Inside Candle StrategyIntroduction
The Inside Candle Breakout Strategy leverages the concept of inside candles as a primary signal for potential breakouts. Unlike common trend-following or scalping strategies, this method focuses on the volatility squeeze indicated by inside candles and aims to capture the momentum that follows these periods of consolidation. The strategy's originality lies in its specific integration of timeframes for signal detection and its application across diverse market conditions without relying on conventional trend indicators.
Strategy Description and Mechanics
Inside Candle Identification: At the heart of this strategy is the detection of inside candles, defined as candles fully contained within the range of the preceding candle. This pattern signifies a temporary balance between buyers and sellers, often preceding significant price movements. The strategy scans for these candles within a user-specified timeframe in the input section of the settings of the strategy, allowing for tailored signal generation based on individual trading preferences.
Entry Points and Market Entries: Upon identifying an inside candle and only once this candle closes, the strategy prepares to enter a trade in the direction of the breakout. Trades are executed in the timeframe selected on the chart, ensuring that entry points are aligned with real-time market movements. This process highlights the strategy's adaptability, making it suitable for various trading styles, from day trading to swing trading.
Overlay Indicator for Enhanced Market Analysis: Accompanying the breakout signals is an overlay indicator comprising two moving averages and a volatility cloud. This feature serves as a secondary tool for market analysis, offering insights into the prevailing market trend and volatility levels. While it doesn't influence the entry or exit signals directly, it provides traders with additional context for refining their decisions, enhancing the strategy's utility. This assistance tool is composed by one moving average and a second line which is calculated adding or subtracting the historical volatility of the asset on the moving average, depending on his momentum.
Strategy Results and Commitment to Realism
Backtesting Protocol: In our commitment to transparency and realism, backtesting results are derived from a dataset that ensures a sufficient number of trades (over 100) to validate the strategy's effectiveness. This approach underscores our dedication to providing traders with reliable and actionable insights.
Risk Management and Trade Sizing: Recognizing the importance of sustainable trading practices, the strategy incorporates strict risk management guidelines. Trades are sized to ensure that only a small percentage of equity is risked on a single trade, adhering to widely accepted risk tolerance levels. The initial account size for this script is set to 10000$.
Strategy Defaults and Justification: The default properties of the strategy, including the risk-reward ratio, average length for moving averages, and other parameters, are carefully chosen based on extensive testing and analysis. These settings represent a balanced approach, aiming to optimize the strategy's performance across a variety of market conditions.
Strategy Components:
- Inside Candles: An inside candle occurs when a candle's high and low are completely contained within the high and low of the previous candle. This pattern indicates a period of consolidation or indecision in the market, often preceding a significant price movement. The strategy detects inside candles based on the user-selected timeframe, allowing traders to capture potential breakouts.
Indicator Overlays:
- Moving Average: A simple moving average (SMA) is calculated over a user-defined length (`Average Length`), providing a dynamic baseline to gauge the market's direction. The strategy offers an option (`Show Moving Average`) to display or hide this moving average on the chart, giving traders control over the visual complexity.
- Volatility Measurement: Alongside the moving average, the strategy assesses market volatility using the standard deviation of the closing prices over the same period defined by the `Average Length`. The moving average is adjusted upwards or downwards by this volatility measure, creating a dynamic channel that reflects the current market conditions.
- Color Gradients for Volatility: The strategy uses a color gradient to fill the area between the moving average and its volatility-adjusted counterpart. This gradient visually represents the volatility level, transitioning from gray (low volatility) to a lighter shade (higher volatility), aiding in the assessment of market sentiment and volatility.
Trading Entries:
- Long Entry: A long position is triggered when the closing price exceeds the high of an inside candle, indicating potential bullish momentum. The strategy places a stop-loss at the low of the inside candle and sets a take-profit level based on the predefined risk-reward ratio (`RR Ratio`).
- Short Entry: Conversely, a short position is initiated when the closing price falls below the low of an inside candle, suggesting bearish pressure. A stop-loss is set at the high of the inside candle, with the take-profit level adjusted according to the risk-reward ratio.
Customization Settings:
- Timeframe: Traders can select the desired timeframe for inside candle detection, tailoring the strategy to fit various trading styles and time horizons.
- RR Ratio: The risk-reward ratio is adjustable, allowing traders to manage the potential risk and return of each trade according to their risk tolerance.
- Average Length: This setting determines the period over which the moving average and volatility are calculated, affecting the sensitivity of the strategy to price movements.
- Visual Settings: Users can customize the appearance of the strategy on their charts, including the colors of the moving average and volatility lines, as well as the line width, enhancing chart readability and personal preference adherence.
Disclaimer
Trading involves significant risk, and it is crucial for traders to conduct their own due diligence before engaging with any strategy. The Inside Candle Breakout Strategy is presented for informational purposes only and does not constitute financial advice.
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FlexiMA x FlexiST - Strategy [presentTrading]█ Introduction and How it is Different
The FlexiMA x FlexiST Strategy blends two analytical methods - FlexiMA and FlexiST, which are opened in my early post.
- FlexiMA calculates deviations between an indicator source and a dynamic moving average, controlled by a starting factor and increment factor.
- FlexiST, on the other hand, leverages the SuperTrend model, adjusting the Average True Range (ATR) length for a comprehensive trend-following oscillator.
This synergy offers traders a more nuanced and multifaceted tool for market analysis.
BTC 6H L/S Performance
Local
█ Strategy, How It Works: Detailed Explanation
The strategy combines two components: FlexiMA and FlexiST, each utilizing unique methodologies to analyze market trends.
🔶FlexiMA Component:
- Calculates deviations between an indicator source and moving averages of variable lengths.
- Moving average lengths are dynamically adjusted using a starting factor and increment factor.
- Deviations are normalized and analyzed to produce median and standard deviation values, forming the FlexiMA oscillator.
Length indicator (50)
🔶FlexiST Component:
- Uses SuperTrend indicators with varying ATR (Average True Range) lengths.
- Trends are identified based on the position of the indicator source relative to the SuperTrend bands.
- Deviations between the indicator source and SuperTrend values are calculated and normalized.
Starting Factor (5)
🔶Combined Strategy Logic:
- Entry Signals:
- Long Entry: Triggered when median values of both FlexiMA and FlexiST are positive.
- Short Entry: Triggered when median values of both FlexiMA and FlexiST are negative.
- Exit Signals:
- Long Exit: Triggered when median values of FlexiMA or FlexiST turn negative.
- Short Exit: Triggered when median values of FlexiMA or FlexiST turn positive.
This strategic blend of FlexiMA and FlexiST allows for a nuanced analysis of market trends, providing traders with signals based on a comprehensive view of market momentum and trend strength.
█ Trade Direction
The strategy is designed to cater to various trading preferences, offering "Long", "Short", and "Both" options. This flexibility allows traders to align the strategy with their specific market outlook, be it bullish, bearish, or a combination of both.
█ Usage
Traders can effectively utilize the FlexiMA x FlexiST Strategy by first selecting their desired trade direction. The strategy then generates entry signals when the conditions for either the FlexiMA or FlexiST are met, indicating potential entry points in the market. Conversely, exit signals are generated when the conditions for these indicators diverge, thus signaling a potential shift in market trends and suggesting a strategic exit point.
█ Default Settings
1. Indicator Source (HLC3): Provides a balanced and stable price source, reducing the impact of extreme market fluctuations.
2. Indicator Lengths (20 for FlexiMA, 10 for FlexiST): Longer FlexiMA length smooths out short-term fluctuations, while shorter FlexiST length allows for quicker response to market changes.
3. Starting Factors (1.0 for FlexiMA, 0.618 for FlexiST): Balanced start for FlexiMA and a harmonized approach for FlexiST, resonating with natural market cycles.
4. Increment Factors (1.0 for FlexiMA, 0.382 for FlexiST): FlexiMA captures a wide range of market behaviors, while FlexiST provides a gradual transition to capture finer trend shifts.
5. Normalization Methods ('None'): Uses raw deviations, suitable for markets where absolute price movements are more significant.
6. Trade Direction ('Both'): Allows strategy to consider both long and short opportunities, ideal for versatile market engagement.
*More details:
1. FlexiMA
2. FlexiST
Three Candle Rolling Pivot Range**Strategy Description: Three Previous Candle Rolling Pivot Range**
**Introduction:**
This trading strategy is based on the concept of the rolling pivot range calculated from the high, low, and close prices of the three previous candles. The rolling pivot range serves as a dynamic support and resistance level, and this strategy aims to capture potential trading opportunities based on the price relationship with this range.
**Strategy Components:**
**1. Rolling Pivot Range Calculation:**
- **Rolling Pivot:** Calculate the rolling pivot by averaging the high, low, and close prices of the three previous candles.
- **Second Number:** Find the midpoint between the high and low of the three previous candles.
- **Pivot Differential:** Measure the difference between the rolling pivot and the second number.
- **Rolling Pivot Range High:** Set as rolling pivot + pivot differential.
- **Rolling Pivot Range Low:** Set as rolling pivot - pivot differential.
**2. Entry Rules:**
- **Long Entry:**
- Initiate a long entry when the current close is above both the rolling pivot range high and the rolling pivot.
- Continue the long entry as long as both the rolling pivot range high and low are higher than the corresponding values of the previous candle.
- **Short Entry:**
- Start a short entry when the current close is below both the rolling pivot range high and the rolling pivot.
- Continue the short entry as long as both the rolling pivot range high and low are lower than the corresponding values of the previous candle.
**Visualization:**
- **Plotting:**
- The rolling pivot range high, rolling pivot, and rolling pivot range low are plotted on the chart for visual reference.
- Long entry points are marked with a green triangle below the corresponding candle.
- Short entry points are marked with a red triangle above the corresponding candle.
**Conclusion:**
This strategy leverages the rolling pivot range to identify potential reversal points in the market. By considering the relative position of the current price compared to the dynamic support and resistance levels, the strategy aims to capture favorable trading opportunities. However, like all trading strategies, it should be used cautiously and backtested thoroughly on historical data to ensure its effectiveness before implementation in a live trading environment. Additionally, risk management techniques should always be applied to safeguard trading capital.
3kilos BTC 15mThe "3kilos BTC 15m" is a comprehensive trading strategy designed to work on a 15-minute timeframe for Bitcoin (BTC) or other cryptocurrencies. This strategy combines multiple indicators, including Triple Exponential Moving Averages (TEMA), Average True Range (ATR), and Heikin-Ashi candlesticks, to generate buy and sell signals. It also incorporates risk management features like take profit and stop loss.
Indicators
Triple Exponential Moving Averages (TEMA): Three TEMA lines are used with different lengths and sources:
Short TEMA (Red) based on highs
Long TEMA 1 (Blue) based on lows
Long TEMA 2 (Green) based on closing prices
Average True Range (ATR): Custom ATR calculation with EMA smoothing is used for volatility measurement.
