Relative Trend Index (RTI) by Zeiierman█ Overview
The Relative Trend Index (RTI) developed by Zeiierman is an innovative technical analysis tool designed to measure the strength and direction of the market trend. Unlike some traditional indicators, the RTI boasts a distinctive ability to adapt and respond to market volatility, while still minimizing the effects of minor, short-term market fluctuations.
The Relative Trend Index blends trend-following and mean-reverting characteristics, paired with a customizable and intuitive approach to trend strength, and its sensitivity to price action makes this indicator stand out.
█ Benefits of using this RTI instead of RSI
The Relative Strength Index (RSI) and the Relative Trend Index (RTI) are both powerful technical indicators, each with its own unique strengths.
However, there are key differences that make the RTI arguably more sophisticated and precise, especially when it comes to identifying trends and overbought/oversold (OB/OS) areas.
The RSI is a momentum oscillator that measures the speed and change of price movements and is typically used to identify overbought and oversold conditions in a market. However, its primary limitation lies in its tendency to produce false signals during extended trending periods.
On the other hand, the RTI is designed specifically to identify and adapt to market trends. Instead of solely focusing on price changes, the RTI measures the relative positioning of the current closing price within its recent range, providing a more comprehensive view of market conditions.
The RTI's adaptable nature is particularly valuable. The user-adjustable sensitivity percentage allows traders to fine-tune the indicator's responsiveness, making it more resilient to sudden market fluctuations and noise that could otherwise produce false signals. This feature is advantageous in various market conditions, from trending to choppy and sideways-moving markets.
Furthermore, the RTI's unique method of defining OB/OS zones takes into account the prevailing trend, which can provide a more precise reflection of the market's condition.
While the RSI is an invaluable tool in many traders' toolkits, the RTI's unique approach to trend identification, adaptability, and enhanced definition of OB/OS zones can provide traders with a more nuanced understanding of market conditions and potential trading opportunities. This makes the RTI an especially powerful tool for those seeking to ride long-term trends and avoid false signals.
█ Calculations
In summary, while simple enough, the math behind the RTI indicator is quite powerful. It combines the quantification of price volatility with the flexibility to adjust the trend sensitivity. It provides a normalized output that can be interpreted consistently across various trading scenarios.
The math behind the Relative Trend Index (RTI) indicator is rooted in some fundamental statistical concepts: Standard Deviation and Percentiles.
Standard Deviation: The Standard Deviation is a measure of dispersion or variability in a dataset. It quantifies the degree to which each data point deviates from the mean (or average) of the data set. In this script, the standard deviation is computed on the 'close' prices over a specified number of periods. This provides a measure of the volatility in the price over that period. The higher the standard deviation, the more volatile the price has been.
Percentiles: The percentile is a measure used in statistics indicating the value below which a given percentage of observations in a group falls. After calculating the upper and lower trends for the last 'length' periods and sorting these values, the script uses the 'Sensitivity ' parameter to extract percentiles from these sorted arrays. This is a powerful concept because it allows us to adjust the sensitivity of our signals. By choosing different percentiles (controlled through the 'Sensitivity' parameter), we can decide whether we want to react only to extreme events (high percentiles) or be more reactive and consider smaller deviations from the norm as significant (lower percentiles).
Finally, the script calculates the Relative Trend Index value, which is essentially a normalized measure indicating where the current price falls between the upper and lower trend values. This simple ratio is incredibly powerful as it provides a standardized measure that can be used across different securities and market conditions to identify potential trading signals.
Core Components
Trend Data Count: This parameter denotes the number of data points used in the RTI's calculation, determining the trend length. A higher count captures a more extended market view (long-term trend), providing smoother results that are more resistant to sudden market changes. In contrast, a lower count focuses on more recent data (short-term trend), yielding faster responses to market changes, albeit at the cost of increased susceptibility to market noise.
Trend Sensitivity Percentage: This parameter is employed to select the indices within the trend arrays used for upper and lower trend definitions. By adjusting this value, users can affect the sensitivity of the trend, with higher percentages leading to a less sensitive trend.
█ How to use
The RTI plots a line that revolves around a mid-point of 50. When the RTI is above 50, it implies that the market trend is bullish (upward), and when it's below 50, it indicates a bearish (downward) trend. Furthermore, the farther the RTI deviates from the 50 line, the stronger the trend is perceived to be.
Bullish
Bearish
The RTI includes user-defined Overbought and Oversold levels. These thresholds suggest potential trading opportunities when they are crossed, serving as a cue for traders to possibly buy or sell. This gives the RTI an additional use case as a mean-reversion tool, in addition to being a trend-following indicator.
In short
Trend Confirmation and Reversals: If the percentage trend value is consistently closer to the upper level, it can indicate a strong uptrend. Similarly, if it's closer to the lower level, a downtrend may be in play. If the percentage trend line begins to move away from one trend line towards the other, it could suggest a potential trend reversal.
Identifying Overbought and Oversold Conditions: When the percentage trend value reaches the upper trend line (signified by a value of 1), it suggests an overbought condition - i.e., the price has been pushed up, perhaps too far, and could be due for a pullback, or indicating a strong positive trend. Conversely, when the percentage trend value hits the lower trend line (a value of 0), it indicates an oversold condition - the price may have been driven down and could be set to rebound, or indicate a strong negative trend. Traders often use these overbought and oversold signals as contrarian indicators, considering them potential signs to sell (in overbought conditions) or buy (in oversold conditions). If the RTI line remains overbought or oversold for an extended period, it indicates a strong trend in that direction.
█ Settings
One key feature of the RTI is its configurability. It allows users to set the trend data length and trend sensitivity.
The trend data length represents the number of data points used in the trend calculation. A longer trend data length will reflect a more long-term trend, whereas a shorter trend data length will capture short-term movements.
Trend sensitivity refers to the threshold for determining what constitutes a significant trend. High sensitivity levels will deem fewer price movements as significant, hence making the trend less sensitive. Conversely, low sensitivity levels will deem more price movements as significant, hence making the trend more sensitive.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Pesquisar nos scripts por "the script"
Psychological levels (Bank levels) PsychoLevels v3 - TartigradiaPsychological levels (Bank levels) plots the closest "round" price levels above and below current price, based on neuroscience research of how humans intuitively calculate in logarithms.
Psychological levels, also called bank levels, are "round" price numbers, by truncating after the nth leftmost digits, around which price often experience resistance or support, because traders and investors tend to set orders around these round numbers.
The calculation done here is fully automatic and dynamic, contrary to other similar scripts, this one uses a mathematical calculation that extracts the 1, 2 or 3 leftmost digits and calculate the previous and next level by incrementing/decrementing these digits. This means it works for any symbol under any price range.
This approach is based on neuroscience research, which found that human brains intuitively approximate numbers on a logarithmic scale, adults and children alike, and similarly to macaques, for more info see Numerical Cognition , Weber-Fechner Law , Zipf law .
For example, if price is at 0.0421, the next major price level is 0.05 and medium one is 0.043. For another asset currently priced at 19354, the next and previous major price levels are 20000 and 10000 respectively, and the next/previous medium levels are 20000 and 19000, and the next/previous weak levels are 19400 and 19300.
IMPORTANT: Please enable "Scale price chart only" in the chart's scale's options, as otherwise major levels may make the chart's scale very small and hard to read.
How it works
At any time, there are 3 levels of strength (1 leftmost digit, 2 leftmost digits, 3 leftmost digits) represented by different sizes, and 3 directional levels for each of these strengths (level above, level below, and half-level) represented by different colors and positions, around current price.
Indeed, contrary to other similar price levels scripts, we do not plot ALL price levels at all times, because otherwise the chart becomes wayyy too cluttered, and also it's highly processing intensive to plot so many lines. So we here use a dynamical approach: we plot only the relevant levels, the closest ones according to current price.
Hence, when a level disappears, it does not mean that it does not exist anymore, but simply that we are not drawing it right now because it is not pertinent for the current price movement (ie, too far away).
Breakouts can be detected in two different ways depending on if SMA is set to a value higher than 1 or not: if SMA == 1, then there is no smoothing, so the levels adapt instantaneously to the current price, so to detect breakout, you should refer to the levels at the previous tick and whether they were broken by current tick's price; if SMA > 1, then there is some smoothing, and so the levels will stay in-place even if there is a breakout, so it's easier to spot breakouts without having to look at the previous ticks, but on the other hand you won't see the new levels for the new price range until after a few more ticks for the smoothing window to adapt. Hence, by default, smoothing is disabled, so that you can see the currently pertinent levels at all time, even right after or during a breakout.
By default, the strong above level is in green, strong below level is in red, medium above level is in blue, medium below level is in yellow, and weak levels aren't displayed but can be. Half levels are also displayed, in a darker color. Strong levels are increments of the first leftmost digit (eg, 10000 to 20000), medium levels are increments of the second leftmost digit (eg, 19000 to 20000), and weak levels of the third leftmost digit (eg, 19100 to 19200). Instead of plotting all the psychological levels all at once as a grid, which makes the chart unintelligible, here the levels adapt dynamically around the current price, so that they show the above/below/half levels relatively to the current price.
Indeed, "half-levels" are also displayed (eg, medium level can also display 19500 instead of only 19000 or 20000). This was made because otherwise the gap between two levels was too big, especially for the strongest levels (eg, there was no major level between 20000 and 30000, but with a half-step we also get a half-level at 25000, and empirically price tends to respect these half levels - I also tried quarter levels but empirically the results were not good). In addition to this hard-coded half-level, you can also create more subdivisions (eg, quarter levels) by setting the simple moving average to a value higher than 1.
The script can be made to run on the daily timeframe whatever the current chart's timeframe is, to reduce the variability in levels, to make it less noisy than intraday price movement. But by default, the chart resolution is used, because I empirically found that the levels found with this indicator work on all time resolutions quite well.
The step can be adjusted to increase the gap between levels, eg, if you want to display one every 2 levels then input step = 2 (eg, 22000, 24000, 26000, etc), or if you want to display quarter levels, input 0.25 (eg, 22000, 22250, 22500, etc). The default values should fit most use cases and cover most psychological levels.
How to read
Focust first on bigger dotted levels, they are stronger and more likely to cause a rebound or a major event or price to stay at this level.
Remember that it's not enough to just look at levels, the context is important, because levels have various effects depending on current price movement: if price is above a level, the level is a support on which price can rebound; if price is below a level, the level is a resistance on which price can rebound (or break); and finally sometimes price also stays hovering around a level for some time.
Levels closer to 9 are less weaker, and levels closer to 0 are stronger, according to Zipf law. This is now reflected since v3 in the transparency, levels that are closer to 9 will be more transparent.
The switch in color for the same level illustrates how a level switches from being a support to a resistance and inversely. Eg, if a major level turns from green to red, then it changed from being a resistance (above) to a support (below).
As is well known in trading, longer standing levels are stronger. This indicator provides a direct illustration: in practice, the number of consecutive dots on the same line influences the strength of the level: the longer the chain of dots, the more you can expect this price level to be significant. The length does not mean the level will necessarily hold, but that other traders are likely to monitor if it holds, and if not then price will break down. Hence, longer levels are good spots to place stop losses, or to enter trades depending on your strategy. In general, a single dot is not enough to consider a level significant, but 2 or more is a good enough level, and 10+ is a strong level. Intuitively, this makes sense, and is what pro traders do: the longer a level is tested, the stronger it is. This indicator can visually represent this intuition and allows to use it as a more systematic trading signal.
Motivation
I initially made the first version of the PsychoLevels indicator mainly to train with PineScript, but I found it surprisingly accurate to define levels that are respected by price movements. So I guess it can be useful for new traders and experienced traders alike, as it's easy to forget that psychological levels can often be as strong if not stronger than technical levels. It can also be used to quickly screen other minor assets for trading opportunities. For example, a hybrid strategy would be to manually define levels on BTCUSD but using this script to automatically define levels in crypto altcoins and quickly screen them for a trade opportunity that can be greater than with BTCUSD but with the same trend.
Personally, although initially I did not believe an automated tool would work well for this purpose, I could now empirically verify that it is quite reliable for the purpose of detecting levels, and so I use it all the time to find the levels automatically and help me monitor them like a hawk, so that I only have to draw uber major levels, the ones that last between cycles and that are hard to autodetect, but otherwise all daily/weekly levels are usually covered. However, trendlines must still be drawn manually or with another indicator (but note that up to now I have found none that worked well enough), as PsychoLevels only draws levels (ie, horizontal lines, not oblique ones!).
