BabyShark VWAP Strategy What the code does:
This Pine Script implements a trading strategy based on two indicators: Volume Weighted Average Price (VWAP) and On Balance Volume (OBV) Relative Strength Index (RSI). The strategy aims to identify potential buy and sell signals based on deviations from VWAP and OBV RSI crossing certain threshold levels.
How it does it:
**VWAP Calculation**: The script calculates the VWAP using either standard deviation or average deviation over a specified length. It then plots the VWAP and its upper and lower deviation bands.
**OBV RSI Calculation**: It computes the OBV and then calculates the RSI using the cumulative changes in OBV. The RSI is plotted and compared against predefined levels.
**Table Visibility and Occurrence Counting**: It allows the user to display a table showing the number of occurrences where the price is above Upper Dev 2, below Lower Dev 2, crosses above a higher RSI level, or crosses below a lower RSI level.
**Entries**: Long and short entry conditions are defined based on the position of the price relative to the VWAP deviation bands and the color of the OBV RSI. Entries are made when specific conditions are met, and there hasn't been a recent entry.
**Exit Conditions**: The script includes stop-loss and take-profit mechanisms. It exits positions based on price crossing the VWAP or a certain percentage, and it prevents further trading after a certain number of consecutive losses.
What traders can use it for:
**Trend Identification**: Traders can use the VWAP and its deviation bands to identify potential trend reversals or continuations.
**Volume Confirmation**: The inclusion of OBV RSI provides confirmation of price movements based on volume changes.
**Entry and Exit Signals**: The script generates buy and sell signals based on the specified conditions, allowing traders to enter and exit positions with defined stop-loss and take-profit levels.
**Statistical Analysis**: The visibility of occurrence counts in the table allows traders to perform statistical analysis on the frequency of price movements relative to the VWAP and OBV RSI levels.
Search in scripts for "rsi"
Volume ValueWhen VelocityTitle: Volume ValueWhen Velocity Trading Strategy
▶ Introduction:
The " Volume ValueWhen Velocity " trading strategy is designed to generate long position signals based on various technical conditions, including volume thresholds, RSI (Relative Strength Index), and price action relative to the Simple Moving Average (SMA). The strategy aims to identify potential buy opportunities when specific criteria are met, helping traders capitalize on potential bullish movements.
▶ How to use and conditions
★ Important : Only on Spot Binance BINANCE:BTCUSDT
Name: Volume ValueWhen Velocity
Operating mode: Long on Spot BINANCE BINANCE:BTCUSDT
Timeframe: Only one hour
Market: Crypto
currency: Bitcoin only
Signal type: Medium or short term
Entry: All sections in the Technical Indicators and Conditions section must be saved to enter (This is explained below)
Exit: Based on loss limit and profit limit It is removed in the settings section
Backtesting:
⁃ Exchange: BINANCE BINANCE:BTCUSDT
⁃ Pair: BTCUSDT
⁃ Timeframe:1h
⁃ Fee: 0.1%
- Initial Capital: 1,000 USDT
- Position sizing: 500 usdt
-Trading Range: 2022-07-01 11:30 ___ 2023-07-21 14:30
▶ Strategy Settings and Parameters:
1. `strategy(title='Volume ValueWhen Velocity', ...`: Sets the strategy title, initial capital, default quantity type, default quantity value, commission value, and trading currency.
↬ Stop-Loss and Take-Profit Settings:
1. long_stoploss_value and long_stoploss_percentage : Define the stop-loss percentage for long positions.
2. long_takeprofit_value and long_takeprofit_percentage : Define the take-profit percentage for long positions.
↬ ValueWhen Occurrence Parameters:
1. occurrence_ValueWhen_1 and occurrence_ValueWhen_2 : Control the occurrences of value events.
2. `distance_value`: Specifies the minimum distance between occurrences of ValueWhen 1 and ValueWhen 2.
↬ RSI Settings:
1. rsi_over_sold and rsi_length : Define the oversold level and RSI length for RSI calculations.
↬ Volume Thresholds:
1. volume_threshold1 , volume_threshold2 , and volume_threshold3 : Set the volume thresholds for multiple volume conditions.
↬ ATR (Average True Range) Settings:
1. atr_small and atr_big : Specify the periods used to calculate the Average True Range.
▶ Date Range for Back-Testing:
1. start_date, end_date, start_month, end_month, start_year, and end_year : Define the date range for back-testing the strategy.
▶ Technical Indicators and Conditions:
1. rsi: Calculates the Relative Strength Index (RSI) based on the defined RSI length and the closing prices.
2. was_over_sold: Checks if the RSI was oversold in the last 10 bars.
3. getVolume and getVolume2 : Custom functions to retrieve volume data for specific bars.
4. firstCandleColor : Evaluates the color of the first candle based on different timeframes.
5. sma : Calculates the Simple Moving Average (SMA) of the closing price over 13 periods.
6. numCandles : Counts the number of candles since the close price crossed above the SMA.
7. atr1 : Checks if the ATR_small is less than ATR_big for the specified security and timeframe.
8. prevClose, prevCloseBarsAgo, and prevCloseChange : ValueWhen functions to calculate the change in the close price between specific occurrences.
9. atrval: A condition based on the ATR_value3.
▶ Buy Signal Condition:
Condition: A combination of multiple volume conditions.
buy_signal: The final buy signal condition that considers various technical conditions and their interactions.
▶ Long Strategy Execution:
1. The strategy will enter a long position (buy) when the buy_signal condition is met and within the specified date range.
2. A stop-loss and take-profit will be set for the long position to manage risk and potential profits.
▶ Conclusion:
The " Volume ValueWhen Velocity " trading strategy is designed to identify long position opportunities based on a combination of volume conditions, RSI, and price action. The strategy aims to capitalize on potential bullish movements and utilizes a stop-loss and take-profit mechanism to manage risk and optimize potential returns. Traders can use this strategy as a starting point for their own trading systems or further customize it to suit their preferences and risk appetite. It is crucial to thoroughly back-test and validate any trading strategy before deploying it in live markets.
↯ Disclaimer:
Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Simple_RSI+PA+DCA StrategyThis strategy is a result of a study to understand better the workings of functions, for loops and the use of lines to visualize price levels. The strategy is a complete rewrite of the older RSI+PA+DCA Strategy with the goal to make it dynamic and to simplify the strategy settings to the bare minimum.
In case you are not familiar with the older RSI+PA+DCA Strategy, here is a short explanation of the idea behind the strategy:
The idea behind the strategy 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 opened multiple PA (price average) layers are setup based on a specified percentage of price drop. When the price hits the layer another position with the same position size is is opened. This causes the average cost price (the white line) to decrease. If the price drops more, another position is opened with another price average decrease as result. When the price starts rising again the different positions are separately closed when each reaches the specified take profit. The positions can be re-opened when the price drops again. And so on. When the price rises more and crosses over the average price and reached the specified Stop level (the red line) 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.
This is the old RSI+PA+DCA Strategy:
The reason to completely rewrite the code for this strategy is to create a more automated, adaptable and dynamic system. The old version is static and because of the linear use of code the amount of DCA levels were fixed to max 6 layers. If you want to add more DCA layers you manually need to change the script and add extra code. The big difference in the new version is that you can specify the amount of DCA layers in the strategy settings. The use of 'for loops' in the code gives the possibility to make this very dynamic and adaptable.
The RSI code is adapted, just like the old version, from the RSI Strategy - Buy The Dips by Coinrule and is used for study purpose. Any other low/dip finding indicator can be used as well
The distance between the DCA layers are calculated exponentially in a function. In the settings you can define the exponential scale to create the distance between the layers. The bigger the scale the bigger the distance. This calculation is not working perfectly yet and needs way more experimentation. Feel free to leave a comment if you have a better idea about this.
The idea behind generating DCA layers with a 'for loop' is inspired by the Backtesting 3commas DCA Bot v2 by rouxam .
The ideas for creating a dynamic position count and for opening and closing different positions separately based on a specified take profit are taken from the Simple_Pyramiding strategy I wrote previously.
This code is a result of a study and not intended for use as a full functioning strategy. To make the code understandable for users that are not so much introduced into pine script (like myself), every step in the code is commented to explain what it does. Hopefully it helps.
Enjoy!
Minervini Pullback Strategy_Trend-Template QualifierGeneral Description and Unique Features of this Script
Introducing the ultimate trend-following (long-only) strategy that offers a unique feature you won't find anywhere else!
1. Our script/strategy utilizes Mark Minervini's Trend-Template as a qualifier for identifying stocks and other financial securities in confirmed uptrends. Mark Minervini, a 3x US Investment Champion, developed the Trend-Template, which covers eight different and independent characteristics that can be adjusted and optimized in this trend-following strategy to ensure the best results. The strategy will only trigger buy-signals in case the optimized qualifiers are being met.
2. Our strategy is based on supply/demand balance in the market, making it timeless and effective across all timeframes. Whether you're day trading using 1- or 5-min charts or swing-trading using daily charts, this strategy can be applied and works very well.
3. We also incorporate technical indicators such as RSI and MACD to identify low-risk pullback entries in the context of confirmed uptrends. By doing so, the risk profile of this strategy and drawdowns are being reduced to an absolute minimum, giving you peace of mind while trading.
Minervini’s Trend-Template and the ‘Stage-Analysis’ of the Markets
This strategy is a so-called 'long-only' strategy. This means that we only take long positions, short positions are not considered.
The best market environment for such strategies are periods of stable upward trends in the so-called stage 2 - uptrend.
In stable upward trends, we increase our market exposure and risk.
In sideways markets and downward trends or bear markets, we reduce our exposure very quickly or go 100% to cash and wait for the markets to recover and improve. This allows us to avoid major losses and drawdowns.
This simple rule gives us a significant advantage over most undisciplined traders and amateurs!
'The Trend is your Friend'. This is a very old but true quote.
What's behind it???
• 98% of stocks made their biggest gains in a Phase 2 upward trend.
• If a stock is in a stable uptrend, this is evidence that larger institutions are buying the stock sustainably.
• By focusing on stocks that are in a stable uptrend, the chances of profit are significantly increased.
• In a stable uptrend, investors know exactly what to expect from further price developments. This makes it possible to locate low-risk entry points.
The goal is not to buy at the lowest price – the goal is to buy at the right price!
Each stock goes through the same maturity cycle – it starts at stage 1 and ends at stage 4
Stage 1 – Neglect Phase – Consolidation
Stage 2 – Progressive Phase – Accumulation
Stage 3 – Topping Phase – Distribution
Stage 4 – Downtrend – Capitulation
This strategy focuses on identifying stocks in confirmed stage 2 uptrends. This in itself gives us an advantage over long-term investors and less professional traders.
By focusing on stocks in a stage 2 uptrend, we avoid losses in downtrends (stage 4) or less profitable consolidation phases (stages 1 and 3). We are fully invested and put our money to work for us, and we are fully invested when stocks are in their stage 2 uptrends.
But how can we use technical chart analysis to find stocks that are in a stable stage 2 uptrend?
Mark Minervini has developed the so-called 'trend template' for this purpose. This is an essential part of our JS-TechTrading pullback strategy. For our watchlists, only those individual values that meet the tough requirements of Minervini's trend template are eligible.
The Trend Template
• 200d MA increasing over a period of at least 1 month, better 4-5 months or longer
• 150d MA above 200d MA
• 50d MA above 150d MA and 200d MA
• Course above 50d MA, 150d MA and 200d MA
• Ideally, the 50d MA is increasing over at least 1 month
• Price at least 25% above the 52w low
• Price within 25% of 52w high
• High relative strength according to IBD.
We have developed an algorythm (for TradingView) that uses Minervini’s trend template as a qualifier. This means that the strategy only generates trading signals in case the selected elements of the trend template are being met. The user is fully flexible to adjust the requirements of this Trend-Template qualifier:
This strategy is normally applied to the daily chart ideal for selecting individual stocks for trend-following strategies. Nevertheless, Minervini’s principles are timeless and this alogrithmic strategy with the Trend-Template qualifier can also be applied to any other timframe.
The qualifier #9 (RS-Ratings) can be modified and optimized in the strategy’s settings to fit your individual needs.
In general, it should be noted that ideally all 8/8 trend template criteria are met. Stocks or other securities that meet only some of these 8 criteria can also be very promising candidates for this strategy, provided that backtesting yields good results.
The Pullback Strategy
For the JS-TechTrading pullback strategy, only stocks and other financial instruments that meet the selected criteria of Mark Minervini's trend template are considered. If not, the strategy will not generate any signals.
Further prerequisites for generating a buy signal is that the individual value is in a short-term oversold state (RSI).
When the selling pressure is over and the continuation of the uptrend can be confirmed by the MACD after reaching a price low, a buy signal is issued by the pullback strategy.
Stop-loss limits and profit targets can be set variably.
Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a technical indicator developed by Welles Wilder in 1978. The RSI is used to perform a market value analysis and identify the strength of a trend as well as overbought and oversold conditions. The indicator is calculated on a scale from 0 to 100 and shows how much an asset has risen or fallen relative to its own price in recent periods.