Supertrend: Calculated using ATR and a multiplier to determine the trend direction.
Simple Moving Average (SMA): Applied to the short TEMA to smooth out its values.
Heikin-Ashi Close: Used for additional trend confirmation.
Entry & Exit Conditions
Long Entry: Triggered when the short TEMA is above both long TEMA lines, the Supertrend is bullish, the short TEMA is above its SMA, and the Heikin-Ashi close is higher than the previous close.
Short Entry: Triggered when the short TEMA is below both long TEMA lines, the Supertrend is bearish, the short TEMA is below its SMA, and the Heikin-Ashi close is lower than the previous close.
Take Profit and Stop Loss: Both are calculated as a percentage of the entry price, and they are set for both long and short positions.
Risk Management
Take Profit: Set at 1% above the entry price for long positions and 1% below for short positions.
Stop Loss: Set at 3% below the entry price for long positions and 3% above for short positions.
Commission and Pyramiding
Commission: A 0.07% commission is accounted for in the strategy.
Pyramiding: The strategy does not allow pyramiding.
Note
This strategy is designed for educational purposes and should not be considered as financial advice. Always do your own research and consider consulting a financial advisor before engaging in trading.
Dual-Supertrend with MACD - Strategy [presentTrading]## Introduction and How it is Different
The Dual-Supertrend with MACD strategy offers an amalgamation of two trend-following indicators (Supertrend 1 & 2) with a momentum oscillator (MACD). It aims to provide a cohesive and systematic approach to trading, eliminating the need for discretionary decision-making.
Key advantages over traditional single-indicator strategies:
- Dual Supertrend Validation: Utilizes two Supertrend indicators with different ATR periods and factors to confirm the trend direction. This double-check mechanism minimizes false signals.
- Momentum Confirmation: The MACD histogram acts as a momentum filter, confirming entries and exits, thus adding an extra layer of validation.
- Objective Entry and Exit: The strategy generates buy and sell signals based on a combination of trend direction and momentum, leaving no room for subjective interpretation.
- Automated Trade Management: The strategy includes built-in settings for commission, slippage, and initial capital, automating the trade execution process.
- Adaptability: The strategy allows for easy customization of all its parameters, adapting to a trader's specific needs and varying market conditions.
BTCUSD 8hr chart Long Condition
BTCUSD 6hr chart Long Short Condition
## Strategy, How it Works
The strategy operates on a set of clearly defined rules, primarily focusing on the trend direction confirmed by the Dual-Supertrend and the momentum as indicated by the MACD histogram.
### Entry Rules
- Long Entry: When both Supertrend indicators are bullish and the MACD histogram is above zero.
- Short Entry: When both Supertrend indicators are bearish and the MACD histogram is below zero.
### Exit Rules
- Exit long positions when either of the Supertrends turn bearish or the MACD histogram drops below zero.
- Exit short positions when either of the Supertrends turn bullish or the MACD histogram rises above zero.
### Trade Management
- The strategy uses a fixed commission rate and slippage in its calculations.
- Automated risk management features are integrated to avoid overexposure.
## Trade Direction
The strategy allows for trading in both bullish and bearish markets. Users can select their preferred trading direction ("long", "short", or "both") to align with their market outlook and trading objectives.
## Usage
- The strategy is best applied on timeframes where the trend is evident.
- Users can modify the ATR periods, factors for Supertrends, and MACD settings to suit their trading needs.
## Default Settings
- ATR Period for Supertrend 1: 10
- Factor for Supertrend 1: 3.0
- ATR Period for Supertrend 2: 20
- Factor for Supertrend 2: 5.0
- MACD Fast Length: 12
- MACD Slow Length: 26
- MACD Signal Smoothing: 9
- Commission: 0.1%
- Slippage: 1 point
- Trading Direction: Both
The strategy comes with these default settings to offer a balanced trading approach but can be customized according to individual trading preferences.
TradeTrackerLibrary "TradeTracker"
Simple Library for tracking trades
method track(this)
tracks trade when called on every bar
Namespace types: Trade
Parameters:
this (Trade) : Trade object
Returns: current Trade object
Trade
Has the constituents to track trades generated by any method.
Fields:
id (series int)
direction (series int) : Trade direction. Positive values for long and negative values for short trades
initialEntry (series float) : Initial entry price. This value will not change even if the entry is changed in the lifecycle of the trade
entry (series float) : Updated entry price. Allows variations to initial calculated entry. Useful in cases of trailing entry.
initialStop (series float) : Initial stop. Similar to initial entry, this is the first calculated stop for the lifecycle of trade.
stop (series float) : Trailing Stop. If there is no trailing, the value will be same as that of initial trade
targets (float ) : array of target values.
startBar (series int) : bar index of starting bar. Set by default when object is created. No need to alter this after that.
endBar (series int) : bar index of last bar in trade. Set by tracker on each execution
startTime (series int) : time of the start bar. Set by default when object is created. No need to alter this after that.
endTime (series int) : time of the ending bar. Updated by tracking method.
status (series int) : Integer parameter to track the status of the trade
retest (series bool) : Boolean parameter to notify if there was retest of the entry price
peterzorve-libraryLibrary "library"
is_bullish_engulfing()
is_bearish_engulfing()
is_hammer(fib_level)
Parameters:
fib_level (float)
is_shooting_star(fib_level)
Parameters:
fib_level (float)
is_hammer_and_star(fib_level)
Parameters:
fib_level (float)
is_star_and_hammer(fib_level)
Parameters:
fib_level (float)
is_dogi(dogi_body_ratio)
Parameters:
dogi_body_ratio (float)
is_bear_bear_bullish_engulf()
is_atr_stoploss_takeprofit(atr_multiplier, atr_length, reward_ratio)
Parameters:
atr_multiplier (float)
atr_length (simple int)
reward_ratio (float)
is_fixed_stoploss_takeprofit(stoploss_pips, reward_ratio)
Parameters:
stoploss_pips (float)
reward_ratio (float)
is_step_trailing_stoploss(stoploss_pips)
Parameters:
stoploss_pips (float)
is_atr_trailing_stoploss(atr_multiplier, break_even_pip)
Parameters:
atr_multiplier (float)
break_even_pip (int)
is_pull_back_strategy(length)
Parameters:
length (simple int)
is_trade_statistics(condition, entrypoint, stoploss, takeprofit)
Parameters:
condition (bool)
entrypoint (float)
stoploss (float)
takeprofit (float)
is_table_of_statistics(win_trades, lost_trades, even_trades, pips_won, pips_lost)
Parameters:
win_trades (int)
lost_trades (int)
even_trades (int)
pips_won (float)
pips_lost (float)
is_pine_info(lotsize, stoploss, takeprofit)
Parameters:
lotsize (float)
stoploss (float)
takeprofit (float)
is_support_and_resistance_strategy(look_back, look_forward)
Parameters:
look_back (int)
look_forward (int)
is_choral_strategy(smoothing_period, constant_d)
Parameters:
smoothing_period (int)
constant_d (float)
is_bollinger_band_strategy(length, dev_entry, dev_stoploss, dev_takeprofit)
Parameters:
length (int)
dev_entry (simple float)
dev_stoploss (simple float)
dev_takeprofit (simple float)
PlurexSignalCoreLibrary "PlurexSignalCore"
General purpose functions and helpers for use in more specific Plurex Signal alerting scripts and libraries
plurexMarket()
Build a Plurex market string from a base and quote asset symbol.
Returns: A market string that can be used in Plurex Signal messages.
tickerToPlurexMarket()
Builds Plurex market string from the syminfo
Returns: A market string that can be used in Plurex Signal messages.
simpleMessage(secret, action, marketOverride)
Builds Plurex Signal Message json to be sent to a Signal webhook
Parameters:
secret : The secret for your Signal on plurex
action : The action of the message. One of .
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
entryMessage(secret, isLong, budgetPercentage, priceLimit, marketOverride)
Builds Plurex Signal Entry Message json to be sent to a Signal webhook with optional parameters for budget and price limits.
Parameters:
secret : The secret for your Signal on plurex
isLong : The action of the message. true for LONG, false for SHORT.
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
long(secret, budgetPercentage, priceLimit, marketOverride)
Builds Plurex Signal LONG Message json to be sent to a Signal webhook with optional parameters for budget and price limits.
Parameters:
secret : The secret for your Signal on plurex
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
short(secret, budgetPercentage, priceLimit, marketOverride)
Builds Plurex Signal SHORT Message json to be sent to a Signal webhook with optional parameters for budget and price limits.
Parameters:
secret : The secret for your Signal on plurex
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
closeAll(secret, marketOverride)
Builds Plurex Signal CLOSE_ALL Message json to be sent to a Signal webhook.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
closeShorts(secret, marketOverride)
Builds Plurex Signal CLOSE_SHORTS Message json to be sent to a Signal webhook.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
closeLongs(secret, marketOverride)
Builds Plurex Signal CLOSE_LONGS Message json to be sent to a Signal webhook.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
closeFirstLong(secret, marketOverride)
Builds Plurex Signal CLOSE_FIRST_LONG Message json to be sent to a Signal webhook.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
closeLastLong(secret, marketOverride)
Builds Plurex Signal CLOSE_LAST_LONG Message json to be sent to a Signal webhook.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
closeFirstShort(secret, marketOverride)
Builds Plurex Signal CLOSE_FIRST_SHORT Message json to be sent to a Signal webhook.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
closeLastShort(secret, marketOverride)
Builds Plurex Signal CLOSE_LAST_SHORT Message json to be sent to a Signal webhook.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Returns: A json string message that can be used in alerts to send messages to Plurex.
Coral Trend Pullback Strategy (TradeIQ)Description:
Strategy is taken from the TradeIQ YouTube video called "I Finally Found 80% Win Rate Trading Strategy For Crypto".
Check out the full video for further details/clarification on strategy entry/exit conditions.
The default settings are exactly as TradeIQ described in his video.
However I found some better results by some tweaking settings, increasing R:R ratio and by turning off confirmation indicators.
This would suggest that perhaps the current confirmation indicators are not the best options. I'm happy to try add some other optional confirmation indicators if they look to be more effective.