Differences with the previous version PsychoLevels v2
price levels now have a transparency according to their importance for the human brain: numbers closer to 9 are weaker, and numbers closer to 0 are stronger and represent a major psychological threshold (eg, that's why prices marked as $9.99 sell better than $10.00). This option can be disabled to get the exact same behavior as v2.
modularized and typed code
PsychoLevels v2 can be found here:
TechnicalRating█ OVERVIEW
This library is a Pine Script™ programmer’s tool for incorporating TradingView's well-known technical ratings within their scripts. The ratings produced by this library are the same as those from the speedometers in the technical analysis summary and the "Rating" indicator in the Screener , which use the aggregate biases of 26 technical indicators to calculate their results.
█ CONCEPTS
Ensemble analysis
Ensemble analysis uses multiple weaker models to produce a potentially stronger one. A common form of ensemble analysis in technical analysis is the usage of aggregate indicators together in hopes of gaining further market insight and reinforcing trading decisions.
Technical ratings
Technical ratings provide a simplified way to analyze financial markets by combining signals from an ensemble of indicators into a singular value, allowing traders to assess market sentiment more quickly and conveniently than analyzing each constituent separately. By consolidating the signals from multiple indicators into a single rating, traders can more intuitively and easily interpret the "technical health" of the market.
Calculating the rating value
Using a variety of built-in TA functions and functions from our ta library, this script calculates technical ratings for moving averages, oscillators, and their overall result within the `calcRatingAll()` function.
The function uses the script's `calcRatingMA()` function to calculate the moving average technical rating from an ensemble of 15 moving averages and filters:
• Six Simple Moving Averages and six Exponential Moving Averages with periods of 10, 20, 30, 50, 100, and 200
• A Hull Moving Average with a period of 9
• A Volume-Weighted Moving Average with a period of 20
• An Ichimoku Cloud with a conversion line length of 9, base length of 26, and leading span B length of 52
The function uses the script's `calcRating()` function to calculate the oscillator technical rating from an ensemble of 11 oscillators:
• RSI with a period of 14
• Stochastic with a %K period of 14, a smoothing period of 3, and a %D period of 3
• CCI with a period of 20
• ADX with a DI length of 14 and an ADX smoothing period of 14
• Awesome Oscillator
• Momentum with a period of 10
• MACD with fast, slow, and signal periods of 12, 26, and 9
• Stochastic RSI with an RSI period of 14, a %K period of 14, a smoothing period of 3, and a %D period of 3
• Williams %R with a period of 14
• Bull Bear Power with a period of 50
• Ultimate Oscillator with fast, middle, and slow lengths of 7, 14, and 28
Each indicator is assigned a value of +1, 0, or -1, representing a bullish, neutral, or bearish rating. The moving average rating is the mean of all ratings that use the `calcRatingMA()` function, and the oscillator rating is the mean of all ratings that use the `calcRating()` function. The overall rating is the mean of the moving average and oscillator ratings, which ranges between +1 and -1. This overall rating, along with the separate MA and oscillator ratings, can be used to gain insight into the technical strength of the market. For a more detailed breakdown of the signals and conditions used to calculate the indicators' ratings, consult our Help Center explanation.
Determining rating status
The `ratingStatus()` function produces a string representing the status of a series of ratings. The `strongBound` and `weakBound` parameters, with respective default values of 0.5 and 0.1, define the bounds for "strong" and "weak" ratings.
The rating status is determined as follows:
Rating Value Rating Status
< -strongBound Strong Sell
< -weakBound Sell
-weakBound to weakBound Neutral
> weakBound Buy
> strongBound Strong Buy
By customizing the `strongBound` and `weakBound` values, traders can tailor the `ratingStatus()` function to fit their trading style or strategy, leading to a more personalized approach to evaluating ratings.
Look first. Then leap.
█ FUNCTIONS
This library contains the following functions:
calcRatingAll()
Calculates 3 ratings (ratings total, MA ratings, indicator ratings) using the aggregate biases of 26 different technical indicators.
Returns: A 3-element tuple: ( [(float) ratingTotal, (float) ratingOther, (float) ratingMA ].
countRising(plot)
Calculates the number of times the values in the given series increase in value up to a maximum count of 5.
Parameters:
plot : (series float) The series of values to check for rising values.
Returns: (int) The number of times the values in the series increased in value.
ratingStatus(ratingValue, strongBound, weakBound)
Determines the rating status of a given series based on its values and defined bounds.
Parameters:
ratingValue : (series float) The series of values to determine the rating status for.
strongBound : (series float) The upper bound for a "strong" rating.
weakBound : (series float) The upper bound for a "weak" rating.
Returns: (string) The rating status of the given series ("Strong Buy", "Buy", "Neutral", "Sell", or "Strong Sell").
Oscillator Workbench — Chart [LucF]█ OVERVIEW
This indicator uses an on-chart visual framework to help traders with the interpretation of any oscillator's behavior. The advantage of using this tool is that you do not need to know all the ins and outs of a particular oscillator such as RSI, CCI, Stochastic, etc. Your choice of oscillator and settings in this indicator will change its visuals, which allows you to evaluate different configurations in the context of how the workbench models oscillator behavior. My hope is that by using the workbench, you may come up with an oscillator selection and settings that produce visual cues you find useful in your trading.
The workbench works on any symbol and timeframe. It uses the same presentation engine as my Delta Volume Channels indicator; those already familiar with it will feel right at home here.
█ CONCEPTS
Oscillators
An oscillator is any signal that moves up and down a centerline. The centerline value is often zero or 50. Because the range of oscillator values is different than that of the symbol prices we look at on our charts, it is usually impossible to display an oscillator on the chart, so we typically put oscillators in a separate pane where they live in their own space. Each oscillator has its own profile and properties that dictate its behavior and interpretation. Oscillators can be bounded , meaning their values oscillate between fixed values such as 0 to 100 or +1 to -1, or unbounded when their maximum and minimum values are undefined.
Oscillator weight
How do you display an oscillator's value on a chart showing prices when both values are not on the same scale? The method I use here converts the oscillator's value into a percentage that is used to weigh a reference line. The weight of the oscillator is calculated by maintaining its highest and lowest value above and below its centerline since the beginning of the chart's history. The oscillator's relative position in either of those spaces is then converted to a percentage, yielding a positive or negative value depending on whether the oscillator is above or below its centerline. This method works equally well with bounded and unbounded oscillators.
Oscillator Channel
The oscillator channel is the space between two moving averages: the reference line and a weighted version of that line. The reference line is a moving average of a type, source and length which you select. The weighted line uses the same settings, but it averages the oscillator-weighted price source.
The weight applied to the source of the reference line can also include the relative size of the bar's volume in relation to previous bars. The effect of this is that the oscillator's weight on bars with higher total volume will carry greater weight than those with lesser volume.
The oscillator channel can be in one of four states, each having its corresponding color:
• Bull (teal): The weighted line is above the reference line.
• Strong bull (lime): The bull condition is fulfilled and the bar's close is above the reference line and both the reference and the weighted lines are rising.
• Bear (maroon): The weighted line is below the reference line.
• Strong bear (pink): The bear condition is fulfilled and the bar's close is below the reference line and both the reference and the weighted lines are falling.
Divergences
In the context of this indicator, a divergence is any bar where the slope of the reference line does not match that of the weighted line. No directional bias is assigned to divergences when they occur. You can also choose to define divergences as differences in polarity between the oscillator's slope and the polarity of close-to-close values. This indicator's divergences are designed to identify transition levels. They have no polarity; their bullish/bearish bias is determined by the behavior of price relative to the divergence channel after the divergence channel is built.
Divergence Channel
The divergence channel is the space between two levels (by default, the bar's low and high ) saved when divergences occur. When price has breached a channel and a new divergence occurs, a new channel is created. Until that new channel is breached, bars where additional divergences occur will expand the channel's levels if the bar's price points are outside the channel.
Price breaches of the divergence channel will change its state. Divergence channels can be in one of five different states:
• Bull (teal): Price has breached the channel to the upside.
• Strong bull (lime): The bull condition is fulfilled and the oscillator channel is in the strong bull state.
• Bear (maroon): Price has breached the channel to the downside.
• Strong bear (pink): The bear condition is fulfilled and the oscillator channel is in the strong bear state.
• Neutral (gray): The channel has not been breached.
█ HOW TO USE THE INDICATOR
Load the indicator on an active chart (see here if you don't know how).
The default configuration displays:
• The Divergence channel's levels.
• Bar colors using the state of the oscillator channel.
The default settings use:
• RSI as the oscillator, using the close source and a length of 20 bars.
• An Arnaud-Legoux moving average on the close and a length of 20 bars as the reference line.
• The weighted version of the reference line uses only the oscillator's weight, i.e., without the relative volume's weight.
The weighted line is capped to three standard deviations of the reference.
• The divergence channel's levels are determined using the high and low of the bars where divergences occur.
Breaches of the channel require a bar's low to move above the top of the channel, and the bar's high to move below the channel's bottom.
No markers appear on the chart; if you want to create alerts from this script, you will need first to define the conditions that will trigger the markers, then create the alert, which will trigger on those same conditions.
To learn more about how to use this indicator, you must understand the concepts it uses and the information it displays, which requires reading this description. There are no videos to explain it.
█ FEATURES
The script's inputs are divided in five sections: "Oscillator", "Oscillator channel", "Divergence channel", "Bar Coloring" and "Marker/Alert Conditions".
Oscillator
This is where you configure the oscillator you want to study. Thirty oscillators are available to choose from, but you can also use an oscillator from another indicator that is on your chart, if you want. When you select an external indicator's plot as the oscillator, you must also specify the value of its centerline.
Oscillator Channel
Here, you control the visibility and colors of the reference line, its weighted version, and the oscillator channel between them.
You also specify what type of moving average you want to use as a reference line, its source and its length. This acts as the oscillator channel's baseline. The weighted line is also a moving average of the same type and length as the reference line, except that it will be calculated from the weighted version of the source used in the reference line. By default, the weighted line is capped to three standard deviations of the reference line. You can change that value, and also elect to cap using a multiple of ATR instead. The cap provides a mechanism to control how far the weighted line swings from the reference line. This section is also where you can enable the relative volume component of the weight.
Divergence Channel
This is where you control the appearance of the divergence channel and the key price values used in determining the channel's levels and breaching conditions. These choices have an impact on the behavior of the channel. More generous level prices like the default low and high selection will produce more conservative channels, as will the default choice for breach prices.
In this section, you can also enable a mode where an attempt is made to estimate the channel's bias before price breaches the channel. When it is enabled, successive increases/decreases of the channel's top and bottom levels are counted as new divergences occur. When one count is greater than the other, a bull/bear bias is inferred from it. You can also change the detection mode of divergences, and choose to display a mark above or below bars where divergences occur.
Bar Coloring
You specify here:
• The method used to color chart bars, if you choose to do so.
• If you want to hollow out the bodies of bars where volume has not increased since the last bar.
Marker/Alert Conditions
Here, you specify the conditions that will trigger up or down markers. The trigger conditions can include a combination of state transitions of the oscillator and the divergence channels. The triggering conditions can be filtered using a variety of conditions.
Configuring the marker conditions is necessary before creating an alert from this script, as the alert will use the marker conditions to trigger.
Realtime values will repaint, as is usually the case with oscillators, but markers only appear on bar closes, so they will not repaint. Keep in mind, when looking at markers on historical bars, that they are positioned on the bar when it closes — NOT when it opens.
Raw values
The raw values calculated by this script can be inspected using the Data Window, including the oscillator's value and the weights.
█ INTERPRETATION
Except when mentioned otherwise, this section's charts use the indicator's default settings, with different visual components turned on or off.
The aim of the oscillator channel is to provide a visual representation of an oscillator's general behavior. The simplest characteristic of the channel is its bull/bear state, determined by whether the weighted line is above or below the reference line. One can then distinguish between its bull and strong bull states, as transitions from strong bull to bull states will generally happen when trends are losing steam. While one should not infer a reversal from such transitions, they can be a good place to tighten stops. Only time will tell if a reversal will occur. One or more divergences will often occur before reversals. This shows the oscillator channel, with the reference line and the thicker, weighted line:
The nature of the divergence channel 's design makes it particularly adept at identifying consolidation areas if its settings are kept on the conservative side. The divergence channel will also reveal transition areas. A gray divergence channel should usually be considered a no-trade zone. More adventurous traders can use the oscillator channel to orient their trade entries if they accept the risk of trading in a neutral divergence channel, which by definition will not have been breached by price. This show only the divergence channels:
This chart shows divergence channels and their levels, and colors bars on divergences and on the state of the oscillator channel, which is not visible on the chart:
If your charts are already busy with other stuff you want to hold on to, you could consider using only the chart bar coloring component of this indicator. Here we only color bars using the combined state of the oscillator and divergence channel, and we do not color the bodies of bars where volume has not increased. Note that my chart's settings do not color the candle bodies:
At its simplest, one way to use this indicator would be to look for overlaps of the strong bull/bear colors in both the oscillator channel and a divergence channel, as these identify points where price is breaching the divergence channel when the oscillator's state is consistent with the direction of the breach.