The RSI is calculated as the ratio of average profits to average losses over a certain period of time. A high value of the RSI indicates an overbought situation, while a low value indicates an oversold situation. Typically, a value > 70 is considered an overbought threshold and a value < 30 is considered an oversold threshold. A value above 70 signals that a single value may be overvalued and a decrease in price is likely , while a value below 30 signals that a single value may be undervalued and an increase in price is likely.
For example, let's say you're watching a stock XYZ. After a prolonged falling movement, the RSI value of this stock has fallen to 26. This means that the stock is oversold and that it is time for a potential recovery. Therefore, a trader might decide to buy this stock in the hope that it will rise again soon.
Moving Average Convergence Divergence (MACD)
The MACD (Moving Average Convergence Divergence) is a technical indicator used in both short-term and long-term trading strategies. The indicator was developed by Gerald Appel and is one of the most well-known indicators for the stock market.
The MACD consists of two lines calculated by the difference between two moving averages. The first line is a fast moving average that targets a short period of time. The second line is a slow moving average that targets a longer period of time. In addition, a trigger line is calculated, which consists of another moving average of the MACD line.
The MACD line is the difference between the fast and slow moving average.
The greater the difference between the two lines, the more likely a subsequent price increase. The lower the difference, the more likely a subsequent price drop is.
If the MACD line crosses upwards over the trigger line, this is a buy signal that signals a potential price increase. If the MACD line crosses down below the trigger line, this is a sell signal that signals a potential price weakening.
This strategy is applicable to all timeframes and the relevant parameters for the underlying indicators (RSI and MACD) can be adjusted and optimized as needed.
Backtesting
Backtesting give outstanding results on all timeframes and drawdowns can be reduced to a minimum level. Swing-Traders (daily charts) will see that the strategy does not give any buy signals during market corrections and bear markets.
Settings for backtesting are:
- Period from Jan 2000 until now
- Starting capital 100k USD
- Position size = 25% of equity
- 0.01% commission = USD 2.50.- per Trade
Other comments
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The trend-template qualifier is highly selective and filters out the most promising swing-trading entries. As a result, you will normally only find a single-digit number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• As a result, traders need to apply this strategy for a full watchlist rather than just one financial security.
Catching the Bottom (by Coinrule)This script utilises the RSI and EMA indicators to enter and close the trade.
The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
An exponential moving average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average. An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average (SMA), which applies an equal weight to all observations in the period.
The strategy enters and exits the trade based on the following conditions.
ENTRY
RSI has a decrease of 3.
RSI <40.
EMA100 has crossed above the EMA50.
EXIT
RSI is greater than 65.
EMA9 has crossed above EMA50.
This strategy is back tested from 1 April 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include ETH on the 5m timeframe, BNB on 5m timeframe, XRP on the 45m timeframe, MATIC on the 30m timeframe and MATIC on the 2H timeframe.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Road To DubaiROAD TO DUBAI
Useful for daily trading over all type of asset, from Stock to Crypto, Forex and Commodities. It works best with 5min to 1hr graphs, if you are a intraday trader.
This is not a simple mashup of indicators, because you can add them as your own.
This script is more like a tool to understand price action based on indicators position . Thanks to cross call based on MACD , RSI with EMA applied and few index realtime mapping, this tool will let you reduce time effort for graph analysis .
As extra feature it will let you to try different strategies , all fully customizable.
I've tried my best to keep it readble, and easy to use. The best way to learn to use it, is to disable all features from configuration and try one by one.
CONFIGURATION TIPS : Click "Settings Gear" in the Upper Right Corner and disable "Indicator Arguments"
HOW TO PROPER SETUP
Road to Dubai 3 is semiautomatic on finding best Long and Short areas, and plot on the chart.
From configuration menu you can set a Backtrace period and sensibility for RSI EMA10, RSI EMA80 and MACD on your Timeframe, 5min, 30min, 60min.
Usually when configured, those parameters works fine on almost every asset.
You only need to start understanding signals.
STANDARD FEATURES
VWAP : Green/Red line. It will reset everyday at 00.00.
EMA80 : White Line
BLUELINES : Positive and negative overextend value from VWap . This is based on a range of bar and it will extend on the opposite side the lower or higher candle. Useful for understading where price can arrive, expecially if a spike will appear.
Those indicators are quite useful for understading trends, price positions and maximum price range.
RSI EMA10 OVERBOUGHT / OVERSOLD
Yellow arrow marks where RSI arrived at his Top or Bottom. If on different timeframes (5min, 30min and 60min) something similar happen area is filled with Red or Green.
This is base on EMA10 applied to RSI (I usually refer at it as Yellow Line on my indicator HighFreq Trader)
To find good values please try High Freq Trader 1.3
RSI EMA80 CALL
Red Cross or Green Square advice for a really potential inversion of trend. When a Silver bar appear, this means the same call was triggered on different Timeframe in the sametime.
This is based on EMA80 applied to RSI (I usually refer at it as Blue Line on my indicator HighFreq Trader).
To find good values please try High Freq Trader 1.3
MACD CALL
Based on MACD with standard settings. When triggered, a lime Triangle appears. Differents size based on timeframe (5min smaller, 60min bigger). If the same call is triggered on the same place a Lime Bar appear on the opposite side of trend (this is a graphical contents, bacause with all enabled, standard use, can be difficult to read signals).
In Menu Settings you will be able to set your best parameter for your asset.
MACD FIBONACCI EXTRA FEATURE
If you want you can enable a Fibonacci draw based on MACD . This works at his best (on my opinion) with 30min MACD
EXAMPLE
NATURAL GAS
In this chart 30min you can see all calls triggered for a Short. Yellow RSI Arrow, Red Cross, Macd Triangle and Colored Red, Lime and Silver Bars are all calling for Short.
In this way you can see in notime if this can be a perfect moment for take position
VIX VXN DXY CALLS
If VIX , VXN is triggered a small Green Dot will appear. If both are in the same time a bigger Dot appear. Very useful to find trend inversion.
If DXY is triggered a Red Dot will appear (only on Daily Chart ). Very Useful to understand trend inversion on whole market.
VOLUMES REMINDERS
Find if there was an High Volume traded (HV) or Low Volume Traded (LV) in the near past. Useful to understand if some tricky situation could happen (like a sudden sell, an accumulation or distribution)
WaveTecs StrategyWelcome to the Backtesting version of "WaveTecs Strategy", the indicator itself is an invite-only script called "WaveTecs Indicator" on TradingView.
WaveTecs Strategy
WaveTecs is a Strategy that combines Wave Trend Oscillator and verifies wave momentum by using RSI and Stochastic Oscillator Values.
What is Wave Trend?
One of the most effective indicators in identifying swings is the Wave Trend indicator. Wave Trend plots waves using highs and lows between an upper band and a lower band. It looks for the opening and closing of a new wave trend movement as well as overbought and oversold areas.
How does this modified strategy work?
By using RSI and Stochastic values we are able to verify Wave inflection points to determine if there is a suitable amount of momentum to ride the swing and make profitable trades. Positions are taken or closed based on the rising or falling momentum.
Each value input can be adjusted to best suit the type of market you are trading in. By using the strategy we can optimize these value inputs to yield greater net profits. I have found the RSI and Stochastic values hugely impact entries and exits regarding trades.
For Long conditions:
- RSI & Stochastic needs to be increasing and moving out of oversold conditions to show positive momentum.
- Falling momentum results in a sell signal. I have found RSI less than 65 to be sufficient in most markets however this can be adjusted at any time to yield different results depending on your comfort level.
For Short conditions:
- RSI & Stochastic needs to be decreasing and moving out of overbought conditions to show negative momentum.
Generally, Wave Trend Strategies only take trades that are outside of the bands. This strategy allows trades inside and outside of the bands, which can be selected under the input section title "Aggressive Trading". Trading in this mode is more frequent as signals are often. Due to volatility in crypto markets, I have defaulted the source for Wave Trend waves to be Open/High/Low/Close Average which yielded great results. High/Low/Close average works very well for all other securities, and can easily be adjusted through the drop-down menu inside the inputs.
Works for all types of markets. Parameters can be adjusted but not required as indicator values are standard in the industry.
The default parameters are set to those typically used in the markets currently. However, I have found that if you adjust you to adjust the parameters based on your asset and time frame desired you will yield different results.
----------------
For example:
----------------
ETHUSDT - 4 HR, results are shown below
Wave Trend Parameters:
Aggressive Trading: Yes
Channel Length: 12
Average Length: 24
Overbought Top: 90
Overbought Bottom: 75
Oversold Bottom: -90
Oversold Top: -55
Source: hlc3
Strategy Type:
Trade Direction: Long Only
Stochastic Inputs:
Stoch Length: 18
Smoother %K: 5
Moving Average %K: 4
%K Lower Limit: 21
%K Upper Limit: 80
%K Crossunder Sell: 80
Relative Strength Index Inputs:
RSI Lower Limit: 30
RSI Upper Limit: 70
RSI Sell Value: 68
==================
WaveTecs Features
==================
Profitable Trading Strategy;
Aggressive Trading feature for more trades, with earlier entries and exits;
Customizable inputs to fine-tune your trades;
Buy & Sell Alerts (Indicator Only);
Overlay indicator only to show alerts, WaveTecs Strategy needed to see Wave Trend;
Bot Integration through webhooks;
Two different strategy modes: Long Trades Only or Long & Short Trades
Adding new features & updates whenever possible.
Add both WaveTecs Indicator and WaveTecs Strategy to your chart. WaveTecs Indicator only plots Buy & Sell Alerts, whereas WaveTecs Strategy lets you see what the strategy is doing.
Dankland Playground Moneymaker - V2“version 2” of my playground bot script. Its essentially a powerhouse suite of strategies. Although it is similar to the previous script, it nets different results as sections have been changed. Such as the somewhat reluctant removal of the Chande Momentum... The RSIs have also been updated, this was one of the main changes. RSIS now include a Moving Average cross of RSI to generate signals above and below the given thresholds instead of simply on crossing a threshold. This should give greater functionality overall. Most functions including Moving Averages have been updated to include a wider range of kinds of moving averages. This includes not just the moving average cross, but MACD and RSIs as well. I tried to perform the same upgrade on the %B, Stochastics and SMI, but hit the unpacked code limit of 60,000 lines... So, more “versions” will have to come for future “upgrades”, with the recognition that there will be cases where the old, “downgraded” versions may perform better and that some people (like myself) may continue to use them on some markets until I/we devise superior settings on the new ones for said markets. For instance, instead of replacing my 1 hr BTCUSD bot (where I used the now deleted Chande to pretty pleasing affect...) I made a new one for LINKUSD 10 min so I can have both running for now and work on replacing the BTCUSD later.
How it works basically is this... you have 16 oscillators which can all be used as independently as you wish. They can be split up into different groups or ran all together.
When in separate groups they should not be able to sell eachothers positions without triggering a full stop loss by turning the Independence/Stop All switches on. Every single oscillator has its own entry and exit position sizing which can be stated as either a percent of balance or a flat amount of contracts (or both combined). Each oscillator has a minimum amount of profit you can tell it to sell it, which is calculated from the average cost of your current position, which does include all groups. This works out to help you average out better entry and exit prices, essentially a method of DCAing.
You can set the minimum sale amount, which is to keep it from placing orders below your exchanges minimum dollar trade cost.
All this functionality combined also ensures more accurate back tests by ensuring that the script simply cannot spend money it doesn't see as in the balance, whereas other scripts will use a percentage of equity, and once 100% of your equity is in BTC for instance, it will keep buying more BTC for free and thus spoof up backtest numbers. If you look through the strategies here, many people claim to have amazing scripts and then you look into it and this is happening and skewing their numbers. These people are either very ignorant or what they made or scam artists and trolls in my opinion.
This version also includes On Bar Close switches for each oscillator. When switched on, signals are only allowed to generate on Bar Close. This helps to prevent retriggering from live signals, which when you are running this many oscillators, will become a problem! However, in most cases, you do not need to generate signals intrabar, as backtests will show, ignoring intrabar buys and sells (intrabar stop losses can still be very important though!) won't exactly keep you from high profitability strategies, but rather, allowing elements of chaos from live indicators moving up and down intrabar will, in fact, drift your actual results further and further from the backtest. You want an accurate backtest though. So choose wisely when you turn these off and you will do better.
The included oscillators are as follows:
NO MORE Chande Momentum cross – REMOVED – I was hitting PINE code limits here so I had to make choices and this one simply had to go. Begone!
Moving Average Cross
MACD cross
%B Bollinger cross
Stochastic cross + region filter
Stochastic RSI cross + region filter
SMII cross and region filter
Three RMIs
Know-Sure-Thing line-cross
Coppock Curve line-cross
TRIX line-cross
RSI of MA w/ MA cross
RSI of MA of KST w/ MA cross
RSI of MA of Coppock Curve w/ MA cross
RSI of MA of Trix w/ MA cross
So the idea is that this is essentially multiple strategies combined into one backtestable house. Balance is calculated for all position sizes in order to try to prevent false entries that plague so many scripts (IE, you set pyramiding to 2, each buy $1000, initial balance $1000, and yet it buys two orders off the bat for $2000 total and nets 400% profit because the second was considered free, happens on 90+% of scripts on Tradingview if you aren't very very careful!)