Recommended timeframe: 1H
Strategy incorporates the following features:
Risk management:
Configurable X% loss per stop loss
Configurable R:R ratio
Trade entry:
Based on strategy conditions below
Trade exit:
Based on strategy conditions below
Backtesting:
Configurable backtesting range by date
Trade drawings:
Each entry condition indicator can be turned on and off
TP/SL boxes drawn for all trades. Can be turned on and off
Trade exit information labels. Can be turned on and off
NOTE: Trade drawings will only be applicable when using overlay strategies
Alerting:
Alerts on LONG and SHORT trade entries
Debugging:
Includes section with useful debugging techniques
Strategy conditions
Trade entry:
LONG
C1: Coral Trend is bullish
C2: At least 1 candle where low is above Coral Trend since last cross above Coral Trend
C3: Pullback happens and price closes below Coral Trend
C4: Coral Trend colour remains bullish for duration of pullback
C5: After valid pullback, price then closes above Coral Trend
C6: Optional confirmation indicators (choose either C6.1 or C6.2 or NONE):
C6.1: ADX and DI (Single indicator)
C6.1.1: Green line is above red line
C6.1.2: Blue line > 20
C6.1.3: Blue trending up over last 1 candle
C6.2: Absolute Strengeh Histogram + HawkEye Volume Indicator (Two indicators combined)
C6.2.1: Absolute Strengeh Histogram colour is blue
C6.2.2: HawkEye Volume Indicator colour is green
SHORT
C1: Coral Trend is bearish
C2: At least 1 candle where high is below Coral Trend since last cross below Coral Trend
C3: Pullback happens and price closes above Coral Trend
C4: Coral Trend colour remains bearish for duration of pullback
C5: After valid pullback, price then closes below Coral Trend
C6: Optional confirmation indicators (choose either C6.1 or C6.2 or NONE):
C6.1: ADX and DI (Single indicator)
C6.1.1: Red line is above green line
C6.1.2: Blue line > 20
C6.1.3: Blue trending up over last 1 candle
C6.2: Absolute Strengeh Histogram + HawkEye Volume Indicator (Two indicators combined)
C6.2.1: Absolute Strengeh Histogram colour is red
C6.2.2: HawkEye Volume Indicator colour is red
NOTE: All the optional confirmation indicators cannot be overlayed with Coral Trend so feel free to add each separately to the chart for visual purposes
Trade exit:
Stop Loss: Calculated by recent swing low over previous X candles (configurable with "Local High/Low Lookback")
Take Profit: Calculated from R:R multiplier * Stop Loss size
Credits
Strategy origin: TradeIQ's YouTube video called "I Finally Found 80% Win Rate Trading Strategy For Crypto"
It combines the following indicators for trade entry conditions:
Coral Trend Indicator by @LazyBear (Main indicator)
Absolute Strength Histogram | jh by @jiehonglim (Optional confirmation indicator)
Indicator: HawkEye Volume Indicator by @LazyBear (Optional confirmation indicator)
ADX and DI by @BeikabuOyaji (Optional confirmation indicator)
SSL + Wave Trend StrategyStrategy incorporates the following features:
Risk management:
Configurable X% loss per stop loss
Configurable R:R ratio
Trade entry:
Based on strategy conditions below
Trade exit:
Based on strategy conditions below
Backtesting:
Configurable backtesting range by date
Trade drawings:
Each entry condition indicator can be turned on and off
TP/SL boxes drawn for all trades. Can be turned on and off
Trade exit information labels. Can be turned on and off
NOTE: Trade drawings will only be applicable when using overlay strategies
Alerting:
Alerts on LONG and SHORT trade entries
Debugging:
Includes section with useful debugging techniques
Strategy conditions
Trade entry:
LONG
C1: SSL Hybrid baseline is BLUE
C2: SSL Channel crosses up (green above red)
C3: Wave Trend crosses up (represented by pink candle body)
C4: Entry candle height is not greater than configured threshold
C5: Entry candle is inside Keltner Channel (wicks or body depending on configuration)
C6: Take Profit target does not touch EMA (represents resistance)
SHORT
C1: SSL Hybrid baseline is RED
C2: SSL Channel crosses down (red above green)
C3: Wave Trend crosses down (represented by orange candle body)
C4: Entry candle height is not greater than configured threshold
C5: Entry candle is inside Keltner Channel (wicks or body depending on configuration)
C6: Take Profit target does not touch EMA (represents support)
Trade exit:
Stop Loss: Size configurable with NNFX ATR multiplier
Take Profit: Calculated from Stop Loss using R:R ratio
Credits
Strategy is based on the YouTube video "This Unique Strategy Made 47% Profit in 2.5 Months " by TradeSmart.
It combines the following indicators to determine trade entry/exit conditions:
Wave Trend: Indicator: WaveTrend Oscillator by @LazyBear
SSL Channel: SSL channel by @ErwinBeckers
SSL Hybrid: SSL Hybrid by @Mihkel00
Keltner Channels: Keltner Channels Bands by @ceyhun
Candle Height: Candle Height in Percentage - Columns by @FreeReveller
NNFX ATR: NNFX ATR by @sueun123
DMI StrategyThis strategy is based on DMI indicator. It helps me to identify base or top of the script. I mostly use this script to trade in Nifty bank options, even when the signal comes in nifty . It can be used to trade in other scripts as well. Pivot points can also be used to take entry. Long entry is taken when DI+(11) goes below 10 and DI-(11) goes above 40 , whereas short entry is taken when DI-(11) goes below 10 and DI+(11) goes above 40.
For bank nifty , I take the trade in the strike price for which the current premium is nearby 300, with the SL of 20%. If premium goes below 10% I buy one more lot to average, but exit if the premium goes below 20% of the first entry. If the trade moves in the correct direction, we need to start trailing our stoploss or exit at the pre-defined target.
As this a strategy, there is one problem. While we are in the phase of "long", if again the "long" phase comes, it will not be shown on chart until a "short" phase has come, and vice versa. This has been resolved by creating an indicator instead of strategy with the name of "DMI Buy-sell on chart". Please go through that to get more entry points.
Please have a look at strategy tester to back test
3ngine Global BoilerplateABOUT THE BOILERPLATE
This strategy is designed to bring consistency to your strategies. It includes a macro EMA filter for filtering out countertrend trades,
an ADX filter to help filter out chop, a session filter to filter out trades outside of desired timeframe, alert messages setup for automation,
laddering in/out of trades (up to 6 rungs), trailing take profit , and beautiful visuals for each entry. There are comments throughout the
strategy that provide further instructions on how to use the boilerplate strategy. This strategy uses `threengine_global_automation_library`
throughout and must be included at the top of the strategy using `import as bot`. This allows you to use dot notation
to access functions in the library - EX: `bot.orderCurrentlyExists(orderID)`.
HOW TO USE THIS STRATEGY
1. Add your inputs
There is a section dedicated for adding your own inputs near the top of the strategy, just above the boilerplate inputs
2. Add your calculations
If your strategy requires calculations, place them in the `Strategy Specific Calculations` section
3. Add your entry criteria
Add your criteria to strategySpecificLongConditions (this gets combined with boilerplate conditions in longConditionsMet)
Add your criteria to strategySpecificShortConditions (this gets combined with boilerplate conditions in shortConditionsMet)
Set your desired entry price (calculated on every bar unless stored as a static variable) to longEntryPrice and shortEntryPrice. ( This will be the FIRST ladder if using laddering capabilities. If you pick 1 for "Ladder In Rungs" this will be the only entry. )
4. Plot anything you want to overlay on the chart in addition to the boilerplate plots and labels. Included in boilerplate:
Average entry price
Stop loss
Trailing stop
Profit target
Ladder rungs
Scalping EMA ADX RSI with Buy/Sell AlertsThis is a study indicator that shows the entries in the strategy seen in one of the youtube channel so it does not belong to me. I can't tell who it is because it's against the House Rules to advertise but you can find out if you look for it on youtube. Default values of oscilators and ema adjusted as suggested. He says he got the best results in 5 min timeframe but i tried to make things as modifiable as possible so you can mess around with the settings and create your own strategy for different timeframes if you'd like. Suggested to use with normal candlestick charts. The blue line below indicates the ADX is above the selected threshold set in the settings named "Trend Ready Limit". You can set alerts for Buy, Sell or Buy/Sell signal together.
The entry strategy itself is pretty straight forward.
The rules for entry are as follows, the script will check all of this on auto and will give you buy or sell signal :
Recommended time frame: 5 min
For Long Entry:
- Check if price above the set EMA (Can disable this rule if you'd like in the settings)
- RSI is in Oversold
- ADX is above set "Trend Ready" threshold (Meaning there is a trend going on)
- Price must approve the trend of previous candles. This is bullish for buy entries and bearish for sell entries.
- Enter with stop loss below last swing low with 1:1 or 1.5:1 take profit ratio.
For Short Entry:
- Check if price below the set EMA (Can disable this rule if you'd like in the settings)
- RSI is in Overbought
- ADX is above set "Trend Ready" threshold (Meaning there is a trend going on)
- Price must approve the trend of previous candles. This is bullish for buy entries and bearish for sell entries.
- Enter with stop loss above last swing high with 1:1 or 1.5:1 take profit ratio.
This is my first indicator. Let me know if you want any updates. I am not sure if i can add everything but i'll try nonetheless.
Changed: Signals will check up to 2 candles before if the RSI is below or above the set value to show signal. This is because sometimes the entry signal is right but the response might be a bit late.
RSI 30 CROSSScript will give the RSI 30 40 and 70 level for present price of the stock , when the price cross the green line RSI value will be 70 , blue line RSI value will be 40 and red line RSI value will be 30 . Helps to put entry and exit based on RSI strategy.
RED line give price for RSI 30
BLUE line give price for RSI 40
GREEN line give price for RSI 70
BLACK line give SMA 200
Strategy
Stock price should above 200 MA
price should touch RSI 30 RED line and bounce back.
Entry will be the high of candle lies on RSI 40 BLUE line.
Stop loss will be the RSI 30 price(RED line ) during entry.
Target will be the RSI 70 price ( GREEEN line) during entry.
You can take half profit at RSI 70 and trail stop loss on RSI 70 till it cross.
This will help you to find the Price for stock, when it cross RSI value 30 , 40 and 70 to place entry exit and target based on the trade strategy will follow RSI.
If you want to entry, when stock cross RSI 30 or 40 from below . You can place a stop loss limit buy order at price range .
If you want to exit, When stock cross RSI 70 . you place stock loss at green line price.
Forex Scalping 1min Bollinger Bands, RSI and ADX Trading SystemThis is a Forex Scalping Trading Sytem based on the Bollinger Bands.
Its suited for major pairs, with lowest possible comission (below 1 pip) and with timeframes ranging between 1-15 min.
Indicators:
Bollinger bands
ADX
RSI
Rules for entry:
Long Entry: price to move below the upper Bollinger Bands RSI raise above the 30 line and ADX<32 at the same time.
Short Entry: price to move above the upper Bollinger Bands, RSI raise below the 70 line and ADX<32 at the same time.
Rules for exit
Profit Exit: 3 options: 1, exit position when the price touches the middle band, 2) when the price touches the opposite band, X pips target profit.
