Wunder DCA BotThe bot is based on the DCA system.
1. DCA is the investment method in which you buy a certain portion of the asset after the determined price deviation.
2. For entry, we evaluate the maximum and minimum levels for a given period that you can adjust in the script. The bot enters when price rebound from the specified levels.
3. For the exit, the bot will use the take profit percentage that you will specify in settings.
It is also possible to choose how the take profit is calculated either from the average entry price or from the entry order (first order).
4. DCA uses the following settings:
- Base order Volume: Volume of your first order on entry signal
- Subsequent orders volume: The volume of all subsequent orders except the first
- DCA orders count: This parameter will determine how many entries your overall strategy will have. For example: If you will put 3, that will mean that including your initial position you will have 2 additional orders.
- DCA order price deviation:
This is the value in % which determines the deviation of the additional entries from the entry price. Example: If you go long and the price of the asset is 100$ and you put an order price deviation of 1% that will mean that the first additional entry will occur when the price will drop by 1%, and the second entry will be triggered when the overall price will drop by 2% (as the interval between the first and the second additional entry will be 1%).
- DCA Order Volume Multiplier:
This parameter will determine the amount that you put into each additional position. If this parameter is equal to 1 that means that each additional entry will be equal to the initial amount. The extra volume will be added to your position from the second DCA entry. Example: Your initial position was 10$ and your Volume Multiplier is set to 2. When you reach your 1st DCA target your additional order will have the same volume of 10$. When you reach your 2nd DCA target your additional order will be 20$ (previous position volume * multiplier). Your 3rd DCA target will place the order of 40$.
- DCA order price Deviation Multiplier:
This value will increase the price deviation between each additional entry. It is calculated as the price deviation multiplied by the deviation multiplier. For example: if you enter long at the price 100$ and have a price deviation of 1% with the price deviation multiplier of 2 that will mean that the first additional entry will occur when the price will drop to 99$ however the second will occur when the price will go to 97$. The third additional position will be entered at 94$
5. For full automation of the bot, you should set your comments to the input in the bot settings in the "LONG" and "SHORT" fields. You also need to create an alert signal and set a Webhook to send signals.
IMPORTANT!!!
1. Position calculation should take into account several factors: your deposit, leverage, the number of DCA orders, the distance to the last DCA order;
2. When choosing leverage, it is important to correctly calculate the possible drawdown. If you set a high leverage value, then liquidation awaits and the bot will not be able to take profits and will exit the position ahead of time;
3. The size of the position must be determined in accordance with all risks and take into account the size of your deposit;
4. This DCA Bot is able to earn consistently with the correct calculated money management.
Pesquisar nos scripts por "the script"
Volatility Stop Strategy (by Coinrule)Traders often use the volatility stop to protect trades dynamically, adjusting the stop price gradually based on the asset's volatility.
Just like the volatility stop is a great way to capture trend reversals on the downside, the opposite applies as well. Therefore, another useful application of the volatility stop is to add it to a trading system to signal potential trend reversals to catch a good buy opportunity.
ENTRY
- When the price crosses above the Volatility Stop
EXIT
- When the price crosses below the Volatility Stop
For this strategy, the Volatility stop's multiplier is set to 3 to allow more flexibility to the trade. The strategy is designed for medium-term trades.
Based on the backtest result from a sample of crypto trading pairs, the most profitable time frame is the 2-hr.
The strategy works well with both crypto-to-crypto and crypto-to-fiat pairs. To make results more realistic, a trading fee of 0.1% is added to the script. The fee is aligned to the base fee applied on Binance.
Bagheri IG Ether v2In this version, the winning ratio has been decreased, but the Risk to Reward Ratio (RRR) has been set to be better than the previous version.
This is a technical trading strategy for Ethereum ( BINANCE:ETHUSDT ). We built and developed it on MetaEditor and optimized it with MetaTrader optimizer.
The main indicators are Donchian Channel, Oscillator of ROC , Bears Power, Balance of Power , and Simple Moving Average ( SMA ). Default values in the input panel are the best combination of these indicators, but you can change any of them and try it for better results.
Please notice that this strategy has been optimized on the 1-minute chart of Ethereum .
For each position, you can see the Take Profit (TP) and Stop Loss (SL) levels. Also, you can find the values of mentioned TP and SL in points from the input panel of the script.
Attention: The price of Ethereum has 2 decimal places.
Therefore, 3000 points for TP means 30 USDT for trading 1 BINANCE:ETHUSDT .
Bullish Reversal Bar Strategy [Skyrexio]Overview
Bullish Reversal Bar Strategy leverages the combination of candlestick pattern Bullish Reversal Bar (description in Methodology and Justification of Methodology), Williams Alligator indicator and Williams Fractals to create the high probability setups. Candlestick pattern is used for the entering into trade, while the combination of Williams Alligator and Fractals is used for the trend approximation as close condition. Strategy uses only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator or the candlestick pattern invalidation to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Trend Trade Filter: strategy uses Alligator and Fractal combination as high probability trend filter.
Methodology
The strategy opens long trade when the following price met the conditions:
1.Current candle's high shall be below the Williams Alligator's lines (Jaw, Lips, Teeth)(all details in "Justification of Methodology" paragraph)
2.Price shall create the candlestick pattern "Bullish Reversal Bar". Optionally if MFI and AO filters are enabled current candle shall have the decreasing AO and at least one of three recent bars shall have the squat state on the MFI (all details in "Justification of Methodology" paragraph)
3.If price breaks through the high of the candle marked as the "Bullish Reversal Bar" the long trade is open at the price one tick above the candle's high
4.Initial stop loss is placed at the Bullish Reversal Bar's candle's low
5.If price hit the Bullish Reversal Bar's low before hitting the entry price potential trade is cancelled
6.If trade is active and initial stop loss has not been hit, trade is closed when the combination of Alligator and Williams Fractals shall consider current trend change from upward to downward.
Strategy settings
In the inputs window user can setup strategy setting:
Enable MFI (if true trades are filtered using Market Facilitation Index (MFI) condition all details in "Justification of Methodology" paragraph), by default = false)
Enable AO (if true trades are filtered using Awesome Oscillator (AO) condition all details in "Justification of Methodology" paragraph), by default = false)
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. The first and key concept is the Bullish Reversal Bar candlestick pattern. This is just the single bar pattern. The rules are simple:
Candle shall be closed in it's upper half
High of this candle shall be below all three Alligator's lines (Jaw, Lips, Teeth)
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
How we can use all these indicators in this strategy? This strategy is a counter trend one. Candle's high shall be below all Alligator's lines. During this market stage the bullish reversal bar candlestick pattern shall be printed. This bar during the downtrend is a high probability setup for the potential reversal to the upside: bulls were able to close the price in the upper half of a candle. The breaking of its high is a high probability signal that trend change is confirmed and script opens long trade. If market continues going down and break down the bullish reversal bar's low potential trend change has been invalidated and strategy close long trade.
If market really reversed and started moving to the upside strategy waits for the trend change form the downtrend to the uptrend according to approximation of Alligator and Fractals combination. If this change happens strategy close the trade. This approach helps to stay in the long trade while the uptrend continuation is likely and close it if there is a high probability of the uptrend finish.