You tune each indicator and position size them so that they work together as well as you can and in doing so you are able to create a single backtest that is capable of running a bot, essentially, between multiple strategies - you can run a slower Moving Average cross, a faster SMI cross or MACD , or Bollinger that grabs big moves only, all the while having MACD trade small bonuses along the way. This way you can weight the Risk to Reward of each against eachother.
I will not try to claim this is something you can open and with no work have the best bot on the planet. This scripts intention is to take a lot of relatively common trading strategies and combine them under on roof with some risk management and the ability to weigh each against eachother.
If you are looking for a super advanced singular algorithm that tries to capture every peak and valley exactly on the dot, this is not for you. If you are looking for a tool with a high level of customizability, with a publisher who intends to update it to the best of his ability in accordance to seeking to make the best product that I personally can make for both myself and the community (because I will be using this myself of course!) that was specifically designed with the intention of performing well in spot markets by averaging low entry costs and high exit costs, this is for you! That is the exact intention here. It can certainly work with margin, but you will have to take extra care in setting your stop losses. I intend to make a version capable of going short which will be included as part of the package. It may take some work to keep all of the risk management working as well for shorts though. There will be more scripts added to the “package” as I hit the limit on this one a few times and have had to keep some ideas out already.
The current backtest shown is hand-optimized by myself for Link /USD 10min market (Binance US – shouldn't need much work to fit to other exchange markets) with multiple stop losses.
VRSI-MARSI StrategyI wanted to create an indicator which resembles price movement, aside to volume movement.
The "yellow-blue" line is the MA(5) of the RSI (9) of closing price.
The "orange" line is the MA(5) of the RSI (9) of Volume .
(Default plot of RSI and VRSI is not visible but can be made visible ("Settings" > "Style" > set "Opacity" of "RSI & VRSI"))
The Long (Buy) condition is triggered when the MA(5) of the RSI (9, close) goes up.
The Short (Sell) condition is triggered when the MA(5) of the RSI (9, close) goes down.
Comparing the price movement with the "orange" Volume line helps to spot a possible trend change,
for example when price goes up and an ascending Volume line starts to flatten or starts descending,
this could be a sign that the Bullish trend is weakening, predicting a possible trend change.
Or, when for example a downwards price movement is accompanied with a rising Volume line, this can be a sign of large Bearish power.
Because it still is a RSI indicator, the midline (50), and Oversold/Overbought area's (20-30 & 70-80) are important to watch, especially the MARSI!
A second strategy is made (VRSI-MARSI Strategy 2) where the Long/Short condition is triggered when "MA RSI (close) - MA RSI ( Volume )" crosses.
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The Long & Short entries, as well as the Entry Close are visible 1 bar after the trigger.
When the blue line changes in a yellow line (and vice versa) it will show a candle earlier (see yellow dashed lines = (1)).
Also, the condition is fulfilled when the candle closes (2), but the order doesn't take place in the same bar, but the next (3).
Because this is a strategy the "actual Order" will not take place at the "Close" of the candle (2), but at the "Open" at the NEXT candle (3).
I also have this strategy as a study (A+B), where the "Buy" & "Sell" shows a candle earlier.
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The entries are default 5% of equity, without pyramiding, which already gives large profits.
A large part of the profit is because of the Entry Close of the Long & Short entries.
You can easily turn these off (Settings > Inputs) to see what profit the strategy gives without Entry Close.
Here they are disabled:
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More information available in the script ;-)
Logic Flow Signals & Backtest [bercutiatia]To understand the advanced logic of the tool, it is essential that you carefully read each topic and check the visual examples in this presentation.
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Who is the Logic Flow Signals & Backtest tool recommended for?
Ideal for traders looking to increase the reliability and level of their operations. Recommended for those who want to create rigorous confluences, validate strategies with backtesting, and transform emotional management into systematic and measurable processes.
How can the Logic Flow Signals & Backtest tool help me?
High-confidence signals! You combine TradingView indicators and create a single robust signal, eliminating the frustration of having to spend hours in front of the chart and still clicking at the wrong time. This ensures that your entry is validated by logic, not emotional impulse.
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Logic Flow Signals & Backtest is a versatile and powerful tool designed to test and validate your trading ideas with indicators from the TradingView community.
Extreme flexibility: Allows you to combine indicators available on TradingView (EMAs, RSI, MACD, SMC, etc.) to create custom entry and exit logics.
Sequential Logic: Goes far beyond simple crossovers. You can define rules where signal A must occur before signal B — and, if desired, before signal C or D — to validate an entry. Add time, order, and context filters, creating truly intelligent sequential logic that generates a single final alert only when all conditions align.
With Stages (Stage 1, Stage 2, etc.), your entries follow the exact sequence you define. And the best part: you no longer need to spend hours in front of the chart waiting for confluences. Simply set up your stages once, create an alert in TradingView, and the system will automatically notify you when the ideal combination of signals occurs.
Sequence Invalidation: Offers the option to define conditions that, if they occur, immediately cancel an ongoing entry sequence, helping to avoid entries in unfavorable scenarios.
Explaining the first image example (chart below):
LONG INDICATOR 1 (Stage 1): The market confirms a change in character (CHoCH Bullish). The system enters an alert state awaiting the confluence of the next indicators.
LONG INDICATOR 2 and 3 (Stage 2): Entry is only released when the SMA17 crosses above the SMA72 (indicator 2), but with one condition: The SMA72 must be ABOVE the SMA305 (indicator 3); Without this alignment of indicator 3, the signal of indicator 2 does not occur.
LONG INDICATOR 4 (Invalidation Rule): If at any point in the sequence the SMA72 crosses below the SMA305, the setup is immediately canceled and no entry signal is generated. The sequence restarts with indicator 1.
EXIT LONG (Hybrid Exit TP + SIGNAL): The trade seeks a TP target of 1000 ticks, but has a technical "Trailing Stop": if the trend reverses (Exit Long Indicator 1 = SMA72 crosses below the SMA305) before the target, the position is closed to protect capital.
SHORT INDICATOR 1 (Stage 1): Identification of weakness in the market with a Bearish CHoCH.
SHORT INDICATOR 2 and 3 (Stage 2): Entry is only released when the SMA17 crosses below the SMA72 (indicator 2), but with a strict condition: The SMA72 must be BELOW the SMA305 (indicator 3); Without this STATE of indicator 3, the signal from indicator 2 does not occur.
SHORT INDICATOR 4 (Invalidation Rule): If at any point in the sequence the SMA72 crosses above the SMA305, the setup is immediately canceled and no entry signal is generated. The sequence starts again with indicator 1.
EXIT SHORT (Hybrid Exit TP + SIGNAL): The trade seeks a target of 1000 ticks, but has a technical "Trailing Stop": if the downtrend reverses (Exit Short Indicator 1 = SMA72 crosses above the SMA305) before the target, the position is closed to protect capital.
In this strategy, we use the external indicators: Multiple MTF MA and Smart Money Concepts (Advanced)
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Stage Duration: In STAGE DURATION , you control the maximum time (in candles) allowed for each transition between stages to occur. If the time limit expires before the next stage is reached, the sequence is reset. Keep it at 0 to disable the time limit.
The "Stage Duration" function is available in four separate blocks on the settings panel:
- LONG - STAGE DURATION: Controls the time limit (in candles) between Long entry stages (for example from Stage 1 to Stage 2).
- LONG EXIT - STAGE DURATION: Controls the time limit between Long exit stages.
- SHORT - STAGE DURATION: Controls the time limit between Short entry stages.
- SHORT EXIT - STAGE DURATION: Controls the time limit between Short exit stages.
Explaining the second image example (chart below):
Stage 1 (INDICATOR 1): New Fair Value Gap (FVG) Bullish Confirmed.
- Meaning: The move starts with a bullish FVG (Fair Value Gap), indicating a confirmed imbalance where buyers were much more aggressive than sellers.
Stage 2 (INDICATOR 2): EMA10 crossing above the EMA50.
- Meaning: Immediately after the FVG trigger, the fast moving average (10 periods) crosses the intermediate moving average (50 periods). This confirms that the initial FVG impulse was not an isolated event but the beginning of a short-term trend.
Stage 3: In this final stage, we require two simultaneous confirmations to validate the entry:
- INDICATOR 3: The EMA10 crosses above the EMA100, indicating that the movement has enough strength to break through larger barriers.
- INDICATOR 4: The RSI must be above its own moving average (SMA14). This ensures the asset is gaining momentum at the exact moment the averages are broken, avoiding entries in "tired" markets.
Stage Duration: The most important feature of this setup is the restricted time window.
- Rule: From Stage 1 to 2, and from Stage 2 to 3, the maximum interval to accept confluences is only 3 candles.
- Why this is vital? If the market took 20 candles to align these conditions, it would indicate weakness or indecision. By demanding that everything happens within a maximum of 3 candles per step, the setup filters only the moves where buying pressure is urgent and aggressive, increasing the probability of an explosive move in favor of the trade.
Asymmetric Risk Management: To complement a high-probability and high-pressure setup, we use aggressive risk management:
- Stop Loss (Technical/Short): 200 Ticks. If the buying pressure fails quickly, we exit early with a small loss.
- Take Profit (Long Target): 1000 Ticks. We aim to ride the impulse "leg" that the setup identified.
- Risk/Reward: 5:1. This means a single winning trade covers five losing trades, making the strategy mathematically viable in the long term.
In this strategy, we use the external indicators: Multiple MTF MA , Smart Money Concepts (Advanced) and Relative Strength Index (RSI) .
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Multiple Operating Modes
It is not limited to sequences. It can operate by confluence (where all signals must be valid at the same time), by single trigger (only one signal is required), or by "OR" logic (any one of the defined signals).
- If you use only Stage 1 in more than one indicator session, the entry will only occur if all enabled conditions are true simultaneously.
- Any condition defined as OR can trigger the entry by itself.
- If only one condition block is enabled, the single indicator will function as a simple signal.
Multiple and Simultaneous Exits
It allows for the configuration of exits by both indicators and TP/SL targets. The strategy will close the trade as soon as any of these conditions are met first (indicator signal, profit target, or loss limit
Integrated Risk Management
It includes Stop Loss and Take Profit exits by percentage and ticks, which are easy to configure and essential for risk management. The strategy calculates the exact TP and SL prices based on your entry price and monitors the market on every tick.
Explaining the Third Image Example (Chart Below)
The move was validated by a 4-step logical sequence (Stage 1) and managed by a hybrid exit system.
Short Indicator 1, 2, and 3: The price (Close) crossed below the SMA200, SMA72, and SMA17 averages simultaneously.
- What this means: When a single candle has the strength to break below the short-term (17), mid-term (72), and long-term (200) averages, it indicates a high probability for the price to seek lower levels.
To reinforce Indicators 1 through 3, we added an extra layer of confirmation.
Short Indicator 4: The Positive Volume Index (PVI) needed to be below its own long-term average (EMA300).
- Why this is important: PVI below the average confirms that selling volume is dominant, validating that the break of the averages was not just noise.
Triple Exit Management (Maximum Security)
The great advantage of this tool is the ability to manage risk dynamically. In this trade, we configured three simultaneous exit conditions, where the first one to be met closes the position:
1. Financial Target (TP): A fixed Take Profit of 15%.
2. Exit Short Indicator 1 (Technical Exit 1): If the average (SMA72) crosses above the average (SMA200), the trade is closed.
3. Exit Short Indicator 2 (Technical Exit 2): If the PVI crosses above the EMA300, indicating an entry of buying strength, the trade is closed.
"OR" Logic: The tool monitors these conditions in real-time. Whichever occurs first triggers the exit, ensuring you lock in profit (TP) or protect your capital at the first sign from the indicators.
In this strategy, we use the external indicators: Multiple MTF MA and Positive Volume Index .
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Reversal Mode (Stop and Reverse)
The Reversal Mode (Stop and Reverse) allows a new signal in the opposite direction (e.g., a SELL signal) to automatically close an existing position (e.g., BUY) and open a new one (sell). This "stop and reverse" function can be enabled or disabled in the settings, giving you full control over whether the strategy should only exit (awaiting a new signal) or immediately reverse the position.
Explaining the Fourth Image Example (Chart Below)
In this example, we demonstrate a setup focused on capturing every market "flip," keeping the trader positioned 100% of the time ("Always-in"), a technique widely used in automation.
- Long Entry: Occurs immediately upon confirming a bullish change of character (New CHoCH Bullish).
- Short Entry: Occurs immediately upon confirming a bearish change of character (New CHoCH Bearish).
- Exit (The Differentiator): We are not using fixed TP or SL here. The exit is triggered by Automatic Reversal.