Loss Exit: X pips loss
Bollinger Band with RSI
Using combination bollinger band and RSI indicator as guide to predict price volatility and the best entry point. The strategy logic is pretty straightforward where we're interested with close price that touches the lower bollinger band ; there are only two scenarios that will happened after the price reaches the lower band; the price might rebound from the lower bollinger band or drop lower and continue downtrend. To confirm the price movement, we use a second indicator which is the RSI to further investigate the price trend. For example, if the price reaches the lower bollinger band but the RSI value is not in the oversold region, we can conclude that the price will go lower and continue downtrend. If the RSI value is in the oversold region, we can use this price area as our entry point.
Stop loss is necessary to avoid losing too much capital if the RSI value lingers too long in the oversold region.
Best take profit area is when the price rebound above the middle bollinger band area/upper bollinger band or when the RSI reaches overbought region; whichever comes first.
Long entry:
RSI < 30 & close price < lower bollinger band
Exit entry:
RSI > 70
Default stop loss: -25%
Swing/Daytrading strategy with reversal option
Hello, today I bring a swing reversal strategy that work on all financial markets.
It uses timeframes starting from 1h, the bigger the better.
Its very dangerous because it has no stop loss, neither a take profit. Our exit condition is based on the reversal on the entry .
For entry we have 2 types : normal and reversal
Lets say we want to go long , for that we check the last CLOSE of a candle with the previos HIGH. If its higher than that, and at the same time CLOSE is bigger than the moving average, we have a long entry.
For short we have CLOSE with the previous LOW. If its lower than that and at the same time is lower than moving average, we have a short entry.
For moving average we use T3 MA
For reversal what I do, is , I take the short condition and I apply it to long, and for long I apply the short condition.
On many cases I found out it work amazingly.
I forgot to add: it also has a time entry system, so we use the best hours/sessions for entries .
Exit a trade: lets say we enter short, when we find a long condition, we close short and enter into long. Viceversa for long.
If you have any questions, let me know.
Enjoy it :)
Ruckard TradingLatinoThis strategy tries to mimic TradingLatino strategy.
The current implementation is beta.
Si hablas castellano o espanyol por favor consulta MENSAJE EN CASTELLANO más abajo.
It's aimed at BTCUSDT pair and 4h timeframe.
STRATEGY DEFAULT SETTINGS EXPLANATION
max_bars_back=5000 : This is a random number of bars so that the strategy test lasts for one or two years
calc_on_order_fills=false : To wait for the 4h closing is too much. Try to check if it's worth entering a position after closing one. I finally decided not to recheck if it's worth entering after an order is closed. So it is false.
calc_on_every_tick=false
pyramiding=0 : We only want one entry allowed in the same direction. And we don't want the order to scale by error.
initial_capital=1000 : These are 1000 USDT. By using 1% maximum loss per trade and 7% as a default stop loss by using 1000 USDT at 12000 USDT per BTC price you would entry with around 142 USDT which are converted into: 0.010 BTC . The maximum number of decimal for contracts on this BTCUSDT market is 3 decimals. E.g. the minimum might be: 0.001 BTC . So, this minimal 1000 amount ensures us not to entry with less than 0.001 entries which might have happened when using 100 USDT as an initial capital.
slippage=1 : Binance BTCUSDT mintick is: 0.01. Binance slippage: 0.1 % (Let's assume). TV has an integer slippage. It does not have a percentage based slippage. If we assume a 1000 initial capital, the recommended equity is 142 which at 11996 USDT per BTC price means: 0.011 BTC. The 0.1% slippage of: 0.011 BTC would be: 0.000011 . This is way smaller than the mintick. So our slippage is going to be 1. E.g. 1 (slippage) * 0.01 (mintick)
commission_type=strategy.commission.percent and commission_value=0.1 : According to: binance . com / en / fee / schedule in VIP 0 level both maker and taker fees are: 0.1 %.
BACKGROUND
Jaime Merino is a well known Youtuber focused on crypto trading
His channel TradingLatino
features monday to friday videos where he explains his strategy.
JAIME MERINO STANCE ON BOTS
Jaime Merino stance on bots (taken from memory out of a 2020 June video from him):
'~
You know. They can program you a bot and it might work.
But, there are some special situations that the bot would not be able to handle.
And, I, as a human, I would handle it. And the bot wouldn't do it.
~'
My long term target with this strategy script is add as many
special situations as I can to the script
so that it can match Jaime Merino behaviour even in non normal circumstances.
My alternate target is learn Pine script
and enjoy programming with it.
WARNING
This script might be bigger than other TradingView scripts.
However, please, do not be confused because the current status is beta.
This script has not been tested with real money.
This is NOT an official strategy from Jaime Merino.
This is NOT an official strategy from TradingLatino . net .
HOW IT WORKS
It basically uses ADX slope and LazyBear's Squeeze Momentum Indicator
to make its buy and sell decisions.
Fast paced EMA being bigger than slow paced EMA
(on higher timeframe) advices going long.
Fast paced EMA being smaller than slow paced EMA
(on higher timeframe) advices going short.
It finally add many substrats that TradingLatino uses.
SETTINGS
__ SETTINGS - Basics
____ SETTINGS - Basics - ADX
(ADX) Smoothing {14}
(ADX) DI Length {14}
(ADX) key level {23}
____ SETTINGS - Basics - LazyBear Squeeze Momentum
(SQZMOM) BB Length {20}
(SQZMOM) BB MultFactor {2.0}
(SQZMOM) KC Length {20}
(SQZMOM) KC MultFactor {1.5}
(SQZMOM) Use TrueRange (KC) {True}
____ SETTINGS - Basics - EMAs
(EMAS) EMA10 - Length {10}
(EMAS) EMA10 - Source {close}
(EMAS) EMA55 - Length {55}
(EMAS) EMA55 - Source {close}
____ SETTINGS - Volume Profile
Lowest and highest VPoC from last three days
is used to know if an entry has a support
VPVR of last 100 4h bars
is also taken into account
(VP) Use number of bars (not VP timeframe): Uses 'Number of bars {100}' setting instead of 'Volume Profile timeframe' setting for calculating session VPoC
(VP) Show tick difference from current price {False}: BETA . Might be useful for actions some day.
(VP) Number of bars {100}: If 'Use number of bars (not VP timeframe)' is turned on this setting is used to calculate session VPoC.
(VP) Volume Profile timeframe {1 day}: If 'Use number of bars (not VP timeframe)' is turned off this setting is used to calculate session VPoC.
(VP) Row width multiplier {0.6}: Adjust how the extra Volume Profile bars are shown in the chart.
(VP) Resistances prices number of decimal digits : Round Volume Profile bars label numbers so that they don't have so many decimals.
(VP) Number of bars for bottom VPOC {18}: 18 bars equals 3 days in suggested timeframe of 4 hours. It's used to calculate lowest session VPoC from previous three days. It's also used as a top VPOC for sells.
(VP) Ignore VPOC bottom advice on long {False}: If turned on it ignores bottom VPOC (or top VPOC on sells) when evaluating if a buy entry is worth it.
(VP) Number of bars for VPVR VPOC {100}: Number of bars to calculate the VPVR VPoC. We use 100 as Jaime once used. When the price bounces back to the EMA55 it might just bounce to this VPVR VPoC if its price it's lower than the EMA55 (Sells have inverse algorithm).
____ SETTINGS - ADX Slope
ADX Slope
help us to understand if ADX
has a positive slope, negative slope
or it is rather still.
(ADXSLOPE) ADX cut {23}: If ADX value is greater than this cut (23) then ADX has strength
(ADXSLOPE) ADX minimum steepness entry {45}: ADX slope needs to be 45 degrees to be considered as a positive one.
(ADXSLOPE) ADX minimum steepness exit {45}: ADX slope needs to be -45 degrees to be considered as a negative one.
(ADXSLOPE) ADX steepness periods {3}: In order to avoid false detection the slope is calculated along 3 periods.
____ SETTINGS - Next to EMA55
(NEXTEMA55) EMA10 to EMA55 bounce back percentage {80}: EMA10 might bounce back to EMA55 or maybe to 80% of its complete way to EMA55
(NEXTEMA55) Next to EMA55 percentage {15}: How much next to the EMA55 you need to be to consider it's going to bounce back upwards again.
____ SETTINGS - Stop Loss and Take Profit
You can set a default stop loss or a default take profit.
(STOPTAKE) Stop Loss % {7.0}
(STOPTAKE) Take Profit % {2.0}
____ SETTINGS - Trailing Take Profit
You can customize the default trailing take profit values
(TRAILING) Trailing Take Profit (%) {1.0}: Trailing take profit offset in percentage
(TRAILING) Trailing Take Profit Trigger (%) {2.0}: When 2.0% of benefit is reached then activate the trailing take profit.
____ SETTINGS - MAIN TURN ON/OFF OPTIONS
(EMAS) Ignore advice based on emas {false}.
(EMAS) Ignore advice based on emas (On closing long signal) {False}: Ignore advice based on emas but only when deciding to close a buy entry.
(SQZMOM) Ignore advice based on SQZMOM {false}: Ignores advice based on SQZMOM indicator.
(ADXSLOPE) Ignore advice based on ADX positive slope {false}
(ADXSLOPE) Ignore advice based on ADX cut (23) {true}
(STOPTAKE) Take Profit? {false}: Enables simple Take Profit.
(STOPTAKE) Stop Loss? {True}: Enables simple Stop Loss.
(TRAILING) Enable Trailing Take Profit (%) {True}: Enables Trailing Take Profit.
____ SETTINGS - Strategy mode
(STRAT) Type Strategy: 'Long and Short', 'Long Only' or 'Short Only'. Default: 'Long and Short'.
____ SETTINGS - Risk Management
(RISKM) Risk Management Type: 'Safe', 'Somewhat safe compound' or 'Unsafe compound'. ' Safe ': Calculations are always done with the initial capital (1000) in mind. The maximum losses per trade/day/week/month are taken into account. ' Somewhat safe compound ': Calculations are done with initial capital (1000) or a higher capital if it increases. The maximum losses per trade/day/week/month are taken into account. ' Unsafe compound ': In each order all the current capital is gambled and only the default stop loss per order is taken into account. That means that the maximum losses per trade/day/week/month are not taken into account. Default : 'Somewhat safe compound'.
(RISKM) Maximum loss per trade % {1.0}.
(RISKM) Maximum loss per day % {6.0}.
(RISKM) Maximum loss per week % {8.0}.
(RISKM) Maximum loss per month % {10.0}.
____ SETTINGS - Decimals
(DECIMAL) Maximum number of decimal for contracts {3}: How small (3 decimals means 0.001) an entry position might be in your exchange.