Optionally users can enable MFI and AO filters. First of all, let's briefly explain what are these two indicators. The Awesome Oscillator (AO), created by Bill Williams, is a momentum-based indicator that evaluates market momentum by comparing recent price activity to a broader historical context. It assists traders in identifying potential trend reversals and gauging trend strength.
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
This indicator is filtering signals in the following way: if current AO bar is decreasing this candle can be interpreted as a bullish reversal bar. This logic is applicable because initially this strategy is a trend reversal, it is searching for the high probability setup against the current trend. Decreasing AO is the additional high probability filter of a downtrend.
Let's briefly look what is MFI. The Market Facilitation Index (MFI) is a technical indicator that measures the price movement per unit of volume, helping traders gauge the efficiency of price movement in relation to trading volume. Here's how you can calculate it:
MFI = (High−Low)/Volume
MFI can be used in combination with volume, so we can divide 4 states. Bill Williams introduced these to help traders interpret the interaction between volume and price movement. Here’s a quick summary:
Green Window (Increased MFI & Increased Volume): Indicates strong momentum with both price and volume increasing. Often a sign of trend continuation, as both buying and selling interest are rising.
Fake Window (Increased MFI & Decreased Volume): Shows that price is moving but with lower volume, suggesting weak support for the trend. This can signal a potential end of the current trend.
Squat Window (Decreased MFI & Increased Volume): Shows high volume but little price movement, indicating a tug-of-war between buyers and sellers. This often precedes a breakout as the pressure builds.
Fade Window (Decreased MFI & Decreased Volume): Indicates a lack of interest from both buyers and sellers, leading to lower momentum. This typically happens in range-bound markets and may signal consolidation before a new move.
For our purposes we are interested in squat bars. This is the sign that volume cannot move the price easily. This type of bar increases the probability of trend reversal. In this indicator we added to enable the MFI filter of reversal bars. If potential reversal bar or two preceding bars have squat state this bar can be interpret as a reversal one.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -5.29%
Maximum Single Profit: +29.99%
Net Profit: +5472.66 USDT (+54.73%)
Total Trades: 103 (33.98% win rate)
Profit Factor: 1.634
Maximum Accumulated Loss: 1231.15 USDT (-8.32%)
Average Profit per Trade: 53.13 USDT (+0.94%)
Average Trade Duration: 76 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h ETH/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Bagheri IG EtherThis is a technical trading strategy for Ethereum ( BINANCE:ETHUSDT ). We built and developed it on MetaEditor and optimized it with MetaTrader optimizer.
The main indicators are Donchian Channel, Oscillator of ROC, Bears Power, Balance of Power, and Simple Moving Average (SMA). Default values in the input panel are the best combination of these indicators, but you can change any of them and try it for better results.
Please notice that this strategy has been optimized on the 1-minute chart of Ethereum.
For each position, you can see the Take Profit (TP) and Stop Loss (SL) levels. Also, you can find the values of mentioned TP and SL in points from the input panel of the script.
Attention: The price of Ethereum has 2 decimal places.
Therefore, 3000 points for TP means 30 USDT for trading 1 BINANCE:ETHUSDT .
SNAP BACK 2.0 Strategy
This strategy is designed to allow you to catch the bounce or "SNAP Back" of an equity that has been in a trend.
1) Once the moving averages are in the order of 200SMA > 50 SMA > 34EMA > 20SMA > 8EMA (or reverse for and uptrend), the strategy is setup.
2) Next you wait for a trigger of the closing price crossing the 8EMA, while there is a desired gap size between the 8EMA and the 20SMA (2-10% of stock value preferred).
3) Exit position based on target profit reached (conservative sell half at 34EMA and engage a trailing stop loss for remainder or set static limit) or price crosses 8EMA or stop loss%
*)This code also allows you to determine your desired backtesting date compliments of alanaster
This code is the product of many hours of hard work on the part of the greater tradingview community. The credit goes to everyone in the community who has put code out there for the greater good.
The idea for the coding came from a video I watched on YouTube presented by TradeStation called Snap Back - thank you guys for the inspiration.
UPDATE: I have coded the other side of the strategy to allow you to take advantage of the same set-up in an uptrend for Short plays. You can turn the up or downsides on, off, or both.
The main intent is to catch the bounces of a falling stock. However, I have found that you can do the inverse and catch the drops in a rising stock (the latter is not as reliable). This also tends to work better on less volatile stocks. I have included a large volume of user defined conditions and display entry and exit conditions on the chart to see how your choices are impacting the script.
RSI of Ultimate Oscillator [SHORT Selling] StrategyThis is SHORT selling strategy with Ultimate Oscillator. Instead of drectly using the UO oscillator , I have used RSI on UO (as I did in my previous strategies )
Ultimator Oscillator settings are 5, 10 and 15
RSI of UO setting is 5
Short Sell
==========
I have used moving averages from WilliamAlligator indicator --- settings are 10(Lips), 20(teeth) and 50 (Jaw)
when Lips , Teeth and Jaw are aligned to downtrend (that means Lips < Teeth < Jaw )
Look for RSIofUO dropping below 60 ( setting parameter is Sell Line )
Partial Exit
==========
When RSIofUO crossing up Oversold line i.e 30
Cover Short / Exit
=================
When RSIofUO crosisng above overbought line i.e 70
StopLoss
========
StopLoss defaulted to 3 % , Though it is mentioned in settings , it has not been not used to calcuate and StopLoss Exit... Reason is, when RSIofUO already crossed 60 line (for SHORTING) , then it would take more efforts go up beynd 60. There is saying price takes stairs to climb up but it takes elevator to go down. I have not purely depend on this to exit stop loss, however noticed the trades in this stratgey did not get out with loss higher than when RSIofUO reaching 70 level.
Note
======
Williams Alligator is not drawn from the script. It is manually added to chart for illustration purpose. Please add it when you are using this strategy , whch woould give an idea how the strategy is taking Short Trades.
This is tested on Hourly chart for SPY
Bar color changes to purple when the strategy is in SHORT trade
Warning
========
For the eductional purposes only
RSI Alligator StrategyHello trading family! Just wanted to give a quick write up and share the new code for the RSI Alligator Strategy. I amended it to show every crossover signal, weak and strong, so we can accurately gauge its effectiveness.
Having played with this for a couple hours now I have learned a few things
-Using Heikin Ashi seems to smooth it out a bit and provides about 20% fewer signals, leading to overall more accuracy. However, it can be misleading as the Heikin Ashi opening price doesn't always line up with the market price, especially in cases of large moves. Overall though it didn't seem too far off except for a few instances.
-Also, using the Heikin Ashi gives you a better idea of the trend, which this indicator is primarily used to detect and exploit.
-Having tested on TF of 1H-1D, overall profitability is found to be highest between 4H-12H, with 1D giving the "safest" longer term signals, and lower TF's generating many more signals due to volatility.
-Instead of waiting for the next signal in order to close, you can often use a crossover/crossunder of the 5 and 13 to close the previous trade, especially if paired with a Heikin Ashi of opposite color (green to close a short, red to close a long)
-You will also notice several instances where the Green 5 period show divergences that aren't visible on the regular RSI, another handy little feature
So far I have still only tested this on BTCUSD. Feel free to apply it to any coin and let me know what you find.
