh and structureLow of the current market structure.Alerts:alertcondition: Used to set up alerts in TradingView when BOS or CHOCH signals occur.plot(na):plot(na) is an important statement in indicators that do not plot data series directly on the chart (e.g., not plotting EMA or RSI lines) but instead draw objects (Line, Label, Box).Having plot(na) helps Pine Script recognize that this indicator has an output displayed on the chart, even if it's not a regularly plotted series.3. How to UseCopy all the code in the immersive block above.Go to TradingView and open your desired chart.Click on the "Pine Editor" menu at the bottom of the screen.Delete any existing code and paste the copied code in its place.Click the "Add to Chart" button.The indicator will be added to your chart automatically. You can click the gear icon next to the indicator's name on the chart to access the settings window and customize it to your needs.I hope this explanation helps you understand this indicator in detail. If anything is unclear, or you need further adjustments, please let me know.