EXTRA 1 - PRICE IS IN RANGE indicator
(PRANGE) Print price is in range {False}: Enable a bottom label that indicates if the price is in range or not.
(PRANGE) Price range periods {5}: How many previous periods are used to calculate the medians
(PRANGE) Price range maximum desviation (%) {0.6} ( > 0 ): Maximum positive desviation for range detection
(PRANGE) Price range minimum desviation (%) {0.6} ( > 0 ): Mininum negative desviation for range detection
EXTRA 2 - SQUEEZE MOMENTUM Desviation indicator
(SQZDIVER) Show degrees {False}: Show degrees of each Squeeze Momentum Divergence lines to the x-axis.
(SQZDIVER) Show desviation labels {False}: Whether to show or not desviation labels for the Squeeze Momentum Divergences.
(SQZDIVER) Show desviation lines {False}: Whether to show or not desviation lines for the Squeeze Momentum Divergences.
EXTRA 3 - VOLUME PROFILE indicator
WARNING: This indicator works not on current bar but on previous bar. So in the worst case it might be VP from 4 hours ago. Don't worry, inside the strategy calculus the correct values are used. It's just that I cannot show the most recent one in the chart.
(VP) Print recent profile {False}: Show Volume Profile indicator
(VP) Avoid label price overlaps {False}: Avoid label prices to overlap on the chart.
EXTRA 4 - ZIGNALY SUPPORT
(ZIG) Zignaly Alert Type {Email}: 'Email', 'Webhook'. ' Email ': Prepare alert_message variable content to be compatible with zignaly expected email content format. ' Webhook ': Prepare alert_message variable content to be compatible with zignaly expected json content format.
EXTRA 5 - DEBUG
(DEBUG) Enable debug on order comments {False}: If set to true it prepares the order message to match the alert_message variable. It makes easier to debug what would have been sent by email or webhook on each of the times an order is triggered.
HOW TO USE THIS STRATEGY
BOT MODE: This is the default setting.
PROPER VOLUME PROFILE VIEWING: Click on this strategy settings. Properties tab. Make sure Recalculate 'each time the order was run' is turned off.
NEWBIE USER: (Check PROPER VOLUME PROFILE VIEWING above!) You might want to turn on the 'Print recent profile {False}' setting. Alternatively you can use my alternate realtime study: 'Resistances and supports based on simplified Volume Profile' but, be aware, it might consume one indicator.
ADVANCED USER 1: Turn on the 'Print price is in range {False}' setting and help us to debug this subindicator. Also help us to figure out how to include this value in the strategy.
ADVANCED USER 2: Turn on the all the (SQZDIVER) settings and help us to figure out how to include this value in the strategy.
ADVANCED USER 3: (Check PROPER VOLUME PROFILE VIEWING above!) Turn on the 'Print recent profile {False}' setting and report any problem with it.
JAIME MERINO: Just use the indicator as it comes by default. It should only show BUY signals, SELL signals and their associated closing signals. From time to time you might want to check 'ADVANCED USER 2' instructions to check that there's actually a divergence. Check also 'ADVANCED USER 1' instructions for your amusement.
EXTRA ADVICE
It's advised that you use this strategy in addition to these two other indicators:
* Squeeze Momentum Indicator
* ADX
so that your chart matches as close as possible to TradingLatino chart.
ZIGNALY INTEGRATION
This strategy supports Zignaly email integration by default. It also supports Zignaly Webhook integration.
ZIGNALY INTEGRATION - Email integration example
What you would write in your alert message:
||{{strategy.order.alert_message}}||key=MYSECRETKEY||
ZIGNALY INTEGRATION - Webhook integration example
What you would write in your alert message:
{ {{strategy.order.alert_message}} , "key" : "MYSECRETKEY" }
CREDITS
I have reused and adapted some code from
'Directional Movement Index + ADX & Keylevel Support' study
which it's from TradingView console user.
I have reused and adapted some code from
'3ema' study
which it's from TradingView hunganhnguyen1193 user.
I have reused and adapted some code from
'Squeeze Momentum Indicator ' study
which it's from TradingView LazyBear user.
I have reused and adapted some code from
'Strategy Tester EMA-SMA-RSI-MACD' study
which it's from TradingView fikira user.
I have reused and adapted some code from
'Support Resistance MTF' study
which it's from TradingView LonesomeTheBlue user.
I have reused and adapted some code from
'TF Segmented Linear Regression' study
which it's from TradingView alexgrover user.
I have reused and adapted some code from
"Poor man's volume profile" study
which it's from TradingView IldarAkhmetgaleev user.
FEEDBACK
Please check the strategy source code for more detailed information
where, among others, I explain all of the substrats
and if they are implemented or not.
Q1. Did I understand wrong any of the Jaime substrats (which I have implemented)?
Q2. The strategy yields quite profit when we should long (EMA10 from 1d timeframe is higher than EMA55 from 1d timeframe.
Why the strategy yields much less profit when we should short (EMA10 from 1d timeframe is lower than EMA55 from 1d timeframe)?
Any idea if you need to do something else rather than just reverse what Jaime does when longing?
FREQUENTLY ASKED QUESTIONS
FAQ1. Why are you giving this strategy for free?
TradingLatino and his fellow enthusiasts taught me this strategy. Now I'm giving back to them.
FAQ2. Seriously! Why are you giving this strategy for free?
I'm confident his strategy might be improved a lot. By keeping it to myself I would avoid other people contributions to improve it.
Now that everyone can contribute this is a win-win.
FAQ3. How can I connect this strategy to my Exchange account?
It seems that you can attach alerts to strategies.
You might want to combine it with a paying account which enable Webhook URLs to work.
I don't know how all of this works right now so I cannot give you advice on it.
You will have to do your own research on this subject. But, be careful. Automating trades, if not done properly,
might end on you automating losses.
FAQ4. I have just found that this strategy by default gives more than 3.97% of 'maximum series of losses'. That's unacceptable according to my risk management policy.
You might want to reduce default stop loss setting from 7% to something like 5% till you are ok with the 'maximum series of losses'.
FAQ5. Where can I learn more about your work on this strategy?
Check the source code. You might find unused strategies. Either because there's not a substantial increases on earnings. Or maybe because they have not been implemented yet.
FAQ6. How much leverage is applied in this strategy?
No leverage.
FAQ7. Any difference with original Jaime Merino strategy?
Most of the times Jaime defines an stop loss at the price entry. That's not the case here. The default stop loss is 7% (but, don't be confused it only means losing 1% of your investment thanks to risk management). There's also a trailing take profit that triggers at 2% profit with a 1% trailing.
FAQ8. Why this strategy return is so small?
The strategy should be improved a lot. And, well, backtesting in this platform is not guaranteed to return theoric results comparable to real-life returns. That's why I'm personally forward testing this strategy to verify it.
MENSAJE EN CASTELLANO
En primer lugar se agradece feedback para mejorar la estrategia.
Si eres un usuario avanzado y quieres colaborar en mejorar el script no dudes en comentar abajo.
Ten en cuenta que aunque toda esta descripción tenga que estar en inglés no es obligatorio que el comentario esté en inglés.
CHISTE - CASTELLANO
¡Pero Jaime!
¡400.000!
¡Tu da mun!
Two Take Profits and Two Stop LossThis script is for research purposes only. I am not a financial advisor.
Entry Condition
This strategy is based on two take profit targets, two stop loss, and scaling out strategy. The entry rule is very simple. Whenever the EMA crossover WMA, the long trade is taken and vice versa.
Take Profit and Stop Loss
The first take profit is set at 20 pips above the long entry and the second take profit is set at 40 pips above the long entry. Meanwhile, the first stop loss is set at 20 pips below the long entry and the second stop loss is set at the long entry.
Money Management
When the first take profit is achieved, half of the position is closed and the first stop loss is moved to the entry-level. The rest of the position is open to achieve either second take profit or second stop loss.
There are three outcomes when using this strategy. Let's say you enter the trade with 200 lot size and you are risking 2% of your equity.
1. The first outcome is when the price hits stop loss, you lose the entire 2%.
2. The second outcome is when the price hits the first take profit and you close half of your position. Meaning that you have gained 1%. Then you let the trade running and eventually it hits the second stop loss. Remember your first stop loss has changed to the second stop loss when the first take profit is achieved. The total loss is 0% because the price is at your entry-level. You have gained the earlier 1% and then lost 0%. At this point, you are at 1% gained.
3. The third outcome is similar to the second out but instead of hitting the second stop loss, the trade is running to your favor and hits the second take profit.
Therefore, you gained 1% from the first take profit and you gained another 2% for the second take profit. Your total gained is 3%
Summary
The reason behind this strategy is to minimize risk. with normal strategy, you only have two outcomes which are either win or loss. With this strategy, you have three outcomes which win 3%, win 1%, or loss 2%.
This is my similar strategy but with single stop loss
Two Take Profit StrategyThis script is for research purposes only. I am not a financial advisor.
Entry Condition
This strategy is based on two take profit targets and scaling out strategy. The entry rule is very simple. Whenever the EMA crossover WMA, the long trade is taken and vice versa.
Take Profit and Stop Loss
The first take profit is set at 20 pips above the long entry and the second take profit is set at 40 pips above the long entry. Meanwhile, the stop loss is set at 20 pips below the long entry.
Money Management
When the first take profit is achieved, half of the position is closed. The rest of the position is open to achieve either second take profit or stop loss.
There are three outcomes when using this strategy. Let's say you enter the trade with 200 lot size and you are risking 2% of your equity.
1. The first outcome is when the price hits stop loss, you lose the entire 2%.
2. The second outcome is when the price hits the first take profit and you close half of your position. Meaning that you have gained 1%. Then you let the trade running and eventually it hits stop loss. The total loss is 0% because the remaining lot size which is 200/2=100 times by 20pips is 1%. You have gained the earlier 1% and then loss 1%. At this point, you are at break even.
3. The third outcome is similar to the second out but instead of hiring stop loss, the trade is running to your favor and hits the second take profit.
Therefore, you gained 1% from the first take profit and you gained another 2% for the second take profit. Your total gained is 3%
Summary
The reason behind this strategy is to minimize risk. with normal strategy, you only have two outcomes which are either win or loss. With this strategy, you have three outcomes which are win, loss or break even.
dhruv private 91400//@version=5
//
VERSION = '7.9-X'// 2024.3.20
strategy(
'LE VAN DO® - Swing Signals & Overlays Private™ 7.9-X',
shorttitle = 'LE VAN DO® - Swing Signals & Overlays Private™ 7.9-X' + VERSION,
overlay = true,
explicit_plot_zorder = true,
pyramiding = 0,
default_qty_type = strategy.percent_of_equity,
default_qty_value = 50,
calc_on_every_tick = false,
process_orders_on_close = true,
max_bars_back = 500,
initial_capital = 5000,
commission_type = strategy.commission.percent,
commission_value = 0.02,
max_lines_count = 500
)
//Truncate Function
truncate(number, decimals) =>
factor = math.pow(10, decimals)
int(number * factor) / factor
//
// === INPUTS ===
TPSType = input.string('Trailing', 'What TPS should be taken : ', options = )
setupType = input.string('Open/Close', title='What Trading Setup should be taken : ', options= )
scolor = input(true, title='Show coloured Bars to indicate Trend?')
almaRibbon = input(false, title='Enable Ribbon?')