Here is the script. If you have any ideas or suggestions please let me know!
XPloRR MA-Trailing-Stop StrategyXPloRR MA-Trailing-Stop Strategy
Long term MA-Trailing-Stop strategy with Adjustable Signal Strength to beat Buy&Hold strategy
None of the strategies that I tested can beat the long term Buy&Hold strategy. That's the reason why I wrote this strategy.
Purpose: beat Buy&Hold strategy with around 10 trades. 100% capitalize sold trade into new trade.
My buy strategy is triggered by the fast buy EMA (blue) crossing over the slow buy SMA curve (orange) and the fast buy EMA has a certain up strength.
My sell strategy is triggered by either one of these conditions:
the EMA(6) of the close value is crossing under the trailing stop value (green) or
the fast sell EMA (navy) is crossing under the slow sell SMA curve (red) and the fast sell EMA has a certain down strength.
The trailing stop value (green) is set to a multiple of the ATR(15) value.
ATR(15) is the SMA(15) value of the difference between the high and low values.
The scripts shows a lot of graphical information:
The close value is shown in light-green. When the close value is lower then the buy value, the close value is shown in light-red. This way it is possible to evaluate the virtual losses during the trade.
the trailing stop value is shown in dark-green. When the sell value is lower then the buy value, the last color of the trade will be red (best viewed when zoomed)(in the example, there are 2 trades that end in gain and 2 in loss (red line at end))
the EMA and SMA values for both buy and sell signals are shown as a line
the buy and sell(close) signals are labeled in blue
How to use this strategy?
Every stock has it's own "DNA", so first thing to do is tune the right parameters to get the best strategy values voor EMA , SMA, Strength for both buy and sell and the Trailing Stop (#ATR).
Look in the strategy tester overview to optimize the values Percent Profitable and Net Profit (using the strategy settings icon, you can increase/decrease the parameters)
Then keep using these parameters for future buy/sell signals only for that particular stock.
Do the same for other stocks.
Important : optimizing these parameters is no guarantee for future winning trades!
Here are the parameters:
Fast EMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 10-20)
Slow SMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 30-100)
Minimum Buy Strength: minimum upward trend value of the Fast SMA Buy value (directional coefficient)(use values between 0-120)
Fast EMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 10-20)
Slow SMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 30-100)
Minimum Sell Strength: minimum downward trend value of the Fast SMA Sell value (directional coefficient)(use values between 0-120)
Trailing Stop (#ATR): the trailing stop value as a multiple of the ATR(15) value (use values between 2-20)
Example parameters for different stocks (Start capital: 1000, Order=100% of equity, Period 1/1/2005 to now) compared to the Buy&Hold Strategy(=do nothing):
BEKB(Bekaert): EMA-Buy=12, SMA-Buy=44, Strength-Buy=65, EMA-Sell=12, SMA-Sell=55, Strength-Sell=120, Stop#ATR=20
NetProfit: 996%, #Trades: 6, %Profitable: 83%, Buy&HoldProfit: 78%
BAR(Barco): EMA-Buy=16, SMA-Buy=80, Strength-Buy=44, EMA-Sell=12, SMA-Sell=45, Strength-Sell=82, Stop#ATR=9
NetProfit: 385%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 55%
AAPL(Apple): EMA-Buy=12, SMA-Buy=45, Strength-Buy=40, EMA-Sell=19, SMA-Sell=45, Strength-Sell=106, Stop#ATR=8
NetProfit: 6900%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 2938%
TNET(Telenet): EMA-Buy=12, SMA-Buy=45, Strength-Buy=27, EMA-Sell=19, SMA-Sell=45, Strength-Sell=70, Stop#ATR=14
NetProfit: 129%, #Trade
LONDON RIPPER Breakout · Daytrade EURUSDWhat it does
The script hunts for the first decisive break of the Tokyo range when London liquidity comes online. It fires long or short only if:
Price leaves the Asia box (05 : 00 – 06 : 55 GMT).
The break occurs inside the EU Entry Window (07 : 00 – 08 : 30 GMT).
Relative Volume (rVol) confirms momentum
- Longs: rVol ≥ 1 - Shorts: rVol < 1
Bollinger Band filter adds extra thrust confirmation
- Longs: close > upper band - Shorts: close < lower band.
Stop-loss is always the opposite side of the Asia box. No targets—let the move run.
All orders are sent on bar close with standard OHLC fills—no repaint, no intrabar peeking.
Default inputs
Anchor TF ………… 1 Day (volume baseline)
rVol Length ………… 9 bars (cumulative mode)
Tokyo Session …… 05 : 00-06 : 55 GMT
EU Session (full) … 07 : 00-13 : 00 GMT
EU Entry Window … 07 : 00-08 : 30 GMT
BB Length ………… 20 | Basis MA: SMMA (RMA) | StDev Mult: 2
All times are editable and use the Session Time-Zone = GMT by default.
Strategy properties used in the back-test
Initial capital: 100 000
Order size: 5 % of equity | Pyramiding: 1
Commission: 0.0001 USD per contract
Slippage: 3 ticks
Recalculate: none | Fill orders: On bar close + Standard OHLC
Feel free to adjust these values to match your broker’s conditions.
How to use
Add the script to any intraday EURUSD chart (≤ 30 min works best from our testings).
Check that your broker’s session times line up—modify if needed.
Keep risk sensible; the default 5 % per trade is a placeholder, not advice.
Let the strategy run only during the European session; it auto-flattens outside 07-13 GMT.
Important notes
Requires a feed that supplies real volume (needed for rVol).
No request.security() with look-ahead—this code is 100 % forward-safe.
Past results never guarantee future returns. London news spikes can still blow through stops. Test before you trade live.
Credits
Built from scratch using only TradingView built-in functions and the official ta library. No external code reused.
Trade disciplined, and may the Ripper be with you!
Top Movers RSI StrategyEntry Signal (Buy): The script triggers a buy order when the chosen indicator(s) confirm a bullish trend or oversold condition, indicating a potential upward price movement.
Exit Signal (Sell): The script triggers a sell order when the indicator(s) signal a bearish trend or overbought condition, suggesting the price may decline.
Risk Management: The strategy includes stop-loss and take-profit levels to limit losses and secure profits.
Timeframe: The strategy operates on a chart to capture relevant price action.
Additional Filters: Optional filters like volume confirmation, moving average crossovers, or RSI thresholds can be included to reduce false signals.
Long/Short/Exit/Risk management Strategy # LongShortExit Strategy Documentation
## Overview
The LongShortExit strategy is a versatile trading system for TradingView that provides complete control over entry, exit, and risk management parameters. It features a sophisticated framework for managing long and short positions with customizable profit targets, stop-loss mechanisms, partial profit-taking, and trailing stops. The strategy can be enhanced with continuous position signals for visual feedback on the current trading state.
## Key Features
### General Settings
- **Trading Direction**: Choose to trade long positions only, short positions only, or both.
- **Max Trades Per Day**: Limit the number of trades per day to prevent overtrading.
- **Bars Between Trades**: Enforce a minimum number of bars between consecutive trades.
### Session Management
- **Session Control**: Restrict trading to specific times of the day.