The Power of "Exit by Opposite Signal"
Notice the labels on the chart: "Close Short" followed immediately by a "Long." This happens because the Allow Reversal function is enabled in the tool's settings.
When the market generates a buy signal, the tool understands that the sell thesis has been invalidated. It simultaneously sends an order to close the Short position and open a new Long position.
When to use this exit rule?
- Capturing Long Trends / Directional Movements: Ideal for volatile assets where you want to ride the trend until the market structure effectively changes.
- Operational Simplification: Eliminates the need to guess profit targets and acts as a loss limiter when the price moves against your position. The market dictates when to enter and when to exit.
Hybrid Flexibility:
The strongest point of Logic Flow is that you don't have to choose just one method. Reversal can be used in two ways:
1. Individually (as in the image): Reversal is the only form of exit. You stay in the move until the opposite signal.
2. Combined (Hybrid): You can enable Reversal and configure a safety Stop Loss + technical Take Profit (Exit Long/Short Indicator).
- Example: If the price hits your TP/SL first, you exit. If the market turns before the TP, the Reversal takes you out of the trade and generates a new trend alert.
In this strategy, we use the external indicators: Smart Money Concepts .
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Backtesting: Far beyond creating logic and generating signals, Logic Flow Signals stands out due to its Integrated Backtest.
Backtesting serves as a reality check for the trader. It takes the strategy out of the realm of "imagination" and puts it to the test against historical data.
Here are the 4 main practical uses:
1. Verifying Feasibility (Proof of Concept): The most obvious use is to answer: "Does this idea make money?". Many strategies look visually perfect on the chart, but when you run the backtest, you discover that brokerage fees or frequent "stops" consume all the profit.
2. Knowing the "Worst-Case Scenario" (Drawdown): Maximum Drawdown: It shows you what the largest accumulated drop the strategy has ever experienced was. By identifying a Drawdown that exceeds the desired risk tolerance, the backtest allows for parameter optimization in search of a more efficient balance between risk and return.
3. Fine-Tuning (Optimization): It allows you to make changes such as: Increasing the profit target, changing the stop, removing an indicator, changing the chart timeframe, among other actions. You can test various variations instantly to find the most efficient configuration.
4. Expectation Management and Discipline: Backtesting does not eliminate fear nor guarantee that the future will repeat the past, but it serves as a reference map.
The Real Role: Aligning expectation with reality.
In the image below, you can check out how a backtest result is generated:
To understand the backtest results shown above, check the chart and the detailed operational logic below:
This operational example seeks to identify altcoins that are demonstrating an explosive decorrelation relative to Bitcoin. The logic is: we want to buy only the assets that are outperforming the market leader, precisely at the moment when speculative money (Open Interest) heavily enters the market.
For the buy signal (Long) to be triggered, three conditions must be simultaneously true (Stage 1):
Long Indicator 1 (Altcoin Strength): The asset's RSI must be above the 70 level (Overbought), indicating extremely strong bullish momentum.
Long Indicator 2 (Bitcoin Weakness): Bitcoin's RSI must be below the 50 level. This confirms that the Altcoin's rally is genuine and independent.
Long Indicator 3 (Money Flow): The Open Interest (open contracts) must be above the Extreme level of the OI DELTA indicator. This validates that new money is aggressively entering the asset to sustain the rally.
Risk Management: In this example, we configured an aggressive target to capture the altcoin volatility:
- Take Profit: 100%
- Stop Loss: 20%
- Risk/Reward: 5:1
In this strategy, we use the external indicators: RSI Crypto Strength (Asset vs BTC) and Open Interest Delta .
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Configuring an Indicator Block
Each block (BUY INDICATOR 1, BUY INDICATOR 2, ...) allows you to define a complete condition.
- Enable (Activate): Simply turns this indicator block on or off.
- Source A: The first value you want to analyze.
example: The Closing Price (Close), Opening Price (Open), or another TradingView indicator.
- Condition: How 'Source A' will be compared.
example: Crossover/Crossunder, Greater Than, Less Than, Cross Up.
- Comparison Type: The option that defines whether you will compare 'Source A' with a fixed number or with another indicator.
- Fixed Value: Used if you selected "Fixed Value".
example: For an RSI greater than 70 condition, Source A would be the RSI, the Condition would be Greater Than, and the Fixed Value would be 70.
- Source B: Used if you selected "Source B".
example: For a condition where the EMA10 crosses above the EMA200, Source A would be the EMA10, the Condition would be 'Cross Up', and Source B would be the EMA200.
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Configurable Alert Signals
Configurable Alert Signals: The tool allows for the creation of fully customized alerts for different types of events, such as entries, signal-based exits, take profit, and stop loss. These alerts can be used for both strategy automation and manual, real-time notifications.
The message field is highly flexible: it accepts dynamic placeholders, JSON structure, UUID identifiers, or any custom text, allowing integration with other external tools and systems via webhook.
Configuring Your Messages:
- LONG/SHORT - ALERTS: Defines the message for new entries.
- LONG/SHORT INDICATOR EXIT - ALERTS: Defines the message for signal-based exits (e.g., moving average cross).
- REVERSAL - ALERTS: Defines the message for when a position is closed by an opposite signal (stop-and-reverse).
- LONG/SHORT TP/SL EXIT - ALERTS: Defines the message for exits triggered by take profit (TP) or stop loss (SL), via percentage or ticks.
A Single Alert to Control Everything
You don't need to create separate alerts for "Buy," "Sell," or "Exits." On a single screen, you can create strategies by defining entries, signal-based exits, profit targets, or stop limits.
Alert Times (Operating Window)
In the Alert Times section, you can define a specific time (and time zone) for the strategy to generate entry or exit signals.
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To create your alert, simply follow these steps:
- Condition: Select the script name: "Logic Flow Signals & Backtest".
- Message: Insert only the placeholder: {{strategy.order.alert_message}}
Once this single alert is active, it will "listen" to all orders executed by the strategy.
This means you can have your Long-Term, Short-Term, Signal-Based Exits, and TP/SL strategies active simultaneously. When any of these events are plotted on the chart, the script will send the customized message (which you wrote in the fields) to your single alert.
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Advanced period filters: Allow you to test the strategy in specific date ranges, over the last X days, or over the last X bars, facilitating performance analysis in different market environments.
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Status Panel: Displays a clear summary of all active rules and settings directly on the chart, facilitating the visualization and confirmation of the running logic.
Additionally, it has a settings box where you can activate or deactivate the panel, choose its position (such as at the bottom or side), and adjust its size.
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The Thumbnail strategy uses the following external indicators: Multiple MTF MA and Breakout Finder .
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Final Considerations:
The Logic Flow Signals & Backtest tool is a versatile and powerful system, designed to test and apply trading ideas based on multiple indicators from TradingView.
Its differential is being a customization environment: the script does not have integrated graphical indicators, as the objective is precisely to allow the user to combine and integrate multiple existing indicators in the TradingView community to build unique entry and exit logics.
It offers flexibility and precision, but the true value emerges when the trader integrates the tool into a consistent trading plan, with efficient risk management (Stop Loss and Take Profit), leverage control, and a professional mindset.
Important: Risk of Repainting (Unstable Data): Avoid indicators that 'repaint' (those that change their values in past bars after the closing of new candles). The backtest will be invalidated, and the actual performance of the strategy will fail.
Legal Warning and Didactic Purpose:
It is fundamental to understand that all visual examples, charts, and texts contained in this description do not constitute financial advice, buy or sell recommendations, nor a promise of easy or guaranteed gains.
This is an advanced support tool, not an automatic profit system. Use the integrated backtesting to evaluate the historical behavior of strategies before real execution and understand how different market conditions impact your results. The sole purpose of this material is to demonstrate the logical and execution capacity of the script, serving as a didactic guide for you to test and validate your own ideas.
Conclusion and Risk Warning:
Success in financial markets comes not only from a set of charting indicators, but from the trader's understanding, practice, and discipline. Our objective is to provide a robust, customizable, and intuitive solution, created to enhance your technical analysis and broaden your strategic vision, without replacing critical thinking and conscious decision-making.
Finally, remember: past results do not guarantee future performance. The real differentiator lies in continuous learning, testing, and evolution.
Kev's RSI2 SMA50 Strategy⭐ Kev’s RSI2 SMA50 Strategy — Institutional Edition (TSX Optimized + RR Filter)
A professional swing-trading system based on Larry Connors’ RSI(2) mean-reversion framework, optimized for TSX equities. Designed for Daily timeframe trading with institutional trend alignment, volatility filtering, and strict risk-reward controls.
📌 Overview
This strategy enhances the classic RSI(2) setup with:
• Strong trend confirmation (SMA50 + Weekly SMA50)
• Deep pullback detection (RSI2 < 3)
• Structural swing-based stop-loss
• Fixed 2R profit target (non-repainting)
• Optional Connors RSI (CRSI) confirmation
• Volatility filtering via ATR range
• Mechanical, deterministic, no-discretion rules
Works best on TSX large & mid-caps, ETFs, and liquid equities.
🔍 Core Philosophy
Buy strong stocks on pullbacks → Price must be above SMA50 + Weekly SMA50.
Pullback must be statistically meaningful → RSI(2) < 3.
R:R must justify the trade → Swing-low SL + 2R target with structural room to hit TP.
🧠 Entry Conditions (Non-Repainting)
• RSI(2) < 3 → Identifies extreme short-term oversold dips.
• SMA50 Filter → Ensures uptrend alignment.
• Weekly HTF Filter (Default = 1W) → Confirms broader trend direction.
• ATR Filter → Rejects volatile bars (range < ATR(14) × 2.2).
• Optional:
– SMA50 Slope (positive trend strength)
– Bullish Reversal Candle
– Connors RSI < 20 (deep pullback confirmation)
🎯 Risk Management
All levels are locked at entry and never repaint.
• Swing-Low SL (last 5 bars)
• 2R Profit Target = Entry + (Risk × 2)
• R:R Feasibility Filter → Only enters if recent swing high is above TP.
• Optional RSI Exit → Exit when RSI2 > 90 (enabled by default).
• Optional SMA Exit (disabled by default) → Conservative early exit.
📈 Visuals
The script plots:
• SMA50
• Weekly SMA50
• Swing-Low SL (fixed)
• 2R TP (fixed)
• Optional SMA exit line
All are non-repainting and update only on confirmed bars.
🔔 Alerts
Buy Signal → All entry filters aligned (RSI2, SMA50, HTF, ATR, RR check).
Exit Signal → 2R hit, SL hit, RSI exit, or SMA exit (if enabled).
🧭 Recommended Usage
• Timeframe: Daily
• HTF: Weekly (default)
• Best For: TSX equities, mid/large-cap stocks, ETFs
• Style: Short-term swing trading (1–10 bars)
• Avoid: Low-volume tickers, microcaps, crypto, biotech, news-driven spikes.
🛑 Notes
• All HTF data uses lookahead_off → non-repainting.
• Rules are fully mechanical and deterministic.
• Position sizing uses % equity by default.
• This script is for educational purposes only and not financial advice.
• Always forward-test before using live capital.
v2.0—Tristan's Multi-Indicator Reversal Strategy🎯 Multi-Indicator Reversal Strategy - Optimized for High Win Rates
A powerful confluence-based strategy that combines RSI, MACD, Williams %R, Bollinger Bands, and Volume analysis to identify high-probability reversal points . Designed to let winners run with no stop loss or take profit - positions close only when opposite signals occur.
Also, the 3 hour timeframe works VERY well—just a lot less trades.
📈 Proven Performance
This strategy has been backtested and optimized on multiple blue-chip stocks with 80-90%+ win rates on 1-hour timeframes from Aug 2025 through Oct 2025:
✅ V (Visa) - Payment processor
✅ MSFT (Microsoft) - Large-cap tech
✅ WMT (Walmart) - Retail leader
✅ IWM (Russell 2000 ETF) - Small-cap index
✅ NOW (ServiceNow) - Enterprise software
✅ WM (Waste Management) - Industrial services
These stocks tend to mean-revert at extremes, making them ideal candidates for this reversal-based approach. I only list these as a way to show you the performance of the script. These values and stock choices may change over time as the market shifts. Keep testing!
🔑 How to Use This Strategy Successfully
Step 1: Apply to Chart
Open your desired stock (V, MSFT, WMT, IWM, NOW, WM recommended)
Set timeframe to 1 Hour
Apply this strategy
Check that the Williams %R is set to -20 and -80, and "Flip All Signals" is OFF (can flip this for some stocks to perform better.)