//tradeType = input.string('BOTH', title='What trades should be taken : ', options= )
// === /INPUTS ===
// Display the probabilities in a table
//text01_ = str.tostring(timeframe.multiplier * intRes, '####')
//t = timenow + math.round(ta.change(time) * 25)
//var label lab01 = na
//label.delete(lab01)
//lab01 := label.new(t, close, text=text01_, style=label.style_label_left, yloc=yloc.price, xloc=xloc.bar_time, textalign=text.align_left, textcolor=color.white)
// Constants colours that include fully non-transparent option.
green100 = #008000FF
lime100 = #66bb6a
red100 = #f7525f
blue100 = #0000FFFF
aqua100 = #00FFFFFF
darkred100 = #8B0000FF
gray100 = #808080FF
/////////////////////////////////////////////
// Create non-repainting security function
rp_security(_symbol, _res, _src) =>
request.security(_symbol, _res, _src )
//
f_tfInMinutes() =>
_tfInMinutes = timeframe.period == '1' ? '3' : timeframe.period == '3' ? '5' : timeframe.period == '5' ? '15' : timeframe.period == '15' ? '30' : timeframe.period == '30' ? '60' : timeframe.period == '60' ? '240' : 'D'
_tfInMinutes
my_time1 = f_tfInMinutes()
tfmult = 18 //input.int(18, "Input Timeframe Multiplier")
f_resInMinutes() =>
_resInMinutes = timeframe.multiplier * (
timeframe.isseconds ? 1. / 60. :
timeframe.isminutes ? 1. :
timeframe.isdaily ? 1440. :
timeframe.isweekly ? 10080. :
timeframe.ismonthly ? 43800. : na)
my_time = str.tostring(f_resInMinutes()*tfmult)
useSource = close //input.string('Close', 'What Source to be used?', options = )
enableFilter = input(true, "Enable Backtesting Range Filtering")
fromDate = input.time(timestamp("01 Jan 2023 00:00 +0300"), "Start Date")
toDate = input.time(timestamp("31 Dec 2099 00:00 +0300"), "End Date")
tradeDateIsAllowed = not enableFilter or (time >= fromDate and time <= toDate)
filter1 = 'Filter with Atr'
filter2 = 'Filter with RSI'
filter3 = 'Atr or RSI'
filter4 = 'Atr and RSI'
filter5 = 'No Filtering'
filter6 = 'Entry Only in sideways market(By ATR or RSI)'
filter7 = 'Entry Only in sideways market(By ATR and RSI)'
typefilter = input.string(filter5, title='Sideways Filtering Input', options= , group='Strategy Options')
RSI = truncate(ta.rsi(close, input.int(7, group='RSI Filterring')), 2)
toplimitrsi = input.int(45, title='TOP Limit', group='RSI Filterring')
botlimitrsi = input.int(10, title='BOT Limit', group='RSI Filterring')
//ST = input.bool(true, title='Show Supertrend?', group='Supertrend Indicator')
//period = input.int(1440, group='Supertrend Indicator')
//mult = input.float(2.612, group='Supertrend Indicator')
atrfiltLen = 5 //input.int(5, minval=1, title='atr Length', group='Sideways Filtering Input')
atrMaType = 'EMA' //input.string('EMA', options= , group='Sideways Filtering Input', title='atr Moving Average Type')
atrMaLen = 5 //input.int(5, minval=1, title='atr MA Length', group='Sideways Filtering Input')
//filtering
atra = request.security(syminfo.tickerid, '', ta.atr(atrfiltLen))
atrMa = atrMaType == 'EM' ? ta.ema(atra, atrMaLen) : ta.sma(atra, atrMaLen)
updm = ta.change(high)
downdm = -ta.change(low)
plusdm = na(updm) ? na : updm > downdm and updm > 0 ? updm : 0
minusdm = na(downdm) ? na : downdm > updm and downdm > 0 ? downdm : 0
cndSidwayss1 = atra >= atrMa
cndSidwayss2 = RSI > toplimitrsi or RSI < botlimitrsi
cndSidways = cndSidwayss1 or cndSidwayss2
cndSidways1 = cndSidwayss1 and cndSidwayss2
Sidwayss1 = atra <= atrMa
Sidwayss2 = RSI < toplimitrsi and RSI > botlimitrsi
Sidways = Sidwayss1 or Sidwayss2
Sidways1 = Sidwayss1 and Sidwayss2
trendType = typefilter == filter1 ? cndSidwayss1 : typefilter == filter2 ? cndSidwayss2 : typefilter == filter3 ? cndSidways : typefilter == filter4 ? cndSidways1 : typefilter == filter5 ? RSI > 0 : typefilter == filter6 ? Sidways : typefilter == filter7 ? Sidways1 : na
// === /INPUTS ===
tf = my_time //input('15')
r = ticker.heikinashi(syminfo.tickerid)
openSeriesAlt = request.security(r, tf, open, lookahead=barmerge.lookahead_on)
closeSeriesAlt = request.security(r, tf, close, lookahead=barmerge.lookahead_on)
//openP = plot(almaRibbon ? openSeriesAlt : na, color=color.new(color.lime, 0), linewidth=3)
//closeP = plot(almaRibbon ? closeSeriesAlt : na, color=color.new(color.red, 0), linewidth=3)
BUYOC = ta.crossover(closeSeriesAlt, openSeriesAlt) and setupType == "Open/Close" and trendType
SELLOC = ta.crossunder(closeSeriesAlt, openSeriesAlt) and setupType == "Open/Close" and trendType
//strategy.entry('sell', direction=strategy.short, qty=trade_size, comment='sell', when=sel_entry)
//strategy.entry('buy', direction=strategy.long, qty=trade_size, comment='buy', when=buy_entry)
//trendColour = closeSeriesAlt > openSeriesAlt ? color.green : color.red
//bcolour = closeSeriesAlt > openSeriesAlt ? lime100 : red100
//barcolor(scolor ? bcolour : na, title='Bar Colours')
//closeP = plot(almaRibbon ? closeSeriesAlt : na, title='Close Series', color=color.new(trendColour, 20), linewidth=2, style=plot.style_line)
//openP = plot(almaRibbon ? openSeriesAlt : na, title='Open Series', color=color.new(trendColour, 20), linewidth=2, style=plot.style_line)
//fill(closeP, openP, color=color.new(trendColour, 80))
//
//rt = input(true, title="ATR Based REnko is the Default, UnCheck to use Traditional ATR?")
atrLen = 3 //input.int(3, title="RENKO_ATR", group = "Renko Settings")
isATR = true //input.bool(true, title="RENKO_USE_RENKO_ATR", group = "Renko Settings")
tradLen1 = 1000 //input.int(1000, title="RENKO_TRADITIONAL", group = "Renko Settings")
//Code to be implemented in V2
//mul = input(1, "Number Of minticks")
//value = mul * syminfo.mintick
tradLen = tradLen1 * 1
param = isATR ? ticker.renko(syminfo.tickerid, "ATR", atrLen) : ticker.renko(syminfo.tickerid, "Traditional", tradLen)
renko_close = request.security(param, my_time, close, lookahead=barmerge.lookahead_on)
renko_open = request.security(param, my_time, open, lookahead=barmerge.lookahead_on)
//============================================
//Sniper------------------------------------------------------------------------------------------------------------------------------------- // Signal 2
//============================================
//============================================
//EMA_CROSS-------------------------------------------------------------------------------------------------------------------------------- // Signal 4
//============================================
EMA1_length=input.int(2, "EMA1_length", group = "Renko Settings")
EMA2_length=input.int(10, "EMA2_length", group = "Renko Settings")
a = ta.ema(renko_close, EMA1_length)
b = ta.ema(renko_close, EMA2_length)
//BUY = ta.cross(a, b) and a > b and renko_open < renko_close
//SELL = ta.cross(a, b) and a < b and renko_close < renko_open
///////////////////////////////
// Determine long and short conditions
BUYR = ta.crossover(a, b) and setupType == "Renko" and trendType
SELLR = ta.crossunder(a, b) and setupType == "Renko" and trendType
sel_color = setupType == "Open/Close" ? closeSeriesAlt < openSeriesAlt : setupType == "Renko" ? renko_close < renko_open : na
buy_color = setupType == "Open/Close" ? closeSeriesAlt > openSeriesAlt : setupType == "Renko" ? renko_close > renko_open : na
sel_entry = setupType == "Open/Close" ? SELLOC : setupType == "Renko" ? SELLR : na
buy_entry = setupType == "Open/Close" ? BUYOC : setupType == "Renko" ? BUYR : na
trendColour = buy_color ? color.green : color.red
bcolour = buy_color ? lime100 : red100
barcolor(scolor ? bcolour : na, title='Bar Colours')
p11=plot(almaRibbon and setupType == "Open/Close" ? closeSeriesAlt : almaRibbon and setupType == "Renko" ? renko_close : na, style=plot.style_circles, linewidth=1, color=color.new(trendColour, 80), title="RENKO_1")
p22=plot(almaRibbon and setupType == "Open/Close" ? openSeriesAlt : almaRibbon and setupType == "Renko" ? renko_open : na, style=plot.style_circles, linewidth=1, color=color.new(trendColour, 80), title="RENKO_2")
fill(p11, p22, color=color.new(trendColour, 50), title="RENKO_fill")
//
lxTrigger = false
sxTrigger = false
leTrigger = buy_entry
seTrigger = sel_entry
// === /ALERT conditions.