- **Time Zone**: Specify the time zone for session calculations.
- **Expiration**: Optionally set a date when the strategy should stop executing.
### Contract Settings
- **Contract Type**: Select from common futures contracts (MNQ, MES, NQ, ES) or custom values.
- **Point Value**: Define the dollar value per point movement.
- **Tick Size**: Set the minimum price movement for accurate calculations.
### Visual Signals
- **Continuous Position Signals**: Implement 0 to 1 visual signals to track position states.
- **Signal Plotting**: Customize color and appearance of position signals.
- **Clear Visual Feedback**: Instantly see when entry conditions are triggered.
### Risk Management
#### Stop Loss and Take Profit
- **Risk Type**: Choose between percentage-based, ATR-based, or points-based risk management.
- **Percentage Mode**: Set SL/TP as a percentage of entry price.
- **ATR Mode**: Set SL/TP as a multiple of the Average True Range.
- **Points Mode**: Set SL/TP as a fixed number of points from entry.
#### Advanced Exit Features
- **Break-Even**: Automatically move stop-loss to break-even after reaching specified profit threshold.
- **Trailing Stop**: Implement a trailing stop-loss that follows price movement at a defined distance.
- **Partial Profit Taking**: Take partial profits at predetermined price levels:
- Set first partial exit point and percentage of position to close
- Set second partial exit point and percentage of position to close
- **Time-Based Exit**: Automatically exit a position after a specified number of bars.
#### Win/Loss Streak Management
- **Streak Cutoff**: Automatically pause trading after a series of consecutive wins or losses.
- **Daily Reset**: Option to reset streak counters at the start of each day.
### Entry Conditions
- **Source and Value**: Define the exact price source and value that triggers entries.
- **Equals Condition**: Entry signals occur when the source exactly matches the specified value.
### Performance Analytics
- **Real-Time Stats**: Track important performance metrics like win rate, P&L, and largest wins/losses.
- **Visual Feedback**: On-chart markers for entries, exits, and important events.
### External Integration
- **Webhook Support**: Compatible with TradingView's webhook alerts for automated trading.
- **Cross-Platform**: Connect to external trading systems and notification platforms.
- **Custom Order Execution**: Implement advanced order flows through external services.
## How to Use
### Setup Instructions
1. Add the script to your TradingView chart.
2. Configure the general settings based on your trading preferences.
3. Set session trading hours if you only want to trade specific times.
4. Select your contract specifications or customize for your instrument.
5. Configure risk parameters:
- Choose your preferred risk management approach
- Set appropriate stop-loss and take-profit levels
- Enable advanced features like break-even, trailing stops, or partial profit taking as needed
6. Define entry conditions:
- Select the price source (such as close, open, high, or an indicator)
- Set the specific value that should trigger entries
### Entry Condition Examples
- **Example 1**: To enter when price closes exactly at a whole number:
- Long Source: close
- Long Value: 4200 (for instance, to enter when price closes exactly at 4200)
- **Example 2**: To enter when an indicator reaches a specific value:
- Long Source: ta.rsi(close, 14)
- Long Value: 30 (triggers when RSI equals exactly 30)
### Best Practices
1. **Always backtest thoroughly** before using in live trading.
2. **Start with conservative risk settings**:
- Small position sizes
- Reasonable stop-loss distances
- Limited trades per day
3. **Monitor and adjust**:
- Use the performance table to track results
- Adjust parameters based on how the strategy performs
4. **Consider market volatility**:
- Use ATR-based stops during volatile periods
- Use fixed points during stable markets
## Continuous Position Signals Implementation
The LongShortExit strategy can be enhanced with continuous position signals to provide visual feedback about the current position state. These signals can help you track when the strategy is in a long or short position.
### Adding Continuous Position Signals
Add the following code to implement continuous position signals (0 to 1):
```pine
// Continuous position signals (0 to 1)
var float longSignal = 0.0
var float shortSignal = 0.0
// Update position signals based on your indicator's conditions
longSignal := longCondition ? 1.0 : 0.0
shortSignal := shortCondition ? 1.0 : 0.0
// Plot continuous signals
plot(longSignal, title="Long Signal", color=#00FF00, linewidth=2, transp=0, style=plot.style_line)
plot(shortSignal, title="Short Signal", color=#FF0000, linewidth=2, transp=0, style=plot.style_line)
```
### Benefits of Continuous Position Signals
- Provides clear visual feedback of current position state (long/short)
- Signal values stay consistent (0 or 1) until condition changes
- Can be used for additional calculations or alert conditions
- Makes it easier to track when entry conditions are triggered
### Using with Custom Indicators
You can adapt the continuous position signals to work with any custom indicator by replacing the condition with your indicator's logic:
```pine
// Example with moving average crossover
longSignal := fastMA > slowMA ? 1.0 : 0.0
shortSignal := fastMA < slowMA ? 1.0 : 0.0
```
## Webhook Integration
The LongShortExit strategy is fully compatible with TradingView's webhook alerts, allowing you to connect your strategy to external trading platforms, brokers, or custom applications for automated trading execution.
### Setting Up Webhooks
1. Create an alert on your chart with the LongShortExit strategy
2. Enable the "Webhook URL" option in the alert dialog
3. Enter your webhook endpoint URL (from your broker or custom trading system)
4. Customize the alert message with relevant information using TradingView variables
### Webhook Message Format Example
```json
{
"strategy": "LongShortExit",
"action": "{{strategy.order.action}}",
"price": "{{strategy.order.price}}",
"quantity": "{{strategy.position_size}}",
"time": "{{time}}",
"ticker": "{{ticker}}",
"position_size": "{{strategy.position_size}}",
"position_value": "{{strategy.position_value}}",
"order_id": "{{strategy.order.id}}",
"order_comment": "{{strategy.order.comment}}"
}
```
### TradingView Alert Condition Examples
For effective webhook automation, set up these alert conditions:
#### Entry Alert
```
{{strategy.position_size}} != {{strategy.position_size}}
```
#### Exit Alert
```
{{strategy.position_size}} < {{strategy.position_size}} or {{strategy.position_size}} > {{strategy.position_size}}
```
#### Partial Take Profit Alert
```
strategy.order.comment contains "Partial TP"
```
### Benefits of Webhook Integration
- **Automated Trading**: Execute trades automatically through supported brokers
- **Cross-Platform**: Connect to custom trading bots and applications
- **Real-Time Notifications**: Receive trade signals on external platforms
- **Data Collection**: Log trade data for further analysis
- **Custom Order Management**: Implement advanced order types not available in TradingView
### Compatible External Applications
- Trading bots and algorithmic trading software
- Custom order execution systems
- Discord, Telegram, or Slack notification systems
- Trade journaling applications
- Risk management platforms
### Implementation Recommendations
- Test webhook delivery using a free service like webhook.site before connecting to your actual trading system
- Include authentication tokens or API keys in your webhook URL or payload when required by your external service
- Consider implementing confirmation mechanisms to verify trade execution
- Log all webhook activities for troubleshooting and performance tracking
## Integrating with Confluence of Signals
The LongShortExit strategy can be enhanced by using it in conjunction with the "Confluence of Alerts" indicator to create more robust entry conditions based on multiple technical signals.
