VWAP Previous VWAP WMQY StdDev Extensions Nadro StyleDisplays Multi-TF VWAP with Std Dev Bands.
Developing VWAP and Std Dev Bands
Previous VWAP and Std Dev Bands
Previous VWAP Extensions
Some Examples
Bands and Channels
BankNifty_Bullish_Intraday
The script uses following mechanism to give a signal of BUY if multiple parameters evaluated are all passed.
ENTRY-
1. 5 min MACD should be more than its previous tick
2. 15 min MACD should be more than its previous tick
3. 60 min MACD should be more than its previous tick
4. ADX should be more than 12
5. RSI should be more than 60
6. Stochastic %k should have cross over with %d
7. Bollinger band upper band value should be more than previous tick
EXIT
If the 5 min bar price closes below 5 min EMA , it gives an exit signal.
BankNifty_Bearish_Intraday
The script uses following mechanism to give a signal of SELL if multiple parameters evaluated are all passed.
ENTRY-
1. 5 min MACD should be less than its previous tick
2. 15 min MACD should be less than its previous tick
3. 60 min MACD should be less than its previous tick
4. ADX should be more than 12
5. RSI should be less than 40
6. Stochastic %k should have negative cross over with %d
7. Bollinger band lower band value should be less than previous tick
EXIT
If the 5 min bar price closes above 5 min EMA , it gives an exit signal.
Elder Impulse VisualisedThis script is based off the original "Elder Impulse" system. It is based off a series of indicators including EMAs and MACD crossovers to change the colors of candlestick bars which can act as buy/sell signals to traders. Additionally this script plots 2 lines on the chart - one red and one green. These lines show the price levels needed for the current bar's close price in order for the current candlestick to close a certain colour.
ie, If the the current bar is green, it must close below the red line in order for the bar to become red, and vice versa.
RSI on Chart Window- The RSI indicator is displayed right on the chart, along with overbought and oversold notification symbols.
- Easily enable/disable the display of RSI Upper Band, Lower Band.
Range Bound - Rev NR - 12-25-22RangeBound - Code tracks price action within a user specified range (lookback), and tracks/charts overall high/lows, open high/lows, and close high/lows. Code resets certain parameters based on break of range to assist with determine price action - Can be useful to determine resistances to movement regardless of S&R levels. Code also uses the previous 5X Close High/Lows ranges as will chart as support and resistance to assist with determine resistance to price action
Note if using "redraw" shorter lookback periods will take additional time to compile due to multiple "redraws/deletes of previous lines" Uncheck redraw to reduce compile time
//The first code I have decided to publish :)
Price Heat MapWhat does this chart show? Take the highest high and lowest low of 200 bars. Divide that into 20 chunks. The more time the price spends in one of those 1/20th pockets, the brighter it is lit up on the chart. Number of bars back can be modified to around 500. It starts to chug beyond that. Brightness level of heat map can be adjusted. 0.5 is default. 1 = brighter, 0 = dimmer. Use on any time frame. When price moves out of a hot zone, it can move very quickly. There's no trading strategy here, just something to help you visualize recent price action. The blue band shows the price at the center of the current "hottest" band. The yellow band is the ema (exponential moving average) of the price using the "bars back" input. --enjoy!
Macro Score - DFMA-BasedA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger.
The DFMA - Democratic Fibonacci Moving Average - is a separate indicator that we have released that takes 10 different Fibonacci MAs (lengths of 3 to 233, at Fibonacci intervals) and averages them to form the DFMA line. This helps by creating a consensus on the trend based on moving averages alone. Crossovers of the DFMA with the various Fib MA lengths as well as a cross of the price source and these lines can provide adequate long and short signals.
This strategy has the signals and weights pre-determined in the code. Heaviest weights have been given to crosses of the DFMA line/Fib MA (233) as well as the crosses of the Fib MA (3)/DFMA. Additionally, there are thresholds for DPO ( Detrended Price Oscillator , above or below 0), CMO ( Chande Momentum Oscillator , above or below 0), Jurik Volatility Bands (above or below 0), and Stoch RSI (above or below 50). These foursignals hold a lighter weight than the MA cross signals.