Tip
One way to use the Workbench is to combine it with my Delta Volume Channels indicator. If both indicators use the same MA as a reference line, you can display its delta volume channel instead of the oscillator channel.
This chart shows such a setup. The Workbench displays its divergence levels, the weighted reference line using the default RSI oscillator, and colors bars on divergences. The DV Channels indicator only displays its delta volume channel, which uses the same MA as the workbench for its baseline. This way you can ascertain the volume delta situation in contrast with the visuals of the Workbench:
█ LIMITATIONS
• For some of the oscillators, assumptions are made concerning their different parameters when they are more complex than just a source and length.
See the `oscCalc()` function in this indicator's code for all the details, and ask me in a comment if you can't find the information you need.
• When an oscillator using volume is selected and no volume information is available for the chart's symbol, an error will occur.
• The method I use to convert an oscillator's value into a percentage is fragile in the early history of datasets
because of the nascent expression of the oscillator's range during those early bars.
█ NOTES
Working with this workbench
This indicator is called a workbench for a reason; it is designed for traders interested in exploring its behavior with different oscillators and settings, in the hope they can come up with a setup that suits their trading methodology. I cannot tell you which setup is the best because its setup should be compatible with your trading methodology, which may require faster or slower transitions, thus different configurations of the settings affecting the calculations of the divergence channels.
For Pine Script™ Coders
• This script uses the new overload of the fill() function which now makes it possible to do vertical gradients in Pine. I use it for both channels displayed by this script.
• I use the new arguments for plot() 's `display` parameter to control where the script plots some of its values,
namely those I only want to appear in the script's status line and in the Data Window.
• I used my ta library for some of the oscillator calculations and helper functions.
• I also used TradingView's ta library for other oscillator calculations.
• I wrote my script using the revised recommendations in the Style Guide from the Pine v5 User Manual.
Position Tool█ OVERVIEW
This script is an interactive measurement tool that can be used to evaluate or keep track of trades. Like the long and short position drawing tools, it calculates a risk reward ratio and a risk-adjusted position size from the entry, stop and take profit levels, but it also does much more:
• It can be used to configure long or short trades.
• All monetary values can be expressed in any number of currencies.
• The value of tick/pip movement (which varies with the position's size) is displayed in the currency you have selected.
• The CAGR ( Compound Annual Growth Rate ) for the trade can be displayed.
• It does live tracking of the position.
• You can configure alerts on entries and exits.
█ HOW TO USE IT
Load the indicator on an active chart (see here if you don't know how).
When you first load this script on a chart, you will enter an interactive selection mode where the script asks you to pick three points in price and time on your chart by clicking on the chart. Directions will appear in a blue box at the bottom of the screen with each click of the mouse. The first selection is the entry point for the trade you are considering, which takes into account both the time and level you choose, the next are the take profit and stop levels. Once you have selected all three points, the script will draw trade zones and labels containing the trade metrics. The script determines if the trade is a long or short from the position of the take profit and stop loss levels in relation to the entry price. If the take profit level is above the entry price, the stop must be below and vice versa, otherwise an error occurs.
You can change levels by dragging the handles that appear when you select the indicator, or by entering new values in the script's settings. The only way to re-enter interactive mode is to re-add the indicator to your chart.
Once you place the position tool on a chart, it will appear at the same levels on all symbols you use. If your scale is not set to "Scale price chart only", the position tool's levels will be taken into account when scaling the chart, which can cause the symbol's bars to be compressed. If your scale is set to "Scale price chart only", the position tool will still be there, but it will not impact the scale of the chart's bars, so you won't see it if it sits outside the symbol's price scale.
If you select the position tool on your chart and delete it, this will also delete the indicator from the chart. You will need to re-add it if you want to draw another position tool. You can add multiple instances of the indicator if you need a position tool on more than one of your charts.
█ FEATURES
Display
The position tool displays the following information for entries:
• The entry's price level with an '@' sign before it.
• Open or Closed P&L : For an open trade, the "Open P&L" displays the difference in money value between the entry level and the chart's current price.
For a closed trade, the "Closed P&L" displays the realized P&L on the trade.
• Quantity : The trade size, which takes into account the risk tolerance you set in the script's settings.
• RR : The reward to risk ratio expresses the relationship of the distance between the entry and the take profit level vs the entry and the stop level.
Example: A $100 stop with a $100 target will have a ratio of 1:1, whereas a $200 target with the same stop will have a 2:1 ratio.
• Per tick/pip : Represents the money value of a tick or pip movement.
• CAGR : The Compound Annual Growth Rate will be displayed on the main order label on trades that exceed one day in duration.
This value is calculated the same way as in our CAGR Custom Range indicator.
If the trade duration is less than one day, the metric will not be present in the display.
The stop and take profit levels display:
• Their price level with an '@' sign before it.
• Their distance from the entry in money value, percentage and ticks/pips.
• The projected end money value of the position if the level is reached. These values are calculated based on the trade size and the currency.
Currency adjustments
This indicator modifies the trade label's colors and values based on the final Profit and Loss (P&L), which considers the dynamic exchange rate between base and conversion currencies in its calculations when the conversion currency is a specified value other than the default. Depending on the cross rate between the base and account currencies, this process can yield a negative P&L on an otherwise successful simulated trade.
For instance, if your account is in currency XYZ, you might buy 10 Apple shares at $150 each, with the XYZ to USD exchange rate being 2:1. This purchase would cost you 3000 units of XYZ. Suppose that later on, the shares appreciate to $170 each, and you decide to sell. One might expect this trade to result in profit. However, if the exchange rate has now equalized to 1:1, the return on selling the shares, calculated in XYZ, would only be 1700 units, resulting in a loss of 1300 units XYZ.
The indicator will mark the P&L and the target labels in red in such cases, regardless of whether the market price reached the profit target, as the trade produced a net loss due to reduced funds after currency conversion. Conversely, an otherwise unsuccessful position can result in a net profit in the account currency due to conversion rate fluctuations. The final losses or gains appear in the label metrics, and the corresponding color coding reflects the trade's success or failure.
Settings
The settings in the "Trade sizing" section are used to calculate the position size and the monetary value of trades. Two types of risk can be chosen from the menu; a percentage based risk calculation, or a fixed money value. The risk is used to calculate the quantity of units to purchase to achieve that level of risk exposure. Example: An account size of $1000 and 10% risk will have a projected end amount of $900 if the stop loss is hit. The quantity is a product of this relationship; a projected number of units to allow for the equivalent of $100 of risk exposure over the change in price from the entry to the stop value.
The "Trade levels" allow you to manually set the entry, take profit and stop levels of an existing position tool on your chart.
You can control the appearance of the tool and the values it displays in the settings following these first two sections.
Alerts
Three alerts that will trigger when you configure an alert on this indicator. The first will send an alert when the entry price is breached by price action if that price has not already been breached in the previous price history. This is dependant on the entry location you select when placing the indicator on the chart. The other two alerts will trigger when either the stop loss or the take profit level is breached to signal that a trade exit has occurred.
█ NOTES FOR Pine Script™ CODERS
• Interactive inputs are implemented for input.time() and input.price() . These specialized input functions allow users to interact with a script.
You can create one interactive input for both time and price values by using the same `inline` argument in a pair of input.time() and input.price() function calls.
• We use the `cagr()` function from our ta library.
• The script uses the runtime.error() function to throw an error if the stop and limit prices are not placed on opposing sides of the entry price.
• We use the `currency` parameter in a request.security() call to convert currencies.
Look first. Then leap.
Ichimoku Cloud MasterIchimoku Cloud Master aims to provide the ichimoku trader with easy alert functionality to not miss out on valuable trade setups. The key purpose of this script is to better visualise crucial moments in Ichimoku trading. These alerts should not be used for botting in my opinion as they always need a human to confirm the ichimoku market structure. For example, is the Kijun-Sen flat and too far away from price? A good ichimoku trader will not enter at such a point in time.
Explanation of script:
Chikou(lagging span): pink line, this is price plotted 26 bars ago. People ignore the power of this it is crucial to see how chikou behaves towards past price action as seen in the chart below where we got an entry at red arrow because chikou bounced from past fractal bottom.
Kijun-Sen(base line): Black line or color coded line. This is the equilibrium of last 26 candles. To me this is the most important line in the system as it attracts price.
Kijun = (Highest high of 26 periods + Lowest low of 26 periods) ÷ 2
Tenkan-Sen(conversion line): Blue line. This is the equilibrium of last 9 candles. In a strong uptrend price stays above this line.
Tenkan = (Highest high of 9 periods + Lowest low of 9 periods) ÷ 2
Senkou A (Leading span A)= Pink cloud line, this is the average of the 2 components projected 26 bars in the future.
Senkou A = (Tenkan + Kijun) ÷ 2
Senkou B (Leading span B) = Green cloud line, this is the 52 day equilibrium projected 26 bars in the future.
Senkou B = (Highest high of prior 52 periods + Lowest low of prior 52 periods) ÷ 2
Notice how the distance between Chikou and the cloud is also 52 bars. This is all part of Hosoda's numbers which I am not going to explain here.
Fractals: These are the black triangles you find at key turning point. If you want to know how they work reseach williams fractals. I've used fractals with a period of 9 as it is an ichimoku number. These fractals are useful when working with ichimoku wave theory. Again I will not explain that here but in further education
Fractal Support: Ability to extend lines from the fractals which can be used as an entry/exit mechanism in your trading. For example wait for tenkan to cross kijun and then enter on fractal breakout.
Signals:
Crossing of Chikou (lagging span) with past Kijun-Sen: this will color code the Bars / Kijun-Sen (you can turn this off in options)
The script also has a signal for this, this will be the green and purple diamonds. Where green is bullish and purple is bearish.
wy is this important?
When current price plotted 26 candles back (chikou) crosses over the past equilibrium (kijun-sen) this usualy means price has moved past resistance levels where sellers come in. This indicates a switch in market structure and price is bullish from this point, this is the same in the other direction.
Kumo Twist: when the kumo cloud (future) has a crossover from for example green to red (bull to bear). The script plots these using the colored cross symbols as seen in the picture above. A chikou cross + a Kumo twist at same bar of next to eachother below the cloud can be a great entry sign: this would be an entry after cross in the chart above.
Kijun Bounce: when in an uptrend the price retraces back to Kijun-Sen and starts to go back up. These are marked by the yellow circles as seen in chart below:
low below Kijun-Sen and close above it
Strong Trend: when Tenkan is above Kijun, price above cloud, future cloud green, chikou above close, chikou above Kijun we establish a strong bullish trend. For bearish the exact opposite. The script has a function to send an alert at the start of such trends and to plot them with small colored circles above the bars.
Customisation:
I've added options to disable specific aspects of the indicator for those traders who do not want to use all aspects of the indicator. In the customisation tab I've given each part a clear title so you can use your own colors/shapes.
The perfect entry?
Further info:
Look into my education pane, I will be adding education in the future. The chance of me making a more advanced version of the script including line forecasting etc is rather high so watch out for that.
For those who want to master this system I recommend reading the book:
How to make money with the ichimoku system by Balkrishna M. Sadekar
Or the originals books by Hosoda the inventor of Ichimoku if you can get your hands on them and can read Japanese.
Almost all info about the ichimoku system you find on the internet will lose you money because they reduce the system to simple signals that do not generate money.
I will be providing educational material on tradingview using this indicator.
FULL MA Optimization ScriptHello!
This script measures the performance of 10 moving averages and compares them!
Crossover and crossunders are both tested.
The tested moving averages include: TEMA, DEMA, EMA, SMA, ALMA, HMA, T3 Average, WMA, VWMA, LSMA.
You can select the length of the moving averages and the data source (I.E, close, open, ohlc4, etc.) and the script will calculate your selections!
For instance, if you select a length of 32 and a source of ohlc4 for crossovers, the script will assign the ten moving averages that length and data source and compare the performance for ohlc4 crossovers of the 32TEMA, 32DEMA, 32SMA, 32WMA, etc. If you select crossunder, the script will calculate the performance of ohlc4 crossunders of the same moving average lengths.
Moving average performances are listed in descending order (best to worst) and are categorized by tier: Upper-Tier, Mid-Tier, Lower-Tier. The Upper-Tier displays the three best performing averages relative to the MA length and data source, for the asset on the relevant chart timeframe. The Lower-Tier displays the three worst performing averages. The Mid-Tier displays the moving averages whose performance did not achieve a top three spot or a bottom three spot.
Also calculated is the moving average which achieved the highest cumulative gain/loss and the lowest cumulative gain/loss. Any asset and timeframe can be tested; the script recalculates relative to the chart timeframe. I added a "Benchmark Moving Average" free parameter and a "Custom Moving Average" free parameter. The two operate identically; you can set the length and data source of both for quick and simple comparison between differing average lengths and sources.