### What is Confluence of Signals?
The Confluence of Alerts indicator allows you to define up to 8 different technical conditions that must be met simultaneously to generate a trading signal. This approach helps filter out false signals and only enters trades when multiple technical factors align.
### Integration Approach
#### Method 1: Using Confluence as a Signal Source
1. Add the Confluence of Alerts indicator to your chart
2. Configure your desired technical conditions (RSI, moving averages, support/resistance, etc.)
3. In the LongShortExit strategy settings:
- Set Long Source to `plot("Long All")` from the Confluence indicator
- Set Long Value to `1` with "Equals" condition
- Similarly for Short Source using `plot("Short All")`
#### Method 2: Modifying the Strategy Code
For more advanced integration, you can incorporate the condition logic directly:
```pine
// Add to the top of your LongShortExit strategy
//@import TradersPost/Confluence_of_Alerts/1
// Replace simple entry conditions with confluence signals
longCondition = confluence_long_signal and longEntryCondition
shortCondition = confluence_short_signal and shortEntryCondition
```
### Confluence Configuration Examples
#### Trend-Following Configuration
1. **Condition 1**: When SMA(20) crossing up SMA(50)
2. **Condition 2**: When RSI(14) greater than 50
3. **Condition 3**: When close greater than VWAP
4. **Condition 4**: When ADX(14) greater than 25
#### Support/Resistance Configuration
1. **Condition 1**: When price crossing up pivot support
2. **Condition 2**: When Stochastic %K crossing up %D
3. **Condition 3**: When volume greater than average volume
4. **Condition 4**: When price greater than previous day's close
### Benefits of Using Confluence with LongShortExit
- **Reduced False Signals**: Enter trades only when multiple conditions confirm the signal
- **Higher Probability Trades**: Each additional confirming factor increases trade success probability
- **Customizable Filter**: Adapt the conditions to suit different market environments and trading styles
- **Visual Confirmation**: The Confluence indicator provides clear visual signals when all conditions are met
### Implementation Tips
1. Start with 2-3 conditions before adding more complexity
2. Ensure conditions aren't redundant (e.g., don't use multiple similar indicators)
3. Include conditions from different categories:
- Trend indicators (moving averages, ADX)
- Momentum indicators (RSI, MACD)
- Volume indicators
- Support/resistance levels
4. Test different timeframes for the conditions
5. Use the "on Bar Close" option for more reliable signals
## Strategy Customization Tips
### For Scalping
- Set smaller profit targets (1-3 points)
- Use tighter stop-losses
- Enable break-even feature after small profit
- Set higher max trades per day
### For Day Trading
- Use moderate profit targets
- Implement partial profit taking
- Enable trailing stops
- Set reasonable session trading hours
### For Swing Trading
- Use longer-term charts
- Set wider stops (ATR-based often works well)
- Use higher profit targets
- Disable daily streak reset
## Common Troubleshooting
### Low Win Rate
- Consider widening stop-losses
- Verify that entry conditions aren't triggering too frequently
- Check if the equals condition is too restrictive; consider small tolerances
### Missing Obvious Trades
- The equals condition is extremely precise. Price must exactly match the specified value.
- Consider using floating-point precision for more reliable triggers
### Frequent Stop-Outs
- Try ATR-based stops instead of fixed points
- Increase the stop-loss distance
- Enable break-even feature to protect profits
## Important Notes
- The exact equals condition is strict and may result in fewer trade signals compared to other conditions.
- For instruments with decimal prices, exact equality might be rare. Consider the precision of your value.
- Break-even and trailing stop calculations are based on points, not percentage.
- Partial take-profit levels are defined in points distance from entry.
- The continuous position signals (0 to 1) provide valuable visual feedback but don't affect the strategy's trading logic directly.
- When implementing continuous signals, ensure they're aligned with the actual entry conditions used by the strategy.
---
*This strategy is for educational and informational purposes only. Always test thoroughly before using with real funds.*
Strategy [High-Low Cloud Trend] (v6, perf-safe)Description
High-Low Cloud Trend Strategy (Performance-Safe Edition)
Version 6 • RezzoRedPriest (based on the original logic by @rottor29)
How it works
Dynamic range ― The script tracks the highest high / lowest low over a look-back of N bars (len). When price tags one extreme, a “pivot” flips to the opposite extreme, forming the core of the cloud.
Trend filter ― If the candle closes above the pivot, trend = bullish; below it, trend = bearish. The optional “Trade only with trend” switch forces longs in bullish mode and shorts in bearish mode.
Signals
Cloud Retest – price pulls back to the inner edge (band1) and rejects it.
Cloud Cross – price breaks through the outer edge (band).
Mean Reversion – spikes beyond the inner edge and snap back (optional).
Execution model – trades are processed once per bar (process_orders_on_close = true), capped at maxTradesPerDay.
Performance guardrails
Only the most-recent visBars bars are calculated and painted.
Object limits: max_labels_count = 400, max_lines_count = 30.
Inputs
Group Name Purpose
Display Drawings: show last N bars Hard cap for calculations & drawings (default = 500).
Display Show markers / labels Toggle all arrows / diamonds.
Display Show cloud fill & background Toggle the colored cloud & background.
Strategy Look-back period (len) Width of the cloud; larger = smoother trend.
Strategy Enable trading Completely turn trade logic on/off.
Strategy Take cloud-retest / cross / mean-reversion signals Select which setups feed the engine.
Strategy Trade only with trend Filter counter-trend signals.
Risk Max trades per day Hard daily cap.
Recommended use
Works on any timeframe; common sweet spots are 5 m & 15 m for liquid futures / FX.
Increase len for higher timeframes (e.g. 55–100 on 1 H) to avoid noise.
If your chart still lags, either:
Lower Drawings: show last N bars, or
Turn Show cloud fill off – the fill is the heaviest operation.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Always test on demo data first and use proper risk management.
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.
AltCoin Index Correlation🧠 AltCoin Index Correlation — Strategy Overview
AltCoin Index Correlation is a dynamic EMA-based trading strategy designed primarily for altcoins, but also adaptable to stocks and indices, thanks to its flexible reference index system.
🧭 Strategy Philosophy
The core idea behind this strategy is simple yet powerful:
Price action becomes more meaningful when it aligns with broader market context.
This script analyzes the correlation between the asset’s trend and a reference index trend, using dual EMA (Exponential Moving Average) crossovers for both.
When both the altcoin and the reference index (e.g. Altcoin Dominance, BTC Dominance, Total Market Cap, or even indices like the NASDAQ 100 or S&P 500) are aligned in trend direction, the script considers it a high-confidence setup.
It also includes:
Optional inverse correlation logic (for contrarian setups)
Custom leverage settings (e.g., 1x, 1.8x, etc.)