The macro score itself is printed in an underlay as a white line that goes between -10 and 10 for this strategy. In addition to the macro score line, a blue momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to a threshold for the macro score (-5/5).
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else.
Default Properties, for AVAX 20M:
DPO - 40, uncentered
CMO - 25, open
K/D - 3/3
RSI Stoch Length - 3
Stoch Length - 4
Stoch Source - open
JVB Length - 25
JVB Smoothing - 2
DFMA source - close
Macro Length - 13
TP % - 1.5%
TTP % - 0.005%
SL % - 2%
Percentile Nearest Rank Rainbow Overlay (PNRV)The Percentile Nearest Rank Rainbow Overlay (PNRV) is an indicator for the TradingView platform that aims to visualize the ranking of a given source data within its own percentile range.
The PNRV indicator takes a single input, "src", which is the source data that the indicator will operate on. This input can be any series of data, such as stock prices, volume, or any other numerical data.
The indicator then maps the values of the src data onto a gradient of 60 colors, ranging from blue to green to yellow, with each color representing a percentile range. For example, values in the 0th percentile will be represented by a deep blue color, while values in the 50th percentile will be represented by a yellow color.
The PNRV indicator is designed to be overlaid on top of a chart, with the color of each data point representing its percentile ranking within the src data. This allows traders to easily identify trends and patterns within the data, as well as to compare the relative strength or weakness of different securities.
One potential use case for the PNRV indicator is in identifying potential overbought or oversold conditions in a stock or other security. For example, if the PNRV indicator shows that a stock's price is consistently ranking in the upper percentiles, this could be a sign that the stock is overbought and may be due for a correction. Conversely, if the PNRV indicator shows that a stock's price is consistently ranking in the lower percentiles, this could be a sign that the stock is undervalued and may be a good buying opportunity.
Overall, the PNRV indicator is a useful tool for traders looking to quickly and easily visualize the ranking of a given data series within its own percentile range.
Range Filter Buy and Sell 5min - guikroth versionRange Filter Buy and Sell 5min - the @guikroth version, republished.
Since this popular version of the Range Filter is no longer available via the original author, I republish it here under the same name.
This version remains true to the guikroth version from the calculations to the default settings and comments in the code, with the exception of an update to the latest version of PineScript, minor styling adjustments and the addition of an all-in-one 'buy or sell' alert option.
The guikroth version was a simplified modification of the original Range Filter by @DonovanWall .
Including having just 3 bar colours based on the filtered price trend, different source input options to the original, and the addition of buy and sell signals and alerts based upon the Range Filter colour change. It consisted of just three inputs; source, sampling period, and range multipler. With the update to version 5, external indicators can also be used as inputs, for example using a VWAP or EMA loaded on your chart as the input on the Range Filter is now also possible.
What is the Range Filter?
As the author of the original Range Filter describes it:
"This is an experimental study designed to filter out minor price action for a clearer view of trends. Inspired by the QQE's volatility filter, this filter applies the process directly to price rather than to a smoothed RSI .
First, a smooth average price range is calculated for the basis of the filter and multiplied by a specified amount.
Next, the filter is calculated by gating price movements that do not exceed the specified range.
Lastly the target ranges are plotted to display the prices that will trigger filter movement.
Custom bar colors are included. The color scheme is based on the filtered price trend."
Popularity of the Range Filter
The Range Filter is a very popular and effective indicator in its own right, with adjustments to the few simple settings it is possible to use the Range Filter for helping filter price movement, whether helping to determine trend direction or ranges, to timing breakout or even reversal entries. Its practical versatility makes it ideal for integrating it's signals into a variety of trading strategies or even other indicators.
With many thanks to the authors of the previous and original versions; @guikroth and @DonovanWall .
MA ChannelThis indicator creates a high and low channel of moving average type selected, it also can draw deviation bands based on the channel for a unique representation of squeezes.
Features
Moving average channel displays constant high and low price trend.