Step 2: Understand the Signals
🟢 Green Triangle (BUY) Below Candle:
Multiple indicators (RSI, Williams %R, MACD, Bollinger Bands) show oversold conditions
Enter LONG position
Strategy will pyramid up to 10 entries if more buy signals occur
Hold until red triangle appears
🔴 Red Triangle (SELL) Above Candle:
Multiple indicators show overbought conditions
Enter SHORT position (or close existing long)
Strategy will pyramid up to 10 entries if more sell signals occur
Hold until green triangle appears
🟣 Purple Labels (EXIT):
Shows when positions close
Displays count if multiple entries were pyramided (e.g., "Exit Long x5")
Step 3: Let the Strategy Work
Key Success Principles:
✅ Be Patient - Signals don't occur every day, wait for quality setups
✅ Trust the Process - Don't manually close positions, let opposite signals exit
✅ Watch Pyramiding - The strategy can add up to 10 positions in the same direction
✅ No Stop Loss - Positions ride through drawdowns until reversal confirmed
✅ Session Filter - Only trades during NY session (9:30 AM - 4:00 PM ET)
⚙️ Winning Settings (Already Set as Defaults)
INDICATOR SETTINGS:
- RSI Length: 14
- RSI Overbought: 70
- RSI Oversold: 30
- MACD: 12, 26, 9 (standard)
- Williams %R Length: 14
- Williams %R Overbought: -20 ⭐ (check this! And adjust to your liking)
- Williams %R Oversold: -80 ⭐ (check this! And adjust to your liking)
- Bollinger Bands: 20, 2.0
- Volume MA: 20 periods
- Volume Multiplier: 1.5x
SIGNAL REQUIREMENTS:
- Min Indicators Aligned: 2
- Require Divergence: OFF
- Require Volume Spike: OFF
- Require Reversal Candle: OFF
- Flip All Signals: OFF ⭐
RISK MANAGEMENT:
- Use Stop Loss: OFF ⭐⭐⭐
- Use Take Profit: OFF ⭐⭐⭐
- Allow Pyramiding: ON ⭐⭐⭐
- Max Pyramid Entries: 10 ⭐⭐⭐
SESSION FILTER:
- Trade Only NY Session: ON
- NY Session: 9:30 AM - 4:00 PM ET
**⭐ = Critical settings for success**
## 🎓 Strategy Logic Explained
### **How It Works:**
1. **Multi-Indicator Confluence**: Waits for at least 2 out of 4 technical indicators to align before generating signals
2. **Oversold = Buy**: When RSI < 30, Williams %R < -80, price below lower Bollinger Band, and/or MACD turning bullish → BUY signal
3. **Overbought = Sell**: When RSI > 70, Williams %R > -20, price above upper Bollinger Band, and/or MACD turning bearish → SELL signal
4. **Pyramiding Power**: As trend continues and more signals fire in the same direction, adds up to 10 positions to maximize gains
5. **Exit Only on Reversal**: No arbitrary stops or targets - only exits when opposite signal confirms trend change
6. **Session Filter**: Only trades during liquid NY session hours to avoid overnight gaps and low-volume periods
### **Why No Stop Loss Works:**
Traditional reversal strategies fail because they:
- Get stopped out too early during normal volatility
- Miss the actual reversal that happens later
- Cut winners short with tight take profits
This strategy succeeds because it:
- ✅ Rides through temporary noise
- ✅ Captures full reversal moves
- ✅ Uses multiple indicators for confirmation
- ✅ Pyramids into winning positions
- ✅ Only exits when technical picture completely reverses
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## 📊 Understanding the Display
**Live Indicator Counter (Top Corner / end of current candles):**
Bull: 2/4
Bear: 0/4
(STANDARD)
Shows how many indicators currently align bullish/bearish
"STANDARD" = normal reversal mode (buy oversold, sell overbought)
"FLIPPED" = momentum mode if you toggle that setting
Visual Indicators:
🔵 Blue background = NY session active (trading window)
🟡 Yellow candle tint = Volume spike detected
💎 Aqua diamond = Bullish divergence (price vs RSI)
💎 Fuchsia diamond = Bearish divergence
⚡ Advanced Tips
Optimizing for Different Stocks:
If Win Rate is Low (<50%):
Try toggling "Flip All Signals" to ON (switches to momentum mode)
Increase "Min Indicators Aligned" to 3 or 4
Turn ON "Require Divergence"
Test on different timeframe (4-hour or daily)
If Too Few Signals:
Decrease "Min Indicators Aligned" to 2
Turn OFF all requirement filters
Widen Williams %R bands to -15 and -85
If Too Many False Signals:
Increase "Min Indicators Aligned" to 3 or 4
Turn ON "Require Divergence"
Turn ON "Require Volume Spike"
Reduce Max Pyramid Entries to 5
Stock Selection Guidelines:
Best Suited For:
Large-cap stable stocks (V, MSFT, WMT)
ETFs (IWM, SPY, QQQ)
Stocks with clear support/resistance
Mean-reverting instruments
Avoid:
Ultra low-volume penny stocks
Extremely volatile crypto (try traditional settings first)
Stocks in strong one-directional trends lasting months
🔄 The "Flip All Signals" Feature
If backtesting shows poor results on a particular stock, try toggling "Flip All Signals" to ON:
STANDARD Mode (OFF):
Buy when oversold (reversal strategy)
Sell when overbought
May work best for: V, MSFT, WMT, IWM, NOW, WM
FLIPPED Mode (ON):
Buy when overbought (momentum strategy)
Sell when oversold
May work best for: Strong trending stocks, momentum plays, crypto
Test both modes on your stock to see which performs better!
📱 Alert Setup
Create alerts to notify you of signals:
📊 Performance Expectations
With optimized settings on recommended stocks:
Typical results we are looking for:
Win Rate: 70-90%
Average Winner: 3-5%
Average Loser: 1-3%
Signals Per Week: 1-3 on 1-hour timeframe
Hold Time: Several hours to days
Remember: Past performance doesn't guarantee future results. Always use proper risk management.
Universal Breakout Strategy [KedArc Quant]Description:
A flexible breakout framework where you can test different logics (Prev Day, Bollinger, Volume, ATR, EMA Trend, RSI Confirm, Candle Confirm, Time Filter) under one system.
Choose your breakout mode, and the strategy will handle entries, exits, and optional risk management (ATR stops, take-profits, daily loss guard, cooldowns).
An on-chart info table shows live mode values (like Prev High/Low, Bollinger levels, RSI, etc.) plus P&L stats for quick analysis.
Use it to compare which breakout style works best on your instrument and timeframe, whether intraday, swing, or positional trading
🔑 Why it’s useful
* Flexibility: Switch between breakout strategies without loading different indicators.
* Clarity: On-chart info table displays current mode, relevant indicator levels, and live strategy P&L stats.
* Testing efficiency: Quickly A/B test different breakout styles under the same backtest environment.
* Transparency: Every trade is rule-based and displayed with entry/exit markers.
🚀 How it helps traders
* Lets you experiment with breakout strategies quickly without loading multiple scripts.
* Helps identify which breakout method fits your instrument & timeframe.
* Gives clear on-chart visual + statistical feedback for confident decision-making.
⚙️ Input Configuration
* Breakout Mode → choose which strategy to test:
* *Prev Day* → breakouts of yesterday’s High/Low.
* *Bollinger* → Upper/Lower BB pierce.
* *Volume* → Breakout confirmed with volume above average.
* *ATR Stop* → Wide range breakout using ATR filter.
* *Time Filter* → Breakouts inside defined session hours.
* *EMA Trend* → Breakouts only in EMA fast > slow alignment.
* *RSI Confirm* → Breakouts with RSI confirmation (e.g. >55 for longs).
* *Candle Confirm* → Breakouts validated by bullish/bearish candle.
* Lookback / ATR / Bollinger inputs → adjust sensitivity.
* Intrabar mode → option to evaluate breakouts using bar highs/lows instead of closes.
* Table options → show/hide info table, show/hide P&L stats, choose corner placement.
📈 Entry & Exit Logic
* Entry → occurs when breakout condition of chosen mode is met.
* Exit → default exits via opposite signals or optional stop/target if enabled.
* Session filter → optional auto-flat at session end.
* P&L management → optional daily loss guard, cooldown between trades, and ATR-based stop/take profit.
❓ FAQ — Choosing the best setup
Q: Which strategy should I use for which chart?
* *Prev Day Breakouts*: Best on indices, FX, and liquid futures with strong daily levels.
* *Bollinger*: Works well in range-bound environments, or crypto pairs with volatility compression.
* *Volume*: Good on equities where breakout strength is tied to volume spikes.
* *ATR Stop*: Suits volatile instruments (commodities, crypto).
* *EMA Trend*: Useful in trending markets (stocks, indices).
* *RSI Confirm*: Adds momentum filter, better for swing trades.
* *Candle Confirm*: Ideal for scalpers needing visual confirmation.
* *Time Filter*: For intraday traders who want signals only in high-liquidity sessions.
Q: What timeframe should I use?
* Intraday traders → 5m to 15m (Time Filter, Candle Confirm).
* Swing traders → 1H to 4H (EMA Trend, RSI Confirm, ATR Stop).
* Position traders → Daily (Prev Day, Bollinger).
* Breakout
A trade entry condition triggered when price crosses above a resistance level (for longs) or below a support level (for shorts).
* Prev Day High/Low
Formula:
Prev High = High of (Day )
Prev Low = Low of (Day )
* Bollinger Bands
Formula:
Basis = SMA(Close, Length)
Upper Band = Basis + (Multiplier × StdDev(Close, Length))
Lower Band = Basis – (Multiplier × StdDev(Close, Length))
* Volume Confirmation
A breakout is only valid if:
Volume > SMA(Volume, Length)
* ATR (Average True Range)
Measures volatility.
Formula:
ATR = SMA(True Range, Length)
where True Range = max(High–Low, |High–Close |, |Low–Close |)
* EMA (Exponential Moving Average)
Weighted moving average giving more weight to recent prices.
Formula:
EMA = (Price × α) + (EMA × (1–α))
with α = 2 / (Length + 1)
* RSI (Relative Strength Index)
Momentum oscillator scaled 0–100.
Formula:
RSI = 100 – (100 / (1 + RS))
where RS = Avg(Gain, Length) ÷ Avg(Loss, Length)
* Candle Confirmation
Bullish candle: Close > Open AND Close > Close
Bearish candle: Close < Open AND Close < Close
Win Rate (%)
Formula:
Win Rate = (Winning Trades ÷ Total Trades) × 100
* Average Trade P&L
Formula:
Avg Trade = Net Profit ÷ Total Trades
📊 Performance Notes
The Universal Breakout Strategy is designed as a framework rather than a single-asset optimized system. Results will vary depending on the chart, timeframe, and asset chosen.
On the current defaults (15-minute, INR-denominated example), the backtest produced 132 trades over the selected period. This provides a statistically sufficient sample size.
Win rate (~35%) is relatively low, but this is balanced by a positive reward-to-risk ratio (~1.8). In practice, a lower win rate with larger wins versus smaller losses is sustainable.
The average P&L per trade is close to breakeven under default settings. This is expected, as the strategy is not tuned for a single symbol but offered as a universal breakout framework.
Commissions (0.1%) and slippage (1 tick) are included in the simulation, ensuring realistic conditions.
Risk management is conservative, with order sizing set at 1 unit per trade. This avoids over-leveraging and keeps exposure well under the 5-10% equity risk guideline.
👉 Traders are encouraged to:
Experiment with inputs such as ATR period, breakout length, or Bollinger parameters.
Test across different timeframes and instruments (equities, futures, forex, crypto) to find optimal setups.
Combine with filters (trend direction, volatility regimes, or volume conditions) for further refinement.
⚠️ Disclaimer This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Quantum Reversal# 🧠 Quantum Reversal
## **Quantitative Mean Reversion Framework**
This algorithmic trading system employs **statistical mean reversion theory** combined with **adaptive volatility modeling** to capitalize on Bitcoin's inherent price oscillations around its statistical mean. The strategy integrates multiple technical indicators through a **multi-layered signal processing architecture**.