A dynamic scale-out mechanism during weakening trends
Date filtering for controlled backtests
A live performance dashboard with equity, PnL, win rate, drawdown, APR, and more
⚙️ Default Settings & Backtest Results
Timeframe tested: 1H
Test date: May 20, 2025
Sample: 100 high-cap altcoins
Reference index: CRYPTOCAP:OTHERS.D (Altcoin Dominance)
Leverage: 1.8x (180% of capital used)
📊 With default settings:
Win rate: ~80%
Higher profits, due to increased exposure
Best suited for confident trend followers with higher risk tolerance
📉 With fixed capital or 1x leverage:
Win rate improves to ~90%
Lower returns, but greater capital preservation
Ideal for conservative or risk-managed trading styles
🔄 Versatility
While tailored for altcoins, this strategy supports traditional markets as well:
Easily switch the reference index to OANDA:NAS100USD or S&P 500 for stock correlation trading
Adjust EMA lengths and leverage to match the asset class and volatility profile
🧩 Suggested Use
Best used on trending markets (not sideways)
Ideal for 1H timeframes, but adjustable
Suitable for traders who want a rules-based, macro-aware entry/exit system
Try it out, customize it to your style, try different settings and share your results with the community!
Feedback is welcome — and improvements are always in progress.
🚀 ### Check my profile for other juicy hints and original strategies. ### 🚀
Liquidity Grab Strategy (Volume Trap)🧠 Strategy Logic:
Liquidity Grab Detection:
The script looks for a sharp drop in price (bearish engulfing or breakdown candle).
However, volume remains flat (within 5% of the 20-period moving average), suggesting the move is manipulated, not genuine.
Fair Value Gap Confirmation (FVG):
It confirms that a Fair Value Gap exists — a gap between recent candle bodies that price is likely to retrace into.
This gap represents a high-probability entry zone.
Trade Setup:
A limit BUY order is placed at the base of the FVG.
Stop Loss (SL) is placed below the gap.
Take Profit (TP) is placed at the most recent swing high.
📈 How to Use It:
Add the strategy to your TradingView chart (1–5 min or 15 min works well for intraday setups).
Look for green BUY labels and plotted lines:
💚 Green = Entry price
🔴 Red = Stop loss
🔵 Blue = Take profit
The script will automatically simulate entries when conditions are met and exit either at TP or SL.
Use TradingView’s Strategy Tester to review:
Win rate
Net profit
Risk-adjusted performance
Triangle Breakout Strategy with TP/SL, EMA Filter📌 Triangle Breakout Strategy with TP/SL, EMA Filters, and Backtest – Explained.
✅ 1. Pattern Detection – Triangle Breakout
The script scans for triangle patterns by detecting local pivot highs and pivot lows.
It uses two recent highs and two recent lows to draw converging trendlines (upper and lower boundaries of the triangle).
If the price breaks above the upper trendline, a bullish breakout signal is generated.
🎯 2. TP (Take Profit) & SL (Stop Loss)
When a bullish breakout is detected:
A buy order is placed using strategy.entry.
TP and SL levels are calculated relative to the current close price:
TP = 3% above the entry price
SL = 1.5% below the entry price
These are defined using strategy.exit.
📊 3. EMA Filter
An optional filter checks if:
Price is above both EMA 20 and EMA 50
Only if this condition is met, the strategy allows a long entry.
You can toggle the filter on or off with useEMAFilter.
📈 4. Backtesting with Strategy Tester
This script uses strategy() instead of indicator() to enable TradingView’s built-in backtest engine.
Every buy entry and exit (based on TP or SL) is recorded.
📌 5. Visuals
EMA 20 and EMA 50 lines are plotted on the chart.
A label is shown when a breakout is detected: "Breakout Up"
Results (profit, win rate, drawdown, etc.) can be viewed in the Strategy Tester panel.
Arbitrage Spot-Futures Don++Strategy: Spot-Futures Arbitrage Don++
This strategy has been designed to detect and exploit arbitrage opportunities between the Spot and Futures markets of the same trading pair (e.g. BTC/USDT). The aim is to take advantage of price differences (spreads) between the two markets, while minimizing risk through dynamic position management.
[Operating principle
The strategy is based on calculating the spread between Spot and Futures prices. When this spread exceeds a certain threshold (positive or negative), reverse positions are opened simultaneously on both markets:
- i] Long Spot + Short Futures when the spread is positive.
- i] Short Spot + Long Futures when the spread is negative.
Positions are closed when the spread returns to a value close to zero or after a user-defined maximum duration.
[Strategy strengths
1. Adaptive thresholds :
- Entry/exit thresholds can be dynamic (based on moving averages and standard deviations) or fixed, offering greater flexibility to adapt to market conditions.
2. Robust data management :
- The script checks the validity of data before executing calculations, thus avoiding errors linked to missing or invalid data.
3. Risk limitation :
- A position size based on a percentage of available capital (default 10%) limits exposure.
- A time filter limits the maximum duration of positions to avoid losses due to persistent spreads.
4. Clear visualization :
- Charts include horizontal lines for entry/exit thresholds, as well as visual indicators for spread and Spot/Futures prices.
5. Alerts and logs :
- Alerts are triggered on entries and exits to inform the user in real time.
[Points for improvement or completion
Although this strategy is functional and robust, it still has a few limitations that could be addressed in future versions:
1. [Limited historical data :
- TradingView does not retrieve real-time data for multiple symbols simultaneously. This can limit the accuracy of calculations, especially under conditions of high volatility.
2. [Lack of liquidity management :
- The script does not take into account the volumes available on the order books. In conditions of low liquidity, it may be difficult to execute orders at the desired prices.
3. [Non-dynamic transaction costs :
- Transaction costs (exchange fees, slippage) are set manually. A dynamic integration of these costs via an external API would be more realistic.
4. User-dependency for symbols :
- Users must manually specify Spot and Futures symbols. Automatic symbol validation would be useful to avoid configuration errors.
5. Lack of advanced backtesting :
- Backtesting is based solely on historical data available on TradingView. An implementation with third-party data (via an API) would enable the strategy to be tested under more realistic conditions.
6. [Parameter optimization :
- Certain parameters (such as analysis period or spread thresholds) could be optimized for each specific trading pair.
[How can I contribute?
If you'd like to help improve this strategy, here are a few ideas:
1. Add additional filters:
- For example, a filter based on volume or volatility to avoid false signals.
2. Integrate dynamic costs:
- Use an external API to retrieve actual costs and adjust thresholds accordingly.
3. Improve position management:
- Implement hedging or scalping mechanisms to maximize profits.
4. Test on other pairs:
- Evaluate the strategy's performance on other assets (ETH, SOL, etc.) and adjust parameters accordingly.
5. Publish backtesting results :
- Share detailed analyses of the strategy's performance under different market conditions.
[Conclusion
This Spot-Futures arbitrage strategy is a powerful tool for exploiting price differentials between markets. Although it is already functional, it can still be improved to meet more complex trading scenarios. Feel free to test, modify and share your ideas to make this strategy even more effective!
[Thank you for contributing to this open-source community!
If you have any questions or suggestions, please feel free to comment or contact me directly.
PVSRA v5Overview of the PVSRA Strategy
This strategy is designed to detect and capitalize on volume-driven threshold breaches in price candles. It operates on the premise that when a high-volume candle breaks a critical price threshold, not all orders are filled within that candle’s range. This creates an imbalance—similar to a physical system being perturbed—causing the price to revert toward the level where the breach occurred to “absorb” the residual orders.
Key Features and Their Theoretical Underpinnings
Dynamic Volume Analysis and Threshold Detection
Volume Surges as Market Perturbations:
The script computes a moving average of volume over a short window and flags moments when the current volume significantly exceeds this average. These surges act as a perturbation—injecting “energy” into the market.