Center band displays color representative of trend direction constantly.
High price trend line disappears during downtrends, and low price trend line disappears during uptrends.
Deviation band display accurately reports squeezes between price and channel data.
Deviation band fill reports price range expansion as possible trend weakness.
Settings
Period adjusts historical price data to use for trend analysis.
Average Type adjusts the type of average calculation used in the trend plots.
Show Deviation Band toggles display of deviation bands and their fill.
Deviation Multiplier adjusts the deviation calculation, 2.0 is common.
Style adjustments include up/down trend strong/weak color customization (default theme supports color blindness).
Color Bar displays overall trend color on each bar.
Deviation Band Fill With Squeeze Measurement adjusts opacity to represent deviation band squeeze, when bands contract the colors disappear, when bands expand the colors reappear.
Usage
Trend Analysis
When price has broken above the channel then it's an uptrend, price below the channel is a downtrend.
Pay attention to when inverse trend line appears only momentarily, these could be excellent trend continuation entry areas.
Reversals
Reversal areas can be spotted where price breaks the channel central ribbon but doesn't close outside on the opposite end of previous trend.
Squeeze
Band fill squeeze mode aims to make it a simple task to see when a squeeze may be weakening, with the color trend brightening during periods of expansion, and disappearing during periods of contraction (squeezing).
McGinley Dynamic x Donchian ChannelsThis indicator combines the McGinley Dynamic and Donchian Channels by taking the lowest and highest values over a set length (defaulted to 14) then applying the McGinley Dynamic math to these values. The upper range is denoted by a green line while the lower range is denoted by a red line. Additionally, standard deviations of 1, 2, and 3 have been put in place using the upper and lower values as the basis for the deviations as opposed to the baseline average of the upper and lower bands. These deviations are plotted as lime and orange colors. These channels can be used to determine when the price is gaining or losing momentum based on the distance between the channels. Otherwise, the channels can be used to determine potential overbought and oversold levels.
RobokiteTrading_By [kushal harsola]This script is for custom candles based on an MA calculation with a default period of 14 as well as an SMA of the close price, defaulted to 1 period to only show the current price. The purpose of the custom candles is to try and reduce noise from candles and help identify trends.
Explained:
- High, Low and Close are all calculated using an MA calculation based on a user input length/period, defaulted at 14.
- Trend line = color black BUY "if candle close above the trend line & SELL "if candle close below the trend line.
- Stop loss = for buying stop loss color = red line
= for selling stop loss color = green line
- master stop loss = for buying SL - High 14
= for selling SL - low 14
NSE:NIFTY
DISCLAIMER: For educational and entertainment purposes only.
Impulse Alerts - Riccardo Di GiacomoThis is the Impulse indicator that allows you to receive alerts in the case one of the following situation occurs:
1) Buy Setup
- Price above Exponential Moving Average 260
- Moving Average 21 above Exponential Moving Average 260
- Moving Average 9 above Moving Average 21
- RSI(14) above 50
- Stochastic equal or below 20
2) Sell Setup
- Price below Exponential Moving Average 260
- Moving Average 21 below Exponential Moving Average 260
- Moving Average 9 below Moving Average 21
- RSI(14) below 50
- Stochastic equal or above 80
The Bollinger Bands represents another useful information:
- If the price is near the upper band when the first situation occurs, it is another green light, otherwise be careful
- If the price is near the lower band when the second situation occurs, it is another green light, otherwise be careful
Binomial MA BandsThe Binomial MA Bands is a simple and straightforward trading tool that uses a binomial distribution to calculate the moving average and standard deviation of a given price series. It allows users to adjust the length of the moving average and the multiplier for the standard deviation, providing some flexibility in its usage. However, it should be noted that the binomial distribution may not always provide the most accurate representation of market movements and trends, and may not always be the best choice for all traders. Additionally, the tool only has a limited range of adjustable parameters, so it may not be suitable for traders with more advanced or complex strategies. Overall, the Binomial MA Bands may be a useful tool for some traders, but its limitations should be kept in mind when considering its use in trading.