---
## ⚡ **Core Technical Architecture**
### 📊 **Statistical Foundation**
- **Bollinger Band Mean Reversion Model**: Utilizes 20-period moving average with 2.2 standard deviation bands for volatility-adjusted entry signals
- **Adaptive Volatility Threshold**: Dynamic standard deviation multiplier accounts for Bitcoin's heteroscedastic volatility patterns
- **Price Action Confluence**: Entry triggered when price breaches lower volatility band, indicating statistical oversold conditions
### 🔬 **Momentum Analysis Layer**
- **RSI Oscillator Integration**: 14-period Relative Strength Index with modified oversold threshold at 45
- **Signal Smoothing Algorithm**: 5-period simple moving average applied to RSI reduces noise and false signals
- **Momentum Divergence Detection**: Captures mean reversion opportunities when momentum indicators show oversold readings
### ⚙️ **Entry Logic Architecture**
```
Entry Condition = (Price ≤ Lower_BB) OR (Smoothed_RSI < 45)
```
- **Dual-Condition Framework**: Either statistical price deviation OR momentum oversold condition triggers entry
- **Boolean Logic Gate**: OR-based entry system increases signal frequency while maintaining statistical validity
- **Position Sizing**: Fixed 10% equity allocation per trade for consistent risk exposure
### 🎯 **Exit Strategy Optimization**
- **Profit-Lock Mechanism**: Positions only closed when showing positive unrealized P&L
- **Trend Continuation Logic**: Allows winning trades to run until momentum exhaustion
- **Dynamic Exit Timing**: No fixed profit targets - exits based on profitability state rather than arbitrary levels
---
## 📈 **Statistical Properties**
### **Risk Management Framework**
- **Long-Only Exposure**: Eliminates short-squeeze risk inherent in cryptocurrency markets
- **Mean Reversion Bias**: Exploits Bitcoin's tendency to revert to statistical mean after extreme moves
- **Position Management**: Single position limit prevents over-leveraging
### **Signal Processing Characteristics**
- **Noise Reduction**: SMA smoothing on RSI eliminates high-frequency oscillations
- **Volatility Adaptation**: Bollinger Bands automatically adjust to changing market volatility
- **Multi-Timeframe Coherence**: Indicators operate on consistent timeframe for signal alignment
---
## 🔧 **Parameter Configuration**
| Technical Parameter | Value | Statistical Significance |
|-------------------|-------|-------------------------|
| Bollinger Period | 20 | Standard statistical lookback for volatility calculation |
| Std Dev Multiplier | 2.2 | Optimized for Bitcoin's volatility distribution (95.4% confidence interval) |
| RSI Period | 14 | Traditional momentum oscillator period |
| RSI Threshold | 45 | Modified oversold level accounting for Bitcoin's momentum characteristics |
| Smoothing Period | 5 | Noise reduction filter for momentum signals |
---
## 📊 **Algorithmic Advantages**
✅ **Statistical Edge**: Exploits documented mean reversion tendency in Bitcoin markets
✅ **Volatility Adaptation**: Dynamic bands adjust to changing market conditions
✅ **Signal Confluence**: Multiple indicator confirmation reduces false positives
✅ **Momentum Integration**: RSI smoothing improves signal quality and timing
✅ **Risk-Controlled Exposure**: Systematic position sizing and long-only bias
---
## 🔬 **Mathematical Foundation**
The strategy leverages **Bollinger Band theory** (developed by John Bollinger) which assumes that prices tend to revert to the mean after extreme deviations. The RSI component adds **momentum confirmation** to the statistical price deviation signal.
**Statistical Basis:**
- Mean reversion follows the principle that extreme price deviations from the moving average are temporary
- The 2.2 standard deviation multiplier captures approximately 97.2% of price movements under normal distribution
- RSI momentum smoothing reduces noise inherent in oscillator calculations
---
## ⚠️ **Risk Considerations**
This algorithm is designed for traders with understanding of **quantitative finance principles** and **cryptocurrency market dynamics**. The strategy assumes mean-reverting behavior which may not persist during trending market phases. Proper risk management and position sizing are essential.
---
## 🎯 **Implementation Notes**
- **Market Regime Awareness**: Most effective in ranging/consolidating markets
- **Volatility Sensitivity**: Performance may vary during extreme volatility events
- **Backtesting Recommended**: Historical performance analysis advised before live implementation
- **Capital Allocation**: 10% per trade sizing assumes diversified portfolio approach
---
**Engineered for quantitative traders seeking systematic mean reversion exposure in Bitcoin markets through statistically-grounded technical analysis.**
Three Candle Bullish Engulfing StrategyThe Three Candle Bullish Engulfing Strategy is a versatile, multi-mode trading system designed for TradingView, combining classic candlestick patterns with momentum confirmation and dynamic risk management. This script supports both swing trading and intraday approaches, as well as an optional RSI-based breakout mode for additional signal filtering.
Key Features:
Three Candle Pattern Detection:
The strategy identifies potential trend reversal points using a three-candle pattern:
The first candle is a strong bullish (or bearish) move.
The second candle is a doji or small-bodied candle, indicating indecision.
The third candle is a bullish (or bearish) engulfing candle that closes above (or below) the previous high (or low), confirming the reversal.
Flexible Trading Modes:
Swing Long Only: Enter long trades on bullish three-candle setups.
Intraday Long & Short: Trade both long and short based on bullish and bearish three-candle patterns, with automatic session-end exits.
RSI Breakout Mode: Enter long trades when the 1-hour RSI exceeds a user-defined threshold (default 80) and a bullish candle forms, with breakout confirmation and a fixed-percentage stop loss.
Visual Aids:
Plots the RSI breakout trigger price and stop loss on the chart for easy monitoring.
How It Works:
Three Candle Pattern Entries:
Long Entry: Triggered when a bullish candle is followed by a doji, then a bullish engulfing candle closes above the previous high.
Short Entry (Intraday only): Triggered by the inverse pattern—bearish candle, doji, then bearish engulfing candle closing below the previous low.
RSI Breakout Entries:
When the RSI on a higher timeframe (default 1 hour) exceeds the set threshold and a bullish candle forms, the script records a trigger price.
A long trade is entered if the price breaks above this trigger, with a stop loss set a fixed percentage below.
Exits:
Positions are closed if the trailing stop is hit, the session ends (for intraday mode), or the stop loss is triggered in RSI breakout mode.
In RSI breakout mode, positions are also closed if a new breakout trigger forms while in position.
Arena-Hub-DC-Strategy V3.1This script must be individually configured for each cryptocurrency. After monitoring several coins, I’ve realized that each one requires its own unique setup. There's no “one-size-fits-all” — and different timeframes require different configurations as well.
⚠️ Risk management is essential.
If you're not familiar with proper risk management, please do not use this script. Make sure to configure your commission and slippage settings appropriately, as these are critical for realistic backtesting results. The Stop Loss and Take Profit levels are not automated — they must be adjusted by the user.
This script is not a financial advisor. It won't make risk or profit-related decisions for you. It's a tool designed to help identify potential entries, trends, and exit opportunities — but all final decisions must be made by the trader.
The default settings are only examples. You’ll need to customize them for each crypto asset and timeframe to make the strategy truly work for your style and market conditions.
The script evaluates:
The positioning of two RSIs relative to each other
Their alignment with a customizable RSI-EMA
The values of EMAs and the ATR (volatility)
A custom weighting system using ADR and VOLUME, which strongly affects trade signals. The weights can be adjusted in 0.1 increments, and even small changes can have a big impact — so fine-tuning is important!
These indicators were chosen because they complement each other:
RSI and its EMA help identify momentum shifts
ATR gauges volatility to confirm market conditions
ADR and VOLUME help filter weak signals and fine-tune entries and exits
🔍 Important: Only use this script if you understand how RSI, EMA, ATR, ADR, and VOLUME indicators work, and are comfortable making your own trading decisions.
The backtest results are based on historical data — the script cannot see the future, not even guess it. Please use it responsibly.
This script is an advanced trend-following strategy that dynamically combines RSI, SMA, EMA, ATR, ADX, and volume indicators using a unique weighting and filtering mechanism. Instead of simply combining traditional indicators, it applies them in a unique way:
✅ Dual RSI Comparison: The strategy utilizes two RSI indicators, analyzing their relative movement to filter out false signals and provide more precise entry points.
✅ Custom Entry and Exit Rules: EMA crossovers alone do not generate signals; instead, they go through a dynamic RSI filter that takes market volatility into account using ATR and ADX.
✅ Intelligent Trend Identification: Instead of standard moving averages, a uniquely weighted SMA/EMA system is used to assess trend strength and stability.
✅ ATR, ADX & Volume-Based Weighting: The EMA length is dynamically adjusted based on ATR, ADX, and volume, allowing moving averages to react faster in strong trends while smoothing out in choppy markets.
Advanced Dynamic EMA Zone
This is not your typical EMA indicator. It's an enhanced, dynamically adaptive trend zone that:
✅ Applies gradient shading – The zone between EMAs is divided into four layers, highlighting trend strength through smooth color transitions.
✅ Visualizes trend intensity – The strongest trends appear in the darkest shades, while weaker moves fade into lighter tones.
✅ Brings moving averages to life – Instead of static lines, it creates a visually intuitive trend channel.
✅ Differentiates bullish & bearish phases – The cloud fades from dark green to light green during an uptrend and from dark red to light red in a downtrend.
✅ Filters out market noise – Weakening trends appear more transparent, instantly revealing when momentum starts to fade.
✅ Enhances decision-making – Crossovers alone are not trading signals, but the visual representation helps identify market conditions at a glance.
➡️ What makes it unique?
Traditional moving average indicators rely on basic lines, but this is a full-fledged trend visualization system, helping traders filter noise and better understand price momentum.
🔄 Improved Custom EMA Smoothing Control
We’ve enhanced the weighting factor input for better user control! Previously, the EMA smoothing factor (ema1_smooth_factor) had a fixed step size that limited precision. Now, users can fine-tune it in 0.1 increments for greater flexibility.
✅ What’s new?
More precise control over EMA smoothing with adjustable step size (step=0.1).
Better adaptability to different market conditions.
Smoother trend visualization for traders who prefer fine-tuned settings.
This update ensures our custom EMA visualization remains superior to standard indicators. 🎯🔥
Enhanced Range Filter Strategy with ATR TP/SLBuilt by Omotola
## **Enhanced Range Filter Strategy: A Comprehensive Overview**
### **1. Introduction**
The **Enhanced Range Filter Strategy** is a powerful technical trading system designed to identify high-probability trading opportunities while filtering out market noise. It utilizes **range-based trend filtering**, **momentum confirmation**, and **volatility-based risk management** to generate precise entry and exit signals. This strategy is particularly useful for traders who aim to capitalize on trend-following setups while avoiding choppy, ranging market conditions.
---
### **2. Key Components of the Strategy**
#### **A. Range Filter (Trend Determination)**
- The **Range Filter** smooths price fluctuations and helps identify clear trends.
- It calculates an **adjusted price range** based on a **sampling period** and a **multiplier**, ensuring a dynamic trend-following approach.
- **Uptrends:** When the current price is above the range filter and the trend is strengthening.
- **Downtrends:** When the price falls below the range filter and momentum confirms the move.
#### **B. RSI (Relative Strength Index) as Momentum Confirmation**
- RSI is used to **filter out weak trades** and prevent entries during overbought/oversold conditions.
- **Buy Signals:** RSI is above a certain threshold (e.g., 50) in an uptrend.
- **Sell Signals:** RSI is below a certain threshold (e.g., 50) in a downtrend.
#### **C. ADX (Average Directional Index) for Trend Strength Confirmation**
- ADX ensures that trades are only taken when the trend has **sufficient strength**.
- Avoids trading in low-volatility, ranging markets.
- **Threshold (e.g., 25):** Only trade when ADX is above this value, indicating a strong trend.
#### **D. ATR (Average True Range) for Risk Management**
- **Stop Loss (SL):** Placed **one ATR below** (for long trades) or **one ATR above** (for short trades).
- **Take Profit (TP):** Set at a **3:1 reward-to-risk ratio**, using ATR to determine realistic price targets.
- Ensures volatility-adjusted risk management.
---
### **3. Entry and Exit Conditions**
#### **📈 Buy (Long) Entry Conditions:**
1. **Price is above the Range Filter** → Indicates an uptrend.
2. **Upward trend strength is positive** (confirmed via trend counter).
3. **RSI is above the buy threshold** (e.g., 50, to confirm momentum).
4. **ADX confirms trend strength** (e.g., above 25).
5. **Volatility is supportive** (using ATR analysis).
#### **📉 Sell (Short) Entry Conditions:**
1. **Price is below the Range Filter** → Indicates a downtrend.
2. **Downward trend strength is positive** (confirmed via trend counter).
3. **RSI is below the sell threshold** (e.g., 50, to confirm momentum).
4. **ADX confirms trend strength** (e.g., above 25).
5. **Volatility is supportive** (using ATR analysis).
#### **🚪 Exit Conditions:**
- **Stop Loss (SL):**
- **Long Trades:** 1 ATR below entry price.
- **Short Trades:** 1 ATR above entry price.
- **Take Profit (TP):**
- Set at **3x the risk distance** to achieve a favorable risk-reward ratio.
- **Ranging Market Exit:**
- If ADX falls below the threshold, indicating a weakening trend.
---
### **4. Visualization & Alerts**
- **Colored range filter line** changes based on trend direction.
- **Buy and Sell signals** appear as labels on the chart.
- **Stop Loss and Take Profit levels** are plotted as dashed lines.
- **Gray background highlights ranging markets** where trading is avoided.
- **Alerts trigger on Buy, Sell, and Ranging Market conditions** for automation.
---
### **5. Advantages of the Enhanced Range Filter Strategy**
✅ **Trend-Following with Noise Reduction** → Helps avoid false signals by filtering out weak trends.
✅ **Momentum Confirmation with RSI & ADX** → Ensures that only strong, valid trades are executed.
✅ **Volatility-Based Risk Management** → ATR ensures adaptive stop loss and take profit placements.
✅ **Works on Multiple Timeframes** → Effective for day trading, swing trading, and scalping.
✅ **Visually Intuitive** → Clearly displays trade signals, SL/TP levels, and trend conditions.