If "Crossover" is selected, the "(X Candles)" displayed on the tables reflects the average number of sessions the data source remains above a moving average following a crossover. If "Crossunder" is selected, the "(X Candles)" reflects the average number of sessions the data source remains below the moving average following a crossunder.
If "Crossover" is selected, the listed "X%" reflects the average percentage gain/loss following a source crossover of a moving average up until the source crosses back under the moving average. If "Crossunder" is selected, the listed "X%" reflects the average percentage gain/loss following a source crossunder of a moving average up until the source crosses back over the moving average.
If "Crossover" is selected, the listed "X Crosses" reflects the number of instances in which the source crossed over a moving average. If "Crossunder" is selected, the listed "X Crosses" reflects the number of instances in which the source crossed under a moving average.
Additional tooltips and instructions are included should you access the user input menu.
The moving averages can be plotted as a gradient (highest priced MA to lowest priced MA) alongside the best performing moving average. The moving averages can be plotted in full color, light color alongside the best performing average, or not plotted.
This script improves upon a similar script I have released:
I decided not to update the previous script. The previous script calculates crossovers only and, due to being less code intensive, calculates much quicker. If a user is concerned only with price crossovers, not crossunders, the original script is a better option! It's faster, making it the preferable choice!
This script "FULL MA Optimization" calculates crossovers/crossunders and incorporates additional plot styles. I ran into trouble a few times where the script was too large to run on TV. This script is not "slow", I suppose; however, calculations and parameter modifications take a bit longer than the original script!
Coin Bureau BB/EMA/RSI IndicatorThis indicator was inspired by Coin Bureau's How To Spot The Crypto Top video. In the video, Coin Bureau uses Bollinger bands, 7-period EMA and RSI to look for early signs of a top, thus presenting an opportunity to sell.
Using the basic principles found in the video, I've made a tentative indicator as a way to visualise all 3 indicators at once. Alerts will only fire when all 3 criteria are met:
Price closes outside 20-period Bollinger bands
Price closes ~2sd away from 7-period EMA
RSI is overbought or oversold
The indicator will also update in real-time and show when 1, 2 or all 3 conditions are satisfied. Additionally, there is built-in functionality to toggle historical/current alerts and users can set their own bounds for what constitutes a buy or sell alert.
This is just a personal project purely for edutainment purposes and should not be used to make financial decisions. This project is not affiliated with Coin Bureau.
Some caveats:
Using only 7 periods to calculate the standard deviation of price data will not lead to a statistically significant result, thus this figure may have no right being in the script. However, this was more to trial some techniques and to get acquainted with the pine scripting language.
As you can see, there are a lot of false positives. There are moments when the indicator flashes a sell alert only for the price to keep on rising. This is due to the specificity/sensitivity trade-off. The indicator has been tuned to give the optimal sensitivity (the more critical component). These are the best results I could find for this asset in this time frame.
neutronix community bot ML + Alerts 4h-daily (mod. capissimo)Gm traders,
i have been a python programmer for some years studying artificial intelligence for general purpose; after some time i finally decided to have a look at some finance related stuff and scripts.
Moved by curiosity i've decided to make some but decisive modifications to a script i tried to use initially but without success: the LVQ machine learning strategy.
So after studying the charts and indicators, i have rewritten this script made by Capissimo and added heavy filtering thanks to vwap and vwma, then fixed repaint and other issues.
I hope you enjoy it and that it could increase your possibilities of success in trading.
HOW TO USE THE SCRIPT
Add the script to 3h+ charts like for example BTC 4h, 6h, 8h, 12h, daily. (In order for it to work on shorter timeframes charts you can try to change to lookback window but i dont advise it).
Change only rsi and volfilter(volume filtering) settings to try to find the best winrate. Leave dataset to open. Fyi the winrate isn't 100% accurate but can give you a raw vision of final results.
Use alerts included for trading and and in options click on 'Once per bar'. If you have checked 'Reverse Signals' in the control panel you have got more 'risky' signals so be advised if trading futures and stocks.
Exit trade signals not provided, so it is recommended the use of take profits and stop loss (1.5:1 ratio)
As always, the script is for study purposes. Do not risk more than you can spend!
Original LVQ-based strategy made by capissimo
Modified by gravisxv 13/10/2021
3rd WaveHello All,
In Elliott Wave Theory, 3rd wave is not the shortest one in the waves 1/3/5 and it's usually longest one. so if we can catch it then we may get good opportunities to trade. This script finds 3rd wave experimentally. it can be also the 3rd waves in the waves 1, 3, 5, A and C. the 3rd wave should have greater volume than other waves, the script can check its volume and compare with the volumes of the waves 1 and 2 optionally.
Pine Team released Pine version 5! This script was developed in v5 and it uses Library feature of Pine v5 for the zigzag functions. This script is also an example for the Pine developers who learn Pine v5 and Libraries.
Options:
Zigzag Period: is the length that is used to calculate highest/lowest and the zigzag waves
Min/Max Retracements: is the retracement rates to check the wave 2 according to wave 1. for example; if min/max values are 0.500-0.618 then wave 2 must be minimum 0.500 of wave 1 and maximum 0.618 of wave 1.
Check Volume Support: is an option to compare the volumes of1. 2. and . waves. if you enable this option then the script checks their volume and 3rd wave volume must be greater then 1 and 2
there are 4 options for the targets. you can enable/disable and change their levels. targets are calculated using length of wave 1.
Options to show breakout zone, zigzag, wave 1 and 2.
and some options for the colors.
The Library that is used in this script:
P.S. This is an experimental work and can be improved. So do not hesitate to drop your comments under the script ;)
Enjoy!
[SCL] Significant Figures Example FunctionThis script consist of a single example function that takes a floating-point number - one that can, but doesn't have to, include a decimal point - and converts it to a floating-point number with only a certain number of significant digits left.
I'm not aware of another script that does this. There might well be a simpler way, in which case please do let me know.
For example, say you want to display a variable from your script to the user and it comes out to something like 45.366666666666666666666667 or whatever. That looks awful when you, for example, print it in a label.
Now, you could round it up to the nearest integer easily using a built-in function, or even to a certain number of decimal places using a reasonably simple custom function.
But that's a bit arbitrary. Suppose you don't know what asset the script will be used on, and so you can't predict what the price is, and what the value will turn out to be.
It could be 0.00045366666666666666666666667 instead. Now if you round it up to 3 decimal places it comes out as 0.000, which is useless.
My function will round that number to 0.0004536 instead, if told to do it to 4 significant digits.
You're free to use this function in your own scripts, including closed-source scripts, without asking permission. Credit to @SimpleCryptoLife would be appreciated.
RSI+PA+DCA StrategyDear Tradingview community,
This RSI based trading strategy is created as a training exercise. I am not a professional trader, but a committed hobbyist. This not a finished trading strategy meant for trading, but more a combination of different trading ideas I liked to explore deeper. The aim with this exercise was to gain more knowledge and understanding about price averaging and dollar cost averaging strategies. Aside that I wanted to learn how to program a pyramiding strategy, how to plot different order entry layers and how to open positions on a specific time interval.
In this script I adapted code from a couple of strategy examples by Coinrule . Who wrote simple and powerful examples of RSI based strategies and pyramiding strategies.
Also the HOWTO scripts shared by vitvlkv were very helpful for this exercise. In the script description you can find all the sources to the code.
A PA strategy could be a helpful addition to ease the 'stress-management to buy when price drops and resolution in selling when the price is rising' (Coinrule).
The idea behind the strategy is fairly simple and is based on an RSI strategy of buying low. A position is entered when the RSI and moving average conditions are met. The position is closed when it reaches a specified take profit percentage. As soon as the first the position is openend multiple PA (price average) layers are setup based on a specified percentage of price drop. When the price crosses the layer another position with somewhat the same amount of assets is entered. This causes the average cost price (the red plot line) to decrease. If the price drops more, another similar amount of assets is bought with another price average decrease as result. When the price starts rising again the different positions are separately closed when each reaches its specified take profit. The positions can be re-openend when the price drops again. And so on. When the price rises more and crosses over the average price and reached the specified take profit on top of it, it closes all the positions at once and cancels all orders. From that moment on it waits for another price dip before it opens a new position.
Another option is to activate a DCA function that opens a position based on a fixed specified amount. It enters a position at the start of every week and only when there are already other positions openend and if the current price is below the average price of the position. Like this buying on a time interval can help lowering the average price in case the market is down.
I read in some articles that price averaging is also called dollar cost averaging as the result is somewhat the same. Although DCA is really based on buying on fixed time intervals. These strategies are both considered long term investment strategies that can be profitable in the long run and are not suitable for short term investment schemes. The downturn is that the postion size increases when the general market trend is going down and that you have to patiently wait until the market start rising again.
Another notable aspect is that the logic in this strategy works the way it does because the entries are exited based on the FIFO (first in first out) close entry rule. This means that the first exit is applied to the first entry position that is openend. In other words that when the third entry reaches its take profit level and exits, it actually exits the first entry. If you take a close look in the 'List of Trades' of your Strategy Tester panel, you can see that some 'Long1' entries are closed by an 'Exit 3' and not by an 'Exit 1'. This means that your trade partly loses, but causes a decrease in average price that is later balanced out by lower or repeated entering and closing other positions. You can change this logic to a real sequential way of closing your entries, but this changes the averaging logic considerably. In case you want to test this you need to change, in this line in the strategy call 'close_entries_rule = "FIFO"', the word FIFO to ANY.
In the settings you can specify the percentage of portfolio to use for each trade to spread the risk and for each order a trading fee of 0.075% is calculated.
888 BOT #backtest█ 888 BOT #backtest (open source)
This is an Expert Advisor 'EA' or Automated trading script for ‘longs’ and ‘shorts’, which uses only a Take Profit or, in the worst case, a Stop Loss to close the trade.
It's a much improved version of the previous ‘Repanocha’. It doesn`t use 'Trailing Stop' or 'security()' functions (although using a security function doesn`t mean that the script repaints) and all signals are confirmed, therefore the script doesn`t repaint in alert mode and is accurate in backtest mode.
Apart from the previous indicators, some more and other functions have been added for Stop-Loss, re-entry and leverage.
It uses 8 indicators, (many of you already know what they are, but in case there is someone new), these are the following:
1. Jurik Moving Average
It's a moving average created by Mark Jurik for professionals which eliminates the 'lag' or delay of the signal. It's better than other moving averages like EMA , DEMA , AMA or T3.
There are two ways to decrease noise using JMA . Increasing the 'LENGTH' parameter will cause JMA to move more slowly and therefore reduce noise at the expense of adding 'lag'
The 'JMA LENGTH', 'PHASE' and 'POWER' parameters offer a way to select the optimal balance between 'lag' and over boost.
Green: Bullish , Red: Bearish .
2. Range filter
Created by Donovan Wall, its function is to filter or eliminate noise and to better determine the price trend in the short term.
First, a uniform average price range 'SAMPLING PERIOD' is calculated for the filter base and multiplied by a specific quantity 'RANGE MULTIPLIER'.
The filter is then calculated by adjusting price movements that do not exceed the specified range.
Finally, the target ranges are plotted to show the prices that will trigger the filter movement.
Green: Bullish , Red: Bearish .
3. Average Directional Index ( ADX Classic) and ( ADX Masanakamura)
It's an indicator designed by Welles Wilder to measure the strength and direction of the market trend. The price movement is strong when the ADX has a positive slope and is above a certain minimum level 'ADX THRESHOLD' and for a given period 'ADX LENGTH'.
The green color of the bars indicates that the trend is bullish and that the ADX is above the level established by the threshold.
The red color of the bars indicates that the trend is down and that the ADX is above the threshold level.
The orange color of the bars indicates that the price is not strong and will surely lateralize.
You can choose between the classic option and the one created by a certain 'Masanakamura'. The main difference between the two is that in the first it uses RMA () and in the second SMA () in its calculation.
4. Parabolic SAR
This indicator, also created by Welles Wilder, places points that help define a trend. The Parabolic SAR can follow the price above or below, the peculiarity that it offers is that when the price touches the indicator, it jumps to the other side of the price (if the Parabolic SAR was below the price it jumps up and vice versa) to a distance predetermined by the indicator. At this time the indicator continues to follow the price, reducing the distance with each candle until it is finally touched again by the price and the process starts again. This procedure explains the name of the indicator: the Parabolic SAR follows the price generating a characteristic parabolic shape, when the price touches it, stops and turns ( SAR is the acronym for 'stop and reverse'), giving rise to a new cycle. When the points are below the price, the trend is up, while the points above the price indicate a downward trend.
5. RSI with Volume
This indicator was created by LazyBear from the popular RSI .
The RSI is an oscillator-type indicator used in technical analysis and also created by Welles Wilder that shows the strength of the price by comparing individual movements up or down in successive closing prices.
LazyBear added a volume parameter that makes it more accurate to the market movement.