Adaptive Abnormal Volume Threshold:
By calculating a dynamic abnormal threshold using a daily volume average (via an 89-period VWMA) and standard deviation, the strategy identifies when the current volume is abnormally high. This mechanism mirrors the idea that when a system is disturbed (here, by a volume surge), it naturally seeks to return to equilibrium.
Candle Coloring and Visual Signal Identification
Differentiation of Candle Types:
The script distinguishes between bullish (green) and bearish (red) candles. It applies different colors based on the strength of the volume signal, providing a clear, visual representation of whether a candle is likely to trigger a price reversion.
Implication of Unfilled Orders:
A red (bearish) candle with high volume implies that sell pressure has pushed the price past a critical threshold—yet not all buy orders have been fulfilled. Conversely, a green (bullish) candle indicates that aggressive buying has left pending sell orders. In both cases, the market is expected to reverse toward the breach point to restore balance.
Trade Execution Logic: Normal and Reversal Trades
Normal Trades:
When a high-volume candle breaches a threshold and meets the directional conditions (e.g., a red candle paired with price above a daily upper band), the strategy enters a trade anticipating a reversion. The underlying idea is that the market will move back to the level where the threshold was crossed—clearing the residual orders in a manner analogous to a system following the path of least resistance.
Reversal Trades:
The strategy also monitors for clusters of consecutive signals within a short lookback period. When multiple signals accumulate, it interprets this as the market having overextended and, in a corrective move, reverses the typical trade direction. This inversion captures the market’s natural tendency to “correct” itself by moving in discrete, quantized steps—each step representing the absorption of a minimum quantum of order imbalance.
Risk and Trade Management
Stop Loss and Take Profit Buffers:
Both normal and reversal trades include predetermined buffers for stop loss and take profit levels. This systematic risk management approach is designed to capture the anticipated reversion while minimizing potential losses, aligning with the idea that market corrections follow the most energy-efficient path back to equilibrium.
Symbol Flexibility:
An option to override the chart’s symbol allows the strategy to be applied consistently across different markets, ensuring that the volume and price dynamics are analyzed uniformly.
Conceptual Bridge: From Market Dynamics to Trade Execution
At its core, the strategy treats market price movements much like a physical system that seeks to minimize “transactional energy” or inefficiency. When a price candle breaches a key threshold on high volume, it mimics an injection of energy into the system. The subsequent price reversion is the market’s natural response—moving in the most efficient path back to balance. This perspective is akin to the principle of least action, where the system evolves along the trajectory that minimizes cumulative imbalance, and it acknowledges that these corrections occur in discrete steps reflective of quantized order execution.
This unified framework allows the PVSRA strategy to not only identify when significant volume-based threshold breaches occur but also to systematically execute trades that benefit from the expected corrective moves.
GM+For a Short Trade:
When a bullish candle (close > open) is larger than the previous candle and the MACD histogram for the past three bars is consecutively lower (suggesting weakening upward momentum), the script enters a short position.
For a Long Trade:
When a bearish candle (close < open) is larger (in body size) than the previous candle and the MACD histogram for the past three bars is consecutively higher (suggesting the downward move is losing strength), the script enters a long position.
Position Management:
There are no stop loss or take profit levels. The position is closed only when an opposite signal appears.
ICT NY Kill Zone Auto Trading### **ICT NY Kill Zone Auto Trading Strategy (5-Min Chart)**
#### **Overview:**
This strategy is based on Inner Circle Trader (ICT) concepts, focusing on the **New York Kill Zone**. It is designed for trading GBP/USD exclusively on the **5-minute chart**, automatically entering and exiting trades during the US session.
#### **Key Components:**
1. **Time Filter**
- The strategy only operates during the **New York Kill Zone (9:30 AM - 11:00 AM NY Time)**.
- It ensures execution only on the **5-minute timeframe**.
2. **Fair Value Gaps (FVGs) Detection**
- The script identifies areas where price action left an imbalance, known as Fair Value Gaps (FVGs).
- These gaps indicate potential liquidity zones where price may return before continuing in the original direction.
3. **Order Blocks (OBs) Identification**
- **Bullish Order Block:** Occurs when price forms a strong bullish pattern, suggesting further upside movement.
- **Bearish Order Block:** Identified when a strong bearish formation signals potential downside continuation.
4. **Trade Execution**
- **Long Trade:** Entered when a bullish order block forms within the NY Kill Zone and aligns with an FVG.
- **Short Trade:** Entered when a bearish order block forms within the Kill Zone and aligns with an FVG.
5. **Risk Management**
- **Stop Loss:** Fixed at **30 pips** to limit downside risk.
- **Take Profit:** Set at **60 pips**, providing a **2:1 risk-reward ratio**.
6. **Visual Aids**
- The **Kill Zone is highlighted in blue** to help traders visually confirm the active session.
**Objective:**
This script aims to **capitalize on institutional price movements** within the New York session by leveraging ICT concepts such as FVGs and Order Blocks. By automating trade entries and exits, it eliminates emotions and ensures a disciplined trading approach.
Multi-Timeframe RSI Grid Strategy with ArrowsKey Features of the Strategy
Multi-Timeframe RSI Analysis:
The strategy calculates RSI values for three different timeframes:
The current chart's timeframe.
Two higher timeframes (configurable via higher_tf1 and higher_tf2 inputs).
It uses these RSI values to identify overbought (sell) and oversold (buy) conditions.
Grid Trading System:
The strategy uses a grid-based approach to scale into trades. It adds positions at predefined intervals (grid_space) based on the ATR (Average True Range) and a grid multiplication factor (grid_factor).
The grid system allows for pyramiding (adding to positions) up to a maximum number of grid levels (max_grid).
Daily Profit Target:
The strategy has a daily profit target (daily_target). Once the target is reached, it closes all open positions and stops trading for the day.
Drawdown Protection:
If the open drawdown exceeds 2% of the account equity, the strategy closes all positions to limit losses.
Reverse Signals:
If the RSI conditions reverse (e.g., from buy to sell or vice versa), the strategy closes all open positions and resets the grid.
Visualization:
The script plots buy and sell signals as arrows on the chart.
It also plots the RSI values for the current and higher timeframes, along with overbought and oversold levels.
How It Works
Inputs:
The user can configure parameters like RSI length, overbought/oversold levels, higher timeframes, grid spacing, lot size multiplier, maximum grid levels, daily profit target, and ATR length.
RSI Calculation:
The RSI is calculated for the current timeframe and the two higher timeframes using ta.rsi().
Grid System:
The grid system uses the ATR to determine the spacing between grid levels (grid_space).
When the price moves in the desired direction, the strategy adds positions at intervals of grid_space, increasing the lot size by a multiplier (lot_multiplier) for each new grid level.
Entry Conditions:
A buy signal is generated when the RSI is below the oversold level on all three timeframes.
A sell signal is generated when the RSI is above the overbought level on all three timeframes.
Position Management:
The strategy scales into positions using the grid system.
It closes all positions if the daily profit target is reached or if a reverse signal is detected.
Visualization:
Buy and sell signals are plotted as arrows on the chart.
RSI values for all timeframes are plotted, along with overbought and oversold levels.