---
### **6. Who Should Use This Strategy?**
✔ **Trend Traders** who want to enter trades with momentum confirmation.
✔ **Swing Traders** looking for medium-term opportunities with a solid risk-reward ratio.
✔ **Scalpers** who need precise entries and exits to minimize false signals.
✔ **Algorithmic Traders** using alerts for automated execution.
---
### **7. Conclusion**
The **Enhanced Range Filter Strategy** is a powerful trading tool that combines **trend-following techniques, momentum indicators, and risk management** into a structured, rule-based system. By leveraging **Range Filters, RSI, ADX, and ATR**, traders can improve trade accuracy, manage risk effectively, and filter out unfavorable market conditions.
This strategy is **ideal for traders looking for a systematic, disciplined approach** to capturing trends while **avoiding market noise and false breakouts**. 🚀
ETH/USDT EMA Crossover Strategy - OptimizedStrategy Name: EMA Crossover Strategy for ETH/USDT
Description:
This trading strategy is designed for the ETH/USDT pair and is based on exponential moving average (EMA) crossovers combined with momentum and volatility indicators. The strategy uses multiple filters to identify high-probability signals in both bullish and bearish trends, making it suitable for traders looking to trade in trending markets.
Strategy Components
EMAs (Exponential Moving Averages):
EMA 200: Used to identify the primary trend. If the price is above the EMA 200, it is considered a bullish trend; if below, a bearish trend.
EMA 50: Acts as an additional filter to confirm the trend.
EMA 20 and EMA 50 Short: These short-term EMAs generate entry signals through crossovers. A bullish crossover (EMA 20 crosses above EMA 50 Short) is a buy signal, while a bearish crossover (EMA 20 crosses below EMA 50 Short) is a sell signal.
RSI (Relative Strength Index):
The RSI is used to avoid overbought or oversold conditions. Long trades are only taken when the RSI is above 30, and short trades when the RSI is below 70.
ATR (Average True Range):
The ATR is used as a volatility filter. Trades are only taken when there is sufficient volatility, helping to avoid false signals in quiet markets.
Volume:
A volume filter is used to confirm sufficient market participation in the price movement. Trades are only taken when volume is above average.
Strategy Logic
Long Trades:
The price must be above the EMA 200 (bullish trend).
The EMA 20 must cross above the EMA 50 Short.
The RSI must be above 30.
The ATR must indicate sufficient volatility.
Volume must be above average.
Short Trades:
The price must be below the EMA 200 (bearish trend).
The EMA 20 must cross below the EMA 50 Short.
The RSI must be below 70.
The ATR must indicate sufficient volatility.
Volume must be above average.
How to Use the Strategy
Setup:
Add the script to your ETH/USDT chart on TradingView.
Adjust the parameters according to your preferences (e.g., EMA periods, RSI, ATR, etc.).
Signals:
Buy and sell signals will be displayed directly on the chart.
Long trades are indicated with an upward arrow, and short trades with a downward arrow.
Risk Management:
Use stop-loss and take-profit orders in all trades.
Consider a risk-reward ratio of at least 1:2.
Backtesting:
Test the strategy on historical data to evaluate its performance before using it live.
Advantages of the Strategy
Trend-focused: The strategy is designed to trade in trending markets, increasing the probability of success.
Multiple filters: The use of RSI, ATR, and volume reduces false signals.
Adaptability: It can be adjusted for different timeframes, although it is recommended to test it on 5-minute and 15-minute charts for ETH/USDT.
Warnings
Sideways markets: The strategy may generate false signals in markets without a clear trend. It is recommended to avoid trading in such conditions.
Optimization: Make sure to optimize the parameters according to the market and timeframe you are using.
Risk management: Never trade without stop-loss and take-profit orders.
Author
Jose J. Sanchez Cuevas
Version
v1.0
Bollinger Breakout Strategy with Direction Control [4H crypto]Bollinger Breakout Strategy with Direction Control - User Guide
This strategy leverages Bollinger Bands, RSI, and directional filters to identify potential breakout trading opportunities. It is designed for traders looking to capitalize on significant price movements while maintaining control over trade direction (long, short, or both). Here’s how to use this strategy effectively:
How the Strategy Works
Indicators Used:
Bollinger Bands:
A volatility-based indicator with an upper and lower band around a simple moving average (SMA). The bands expand or contract based on market volatility.
RSI (Relative Strength Index):
Measures momentum to determine overbought or oversold conditions. In this strategy, RSI is used to confirm breakout strength.
Trade Direction Control:
You can select whether to trade:
Long only: Buy positions.
Short only: Sell positions.
Both: Trade in both directions depending on conditions.
Breakout Conditions:
Long Trade:
The price closes above the upper Bollinger Band.
RSI is above the midline (50), confirming upward momentum.
The "Trade Direction" setting allows either "Long" or "Both."
Short Trade:
The price closes below the lower Bollinger Band.
RSI is below the midline (50), confirming downward momentum.
The "Trade Direction" setting allows either "Short" or "Both."
Risk Management:
Stop-Loss:
Long trades: Set at 2% below the entry price.
Short trades: Set at 2% above the entry price.
Take-Profit:
Calculated using a Risk/Reward Ratio (default is 2:1).
Adjust this in the strategy settings.
Inputs and Customization
Key Parameters:
Bollinger Bands Length: Default is 20. Adjust based on the desired sensitivity.
Multiplier: Default is 2.0. Higher values widen the bands; lower values narrow them.
RSI Length: Default is 14, which is standard for RSI.
Risk/Reward Ratio: Default is 2.0. Increase for more aggressive profit targets, decrease for conservative exits.
Trade Direction:
Options: "Long," "Short," or "Both."
Example: Set to "Long" in a bullish market to focus only on buy trades.
How to Use This Strategy
Adding the Strategy:
Paste the script into TradingView’s Pine Editor and add it to your chart.
Setting Parameters:
Adjust the Bollinger Band settings, RSI, and Risk/Reward Ratio to fit the asset and timeframe you're trading.
Analyzing Signals:
Green line (Upper Band): Signals breakout potential for long trades.
Red line (Lower Band): Signals breakout potential for short trades.
Blue line (Basis): Central Bollinger Band (SMA), helpful for understanding price trends.
Testing the Strategy:
Use the Strategy Tester in TradingView to backtest performance on your chosen asset and timeframe.
Optimizing for Assets:
Forex pairs, cryptocurrencies (like BTC), or stocks with high volatility are ideal for this strategy.
Works best on higher timeframes like 4H or Daily.
Best Practices
Combine with Volume: Confirm breakouts with increased volume for higher reliability.
Avoid Sideways Markets: Use additional trend filters (like ADX) to avoid trades in low-volatility conditions.
Optimize Parameters: Regularly adjust the Bollinger Bands multiplier and RSI settings to match the asset's behavior.
By utilizing this strategy, you can effectively trade breakouts while maintaining flexibility in trade direction. Adjust the parameters to match your trading style and market conditions for optimal results!
Balthazar by Aloupay📈 BALTHAZAR BY ALOUPAY: Advanced Trading Strategy for Precision and Reliability
BALTHAZAR BY ALOUPAY is a comprehensive trading strategy developed for TradingView, designed to assist traders in making informed and strategic trading decisions. By integrating multiple technical indicators, this strategy aims to identify optimal entry and exit points, manage risk effectively, and enhance overall trading performance.
🌟 Key Features
1. Integrated Indicator Suite
Exponential Moving Averages (EMAs) : Utilizes Fast (12), Medium (26), and Slow (50) EMAs to determine trend direction and strength.
Stochastic RSI : Employs Stochastic RSI with customizable smoothing periods to assess momentum and potential reversal points.
Average True Range (ATR) : Calculates dynamic stop loss and take profit levels based on market volatility using ATR multipliers.
MACD Confirmation : Incorporates MACD histogram analysis to validate trade signals, enhancing the reliability of entries.
2. Customizable Backtesting Parameters
Date Range Selection: Allows users to define specific backtesting periods to evaluate strategy performance under various market conditions.
Timezone Adaptability: Ensures accurate time-based filtering in alignment with the chart's timezone settings.
3. Advanced Risk Management
Dynamic Stop Loss & Take Profit: Automatically adjusts exit points using ATR multipliers to adapt to changing market volatility.
Position Sizing: Configurable to risk a sustainable percentage of equity per trade (recommended: 5-10%) to maintain disciplined money management.
4. Clear Trade Signals
Long & Short Entries: Generates actionable signals based on the convergence of EMA alignment, Stochastic RSI crossovers, and MACD confirmation.
Automated Exits: Implements predefined take profit and stop loss levels to secure profits and limit losses without emotional interference.
5. Visual Enhancements
EMA Visualization: Displays Fast, Medium, and Slow EMAs on the chart for easy trend identification.
Stochastic RSI Indicators: Uses distinct shapes to indicate bullish and bearish momentum shifts.
Risk Levels Display: Clearly marks take profit and stop loss levels on the chart for transparent risk-reward assessment.
🔍 Strategy Mechanics
Trend Identification with EMAs
Bullish Trend: Fast EMA (12) > Medium EMA (26) > Slow EMA (50)
Bearish Trend: Fast EMA (12) < Medium EMA (26) < Slow EMA (50)
Momentum Confirmation with Stochastic RSI
Bullish Signal: %K line crosses above %D line, indicating upward momentum.
Bearish Signal: %K line crosses below %D line, signaling downward momentum.
Volatility-Based Risk Management with ATR
Stop Loss: Positioned at 1.0 ATR below (for long) or above (for short) the entry price.
Take Profit: Positioned at 4.0 ATR above (for long) or below (for short) the entry price.
MACD Confirmation
Long Trades: Executed only when the MACD histogram is positive.
Short Trades: Executed only when the MACD histogram is negative.
💱 Recommended Forex Pairs
While BALTHAZAR BY ALOUPAY has shown robust performance on the 4-hour timeframe for Gold (XAU/USD), it is also well-suited for the following highly liquid forex pairs:
EUR/USD (Euro/US Dollar)
GBP/USD (British Pound/US Dollar)
USD/JPY (US Dollar/Japanese Yen)
AUD/USD (Australian Dollar/US Dollar)
USD/CAD (US Dollar/Canadian Dollar)
NZD/USD (New Zealand Dollar/US Dollar)
EUR/GBP (Euro/British Pound)
These pairs offer high liquidity and favorable trading conditions that complement the strategy's indicators and risk management features.
⚙️ Customization Options
Backtesting Parameters
Start Date: Define the beginning of the backtesting period.
End Date: Define the end of the backtesting period.
EMAs Configuration
Fast EMA Length: Default is 12.
Medium EMA Length: Default is 26.
Slow EMA Length: Default is 50.
Source: Default is Close price.
Stochastic RSI Configuration
%K Smoothing: Default is 5.
%D Smoothing: Default is 4.
RSI Length: Default is 14.
Stochastic Length: Default is 14.
RSI Source: Default is Close price.
ATR Configuration
ATR Length: Default is 14.
ATR Smoothing Method: Options include RMA, SMA, EMA, WMA (default: RMA).
Stop Loss Multiplier: Default is 1.0 ATR.
Take Profit Multiplier: Default is 4.0 ATR.
MACD Configuration
MACD Fast Length: Default is 12.
MACD Slow Length: Default is 26.
MACD Signal Length: Default is 9.
📊 Why Choose BALTHAZAR BY ALOUPAY?
Comprehensive Integration: Combines trend, momentum, and volatility indicators for a multifaceted trading approach.
Automated Precision: Eliminates emotional decision-making with rule-based entry and exit signals.
Robust Risk Management: Protects capital through dynamic stop loss and take profit levels tailored to market conditions.
User-Friendly Customization: Easily adjustable settings to align with individual trading styles and risk tolerance.
Proven Reliability: Backtested over extensive periods across various market environments to ensure consistent performance.
Disclaimer : Trading involves significant risk of loss and is not suitable for every investor. Past performance is not indicative of future results. Always conduct your own research and consider your financial situation before engaging in trading activities.
Harmony Signal Flow By ArunThis Pine Script strategy, titled "Harmony Signal Flow By Arun," uses the Relative Strength Index (RSI) indicator to generate buy and sell signals based on custom thresholds. The script incorporates stop-loss and target management and restricts new trades until the previous position closes. Here's a detailed description:
Custom RSI Metric:
The strategy calculates a 5-period RSI based on the closing price, aiming for a more responsive measure of price momentum.
RSI thresholds are defined:
Lower threshold (30): Indicates oversold conditions, triggering a potential buy.
Upper threshold (70): Indicates overbought conditions, prompting a possible sell.
Entry Conditions:
Buy Signal: The strategy initiates a buy order when the RSI crosses above the lower threshold (30), indicating a shift from oversold conditions.
Sell Signal: A sell order is triggered when the RSI crosses below the upper threshold (70), suggesting an overbought reversal.
Only one order (buy or sell) can be active at a time, ensuring that a new trade begins only when there’s no existing position.
Stop-Loss and Target Management:
For each trade, stop-loss and target conditions are applied to manage risk and secure profits.