MACD Optimizer Pro [Kioseff Trading]Massive update! This script now includes 12 different moving averages and 30+ built-in technical indicators to enhance your trading strategy optimization! (:
This script (MACD Optimizer Pro) allows the user to optimize and test hundreds of MACD strategies, simultaneously, in under 40 seconds. Of course, theoretically, an unlimited number of trading strategies can be tested with the MACD Optimizer Pro. After the optimization period - the MACD Optimizer Pro will show the most profitable MACD strategy or, should you choose, the highest win-rate MACD strategy or the most-efficient MACD strategy!
Optimization results can be backtested and verified using the native TradingView backtester - which is included in the MACD Optimizer Pro - and made easy to use! This feature makes settings alerts a simple practice!
Features
Test hundreds of MACD strategies, simultaneously, in under 40 seconds.
Optimize long MACD strategies and short MACD strategies.
12 different built-in moving averages included to improve your MACD strategy.
30+ built-in technical indicators to improve your MACD strategy.
Runs as a strategy script - profit factor, PnL , win-rate, number of trades, max drawdown, equity curve and other pertinent statistics shown.
Alerts
Optimize any MACD setting
Profit targets, trailing stops, fixed stop losses, and a binary MACD strategy can all be tested.
Strategies can be optimized for highest win rate, highest net profit, most efficient profit.
Limit orders can be simulated.
External indicators can be used for optimization i.e. your own, custom-built indicator, an indicator from your favorite author, or almost any publicly available
TradingView indicator.
Date range for optimization and backtesting are configurable.
Explanation
The image above shows a list of configurations for the optimizer. You can
You can test hundreds of different MACD settings in under 40 seconds on any timeframe, asset, etc.
The image above shows additional settings to filter the outcome of your optimization testing. Additionally, you can test an unlimited number of profit targets and stop losses!
You can add one of several built-in TradingView indicators to filter trade entries.
The image above shows all built-in moving averages and TradingView indicators that can be incorporated into your MACD strategy.
Additionally, you can add your own, custom indicator to the optimization test, your favorite indicator by your favorite author or almost any publicly available indicator on TradingView.
The image above shows the settings section in which you can implement this feature.
The image above shows an example of the custom indicator feature! In this instance, I am using the public indicator titled "Self-Optimizing" RSI and requiring it to measure below a level prior to entry! Almost any custom indicator, your favorite indicator, etc. is compatible with this feature!
The MACD Optimizer has improved user friendliness over previous versions. The optimizer can be as simple or complex as you'd like - capable of handling both "easy" and "difficult" tasks at your discretion.
Additionally, you can configure the optimizer to prioritize MACD strategies that earn profit most efficiently!
The image above shows this feature in action.
You can also configure the optimizer to prioritize MACD strategies that achieve the highest win rate!
The image above shows this feature in action.
Instructions
The instructions below show a rudimentary approach to using the optimizer.
1. Build your strategy in the settings.
You should also disable the "Run a Backtest" feature to improve load times during optimization.
The image above shows my custom strategy settings.
Now that you've got some data on your chart - you should try "Freezing" the "Smoothing" setting for MACD . When doing this, the optimizer will test hundreds of MACD settings with a fixed "Smoothing" setting. Try using the best "Smoothing" setting you were able to find for your initial testing.
2. Take the best "Smoothing" setting and test various MACD and Signal Lengths.
The image above shows me configuring the MACD Optimizer to test different MACD line lengths and Signal line lengths with a fixed "smoothing" setting.
From the results, we can see that there are better MACD settings than what was shown in our initial test!
With this information we can execute a TradingView backtest.
3. Execute a TradingView Backtest.
You must enable the "Run a Backtest" feature to perform a TradingView backtest. Additionally, it's advised to enable the "STOP OPTIMIZATION" feature when performing a TradingView backtest. Enabling this feature will improve load times for the backtest to only a few seconds (since the optimizer won't look for the best setting when this feature is enabled).
The image above shows completion of the process!
From here, you can perform further testing, set alerts, etc.