A good way to use RSI is by considering the 50 'RSI CENTER LINE' centerline. When the oscillator is above, the trend is bullish and when it is below, the trend is bearish .
6. Moving Average Convergence Divergence ( MACD ) and ( MAC-Z )
It was created by Gerald Appel. Subsequently, the histogram was added to anticipate the crossing of MA. Broadly speaking, we can say that the MACD is an oscillator consisting of two moving averages that rotate around the zero line. The MACD line is the difference between a short moving average 'MACD FAST MA LENGTH' and a long moving average 'MACD SLOW MA LENGTH'. It's an indicator that allows us to have a reference on the trend of the asset on which it is operating, thus generating market entry and exit signals.
We can talk about a bull market when the MACD histogram is above the zero line, along with the signal line, while we are talking about a bear market when the MACD histogram is below the zero line.
There is the option of using the MAC-Z indicator created by LazyBear, which according to its author is more effective, by using the parameter VWAP ( volume weighted average price ) 'Z-VWAP LENGTH' together with a standard deviation 'STDEV LENGTH' in its calculation.
7. Volume Condition
Volume indicates the number of participants in this war between bulls and bears, the more volume the more likely the price will move in favor of the trend. A low trading volume indicates a lower number of participants and interest in the instrument in question. Low volumes may reveal weakness behind a price movement.
With this condition, those signals whose volume is less than the volume SMA for a period 'SMA VOLUME LENGTH' multiplied by a factor 'VOLUME FACTOR' are filtered. In addition, it determines the leverage used, the more volume , the more participants, the more probability that the price will move in our favor, that is, we can use more leverage. The leverage in this script is determined by how many times the volume is above the SMA line.
The maximum leverage is 8.
8. Bollinger Bands
This indicator was created by John Bollinger and consists of three bands that are drawn superimposed on the price evolution graph.
The central band is a moving average, normally a simple moving average calculated with 20 periods is used. ('BB LENGTH' Number of periods of the moving average)
The upper band is calculated by adding the value of the simple moving average X times the standard deviation of the moving average. ('BB MULTIPLIER' Number of times the standard deviation of the moving average)
The lower band is calculated by subtracting the simple moving average X times the standard deviation of the moving average.
the band between the upper and lower bands contains, statistically, almost 90% of the possible price variations, which means that any movement of the price outside the bands has special relevance.
In practical terms, Bollinger bands behave as if they were an elastic band so that, if the price touches them, it has a high probability of bouncing.
Sometimes, after the entry order is filled, the price is returned to the opposite side. If price touch the Bollinger band in the same previous conditions, another order is filled in the same direction of the position to improve the average entry price, (% MINIMUM BETTER PRICE ': Minimum price for the re-entry to be executed and that is better than the price of the previous position in a given %) in this way we give the trade a chance that the Take Profit is executed before. The downside is that the position is doubled in size. 'ACTIVATE DIVIDE TP': Divide the size of the TP in half. More probability of the trade closing but less profit.
█ STOP LOSS and RISK MANAGEMENT.
A good risk management is what can make your equity go up or be liquidated.
The % risk is the percentage of our capital that we are willing to lose by operation. This is recommended to be between 1-5%.
% Risk: (% Stop Loss x % Equity per trade x Leverage) / 100
First the strategy is calculated with Stop Loss, then the risk per operation is determined and from there, the amount per operation is calculated and not vice versa.
In this script you can use a normal Stop Loss or one according to the ATR. Also activate the option to trigger it earlier if the risk percentage is reached. '% RISK ALLOWED'
'STOP LOSS CONFIRMED': The Stop Loss is only activated if the closing of the previous bar is in the loss limit condition. It's useful to prevent the SL from triggering when they do a ‘pump’ to sweep Stops and then return the price to the previous state.
█ BACKTEST
The objective of the Backtest is to evaluate the effectiveness of our strategy. A good Backtest is determined by some parameters such as:
- RECOVERY FACTOR: It consists of dividing the 'net profit' by the 'drawdown’. An excellent trading system has a recovery factor of 10 or more; that is, it generates 10 times more net profit than drawdown.
- PROFIT FACTOR: The ‘Profit Factor’ is another popular measure of system performance. It's as simple as dividing what win trades earn by what loser trades lose. If the strategy is profitable then by definition the 'Profit Factor' is going to be greater than 1. Strategies that are not profitable produce profit factors less than one. A good system has a profit factor of 2 or more. The good thing about the ‘Profit Factor’ is that it tells us what we are going to earn for each dollar we lose. A profit factor of 2.5 tells us that for every dollar we lose operating we will earn 2.5.
- SHARPE: (Return system - Return without risk) / Deviation of returns.
When the variations of gains and losses are very high, the deviation is very high and that leads to a very poor ‘Sharpe’ ratio. If the operations are very close to the average (little deviation) the result is a fairly high 'Sharpe' ratio. If a strategy has a 'Sharpe' ratio greater than 1 it is a good strategy. If it has a 'Sharpe' ratio greater than 2, it is excellent. If it has a ‘Sharpe’ ratio less than 1 then we don't know if it is good or bad, we have to look at other parameters.
- MATHEMATICAL EXPECTATION: (% winning trades X average profit) + (% losing trades X average loss).
To earn money with a Trading system, it is not necessary to win all the operations, what is really important is the final result of the operation. A Trading system has to have positive mathematical expectation as is the case with this script: ME = (0.87 x 30.74$) - (0.13 x 56.16$) = (26.74 - 7.30) = 19.44$ > 0
The game of roulette, for example, has negative mathematical expectation for the player, it can have positive winning streaks, but in the long term, if you continue playing you will end up losing, and casinos know this very well.
PARAMETERS
'BACKTEST DAYS': Number of days back of historical data for the calculation of the Backtest.
'ENTRY TYPE': For '% EQUITY' if you have $ 10,000 of capital and select 7.5%, for example, your entry would be $ 750 without leverage. If you select CONTRACTS for the 'BTCUSDT' pair, for example, it would be the amount in 'Bitcoins' and if you select 'CASH' it would be the amount in $ dollars.
'QUANTITY (LEVERAGE 1X)': The amount for an entry with X1 leverage according to the previous section.
'MAXIMUM LEVERAGE': It's the maximum allowed multiplier of the quantity entered in the previous section according to the volume condition.
The settings are for Bitcoin at Binance Futures (BTC: USDTPERP) in 15 minutes.
For other pairs and other timeframes, the settings have to be adjusted again. And within a month, the settings will be different because we all know the market and the trend are changing.
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!
Filter Information Box - PineCoders FAQWhen designing filters it can be interesting to have information about their characteristics, which can be obtained from the set of filter coefficients (weights). The following script analyzes the impulse response of a filter in order to return the following information:
Lag
Smoothness via the Herfindahl index
Percentage Overshoot
Percentage Of Positive Weights
The script also attempts to determine the type of the analyzed filter, and will issue warnings when the filter shows signs of unwanted behavior.
DISPLAYED INFORMATION AND METHODS
The script displays one box on the chart containing two sections. The filter metrics section displays the following information:
- Lag : Measured in bars and calculated from the convolution between the filter's impulse response and a linearly increasing sequence of value 0,1,2,3... . This sequence resets when the impulse response crosses under/over 0.
- Herfindahl index : A measure of the filter's smoothness described by Valeriy Zakamulin. The Herfindahl index measures the concentration of the filter weights by summing the squared filter weights, with lower values suggesting a smoother filter. With normalized weights the minimum value of the Herfindahl index for low-pass filters is 1/N where N is the filter length.
- Percentage Overshoot : Defined as the maximum value of the filter step response, minus 1 multiplied by 100. Larger values suggest higher overshoots.
- Percentage Positive Weights : Percentage of filter weights greater than 0.
Each of these calculations is based on the filter's impulse response, with the impulse position controlled by the Impulse Position setting (its default is 1000). Make sure the number of inputs the filter uses is smaller than Impulse Position and that the number of bars on the chart is also greater than Impulse Position . In order for these metrics to be as accurate as possible, make sure the filter weights add up to 1 for low-pass and band-stop filters, and 0 for high-pass and band-pass filters.
The comments section displays information related to the type of filter analyzed. The detection algorithm is based on the metrics described above. The script can detect the following type of filters:
All-Pass
Low-Pass
High-Pass
Band-Pass
Band-Stop
It is assumed that the user is analyzing one of these types of filters. The comments box also displays various warnings. For example, a warning will be displayed when a low-pass/band-stop filter has a non-unity pass-band, and another is displayed if the filter overshoot is considered too important.
HOW TO SET THE SCRIPT UP
In order to use this script, the user must first enter the filter settings in the section provided for this purpose in the top section of the script. The filter to be analyzed must then be entered into the:
f(input)
function, where `input` is the filter's input source. By default, this function is a simple moving average of period length . Be sure to remove it.
If, for example, we wanted to analyze a Blackman filter, we would enter the following:
f(input)=>
pi = 3.14159,sum = 0.,sumw = 0.
for i = 0 to length-1
k = i/length
w = 0.42 - 0.5 * cos(2 * pi * k) + 0.08 * cos(4 * pi * k)
sumw := sumw + w
sum := sum + w*input
sum/sumw
EXAMPLES
In this section we will look at the information given by the script using various filters. The first filter we will showcase is the linearly weighted moving average (WMA) of period 9.
As we can see, its lag is 2.6667, which is indeed correct as the closed form of the lag of the WMA is equal to (period-1)/3 , which for period 9 gives (9-1)/3 which is approximately equal to 2.6667. The WMA does not have overshoots, this is shown by the the percentage overshoot value being equal to 0%. Finally, the percentage of positive weights is 100%, as the WMA does not possess negative weights.
Lets now analyze the Hull moving average of period 9. This moving average aims to provide a low-lag response.
Here we can see how the lag is way lower than that of the WMA. We can also see that the Herfindahl index is higher which indicates the WMA is smoother than the HMA. In order to reduce lag the HMA use negative weights, here 55% (as there are 45% of positive ones). The use of negative weights creates overshoots, we can see with the percentage overshoot being 26.6667%.
The WMA and HMA are both low-pass filters. In both cases the script correctly detected this information. Let's now analyze a simple high-pass filter, calculated as follows:
input - sma(input,length)
Most weights of a high-pass filters are negative, which is why the lag value is negative. This would suggest the indicator is able to predict future input values, which of course is not possible. In the case of high-pass filters, the Herfindahl index is greater than 0.5 and converges toward 1, with higher values of length . The comment box correctly detected the type of filter we were using.
Let's now test the script using the simple center of gravity bandpass filter calculated as follows:
wma(input,length) - sma(input,length)
The script correctly detected the type of filter we are using. Another type of filter that the script can detect is band-stop filters. A simple band-stop filter can be made as follows:
input - (wma(input,length) - sma(input,length))
The script correctly detect the type of filter. Like high-pass filters the Herfindahl index is greater than 0.5 and converges toward 1, with greater values of length . Finally the script can detect all-pass filters, which are filters that do not change the frequency content of the input.
WARNING COMMENTS
The script can give warning when certain filter characteristics are detected. One of them is non-unity pass-band for low-pass filters. This warning comment is displayed when the weights of the filter do not add up to 1. As an example, let's use the following function as a filter:
sum(input,length)
Here the filter pass-band has non unity, and the sum of the weights is equal to length . Therefore the script would display the following comments:
We can also see how the metrics go wild (note that no filter type is detected, as the detected filter could be of the wrong type). The comment mentioning the detection of high overshoot appears when the percentage overshoot is greater than 50%. For example if we use the following filter:
5*wma(input,length) - 4*sma(input,length)
The script would display the following comment:
We can indeed see high overshoots from the filter:
@alexgrover for PineCoders
Look first. Then leap.
TTM Squeeze Scanner This script scans for TTM Squeezes for the crypto symbols included in the body of the script. The timeframe for the squeeze scan is controlled within the input not the chart.
This script is a merge of @Nico.Muselle's TTM Squeeze script and @QuantNomad's custom screener script. Thanks to both of them!
INFLECTION NEXUS - SPAINFLECTION NEXUS - SPA (Shadow Portfolio Adaptive)
Foreword: The Living Algorithm
For decades, technical analysis has been a conversation between a trader and a static chart. We apply our indicators with their fixed-length inputs, and we hope that our rigid tools can somehow capture the essence of a market that is fluid, chaotic, and perpetually evolving. When our tools fail, we are told to "adapt." But what if the tools themselves could learn that lesson? What if our indicators could adapt not just for us, but with us?
This script, INFLECTION NEXUS - SPA, is the realization of that vision. It is an advanced analytical framework built around a revolutionary core: the Shadow Portfolio Adaptive (SPA) Engine . The buy and sell signals you see on the chart are an evolution of the logic from my previous work, "Turning Point." However, this is not a simple combination of two scripts. The SPA engine so fundamentally transforms the nature of the analysis that it creates an entirely new class of indicator. This publication is a showcase of that groundbreaking, self-learning engine.