buy = leTrigger //ta.crossover(closeSeriesAlt, openSeriesAlt)
sell = seTrigger //ta.crossunder(closeSeriesAlt, openSeriesAlt)
varip wasLong = false
varip wasShort = false
if barstate.isconfirmed
wasLong := false
else
if buy
wasLong := true
if barstate.isconfirmed
wasShort := false
else
if sell
wasShort := true
plotshape(wasLong, color = color.yellow)
plotshape(wasShort, color = color.yellow)
//plotshape(almaRibbon ? buy : na, title = "Buy", text = 'Buy', style = shape.labelup, location = location.belowbar, color= #39ff14, textcolor = #FFFFFF, size = size.tiny)
//plotshape(almaRibbon ? sell : na, title = "Exit", text = 'Exit', style = shape.labeldown, location = location.abovebar, color= #ff1100, textcolor = #FFFFFF, size = size.tiny)
// === STRATEGY ===
i_alert_txt_entry_long = "Short Exit" //input.text_area(defval = "Short Exit", title = "Long Entry Message", group = "Alerts")
i_alert_txt_exit_long = "Long Exit" //input.text_area(defval = "Long Exit", title = "Long Exit Message", group = "Alerts")
i_alert_txt_entry_short = "Go Short" //input.text_area(defval = "Go Short", title = "Short Entry Message", group = "Alerts")
i_alert_txt_exit_short = "Go Long" //input.text_area(defval = "Go Long", title = "Short Exit Message", group = "Alerts")
// Entries and Exits with TP/SL
//tradeType
if buy and TPSType == "Trailing" and tradeDateIsAllowed
strategy.close("Short" , alert_message = i_alert_txt_exit_short)
strategy.entry("Long" , strategy.long , alert_message = i_alert_txt_entry_long)
if sell and TPSType == "Trailing" and tradeDateIsAllowed
strategy.close("Long" , alert_message = i_alert_txt_exit_long)
strategy.entry("Short" , strategy.short, alert_message = i_alert_txt_entry_short)
//tradeType
if buy and TPSType == "Options" and tradeDateIsAllowed
// strategy.close("Short" , alert_message = i_alert_txt_exit_short)
strategy.entry("Long" , strategy.long , alert_message = i_alert_txt_entry_long)
if sell and TPSType == "Options" and tradeDateIsAllowed
strategy.close("Long" , alert_message = i_alert_txt_exit_long)
// strategy.entry("Short" , strategy.short, alert_message = i_alert_txt_entry_short)
G_RISK = '■ ' + 'Risk Management'
//#region ———— <↓↓↓ G_RISK ↓↓↓> {
//ATR SL Settings
atrLength = 20 //input.int(20, minval=1, title='ATR Length')
profitFactor = 2.5 //input(2.5, title='Take Profit Factor')
stopFactor = 1 //input(1.0, title='Stop Loss Factor')
// Calculate ATR
tpatrValue = ta.atr(atrLength)
// Calculate take profit and stop loss levels for buy signals
takeProfit1_buy = 1 * profitFactor * tpatrValue //close + profitFactor * atrValue
takeProfit2_buy = 2 * profitFactor * tpatrValue //close + 2 * profitFactor * atrValue
takeProfit3_buy = 3 * profitFactor * tpatrValue //close + 3 * profitFactor * atrValue
stopLoss_buy = close - takeProfit1_buy //stopFactor * tpatrValue
// Calculate take profit and stop loss levels for sell signals
takeProfit1_sell = 1 * profitFactor * tpatrValue //close - profitFactor * atrValue
takeProfit2_sell = 2 * profitFactor * tpatrValue //close - 2 * profitFactor * atrValue
takeProfit3_sell = 3 * profitFactor * tpatrValue //close - 3 * profitFactor * atrValue
stopLoss_sell = close + takeProfit1_sell //stopFactor * tpatrValue
// ———————————
//Tooltip
T_LVL = '(%) Exit Level'
T_QTY = '(%) Adjust trade exit volume'
T_MSG = 'Paste JSON message for your bot'
//Webhook Message
O_LEMSG = 'Long Entry'
O_LXMSGSL = 'Long SL'
O_LXMSGTP1 = 'Long TP1'
O_LXMSGTP2 = 'Long TP2'
O_LXMSGTP3 = 'Long TP3'
O_LXMSG = 'Long Exit'
O_SEMSG = 'Short Entry'
O_SXMSGSL = 'Short SL'
O_SXMSGA = 'Short TP1'
O_SXMSGB = 'Short TP2'
O_SXMSGC = 'Short TP3'
O_SXMSGX = 'Short Exit'
// on whole pips) for forex currency pairs.
pip_size = syminfo.mintick * (syminfo.type == "forex" ? 10 : 1)
// On the last historical bar, show the instrument's pip size
//if barstate.islastconfirmedhistory
// label.new(x=bar_index + 2, y=close, style=label.style_label_left,
// color=color.navy, textcolor=color.white, size=size.large,
// text=syminfo.ticker + "'s pip size is:\n" +
// str.tostring(pip_size))
// ——————————— | | | Line length guide |
i_lxLvlTP1 = leTrigger ? takeProfit1_buy : seTrigger ? takeProfit1_sell : na //input.float (1, 'Level TP1' , group = G_RISK, tooltip = T_LVL)
i_lxQtyTP1 = input.float (50, 'Qty TP1' , group = G_RISK, tooltip = T_QTY)
i_lxLvlTP2 = leTrigger ? takeProfit2_buy : seTrigger ? takeProfit2_sell : na //input.float (1.5, 'Level TP2' , group = G_RISK, tooltip = T_LVL)
i_lxQtyTP2 = input.float (30, 'Qty TP2' , group = G_RISK, tooltip = T_QTY)
i_lxLvlTP3 = leTrigger ? takeProfit3_buy : seTrigger ? takeProfit3_sell : na //input.float (2, 'Level TP3' , group = G_RISK, tooltip = T_LVL)
i_lxQtyTP3 = input.float (20, 'Qty TP3' , group = G_RISK, tooltip = T_QTY)
i_lxLvlSL = leTrigger ? takeProfit1_buy : seTrigger ? takeProfit1_sell : na //input.float (0.5, 'Stop Loss' , group = G_RISK, tooltip = T_LVL)
i_sxLvlTP1 = i_lxLvlTP1
i_sxQtyTP1 = i_lxQtyTP1
i_sxLvlTP2 = i_lxLvlTP2
i_sxQtyTP2 = i_lxQtyTP2
i_sxLvlTP3 = i_lxLvlTP3
i_sxQtyTP3 = i_lxQtyTP3
i_sxLvlSL = i_lxLvlSL
G_MSG = '■ ' + 'Webhook Message'
i_leMsg = O_LEMSG //input.string (O_LEMSG ,'Long Entry' , group = G_MSG, tooltip = T_MSG)
i_lxMsgSL = O_LXMSGSL //input.string (O_LXMSGSL ,'Long SL' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP1 = O_LXMSGTP1 //input.string (O_LXMSGTP1,'Long TP1' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP2 = O_LXMSGTP2 //input.string (O_LXMSGTP2,'Long TP2' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP3 = O_LXMSGTP3 //input.string (O_LXMSGTP3,'Long TP3' , group = G_MSG, tooltip = T_MSG)
i_lxMsg = O_LXMSG //input.string (O_LXMSG ,'Long Exit' , group = G_MSG, tooltip = T_MSG)
i_seMsg = O_SEMSG //input.string (O_SEMSG ,'Short Entry' , group = G_MSG, tooltip = T_MSG)
i_sxMsgSL = O_SXMSGSL //input.string (O_SXMSGSL ,'Short SL' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP1 = O_SXMSGA //input.string (O_SXMSGA ,'Short TP1' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP2 = O_SXMSGB //input.string (O_SXMSGB ,'Short TP2' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP3 = O_SXMSGC //input.string (O_SXMSGC ,'Short TP3' , group = G_MSG, tooltip = T_MSG)
i_sxMsg = O_SXMSGX //input.string (O_SXMSGX ,'Short Exit' , group = G_MSG, tooltip = T_MSG)
i_src = close
G_DISPLAY = 'Display'
//
i_alertOn = true //input.bool (true, 'Alert Labels On/Off' , group = G_DISPLAY)
i_barColOn = true //input.bool (true, 'Bar Color On/Off' , group = G_DISPLAY)
// ———————————
// @function Calculate the Take Profit line, and the crossover or crossunder
f_tp(_condition, _conditionValue, _leTrigger, _seTrigger, _src, _lxLvlTP, _sxLvlTP)=>
var float _tpLine = 0.0
_topLvl = _src + _lxLvlTP //TPSType == "Fixed %" ? _src + (_src * (_lxLvlTP / 100)) : _src + _lxLvlTP
_botLvl = _src - _lxLvlTP //TPSType == "Fixed %" ? _src - (_src * (_sxLvlTP / 100)) : _src - _sxLvlTP
_tpLine := _condition != _conditionValue and _leTrigger ? _topLvl :
_condition != -_conditionValue and _seTrigger ? _botLvl :
nz(_tpLine )
// @function Similar to "ta.crossover" or "ta.crossunder"
f_cross(_scr1, _scr2, _over)=>
_cross = _over ? _scr1 > _scr2 and _scr1 < _scr2 :
_scr1 < _scr2 and _scr1 > _scr2
// ———————————
//
var float condition = 0.0
var float slLine = 0.0
var float entryLine = 0.0
//
entryLine := leTrigger and condition <= 0.0 ? close :
seTrigger and condition >= 0.0 ? close : nz(entryLine )
//
slTopLvl = TPSType == "Fixed %" ? i_src + (i_src * (i_lxLvlSL / 100)) : i_src + i_lxLvlSL
slBotLvl = TPSType == "Fixed %" ? i_src - (i_src * (i_sxLvlSL / 100)) : i_src - i_lxLvlSL
slLine := condition <= 0.0 and leTrigger ? slBotLvl :
condition >= 0.0 and seTrigger ? slTopLvl : nz(slLine )
slLong = f_cross(low, slLine, false)
slShort = f_cross(high, slLine, true )
//
= f_tp(condition, 1.2,leTrigger, seTrigger, i_src, i_lxLvlTP3, i_sxLvlTP3)
= f_tp(condition, 1.1,leTrigger, seTrigger, i_src, i_lxLvlTP2, i_sxLvlTP2)
= f_tp(condition, 1.0,leTrigger, seTrigger, i_src, i_lxLvlTP1, i_sxLvlTP1)
tp3Long = f_cross(high, tp3Line, true )
tp3Short = f_cross(low, tp3Line, false)
tp2Long = f_cross(high, tp2Line, true )
tp2Short = f_cross(low, tp2Line, false)
tp1Long = f_cross(high, tp1Line, true )
tp1Short = f_cross(low, tp1Line, false)
switch
leTrigger and condition <= 0.0 => condition := 1.0
seTrigger and condition >= 0.0 => condition := -1.0
tp3Long and condition == 1.2 => condition := 1.3
tp3Short and condition == -1.2 => condition := -1.3
tp2Long and condition == 1.1 => condition := 1.2
tp2Short and condition == -1.1 => condition := -1.2
tp1Long and condition == 1.0 => condition := 1.1
tp1Short and condition == -1.0 => condition := -1.1
slLong and condition >= 1.0 => condition := 0.0
slShort and condition <= -1.0 => condition := 0.0
lxTrigger and condition >= 1.0 => condition := 0.0
sxTrigger and condition <= -1.0 => condition := 0.0
longE = leTrigger and condition <= 0.0 and condition == 1.0
shortE = seTrigger and condition >= 0.0 and condition == -1.0
longX = lxTrigger and condition >= 1.0 and condition == 0.0
shortX = sxTrigger and condition <= -1.0 and condition == 0.0
longSL = slLong and condition >= 1.0 and condition == 0.0