Backtest Settings Shown
Initial Capital: The initial capital used for the shown backtests is $3,500 USD. Set the initial capital to replicate your true starting capital (: PnL for the MACD strategies (listed in table) is calculated using a starting capital of $10,000 USD.
Slippage: The slippage settings for the displayed backtest was set to 2 ticks.
Commission: Commission was adjusted to 0.1%.
Verify Price for Limit Orders was set to 2 ticks.
Optimization
Trading system optimization is immensely advantageous when executed with prudence.
Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail.
Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
Thanks for checking this out!
Oscillator ExtremesThe Oscillator Extremes indicator plots the normalized positioning of the selected oscillator versus the Bollinger Bands' upper and lower boundaries. Currently, this indicator has four different oscillators to choose from; RSI, CMO, CCI, and ROC.
When the oscillator pushes towards one extreme, it will bring the value of the prevailing line closer to zero. If the bullish or bearish line crosses the zero line, the oscillator is past the extreme of the Bollinger Band.
Example: If the RSI crosses over the upper boundary of the Bollinger, the bullish(green) line will cross under the zero line.
Crossovers of the bullish and bearish lines can indicate a shift in momentum and are a signal. Where the line crossing under, towards zero, is the prevailing trend. The plotted lines will highlight green(bullish) or red(bearish) to show the prevailing trend. This is similar to a DI+- crossover that is commonly associated with the ADX.
We have included an optional normalized ADX to help validate signals. The ADX will change color based on the slope of the ADX. Purple indicates a positive slope and white for a negative slope.
Kioseff Trading - AI-Optimized Supertrend
AI-Optimized Supertrend
Introducing AI-Optimized Supertrend: a streamlined solution for traders of any skill level seeking to rapidly test and optimize Supertrend. Capable of analyzing thousands of strategies, this tool cuts through the complexity to identify the most profitable, reliable, or efficient approaches.
Paired with TradingView's native backtesting capabilities, the AI-Optimized Supertrend learns from historical performance data. Set up is easy for all skill levels, and it makes fine-tuning trading alerts and Supertrend straightforward.
Features
Rapid Supertrend Strategy Testing : Quickly evaluate thousands of Supertrend strategies to find the most effective ones.
AI-Assisted Optimization : Leverage AI recommendations to fine-tune strategies for superior results.
Multi-Objective Optimization : Prioritize Supertrend based on your preference for the highest win rate, maximum profit, or efficiency.
Comprehensive Analytics : The strategy script provides an array of statistics such as profit factor, PnL, win rate, trade counts, max drawdown, and an equity curve to gauge performance accurately.
Alerts Setup : Conveniently set up alerts to be notified about critical trade signals or changes in performance metrics.
Versatile Stop Strategies : Experiment with profit targets, trailing stops, and fixed stop losses.
Binary Supertrend Exploration : Test binary Supertrend strategies.
Limit Orders : Analyze the impact of limit orders on your trading strategy.
Integration with External Indicators : Enhance strategy refinement by incorporating custom or publicly available indicators from TradingView into the optimization process.
Key Settings
The image above shows explanations for a list of key settings for the optimizer.
Set the Factor Range Limits : The AI suggests optimal upper and lower limits for the Factor range, defining the sensitivity of the Supertrend to price fluctuations. A wider range tests a greater variety, while a narrower range focuses on fine-tuning.
Adjust the ATR Range : Use the AI's recommendations to establish the upper and lower bounds for the Average True Range (ATR), which influences the Supertrend's volatility threshold.
ATR Flip : This option lets you interchange the order of ATR and Factor values to quicky test different sequences, giving you the flexibility to explore various combinations and their impact on the Supertrend indicator's performance.
Strategies Evaluated : Adjust this setting to determine how many Supertrend strategies you want to assess and compare.
Enable AI Mode : Turn this feature on to allow the AI to determine and employ the optimal Supertrend strategy with the desired performance metric, such as the highest win rate or maximum profitability.
Target Metric : Adjust this to direct the AI towards optimizing for maximum profit, top win rates, or the most efficient profits.