This system is undeniably complex. When you first load it, the sheer volume of information may feel overwhelming. That is a testament to the depth of its analysis. This guide is designed to be your comprehensive manual, to break down every single component, every color, every number, into simple, understandable concepts. By the end of this document, you will not only master its functions but will also possess a deeper understanding of the market dynamics it is designed to reveal.
Chapter 1: The Paradigm Shift - Why the SPA Engine is a Leap Forward
To grasp the innovation here, we must first deconstruct the severe limitations of traditional "adaptive" indicators.
Part A: The Traditional Model - Driving by the Rear-View Mirror
Conventional "adaptive" systems are fundamentally reactive. They operate on a slow, inefficient loop: they wait for their own specific, biased signal to fire, wait for that trade to close, and only after a long and statistically significant "warm-up" period of 50-100 trades do they finally make a small, retrospective adjustment. They are always adapting to a market that no longer exists.
Part B: The SPA Model - The Proactive Co-Pilot
The Shadow Portfolio Adaptive (SPA) engine is a complete re-imagining of this process. It is not reactive; it is proactive, data-saturated, and instantly aware.
Continuous, Unbiased Learning: The SPA engine does not wait for a signal to learn. Its Shadow Portfolio is constantly running 5-bar long and short trades in the background. It learns from every single 5-bar slice of market action , giving it a continuous, unbiased stream of performance data. It is the difference between reading a textbook chapter and having a live sparring partner in the ring 24/7.
Instantaneous Market Awareness - The End of the "Warm-Up": This is the critical innovation. The SPA engine does not require a 100-trade warm-up period. The learning does not start after 50 trades; it begins on the 6th bar of the chart when the first shadow trade closes. From that moment on, the system is market-aware, analyzing data, and capable of making intelligent adjustments. The SPA engine is not adapting to old wins and losses. It is adapting, in near real-time, to the market's ever-shifting character, volatility, and personality.
Chapter 2: The Anatomy of the SPA Engine - A Granular Deep Dive
The engine is composed of three primary systems that work in a sophisticated, interconnected symphony.
Section 1: The Shadow Portfolio (The Information Harvester)
What it is, Simply: Think of this as the script's eyes and ears. It's a team of 10 virtual traders (5 long, 5 short) who are constantly taking small, quick trades to feel out the market.
How it Works, Simply: On every new bar, a new "long" trader and a new "short" trader enter the market. Exactly 5 bars later, they close their positions. This cycle is perpetual and relentless.
The Critical 'Why': Because these virtual traders enter and exit based on a fixed time (5 bars), not on a "good" or "bad" signal, their results are completely unbiased . They are simply measuring: "What happened to price over the last 5 bars?" This provides the raw, untainted truth about the market's behavior that the rest of the system needs to learn effectively.
The Golden Metric (ATR Normalization): The engine doesn't just look at dollar P&L. It's smarter than that. It asks a more intelligent question: "How much did this trade make relative to the current volatility?"
Analogy: Imagine a flea and an elephant. If they both jump 1 inch, who is more impressive? The flea. The SPA engine understands this. A $10 profit when the market is dead quiet is far more significant than a $10 profit during a wild, volatile swing.
The Formula: realized_atr = (close - trade.entry) / trade.atr_entry. It takes the raw profit and divides it by the Average True Range (a measure of volatility) at the moment of entry. This gives a pure, "apples-to-apples" score for every single trade, which is the foundational data point for all learning.
Section 2: The Cognitive Map (The Long-Term Brain)
What it is, Simply: This is the engine's deep memory, its library of experiences. Imagine a giant, 64-square chessboard (8x8 grid). Each square on the board represents a very specific type of market environment.
The Two Dimensions of Thought (The 'How'): How does it know which square we are on? It looks at two things:
The Market's Personality (X-Axis): Is the market behaving like a disciplined soldier, marching in a clear trend? Or is it like a chaotic, unpredictable child, running all over the place? The engine calculates a "Regime" score to figure this out.
The Market's Energy Level (Y-Axis): Is the market sleepy and quiet, or is it wide-awake and hyperactive? The engine measures "Normalized Volatility" to determine this.
The Power of Generalization (The 'Why'): When a Shadow Portfolio trade closes, its result is recorded in the corresponding square on the chessboard. But here's the clever part: it also shares a little bit of that lesson with the squares immediately next to it (using a Gaussian Kernel).
Analogy: If you touch a hot stove and learn "don't touch," your brain is smart enough to know you probably shouldn't touch the hot oven door next to it either, even if you haven't touched it directly. The Cognitive Map does the same thing, allowing it to make intelligent inferences even in market conditions it has seen less frequently. Each square remembers what indicator settings worked best in that specific environment.
Section 3: The Adaptive Engine (The Central Nervous System)
What it is, Simply: This is the conductor of the orchestra. It takes information from all other parts of the system and decides exactly what to do.
The Symphony of Inputs: It listens to three distinct sources of information before making a decision:
The Short-Term Memory (Rolling Stats): It looks at the performance of the last rollN shadow trades. This is its immediate, recent experience.
The Long-Term Wisdom (Cognitive Map): It consults the grand library of the Cognitive Map to see what has worked best in the current market type over the long haul.
The Gut Instinct (Bin Learning): It keeps a small "mini-batch" of the most recent trades. If this batch shows a very strong, sudden pattern, it can trigger a rapid, reflexive adjustment, like pulling your hand away from a flame.
The Fusion Process: It then blends these three opinions together in a sophisticated way. It gives more weight to the opinions it's more confident in (e.g., a Cognitive Map square with hundreds of trades of experience) and uses your Adaptation Intensity (dialK) input to decide how much to listen to its "gut instinct." The final decision is then smoothed to ensure the indicator's parameters change in a stable, intelligent way.
Chapter 3: The Control Panel - A Novice's Guide to Every Input
This is the most important chapter. Let's break down what these confusing settings actually do in the simplest terms possible.
--- SECTION 1: THE DRIVER'S SEAT (SIGNAL ENGINE & BASE SETTINGS) ---
🧾 Signal Engine (Turning Point):
What it is: These are the rules for the final BUY and SELL signs.
Think of it like this: The SPA engine is the smart robot that tunes your race car. These settings are you, the driver, telling the robot what kind of race you're in.
Enable Reversal Mode: You tell the robot, "I want to race on a curvy track with lots of turns." The robot will tune the car to be agile for catching tops and bottoms.
Enable Breakout Mode: You tell the robot, "I want to race on a long, straight track." The robot will tune the car for pure speed to follow the trend.
Require New Extreme: This is a quality filter. It tells the driver, "Don't look for a turn unless we've just hit a new top speed on the straightaway." It makes sure the reversal is from a real extreme.
Min Bars Between Signals: This is the "pit stop" rule. You're telling the robot, "After you show me a sign, wait at least 10 bars before showing another one, so I don't get confused."
⚡ ATR Bands (Base Inputs):
What they are: These are the starting settings for your car before the robot starts tuning it. These are your factory defaults.
Sensitivity: This is the "Bump Detector." A low number means the car feels every tiny pebble on the road. A high number means it only notices the big speed bumps. You want to set it so it notices the important bumps (real market structure) but ignores the pebbles (noise).
ATR Period & Multiplier: These set the starting size of the "safety lane" (the green and blue bands) around your car. The robot's main job is to constantly adjust the size of this safety lane to perfectly fit the current road conditions.
📊 & 📈 Filter Settings (RSI & Volume):
What they are: These are your co-pilot's confirmation checks.
Enable RSI Filter: Your co-pilot will check the "Engine Temperature" (RSI). He won't let you hit the gas (BUY) if the engine is already overheating (overbought).
RSI Length & Lookbacks: These tune how your co-pilot's temperature gauge works. The defaults are standard.
Require Volume Spike: Your co-pilot will check the "Crowd Noise" (Volume). He won't give you a signal unless he hears the crowd roar, confirming that a lot of people are interested in this move.
🎯 Signal Quality Control:
Enable Major Levels Only: This tells your co-pilot to be extra picky. He will only confirm signals that happen after a huge, powerful move, ignoring all the small stuff.
--- SECTION 2: THE ROBOT'S BRAIN (ENGINE & LEARNING CONTROLS) ---
🎛️ Master Control:
Adaptation Intensity (dialK): THIS IS THE ROBOT'S PERSONALITY DIAL.
Turn it DOWN (1-5): The robot becomes a "Wise Old Professor." It thinks very slowly and carefully, gathers lots of data, and only makes a change when it is 100% sure. Its advice is very reliable but might come a little late.
Turn it UP (15-20): The robot becomes a "Hyper-Reactive Teenager." It has a short attention span, reacts instantly to everything it sees, and changes its mind constantly. It's super-fast to new information but might get faked out a lot.
The Default (10): A "Skilled Professional." The perfect balance of thoughtful and responsive. Start here.
🧠 Adaptive Engine:
Enable Adaptive System: This is the main power button for your robot. Turn it off, and you're driving a normal, non-smart car. Turn it on, and the robot takes over the tuning.
Use Shadow Cycle: This turns on the robot's "practice laps." The robot can't learn without practicing. This must be on for the robot to work.
Lock ATR Bands: This is a visual choice. "Locked" means the safety lanes on your screen stay where your factory defaults put them (the robot still makes changes to the signals in the background). "Unlocked" means you see the safety lanes moving and changing shape in real-time as the robot tunes them.
🎯 Learning (Global + Risk):
What they are: These are the deep-level settings for how your robot's brain processes information.
Rolling Window Size: This is the robot's "Short-Term Memory." How many of the last few practice laps should it remember? A small number means it only cares about what just happened. A big number means it remembers the last hour of practice.
Learn Rate & Smooth Alpha: This is "How big of a change should the robot make?" and "How smoothly should it make the change?" Think of it as turning the steering wheel. A high learn rate is like yanking the wheel; a low one is like a gentle turn. The smoothing makes sure the turn is graceful.
WinRate Thresholds & PnL Cap: These are rules for the robot's learning. They tell it what a "good" or "bad" outcome looks like and tell it to ignore crazy, once-in-a-lifetime events so its memory doesn't get corrupted.
--- SECTION 3: THE GARAGE (RISK, MEMORY & VISUALS) ---
⚠️ Risk Management:
What they are: These are safety rules you can give to your co-pilot for your own awareness. They appear on the dashboard.
The settings: You can set a max number of trades, a max loss for the day, and a "time out" period after a few losses.
Apply Risk to Shadow: This is an important switch. If you turn this ON, your safety rules also apply to the robot's practice laps. If you hit your max loss, the robot stops practicing and learning. It's recommended to leave this OFF so the robot can learn 24/7, even if you have stopped trading.
🗺️ Cognitive Map, STM & Checkpoints:
What it is: The robot's "Long-Term Memory" or its entire library of racing experience.
Use Cognitive Map & STM: These switches turn on the long-term and short-term memory banks. You want these on for the smartest robot.
Map Settings (Grid, Sigma, Half-Life): These are very advanced settings for neuroscientists. They control how the robot's brain is structured and how it forgets old information. The defaults are expertly tuned.
The Checkpoint System: This is the "Save Your Game" button for the robot.
To Save: Check Emit Checkpoint Now. Go to your alert log, and you will see a very long password. Copy this password.
To Load: Paste that password into the Memory Checkpoint box. Then, check Apply Checkpoint On Next Bar. The robot will instantly download all of its saved memories and experience.
🎨 Visuals & 🧩 Display Params:
What they are: These are all about how your screen looks.
You can control everything: The size and shape of the little diamonds (Entry Orbs), whether you see the purple Adapt Pulse, and where the Dashboards appear on your screen. You can change the Theme to Dark, Light, or Neon. These settings don't change how the robot thinks, only how it presents its information to you.
Chapter 4: The Command Center - Decoding the Dashboard
PANEL A (INFLECTION NEXUS): Your high-level mission control, showing the engine's classification of the current Market Context and the performance summary of the Shadow Portfolio.
PANEL B (SHADOW PORTFOLIO ADAPTIVE): Your deep diagnostic screen.
Performance Metrics: View advanced risk-adjusted stats like the Sharpe Ratio to understand the quality of the market movements the engine is learning from.
Adaptive Parameters (Live vs Base): THIS IS THE MOST CRITICAL SECTION. It shows the engine's Live parameters right next to your (Base) inputs. When the Live values deviate, the engine is communicating its learned wisdom to you. For example, a Live ATR Multiplier of 2.5 versus your Base of 1.4 is the engine telling you: "Caution. The market is currently experiencing high fake-outs and requires giving positions more room to breathe." This section is a direct translation of the engine's learning into actionable insight.