For Buy Positions:
Stop-loss is set 100 points below the entry price.
Target is set 150 points above the entry price.
For Sell Positions:
Stop-loss is set 100 points above the entry price.
Target is 150 points below the entry price.
The strategy closes the trade when either the stop-loss or target is met, marking the trade as "closed" and allowing a new trade entry.
Trade Sequencing:
A new trade (buy or sell) is only permitted after the previous position hits either its stop-loss or target, preventing overlapping trades and ensuring clear trade sequences.
This sequential approach enhances risk management by ensuring only one active position at any time.
End-of-Day Closure:
All open positions are closed automatically at 3:25 PM (Indian market time) to avoid overnight exposure, ensuring the strategy remains strictly intraday.
The flag for trade entry is reset at the end of each day, enabling fresh trades the next day.
Chart Indicators:
The script plots buy and sell signals directly on the chart with visible labels.
It also displays the custom RSI metric with horizontal lines for the lower and upper thresholds, providing visual cues for entry and exit points.
Summary
This strategy is a momentum-based intraday trading approach that uses the RSI for identifying potential reversals and manages trades through predefined stop-loss and target levels. By enforcing trade sequencing and closing positions at the end of the trading day, it prioritizes risk management and seeks to capitalize on short-term trends while avoiding overnight market risks.
Intramarket Difference Index StrategyHi Traders !!
The IDI Strategy:
In layman’s terms this strategy compares two indicators across markets and exploits their differences.
note: it is best the two markets are correlated as then we know we are trading a short to long term deviation from both markets' general trend with the assumption both markets will trend again sometime in the future thereby exhausting our trading opportunity.
📍 Import Notes:
This Strategy calculates trade position size independently (i.e. risk per trade is controlled in the user inputs tab), this means that the ‘Order size’ input in the ‘Properties’ tab will have no effect on the strategy. Why ? because this allows us to define custom position size algorithms which we can use to improve our risk management and equity growth over time. Here we have the option to have fixed quantity or fixed percentage of equity ATR (Average True Range) based stops in addition to the turtle trading position size algorithm.
‘Pyramiding’ does not work for this strategy’, similar to the order size input togeling this input will have no effect on the strategy as the strategy explicitly defines the maximum order size to be 1.
This strategy is not perfect, and as of writing of this post I have not traded this algo.
Always take your time to backtests and debug the strategy.
🔷 The IDI Strategy:
By default this strategy pulls data from your current TV chart and then compares it to the base market, be default BINANCE:BTCUSD . The strategy pulls SMA and RSI data from either market (we call this the difference data), standardizes the data (solving the different unit problem across markets) such that it is comparable and then differentiates the data, calling the result of this transformation and difference the Intramarket Difference (ID). The formula for the the ID is
ID = market1_diff_data - market2_diff_data (1)
Where
market(i)_diff_data = diff_data / ATR(j)_market(i)^0.5,
where i = {1, 2} and j = the natural numbers excluding 0
Formula (1) interpretation is the following
When ID > 0: this means the current market outperforms the base market
When ID = 0: Markets are at long run equilibrium
When ID < 0: this means the current market underperforms the base market
To form the strategy we define one of two strategy type’s which are Trend and Mean Revesion respectively.
🔸 Trend Case:
Given the ‘‘Strategy Type’’ is equal to TREND we define a threshold for which if the ID crosses over we go long and if the ID crosses under the negative of the threshold we go short.
The motivating idea is that the ID is an indicator of the two symbols being out of sync, and given we know volatility clustering, momentum and mean reversion of anomalies to be a stylised fact of financial data we can construct a trading premise. Let's first talk more about this premise.
For some markets (cryptocurrency markets - synthetic symbols in TV) the stylised fact of momentum is true, this means that higher momentum is followed by higher momentum, and given we know momentum to be a vector quantity (with magnitude and direction) this momentum can be both positive and negative i.e. when the ID crosses above some threshold we make an assumption it will continue in that direction for some time before executing back to its long run equilibrium of 0 which is a reasonable assumption to make if the market are correlated. For example for the BTCUSD - ETHUSD pair, if the ID > +threshold (inputs for MA and RSI based ID thresholds are found under the ‘‘INTRAMARKET DIFFERENCE INDEX’’ group’), ETHUSD outperforms BTCUSD, we assume the momentum to continue so we go long ETHUSD.
In the standard case we would exit the market when the IDI returns to its long run equilibrium of 0 (for the positive case the ID may return to 0 because ETH’s difference data may have decreased or BTC’s difference data may have increased). However in this strategy we will not define this as our exit condition, why ?
This is because we want to ‘‘let our winners run’’, to achieve this we define a trailing Donchian Channel stop loss (along with a fixed ATR based stop as our volatility proxy). If we were too use the 0 exit the strategy may print a buy signal (ID > +threshold in the simple case, market regimes may be used), return to 0 and then print another buy signal, and this process can loop may times, this high trade frequency means we fail capture the entire market move lowering our profit, furthermore on lower time frames this high trade frequencies mean we pay more transaction costs (due to price slippage, commission and big-ask spread) which means less profit.
By capturing the sum of many momentum moves we are essentially following the trend hence the trend following strategy type.
Here we also print the IDI (with default strategy settings with the MA difference type), we can see that by letting our winners run we may catch many valid momentum moves, that results in a larger final pnl that if we would otherwise exit based on the equilibrium condition(Valid trades are denoted by solid green and red arrows respectively and all other valid trades which occur within the original signal are light green and red small arrows).
another example...
Note: if you would like to plot the IDI separately copy and paste the following code in a new Pine Script indicator template.
indicator("IDI")
// INTRAMARKET INDEX
var string g_idi = "intramarket diffirence index"
ui_index_1 = input.symbol("BINANCE:BTCUSD", title = "Base market", group = g_idi)
// ui_index_2 = input.symbol("BINANCE:ETHUSD", title = "Quote Market", group = g_idi)
type = input.string("MA", title = "Differrencing Series", options = , group = g_idi)
ui_ma_lkb = input.int(24, title = "lookback of ma and volatility scaling constant", group = g_idi)
ui_rsi_lkb = input.int(14, title = "Lookback of RSI", group = g_idi)
ui_atr_lkb = input.int(300, title = "ATR lookback - Normalising value", group = g_idi)
ui_ma_threshold = input.float(5, title = "Threshold of Upward/Downward Trend (MA)", group = g_idi)
ui_rsi_threshold = input.float(20, title = "Threshold of Upward/Downward Trend (RSI)", group = g_idi)
//>>+----------------------------------------------------------------+}
// CUSTOM FUNCTIONS |
//<<+----------------------------------------------------------------+{
// construct UDT (User defined type) containing the IDI (Intramarket Difference Index) source values
// UDT will hold many variables / functions grouped under the UDT
type functions
float Close // close price
float ma // ma of symbol
float rsi // rsi of the asset
float atr // atr of the asset
// the security data
getUDTdata(symbol, malookback, rsilookback, atrlookback) =>
indexHighTF = barstate.isrealtime ? 1 : 0
= request.security(symbol, timeframe = timeframe.period,
expression = [close , // Instentiate UDT variables
ta.sma(close, malookback) ,
ta.rsi(close, rsilookback) ,
ta.atr(atrlookback) ])
data = functions.new(close_, ma_, rsi_, atr_)
data
// Intramerket Difference Index
idi(type, symbol1, malookback, rsilookback, atrlookback, mathreshold, rsithreshold) =>
threshold = float(na)
index1 = getUDTdata(symbol1, malookback, rsilookback, atrlookback)
index2 = getUDTdata(syminfo.tickerid, malookback, rsilookback, atrlookback)
// declare difference variables for both base and quote symbols, conditional on which difference type is selected
var diffindex1 = 0.0, var diffindex2 = 0.0,
// declare Intramarket Difference Index based on series type, note
// if > 0, index 2 outpreforms index 1, buy index 2 (momentum based) until equalibrium
// if < 0, index 2 underpreforms index 1, sell index 1 (momentum based) until equalibrium
// for idi to be valid both series must be stationary and normalised so both series hae he same scale
intramarket_difference = 0.0
if type == "MA"
threshold := mathreshold
diffindex1 := (index1.Close - index1.ma) / math.pow(index1.atr*malookback, 0.5)
diffindex2 := (index2.Close - index2.ma) / math.pow(index2.atr*malookback, 0.5)
intramarket_difference := diffindex2 - diffindex1
else if type == "RSI"
threshold := rsilookback
diffindex1 := index1.rsi
diffindex2 := index2.rsi
intramarket_difference := diffindex2 - diffindex1
//>>+----------------------------------------------------------------+}
// STRATEGY FUNCTIONS CALLS |
//<<+----------------------------------------------------------------+{
// plot the intramarket difference
= idi(type,
ui_index_1,
ui_ma_lkb,
ui_rsi_lkb,
ui_atr_lkb,
ui_ma_threshold,
ui_rsi_threshold)
//>>+----------------------------------------------------------------+}
plot(intramarket_difference, color = color.orange)
hline(type == "MA" ? ui_ma_threshold : ui_rsi_threshold, color = color.green)
hline(type == "MA" ? -ui_ma_threshold : -ui_rsi_threshold, color = color.red)
hline(0)
Note it is possible that after printing a buy the strategy then prints many sell signals before returning to a buy, which again has the same implication (less profit. Potentially because we exit early only for price to continue upwards hence missing the larger "trend"). The image below showcases this cenario and again, by allowing our winner to run we may capture more profit (theoretically).
This should be clear...
🔸 Mean Reversion Case:
We stated prior that mean reversion of anomalies is an standerdies fact of financial data, how can we exploit this ?
We exploit this by normalizing the ID by applying the Ehlers fisher transformation. The transformed data is then assumed to be approximately normally distributed. To form the strategy we employ the same logic as for the z score, if the FT normalized ID > 2.5 (< -2.5) we buy (short). Our exit conditions remain unchanged (fixed ATR stop and trailing Donchian Trailing stop)
🔷 Position Sizing:
If ‘‘Fixed Risk From Initial Balance’’ is toggled true this means we risk a fixed percentage of our initial balance, if false we risk a fixed percentage of our equity (current balance).
Note we also employ a volatility adjusted position sizing formula, the turtle training method which is defined as follows.
Turtle position size = (1/ r * ATR * DV) * C
Where,
r = risk factor coefficient (default is 20)
ATR(j) = risk proxy, over j times steps
DV = Dollar Volatility, where DV = (1/Asset Price) * Capital at Risk
🔷 Risk Management:
Correct money management means we can limit risk and increase reward (theoretically). Here we employ
Max loss and gain per day
Max loss per trade
Max number of consecutive losing trades until trade skip
To read more see the tooltips (info circle).
🔷 Take Profit:
By defualt the script uses a Donchain Channel as a trailing stop and take profit, In addition to this the script defines a fixed ATR stop losses (by defualt, this covers cases where the DC range may be to wide making a fixed ATR stop usefull), ATR take profits however are defined but optional.
ATR SL and TP defined for all trades
🔷 Hurst Regime (Regime Filter):
The Hurst Exponent (H) aims to segment the market into three different states, Trending (H > 0.5), Random Geometric Brownian Motion (H = 0.5) and Mean Reverting / Contrarian (H < 0.5). In my interpretation this can be used as a trend filter that eliminates market noise.
We utilize the trending and mean reverting based states, as extra conditions required for valid trades for both strategy types respectively, in the process increasing our trade entry quality.
🔷 Example model Architecture:
Here is an example of one configuration of this strategy, combining all aspects discussed in this post.
Future Updates
- Automation integration (next update)
Trend-based Price Action StrategyThis is a strategy script that combines trend-based price action analysis with the Relative Strength Index (RSI) and Exponential Moving Averages (EMA) as trend filters. Here's a summary of the key components and logic:
Price Action Candlestick Patterns:
Bullish patterns: Engulfing candle and Morning Star.
Bearish patterns: Engulfing candle and Evening Star.
RSI Integration:
RSI is used to identify overbought and oversold conditions.
EMA Trend Filter:
Three EMAs with different periods: Fast , Medium and Slow.
Long trend condition occur when the fast EMA is above the medium and the medium is above the slow EMA.
Short trend condition occur when the slow EMA is above the medium and the medium is above the fast EMA.
Long entry conditions: RSI is oversold, RSI is decreasing, bullish candlestick pattern, and EMA trend filter conditions are met.
Short entry conditions: RSI is overbought, RSI is decreasing, bearish candlestick pattern, and EMA trend filter conditions are met.
Exit conditions:
Take profit or stop loss is reached.
Plotting:
Signals are plotted on the chart when entry conditions are met.
EMAs are plotted when the EMA trend filter is enabled.
This script aims to capture potential trend reversal points based on a combination of candlestick patterns, RSI, and EMA trend analysis.
Traders can use this script as a starting point for further customization or as a reference for developing their own trading strategies. It's important to note that past performance is not indicative of future results, and thorough testing and validation are recommended before deploying any trading strategy.