AI Mode Aggressiveness : Set how assertively the AI pursues the chosen performance goal, such as highest profit or win rate.
Strategy Direction : Choose to focus the AI's testing and optimization on either long or short Supertrend strategies.
Stop Loss Type : Specify the stop loss approach for optimization—fixed value, a trailing stop, or Supertrend direction changes.
Limit Order : Decide if you want to execute trades using limit orders for setting your profit targets, stop losses, or apply them to both.
Profit Target : Define your desired profit level when using either a fixed stop loss or a trailing stop.
Stop Loss : Define your desired stop loss when using either a fixed stop loss or a trailing stop.
How to: Find the best Supertrend for trading
It's important to remember that merely having the AI-Optimized Supertrend on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal Supertrend settings and strategy.
Optimizing Supertrend involves adjusting two key parameters: the Factor and the Average True Range (ATR). These parameters significantly influence the Supertrend indicator's sensitivity and responsiveness to price movements.
Factor : This parameter multiplies the ATR to determine the distance of the Supertrend line from the price. Higher values will create a wider band, potentially leading to fewer trade signals, while lower values create a narrower band, which may result in more signals but also more noise.
ATR (Average True Range) : ATR measures market volatility. By using the ATR, the Supertrend adapts to changing market volatility; a higher ATR value means a more volatile market, so the Supertrend adjusts accordingly.
During the optimization process, these parameters are systematically varied to determine the combination that yields the best performance based on predefined criteria such as profitability, win rate, or risk management efficiency. The optimization aims to find the optimal Factor and ATR settings.
1.Starting Your Strategy Setup
Begin by deciding your goals for each trade: your profit target and stop loss, or if all trades exit when Supertrend changes direction. You'll also choose how to manage your stops – whether they stay put (fixed) or move with the price (trailing), and whether you want to exit trades at a specific price (limit orders). Keep the initial settings for Supertrend Factor Range and Supertrend ATR Range at their default to give the tool a broad testing field. The AI's guidance will refine these settings to pinpoint the most effective ones through a process of comprehensive testing.
Demonstration Start: We'll begin with the settings outlined in the key settings section, using Supertrend's direction change to the downside as our exit signal for all trades.
2. Continue applying the AI’s suggestions
Keep updating your optimization settings based on the AI's recommendations. Proceed with this iterative optimization until the "Best Found" message is displayed, signaling that the most effective strategy has been identified.
While following the AI's suggestions, we've been prompted with a new suggestion: increase the
number of strategies evaluated. Keep following the AI's new suggestions to evaluate more strategies. Do this until the "Best Found" message shows up.
Success! We continued to follow the AI’s suggestions until “Best Found” was indicated!
AI Mode
AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components:
Heuristic-Based Decision Making: The algorithm evaluates multiple Supertrend-based trading strategies using metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable strategies for trade execution.
Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions.
Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization.
AI Mode Settings
AI Mode Aggressiveness:
Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from “Low” to “High”, with “High” indicating a more assertive trading approach.
Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies.
Optimization
Trading system optimization is immensely advantageous when executed with prudence.
Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail.
Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
M0PB (Momentum Pullback)Long/short strategy that identifies extreme readings on the rsi as a *momentum signal*, unlike most RSI strategies the script will look to buy or sell the first pullback in the direction of the extreme RSI reading.
Enters positions on the first pullback to the 5ema(low)/ 5ema(high) and exits at rolling 12 bar high/ low. The rolling high/ low feature means that if the price enters into a prolonged consolidation the profit target will begin to reduce with each new bar. The best trades tend to work within 2-6 bars.
Built for use on 5 min intervals on FX, Indexes, and Crypto. Lower than 5 minute time frames tend to be noisier and mean more commissions and a higher risk of slippage so the suggested timeframe is 5 mins.
Hard stop is X ATR (users can experiment with this) from the position entry price. This can be adjusted in user inputs.
There is a lot of slack left in entries and exits but the overall strategy is fairly robust across timeframes and markets and has between 60%-70% win rate with larger winners.