Chapter 5: Reading the Canvas - On-Chart Visuals
The Bands (Green/Blue Lines): These are not static Supertrend lines. They are the physical manifestation of the engine's current thinking. As the engine learns and adapts its ATR Period and Multiplier, you will see these bands widen, tighten, and adjust their distance from price. They are alive.
The Labels (BUY/SELL): These are the final output of the "Turning Point" logic, now supercharged and informed by the fully adaptive SPA engine.
The Purple Pulse (Dot and Background Glow): This is your visual cue that the engine is "thinking." Every time you see this pulse, it means the SPA has just completed a learning cycle and updated its parameters. It is actively recalibrating itself to the market.
Chapter 6: A Manifesto on Innovation and Community
I want to conclude with a personal note on why I dedicate countless hours to building systems like this and sharing them openly.
My purpose is to drive innovation, period. I am not in this space to follow the crowd or to re-package old ideas. The world does not need a 100th version of a slightly modified MACD. Real progress, real breakthroughs, come from venturing into the wilderness, from asking "what if?" and from pursuing concepts that lie at the very edge of possibility.
I am not afraid of being wrong. I am not afraid of being bested by my peers. In fact, I welcome it. If another developer takes an idea from this engine, improves it, and builds something even more magnificent, that is a profound win for our entire community. The only failure I recognize is the failure to try. The only trap I fear is the creative complacency of producing sterile, recycled work just to appease the status quo.
I love this community, and I believe with every fiber of my being that we have barely scratched the surface of what can be discovered and created. This script is my contribution to that shared journey. It is a tool, an idea, and a challenge to all of us: let's keep pushing.
DISCLAIMER: This script is an advanced analytical tool provided for educational and research purposes ONLY. It does not constitute financial advice. All trading involves substantial risk of loss. Past performance is not indicative of future results. Please use this tool responsibly and as part of a comprehensive trading plan.
As the great computer scientist Herbert A. Simon, a pioneer of artificial intelligence, famously said:
"Learning is any process by which a system improves performance from experience."
*Tooltips were updated with a comprehensive guide
May this engine enhance your experience.
— Dskyz, for DAFE Trading Systems
Dual Best MA Strategy AnalyzerDual Best MA Strategy Analyzer (Lookback Window)
What it does
This indicator scans a range of moving-average lengths and finds the single best MA for long crossovers and the single best MA for short crossunders over a fixed lookback window. It then plots those two “winner” MAs on your chart:
Best Long MA (green): The MA length that would have made the highest total profit using a simple “price crosses above MA → long; exit on cross back below” logic.
Best Short MA (red): The MA length that would have made the highest total profit using “price crosses below MA → short; exit on cross back above.”
You can switch between SMA and EMA, set the min/max length, choose a step size, and define the lookback window used for evaluation.
How it works (brief)
For each candidate MA length between Min MA Length and Max MA Length (stepping by Step Size), the script:
Builds the MA (SMA or EMA).
Simulates a naïve crossover strategy over the last Lookback Window candles:
Long model: enter on crossover, exit on crossunder.
Short model: enter on crossunder, exit on crossover.
Sums simple P&L in price units (no compounding, no fees/slippage).
Picks the best long and best short lengths by total P&L and plots those two MAs.
Note: Long and short are evaluated independently. The script plots MAs only; it doesn’t open positions.
Inputs
Min MA Length / Max MA Length – Bounds for MA search.
Step Size – Spacing between tested lengths (e.g., 10 tests 10, 20, 30…).
Use EMA instead of SMA – Toggle average type.
Lookback Window (candles) – Number of bars used to score each MA. Needs enough history to be meaningful.
What the plots mean
Best Long MA (green): If price crosses above this line (historically), that MA length produced the best long-side results over the lookback.
Best Short MA (red): If price crosses below this line (historically), that MA length produced the best short-side results.
These lines can change over time as new bars enter the lookback window. Think of them as adaptive “what worked best recently” guides, not fixed signals.
Practical tips
Timeframe matters: Run it on the timeframe you trade; the “best” length on 1h won’t match 1m or 1D.
Step size trade-off: Smaller steps = more precision but heavier compute. Larger steps = faster scans, coarser choices.
Use with confirmation: Combine with structure, volume, or volatility filters. This is a single-factor tester.
Normalization: P&L is in raw price units. For cross-symbol comparison, consider using one symbol at a time (or adapt the script to percent P&L).
Limitations & assumptions
No fees, funding, slippage, or position sizing.
Simple “in/out” on the next crossover; no stops/targets/filters.
Results rely on lookback choice and will repaint historically as the “best” length is re-selected with new data (the plot is adaptive, not forward-fixed).
The script tests up to ~101 candidates internally (bounded by your min/max/step).
Good uses
Quickly discover a recently effective MA length for trend following.
Compare SMA vs EMA performance on your market/timeframe.
Build a playbook: note which lengths tend to win in certain regimes (trending vs choppy).
Not included (by design)
Alerts, entries/exits, or a full strategy report. It’s an analyzer/overlay.
If you want alerts, you can add simple conditions like:
ta.crossover(close, plotLongMA) for potential long interest
ta.crossunder(close, plotShortMA) for potential short interest
Changelog / Notes
v1: Initial release. Array-based scanner, SMA/EMA toggle, adaptive long/short best MA plots, user-set lookback.
Disclaimer
This is educational tooling, not financial advice. Test thoroughly and use proper risk management.
RSI ADX Bollinger Analysis High-level purpose and design philosophy
This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management.
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What each indicator contributes (component-by-component)
RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side.
ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates.
Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move.
Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy.
4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results.
5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results.
These exercises teach both statistical thinking and the specific failure modes of the mashup.
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Limitations, failure modes and caveats (explicit & teachable)
• ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions.
• Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof.
• RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns.
• Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios.
Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent.
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Originality & mashup justification (text you can paste)
This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength.
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TradingView publication guidance & compliance checklist
To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code):
1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter).
2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each.
3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.”
4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size).
5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest).
6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits.
7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes.
8. Trademark clause: If you used trademark symbols, remove or provide registration proof.
9. Risk disclaimer: Add the copy-ready disclaimer below.
This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning.
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Copy-ready short publication description (paste into TradingView)
Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity.
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Copy-ready risk & misuse disclaimer (paste into description or help file)
This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls.
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Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
Comet C/2025 N1 (ATLAS) Ephemeris☄️ Ephemeris How-To: Plot JPL Horizons Data on TradingView (Educational)
Overview
This open-source Pine Script™ v6 indicator demonstrates how to bring external astronomical ephemeris into TradingView and plot it on a daily chart. Using Comet C/2025 N1 (ATLAS) as an example dataset, it shows the mechanics of structuring arrays, indexing by date, and drawing past and forward ( future projections ) values—strictly as an educational visualization of celestial motion.
Why This Approach
Data is generated from NASA JPL Horizons, a mission-grade, publicly available ephemeris service ( (ssd.jpl.nasa.gov)). On the daily timeframe, Horizons provides high-precision positions you can regenerate whenever solutions update—useful for educational accuracy in exploring orbital data.
What’s Plotted
- Geocentric ecliptic longitude (Earth-view)
- Heliocentric ecliptic longitude (Sun-centered)
- Declination (deg from celestial equator)
Features
- Simple arrays + date indexing (no per-row timestamps)
- Circles for historical/current bars; polylines to connect forward points, emphasizing future projections
- Toggle any series on/off via inputs
- Daily timeframe enforced (runtime error if not 1D)
- Optional table with zodiac conversion (AstroLib by BarefootJoey)
Data & Updates
The example arrays span 2025-07-01 (discovery date) → 2026-01-01. You can refresh them anytime from JPL Horizons (Observer: Geocentric; daily step; include ecliptic lon/lat and declination) and paste the new values into the script.
How we pulled the ephemeris from JPL Horizons (quick guide):
0) Open ssd.jpl.nasa.gov System
1. Ephemeris Type: Observer Table
2. Target Body: C/2025 N1 (ATLAS) (or any object you want)
3. Observer Location: Geocentric
4. Time Specification: set Start, Stop, Step = 1 day
5. Table Settings → Quantities:
* Astrometric RA & Dec
* Heliocentric ecliptic longitude & latitude
* Observer (geocentric) ecliptic longitude & latitude
6. Additional Table Settings:
* Calendar format: Gregorian
* Date/Time: calendar (UTC), Hours & Minutes (HH:MM)
* Angle format: Decimal degrees
* Refraction model: No refraction / airless
* Range units: Astronomical units (au)
7. Generate → Download results (CSV or text).
8. Use AI or a small script to parse columns (e.g., Obs ecliptic lon, Helio ecliptic lon, Declination) into arrays, then paste them into your Pine script.
Educational Note
This indicator’s goal is to show how to prepare and plot ephemeris—so you can adapt the method for other comets or celestial bodies, or swap in data from existing astro libraries, for learning about astronomical projections using JPL daily data.
Credits & License
- Ephemeris: Solar System Dynamics Group, Horizons On-Line Ephemeris System, 4800 Oak Grove Drive, Jet Propulsion Laboratory, Pasadena, CA 91109, USA.
- Zodiac conversion: AstroLib by BarefootJoey
- License: MIT
- For educational use only.
ACR(Average Candle Range) With TargetsWhat is ACR?
The Average Candle Range (ACR) is a custom volatility metric that calculates the mean distance between the high and low of a set number of past candles. ACR focuses only on the actual candle range (high - low) of specific past candles on a chosen timeframe.
This script calculates and visualizes the Average Candle Range (ACR) over a user-defined number of candles on a custom timeframe. It displays a table of recent range values, plots dynamic bullish and bearish target levels, and marks the start of each new candle with a vertical line. All calculations update in real time as price action develops. This script was inspired by the “ICT ADR Levels - Judas x Daily Range Meter°” by toodegrees.
Key Features
Custom Timeframe Selection: Choose any timeframe (e.g., 1D, 4H, 15m) for analysis.
User-Defined Lookback: Calculate the average range across 1 to 10 previous candles.
Dynamic Targets:
Bullish Target: Current candle low + ACR.
Bearish Target: Current candle high – ACR.
Live Updates: Targets adjust intrabar as highs or lows change during the current candle.
Candle Start Markers: Vertical lines denote the open of each new candle on the selected timeframe.
Floating Range Table:
Displays the current ACR value.
Lists individual ranges for the previous five candles.
Extend Target Lines: Choose to extend bullish and bearish target levels fully across the screen.
Global Visibility Controls: Toggle on/off all visual elements (targets, vertical lines, and table) for a cleaner view.
How It Works
At each new candle on the user-selected timeframe, the script:
Draws a vertical line at the candle’s open.
Recalculates the ACR based on the inputted previous number of candles.
Plots target levels using the current candle's developing high and low values.
Limitation
Once the price has already moved a full ACR in the opposite direction from your intended trade, the associated target loses its practical value. For example, if you intended to trade long but the bearish ACR target is hit first, the bullish target is no longer a reliable reference for that session.
Use Case
This tool is designed for traders who:
Want to visualize the average movement range of candles over time.
Use higher or lower timeframe candles as structural anchors.
Require real-time range-based price levels for intraday or swing decision-making.
This script does not generate entry or exit signals. Instead, it supports range awareness and target projection based on historical candle behavior.
Key Difference from Similar Tools
While this script was inspired by “ICT ADR Levels - Judas x Daily Range Meter°” by toodegrees, it introduces a major enhancement: the ability to customize the timeframe used for calculating the range. Most ADR or candle-range tools are locked to a single timeframe (e.g., daily), but this version gives traders full control over the analysis window. This makes it adaptable to a wide range of strategies, including intraday and swing trading, across any market or asset.
Ultimate JLines & MTF EMA (Configurable, Labels)## Ultimate JLines & MTF EMA (Configurable, Labels) — Script Overview
This Pine Script is a comprehensive, multi-timeframe indicator based on J Trader concepts. It overlays various Exponential Moving Averages (EMAs), VWAP, inside bar highlights, and dynamic labels onto price charts. The script is highly configurable, allowing users to tailor which elements are displayed and how they appear.
### Key Features
#### 1. **Multi-Timeframe JLines**
- **JLines** are pairs of EMAs (default lengths: 72 and 89) calculated on several timeframes:
- 1 minute (1m)
- 3 minutes (3m)
- 5 minutes (5m)
- 1 hour (1h)
- Custom timeframe (user-selectable)
- Each pair can be visualized as individual lines and as a "cloud" (shaded area between the two EMAs).
- Colors and opacity for each timeframe are user-configurable.
#### 2. **200 EMA on Multiple Timeframes**
- Plots the 200-period EMA on selectable timeframes: 1m, 3m, 5m, 15m, and 1h.
- Each can be toggled independently and colored as desired.
#### 3. **9 EMA and VWAP**
- Plots a 9-period EMA, either on the chart’s current timeframe or a user-specified one.
- Plots VWAP (Volume-Weighted Average Price) for additional trend context.