Example Scenario
Suppose the current RSI is below 30 (oversold), and the RSI on the 60-minute and 240-minute charts is also below 30. This triggers a buy signal.
The strategy enters a long position with a base lot size.
If the price moves against the position by grid_space, the strategy adds another long position with a larger lot size (scaled by lot_multiplier).
This process continues until the maximum grid level (max_grid) is reached or the daily profit target is achieved.
Key Variables
grid_level: Tracks the current grid level (number of positions added).
last_entry_price: Tracks the price of the last entry.
base_size: The base lot size for the initial position.
daily_profit_target: The daily profit target in percentage terms.
target_reached: A flag to indicate whether the daily profit target has been achieved.
Potential Use Cases
This strategy is suitable for traders who want to combine RSI-based signals with a grid trading approach to capitalize on mean-reverting price movements.
It can be used in trending or ranging markets, depending on the RSI settings and grid parameters.
Limitations
The grid trading system can lead to significant drawdowns if the market moves strongly against the initial position.
The strategy relies heavily on RSI, which may produce false signals in strongly trending markets.
The daily profit target may limit potential gains in highly volatile markets.
Customization
You can adjust the input parameters (e.g., RSI length, overbought/oversold levels, grid spacing, lot multiplier) to suit your trading style and market conditions.
You can also modify the drawdown protection threshold or add additional filters (e.g., volume, moving averages) to improve the strategy's performance.
In summary, this script is a sophisticated trading strategy that combines RSI-based signals with a grid trading system to manage entries, exits, and position sizing. It includes features like daily profit targets, drawdown protection, and multi-timeframe analysis to enhance its robustnes
Multi-Band Comparison Strategy (CRYPTO)Multi-Band Comparison Strategy (CRYPTO)
Optimized for Cryptocurrency Trading
This Pine Script strategy is built from the ground up for traders who want to take advantage of cryptocurrency volatility using a confluence of advanced statistical bands. The strategy layers Bollinger Bands, Quantile Bands, and a unique Power-Law Band to map out crucial support/resistance zones. It then focuses on a Trigger Line—the lower standard deviation band of the upper quantile—to pinpoint precise entry and exit signals.
Key Features
Bollinger Band Overlay
The upper Bollinger Band visually shifts to yellow when price exceeds it, turning black otherwise. This offers a straightforward way to gauge heightened momentum or potential market slowdowns.
Quantile & Power-Law Integration
The script calculates upper and lower quantile bands to assess probabilistic price extremes.
A Power-Law Band is also available to measure historically significant return levels, providing further insight into overbought or oversold conditions in fast-moving crypto markets.
Standard Deviation Trigger
The lower standard deviation band of the upper quantile acts as the strategy’s trigger. If price consistently holds above this line, the strategy interprets it as a strong bullish signal (“green” zone). Conversely, dipping below indicates a “red” zone, signaling potential reversals or exits.
Consecutive Bar Confirmation
To reduce choppy signals, you can fine-tune the number of consecutive bars required to confirm an entry or exit. This helps filter out noise and false breaks—critical in the often-volatile crypto realm.
Adaptive for Multiple Timeframes
Whether you’re scalping on a 5-minute chart or swing trading on daily candles, the strategy’s flexible confirmation and overlay options cater to different market conditions and trading styles.
Complete Plot Customization
Easily toggle visibility of each band or line—Bollinger, Quantile, Power-Law, and more.
Built-in Simple and Exponential Moving Averages can be enabled to further contextualize market trends.
Why It Excels at Crypto
Cryptocurrencies are known for rapid price swings, and this strategy addresses exactly that by combining multiple statistical methods. The quantile-based confirmation reduces noise, while Bollinger and Power-Law bands help highlight breakout regions in trending markets. Traders have reported that it works seamlessly across various coins and tokens, adapting its triggers to each asset’s unique volatility profile.
Give it a try on your favorite cryptocurrency pairs. With advanced data handling, crisp visual cues, and adjustable confirmation logic, the Multi-Band Comparison Strategy provides a robust framework to capture profitable moves and mitigate risk in the ever-evolving crypto space.
Fibonacci Trend - Aynet1. Inputs
lookbackPeriod: Defines the number of bars to consider for calculating swing highs and lows. Default is 20.
fibLevel1 to fibLevel5: Fibonacci retracement levels to calculate price levels (23.6%, 38.2%, 50%, 61.8%, 78.6%).
useTime: Enables or disables time-based Fibonacci projections.
riskPercent: Defines the percentage of risk for trading purposes (currently not used in calculations).
2. Functions
isSwingHigh(index): Identifies a swing high at the given index, where the high of that candle is higher than both its previous and subsequent candles.
isSwingLow(index): Identifies a swing low at the given index, where the low of that candle is lower than both its previous and subsequent candles.
3. Variables
swingHigh and swingLow: Store the most recent swing high and swing low prices.
swingHighTime and swingLowTime: Store the timestamps of the swing high and swing low.
fib1 to fib5: Fibonacci levels based on the difference between swingHigh and swingLow.
4. Swing Point Detection
The script checks if the last bar is a swing high or swing low using the isSwingHigh() and isSwingLow() functions.
If a swing high is detected:
The high price is stored in swingHigh.
The timestamp of the swing high is stored in swingHighTime.
If a swing low is detected:
The low price is stored in swingLow.
The timestamp of the swing low is stored in swingLowTime.
5. Fibonacci Levels Calculation
If both swingHigh and swingLow are defined, the script calculates the Fibonacci retracement levels (fib1 to fib5) based on the price difference (priceDiff = swingHigh - swingLow).
6. Plotting Fibonacci Levels
Fibonacci levels (fib1 to fib5) are plotted as horizontal lines using the line.new() function.
Labels (e.g., "23.6%") are added near the lines to indicate the level.
Lines and labels are color-coded:
23.6% → Blue
38.2% → Green
50.0% → Yellow
61.8% → Orange
78.6% → Red
7. Filling Between Fibonacci Levels
The plot() function creates lines for each Fibonacci level.
The fill() function is used to fill the space between two levels with semi-transparent colors:
Blue → Between fib1 and fib2
Green → Between fib2 and fib3
Yellow → Between fib3 and fib4
Orange → Between fib4 and fib5
8. Time-Based Fibonacci Projections
If useTime is enabled:
The time difference (timeDiff) between the swing high and swing low is calculated.
Fibonacci time projections are added based on multiples of 23.6%.
If the current time reaches a projected time, a label (e.g., "T1", "T2") is displayed near the high price.
9. Trading Logic
Two placeholder variables are defined for trading logic:
longCondition: Tracks whether a condition for a long trade is met (currently not implemented).
shortCondition: Tracks whether a condition for a short trade is met (currently not implemented).
These variables can be extended to define entry/exit signals based on Fibonacci levels.
How It Works
Detect Swing Points: It identifies recent swing high and swing low points on the chart.
Calculate Fibonacci Levels: Based on the swing points, it computes retracement levels.
Visualize Levels: Plots the levels on the chart with labels and fills between them.
Time Projections: Optionally calculates time-based projections for future price movements.
Trading Opportunities: The framework provides tools for detecting potential reversal or breakout zones using Fibonacci levels.