Signals that occur from economic news volatility are best avoided.
Gedhusek ScalpingRangerThis indicator was designed for finding good entries for scalping the market
How does it work:
- It works on a basis of price running out of its bands and its return
- Once the price is out of bands, the system starts scanning for two patterns --> sudden price reversion and losing of momentum.
- If any of these patterns occur, the indicator waits for a confirmation bar and after that it gives you a signal that the price could be moving upwards or downwards.
- These signals are represented by a label and sudden price change of the current bar
- Also you will see a dotted line above or below the bar that can be used as a potential Stop Loss level
Idea behind the trigger patterns:
Sudden price reversion
- Idea behind this pattern is that the price has a higher success of reversion if there is a fast change of its momentum. This pattern is recognized by measuring the divergence between prior and current price change
- The divergence is measured as correlation between shorter-term price action and longer-term price action. If the correlation is negative and statistically significant, it is counted as a reversion signal (= shorter-time price action goes in the opposite direction of longer-term price action)
Losing of momentum
- The idea behind this pattern is that once there is no strong momentum, there is lower probability of a breakout and start of strong trend
- It is calculated as a difference between current price and previous price. If the difference is minimal, it is taken as a signal that the price lost its momentum and therefore there is higher chance of reversion.
When to use:
- This indicator works well in ranging markets, but slightly less well in trending markets. Therefore look for sideways markets and use the indicator there
- Price action patterns work really well with this indicator, such as Support and Resistance levels, double Tops and Bottoms,...
Inputs:
- This indicator has only one input and that is "Analysis Period". This input declares how many bars and going to be used when finding the patterns of possible price reversion
Correlated ATR Bands | AdulariHow do I use it?
Never use this indicator as standalone trading signal, it should be used as confluence.
It is highly recommended to use this indicator on the 15m timeframe and above, try experimenting with the inverse feature and multipliers as well.
When the price is above the moving average this shows the bullish trend is strong.
When the price is below the moving average this shows the bearish trend is strong.
When the moving average is purple, the trend is bullish , when it is gray, the trend is bearish.
When price is above the upper band this may indicate a bearish reversal.
When price is below the lower band this may indicate a bullish reversal.
Features:
Purple line for bullish trend and gray line for bearish trend.
Custom formula combining an ATR and Hull MA to clearly indicate trend strength and direction.
Unique approach to moving averages and bands by taking the average of 2 types of MA's combined with custom ATR's, then multiplying these by correlation factors.
Bands to indicate possible trend reversals when price crosses them.
How does it work?
1 — ATR value is calculated, then the correlation between the source and ATR is calculated.
2 — Final value is calculated using the following formula:
correlation * atr + (1 - correlation) * nz(atr , atr)
3 — Moving average is calculated with the following formula:
ta.hma((1-(correlation/100*(1+weight/10)))*(ta.sma(source+value, smoothing)+ta.sma(source-value,smoothing))/2,flength)
4 — Bands calculation using multipliers.
MarsMine_EnvelopThis indicator is an indicator for use in 5-minute period day trading strategies.
The indicator derives a power power based on past closing prices and substitutes the power value into a multiplier of Euler's constant to derive a range.
Bands were increased by substituting multiples into the derived range, and each band has a role.
You will enter a buy or sell between the first and second bands, and become comfortable on the opposite first band.
The third band is set as a stop loss standard.
이 지표는 5분봉 단타 매매 전략에서 사용하기 위한 보조지표입니다.
해당 지표는 과거 종가를 기반으로 멱수를 도출해내고 해당 멱수값을 오일러 상수의 승수에 대입하여 범위를 도출해냅니다.
도출해 낸 범위에 멀티플을 대입하여 밴드를 증가 시켰으며 각 밴드들은 역할이 존재합니다.
첫번째와 두번째 밴드 사이에서 매수 또는 매도 진입을 하게 되며, 반대의 첫번째 밴드에서 익절하게 됩니다.
세번째 밴드는 손절기준으로 설정합니다.