#### 4. **5/15 EMA Cross Cloud (5min)**
- Calculates and optionally displays a shaded "cloud" between the 5-period and 15-period EMAs on the 5-minute chart.
- Highlights bullish (5 EMA above 15 EMA) and bearish (5 EMA below 15 EMA) conditions with different colors.
- Optionally displays the 5 and 15 EMA lines themselves.
#### 5. **Inside Bar Highlighting**
- Highlights bars where the current high is less than or equal to the previous high and the low is greater than or equal to the previous low (inside bars).
- Color is user-configurable.
#### 6. **9 EMA / VWAP Cross Arrows**
- Plots up/down arrows when the 9 EMA crosses above or below the VWAP.
- Arrow colors and visibility are configurable.
#### 7. **Dynamic Labels**
- On the most recent bar, displays labels for each enabled line (EMAs, VWAP), offset to the right for clarity.
- Labels include the timeframe, type, and current value.
### Customization Options
- **Visibility:** Each plot (line, cloud, arrow, label) can be individually toggled on/off.
- **Colors:** All lines, clouds, and arrows can be colored to user preference, including opacity for clouds.
- **Timeframes:** JLines and EMAs can be calculated on different timeframes, including a custom one.
- **Label Text:** Labels dynamically reflect current indicator values and are color-coded to match their lines.
### Technical Implementation Highlights
- **Helper Functions:** Functions abstract away the logic for multi-timeframe EMA calculation.
- **Security Calls:** Uses `request.security` to fetch data from other timeframes, ensuring accurate multi-timeframe plotting.
- **Efficient Label Management:** Deletes old labels and creates new ones only on the last bar to avoid clutter and maintain performance.
- **Conditional Plotting:** All visual elements are conditionally plotted based on user input, making the indicator highly flexible.
### Use Cases
- **Trend Identification:** Multiple EMAs and VWAP help traders quickly identify trend direction and strength across timeframes.
- **Support/Resistance:** 200 EMA and JLines often act as dynamic support/resistance levels.
- **Entry/Exit Signals:** Crosses between 9 EMA and VWAP, as well as 5/15 EMA clouds, can signal potential trade entries or exits.
- **Pattern Recognition:** Inside bar highlights aid in spotting consolidation and breakout patterns.
### Summary Table of Configurable Elements
| Feature | Timeframes | Cloud Option | Label Option | Color Customizable | Description |
|----------------------------|-------------------|--------------|--------------|--------------------|-----------------------------------------------|
| JLines (72/89 EMA) | 1m, 3m, 5m, 1h, Custom | Yes | Yes | Yes | Key trend-following EMAs with cloud fill |
| 200 EMA | 1m, 3m, 5m, 15m, 1h | No | Yes | Yes | Long-term trend indicator |
| 9 EMA | Any | No | Yes | Yes | Short-term trend indicator |
| VWAP | Chart TF | No | Yes | Yes | Volume-weighted average price |
| 5/15 EMA Cloud (5m) | 5m | Yes | No | Yes | Bullish/bearish cloud between 5/15 EMAs |
| Inside Bar Highlight | Chart TF | No | N/A | Yes | Highlights price consolidation |
| 9 EMA / VWAP Cross Arrows | Chart TF | No | N/A | Yes | Marks EMA/VWAP crossovers with arrows |
This script is ideal for traders seeking a robust, multi-timeframe overlay that combines trend, momentum, and pattern signals in a single, highly customizable indicator. I do not advocate to subscribe to JTrades or the system they tout. This is based on my own observations and not a copy of any JTrades scripts. It is open source to allow full transparency.
FvgPanel█ OVERVIEW
This library provides functionalities for creating and managing a display panel within a Pine Script™ indicator. Its primary purpose is to offer a structured way to present Fair Value Gap (FVG) information, specifically the nearest bullish and bearish FVG levels across different timeframes (Current, MTF, HTF), directly on the chart. The library handles the table's structure, header initialization, and dynamic cell content updates.
█ CONCEPTS
The core of this library revolves around presenting summarized FVG data in a clear, tabular format. Key concepts include:
FVG Data Aggregation and Display
The panel is designed to show at-a-glance information about the closest active FVG mitigation levels. It doesn't calculate these FVGs itself but relies on the main script to provide this data. The panel is structured with columns for timeframes (TF), Bullish FVGs, and Bearish FVGs, and rows for "Current" (LTF), "MTF" (Medium Timeframe), and "HTF" (High Timeframe).
The `panelData` User-Defined Type (UDT)
To facilitate the transfer of information to be displayed, the library defines a UDT named `panelData`. This structure is central to the library's operation and is designed to hold all necessary values for populating the panel's data cells for each relevant FVG. Its fields include:
Price levels for the nearest bullish and bearish FVGs for LTF, MTF, and HTF (e.g., `nearestBullMitLvl`, `nearestMtfBearMitLvl`).
Boolean flags to indicate if these FVGs are classified as "Large Volume" (LV) (e.g., `isNearestBullLV`, `isNearestMtfBearLV`).
Color information for the background and text of each data cell, allowing for conditional styling based on the FVG's status or proximity (e.g., `ltfBullBgColor`, `mtfBearTextColor`).
The design of `panelData` allows the main script to prepare all display-related data and styling cues in one object, which is then passed to the `updatePanel` function for rendering. This separation of data preparation and display logic keeps the library focused on its presentation task.
Visual Cues and Formatting
Price Formatting: Price levels are formatted to match the instrument's minimum tick size using an internal `formatPrice` helper function, ensuring consistent and accurate display.
Large FVG Icon: If an FVG is marked as a "Large Volume" FVG in the `panelData` object, a user-specified icon (e.g., an emoji) is prepended to its price level in the panel, providing an immediate visual distinction.
Conditional Styling: The background and text colors for each FVG level displayed in the panel can be individually controlled via the `panelData` object, enabling the main script to implement custom styling rules (e.g., highlighting the overall nearest FVG across all timeframes).
Handling Missing Data: If no FVG data is available for a particular cell (i.e., the corresponding level in `panelData` is `na`), the panel displays "---" and uses a specified background color for "Not Available" cells.
█ CALCULATIONS AND USE
Using the `FvgPanel` typically involves a two-stage process: initialization and dynamic updates.
Step 1: Panel Creation
First, an instance of the panel table is created once, usually during the script's initial setup. This is done using the `createPanel` function.
Call `createPanel()` with parameters defining its position on the chart, border color, border width, header background color, header text color, and header text size.
This function initializes the table with three columns ("TF", "Bull FVG", "Bear FVG") and three data rows labeled "Current", "MTF", and "HTF", plus a header row.
Store the returned `table` object in a `var` variable to persist it across bars.
// Example:
var table infoPanel = na
if barstate.isfirst
infoPanel := panel.createPanel(
position.top_right,
color.gray,
1,
color.new(color.gray, 50),
color.white,
size.small
)
Step 2: Panel Updates
On each bar, or whenever the FVG data changes (typically on `barstate.islast` or `barstate.isrealtime` for efficiency), the panel's content needs to be refreshed. This is done using the `updatePanel` function.
Populate an instance of the `panelData` UDT with the latest FVG information. This includes setting the nearest bullish/bearish mitigation levels for LTF, MTF, and HTF, their LV status, and their desired background and text colors.
Call `updatePanel()`, passing the persistent `table` object (from Step 1), the populated `panelData` object, the icon string for LV FVGs, the default text color for FVG levels, the background color for "N/A" cells, and the general text size for the data cells.
The `updatePanel` function will then clear previous data and fill the table cells with the new values and styles provided in the `panelData` object.
// Example (inside a conditional block like 'if barstate.islast'):
var panelData fvgDisplayData = panelData.new()
// ... (logic to populate fvgDisplayData fields) ...
// fvgDisplayData.nearestBullMitLvl = ...
// fvgDisplayData.ltfBullBgColor = ...
// ... etc.
if not na(infoPanel)
panel.updatePanel(
infoPanel,
fvgDisplayData,
"🔥", // LV FVG Icon
color.white,
color.new(color.gray, 70), // NA Cell Color
size.small
)
This workflow ensures that the panel is drawn only once and its cells are efficiently updated as new data becomes available.
█ NOTES
Data Source: This library is solely responsible for the visual presentation of FVG data in a table. It does not perform any FVG detection or calculation. The calling script must compute or retrieve the FVG levels, LV status, and desired styling to populate the `panelData` object.
Styling Responsibility: While `updatePanel` applies colors passed via the `panelData` object, the logic for *determining* those colors (e.g., highlighting the closest FVG to the current price) resides in the calling script.
Performance: The library uses `table.cell()` to update individual cells, which is generally more efficient than deleting and recreating the table on each update. However, the frequency of `updatePanel` calls should be managed by the main script (e.g., using `barstate.islast` or `barstate.isrealtime`) to avoid excessive processing on historical bars.
`series float` Handling: The price level fields within the `panelData` UDT (e.g., `nearestBullMitLvl`) can accept `series float` values, as these are typically derived from price data. The internal `formatPrice` function correctly handles `series float` for display.
Dependencies: The `FvgPanel` itself is self-contained and does not import other user libraries. It uses standard Pine Script™ table and string functionalities.
█ EXPORTED TYPES
panelData
Represents the data structure for populating the FVG information panel.
Fields:
nearestBullMitLvl (series float) : The price level of the nearest bullish FVG's mitigation point (bottom for bull) on the LTF.
isNearestBullLV (series bool) : True if the nearest bullish FVG on the LTF is a Large Volume FVG.
ltfBullBgColor (series color) : Background color for the LTF bullish FVG cell in the panel.
ltfBullTextColor (series color) : Text color for the LTF bullish FVG cell in the panel.
nearestBearMitLvl (series float) : The price level of the nearest bearish FVG's mitigation point (top for bear) on the LTF.
isNearestBearLV (series bool) : True if the nearest bearish FVG on the LTF is a Large Volume FVG.
ltfBearBgColor (series color) : Background color for the LTF bearish FVG cell in the panel.
ltfBearTextColor (series color) : Text color for the LTF bearish FVG cell in the panel.
nearestMtfBullMitLvl (series float) : The price level of the nearest bullish FVG's mitigation point on the MTF.
isNearestMtfBullLV (series bool) : True if the nearest bullish FVG on the MTF is a Large Volume FVG.
mtfBullBgColor (series color) : Background color for the MTF bullish FVG cell.
mtfBullTextColor (series color) : Text color for the MTF bullish FVG cell.
nearestMtfBearMitLvl (series float) : The price level of the nearest bearish FVG's mitigation point on the MTF.
isNearestMtfBearLV (series bool) : True if the nearest bearish FVG on the MTF is a Large Volume FVG.
mtfBearBgColor (series color) : Background color for the MTF bearish FVG cell.
mtfBearTextColor (series color) : Text color for the MTF bearish FVG cell.
nearestHtfBullMitLvl (series float) : The price level of the nearest bullish FVG's mitigation point on the HTF.
isNearestHtfBullLV (series bool) : True if the nearest bullish FVG on the HTF is a Large Volume FVG.
htfBullBgColor (series color) : Background color for the HTF bullish FVG cell.
htfBullTextColor (series color) : Text color for the HTF bullish FVG cell.
nearestHtfBearMitLvl (series float) : The price level of the nearest bearish FVG's mitigation point on the HTF.
isNearestHtfBearLV (series bool) : True if the nearest bearish FVG on the HTF is a Large Volume FVG.
htfBearBgColor (series color) : Background color for the HTF bearish FVG cell.
htfBearTextColor (series color) : Text color for the HTF bearish FVG cell.
█ EXPORTED FUNCTIONS
createPanel(position, borderColor, borderWidth, headerBgColor, headerTextColor, headerTextSize)
Creates and initializes the FVG information panel (table). Sets up the header rows and timeframe labels.
Parameters:
position (simple string) : The position of the panel on the chart (e.g., position.top_right). Uses position.* constants.
borderColor (simple color) : The color of the panel's border.
borderWidth (simple int) : The width of the panel's border.
headerBgColor (simple color) : The background color for the header cells.
headerTextColor (simple color) : The text color for the header cells.
headerTextSize (simple string) : The text size for the header cells (e.g., size.small). Uses size.* constants.
Returns: The newly created table object representing the panel.
updatePanel(panelTable, data, lvIcon, defaultTextColor, naCellColor, textSize)
Updates the content of the FVG information panel with the latest FVG data.
Parameters:
panelTable (table) : The table object representing the panel to be updated.
data (panelData) : An object containing the FVG data to display.
lvIcon (simple string) : The icon (e.g., emoji) to display next to Large Volume FVGs.
defaultTextColor (simple color) : The default text color for FVG levels if not highlighted.
naCellColor (simple color) : The background color for cells where no FVG data is available ("---").
textSize (simple string) : The text size for the FVG level data (e.g., size.small).
Returns: _void