shortSL = slShort and condition <= -1.0 and condition == 0.0
longTP3 = tp3Long and condition == 1.2 and condition == 1.3
shortTP3 = tp3Short and condition == -1.2 and condition == -1.3
longTP2 = tp2Long and condition == 1.1 and condition == 1.2
shortTP2 = tp2Short and condition == -1.1 and condition == -1.2
longTP1 = tp1Long and condition == 1.0 and condition == 1.1
shortTP1 = tp1Short and condition == -1.0 and condition == -1.1
// ——————————— {
//
if strategy.position_size <= 0 and longE and TPSType == "ATR" and tradeDateIsAllowed
strategy.entry( 'Long', strategy.long, alert_message = i_leMsg, comment = 'LE')
if strategy.position_size > 0 and condition == 1.0 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'LXTP1', from_entry = 'Long', qty_percent = i_lxQtyTP1, limit = tp1Line, stop = slLine, comment_profit = 'LXTP1', comment_loss = 'SL', alert_profit = i_lxMsgTP1, alert_loss = i_lxMsgSL)
if strategy.position_size > 0 and condition == 1.1 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'LXTP2', from_entry = 'Long', qty_percent = i_lxQtyTP2, limit = tp2Line, stop = slLine, comment_profit = 'LXTP2', comment_loss = 'SL', alert_profit = i_lxMsgTP2, alert_loss = i_lxMsgSL)
if strategy.position_size > 0 and condition == 1.2 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'LXTP3', from_entry = 'Long', qty_percent = i_lxQtyTP3, limit = tp3Line, stop = slLine, comment_profit = 'LXTP3', comment_loss = 'SL', alert_profit = i_lxMsgTP3, alert_loss = i_lxMsgSL)
if longX and tradeDateIsAllowed
strategy.close( 'Long', alert_message = i_lxMsg, comment = 'LX')
//
if strategy.position_size >= 0 and shortE and TPSType == "ATR" and tradeDateIsAllowed
strategy.entry( 'Short', strategy.short, alert_message = i_leMsg, comment = 'SE')
if strategy.position_size < 0 and condition == -1.0 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'SXTP1', from_entry = 'Short', qty_percent = i_sxQtyTP1, limit = tp1Line, stop = slLine, comment_profit = 'SXTP1', comment_loss = 'SL', alert_profit = i_sxMsgTP1, alert_loss = i_sxMsgSL)
if strategy.position_size < 0 and condition == -1.1 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'SXTP2', from_entry = 'Short', qty_percent = i_sxQtyTP2, limit = tp2Line, stop = slLine, comment_profit = 'SXTP2', comment_loss = 'SL', alert_profit = i_sxMsgTP2, alert_loss = i_sxMsgSL)
if strategy.position_size < 0 and condition == -1.2 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'SXTP3', from_entry = 'Short', qty_percent = i_sxQtyTP3, limit = tp3Line, stop = slLine, comment_profit = 'SXTP3', comment_loss = 'SL', alert_profit = i_sxMsgTP3, alert_loss = i_sxMsgSL)
if shortX and tradeDateIsAllowed
strategy.close( 'Short', alert_message = i_sxMsg, comment = 'SX')
// ———————————
c_tp = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.green
c_entry = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.blue
c_sl = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.red
p_tp1Line = plot ( condition == 1.0 or condition == -1.0 ? tp1Line : na, title = "TP Line 1", color = c_tp, linewidth = 1, style = plot.style_linebr)
p_tp2Line = plot ( condition == 1.0 or condition == -1.0 or condition == 1.1 or condition == -1.1 ? tp2Line : na, title = "TP Line 2", color = c_tp, linewidth = 1, style = plot.style_linebr)
p_tp3Line = plot ( condition == 1.0 or condition == -1.0 or condition == 1.1 or condition == -1.1 or condition == 1.2 or condition == -1.2 ? tp3Line : na, title = "TP Line 3", color = c_tp, linewidth = 1, style = plot.style_linebr)
p_entryLine = plot ( condition >= 1.0 or condition <= -1.0 ? entryLine : na, title = "Entry Line", color = c_entry, linewidth = 1, style = plot.style_linebr)
p_slLine = plot ( condition == 1.0 or condition == -1.0 or condition == 1.1 or condition == -1.1 or condition == 1.2 or condition == -1.2 ? slLine : na, title = "SL Line", color = c_sl, linewidth = 1, style = plot.style_linebr)
//fill( p_tp3Line, p_entryLine, color = leTrigger or seTrigger ? na :color.new(color.green, 90))
fill( p_entryLine, p_slLine, color = leTrigger or seTrigger ? na :color.new(color.red, 90))
//
plotshape( i_alertOn and longE, title = 'Long', text = 'Long', textcolor = color.white, color = color.green, style = shape.labelup, size = size.tiny, location = location.belowbar)
plotshape( i_alertOn and shortE, title = 'Short', text = 'Short', textcolor = color.white, color = color.red, style = shape.labeldown, size = size.tiny, location = location.abovebar)
plotshape( i_alertOn and (longX or shortX) ? close : na, title = 'Close', text = 'Close', textcolor = color.white, color = color.gray, style = shape.labelup, size = size.tiny, location = location.absolute)
l_tp = i_alertOn and (longTP1 or shortTP1) ? close : na
plotshape( l_tp, title = "TP1 Cross", text = "TP1", textcolor = color.white, color = #ec407a, style = shape.labelup, size = size.tiny, location = location.absolute)
plotshape( i_alertOn and (longTP2 or shortTP2) ? close : na, title = "TP2 Cross", text = "TP2", textcolor = color.white, color = #ec407a, style = shape.labelup, size = size.tiny, location = location.absolute)
plotshape( i_alertOn and (longTP3 or shortTP3) ? close : na, title = "TP3 Cross", text = "TP3", textcolor = color.white, color = #ec407a, style = shape.labelup, size = size.tiny, location = location.absolute)
plotshape( i_alertOn and (longSL or shortSL) ? close : na, title = "SL Cross", text = "SL", textcolor = color.white, color = color.maroon, style = shape.labelup, size = size.tiny, location = location.absolute)
//
plot( na, title = "─── ───", editable = false, display = display.data_window)
plot( condition, title = "condition", editable = false, display = display.data_window)
plot( strategy.position_size * 100, title = ".position_size", editable = false, display = display.data_window)
//#endregion }
// ——————————— <↑↑↑ G_RISK ↑↑↑>
//#region ———— <↓↓↓ G_SCRIPT02 ↓↓↓> {
// @function Queues a new element in an array and de-queues its first element.
f_qDq(_array, _val) =>
array.push(_array, _val)
_return = array.shift(_array)
_return
var line a_slLine = array.new_line(1)
var line a_entryLine = array.new_line(1)
var line a_tp3Line = array.new_line(1)
var line a_tp2Line = array.new_line(1)
var line a_tp1Line = array.new_line(1)
var label a_slLabel = array.new_label(1)
var label a_tp3label = array.new_label(1)
var label a_tp2label = array.new_label(1)
var label a_tp1label = array.new_label(1)
var label a_entryLabel = array.new_label(1)
newEntry = longE or shortE
entryIndex = 1
entryIndex := newEntry ? bar_index : nz(entryIndex )
lasTrade = bar_index >= entryIndex
l_right = 10
if TPSType == "ATR"
line.delete( f_qDq(a_slLine, line.new( entryIndex, slLine, last_bar_index + l_right, slLine, style = line.style_solid, color = c_sl)))
if TPSType == "ATR"
line.delete( f_qDq(a_entryLine, line.new( entryIndex, entryLine, last_bar_index + l_right, entryLine, style = line.style_solid, color = color.blue)))
if TPSType == "ATR"
line.delete( f_qDq(a_tp3Line, line.new( entryIndex, tp3Line, last_bar_index + l_right, tp3Line, style = line.style_solid, color = c_tp)))
if TPSType == "ATR"
line.delete( f_qDq(a_tp2Line, line.new( entryIndex, tp2Line, last_bar_index + l_right, tp2Line, style = line.style_solid, color = c_tp)))
if TPSType == "ATR"
line.delete( f_qDq(a_tp1Line, line.new( entryIndex, tp1Line, last_bar_index + l_right, tp1Line, style = line.style_solid, color = c_tp)))
if TPSType == "ATR"
label.delete( f_qDq(a_slLabel, label.new( last_bar_index + l_right, slLine, 'SL: ' + str.tostring(slLine, '##.###'), style = label.style_label_left, textcolor = color.white, color = c_sl)))
if TPSType == "ATR"
label.delete( f_qDq(a_entryLabel, label.new( last_bar_index + l_right, entryLine, 'Entry: ' + str.tostring(entryLine, '##.###'), style = label.style_label_left, textcolor = color.white, color = color.blue)))
if TPSType == "ATR"
label.delete( f_qDq(a_tp3label, label.new( last_bar_index + l_right, tp3Line, 'TP3: ' + str.tostring(tp3Line, '##.###') + " - Target Pips : - " + str.tostring(longE ? tp3Line - entryLine : entryLine - tp3Line, "#.##"), style = label.style_label_left, textcolor = color.white, color = c_tp)))
if TPSType == "ATR"
label.delete( f_qDq(a_tp2label, label.new( last_bar_index + l_right, tp2Line, 'TP2: ' + str.tostring(tp2Line, '##.###'), style = label.style_label_left, textcolor = color.white, color = c_tp)))
if TPSType == "ATR"
label.delete( f_qDq(a_tp1label, label.new( last_bar_index + l_right, tp1Line, 'TP1: ' + str.tostring(tp1Line, '##.###'), style = label.style_label_left, textcolor = color.white, color = c_tp)))
//#endregion }
// ——————————— <↑↑↑ G_SCRIPT02 ↑↑↑>
c_barCol = close > open ? color.rgb(120, 9, 139) : color.rgb(69, 155, 225)
barcolor(
i_barColOn ? c_barCol : na)
// ———————————
//
if longE or shortE or longX or shortX
alert(message = 'Any Alert', freq = alert.freq_once_per_bar_close)
if longE
alert(message = 'Long Entry', freq = alert.freq_once_per_bar_close)
if shortE
alert(message = 'Short Entry', freq = alert.freq_once_per_bar_close)
if longX
alert(message = 'Long Exit', freq = alert.freq_once_per_bar_close)
if shortX
alert(message = 'Short Exit', freq = alert.freq_once_per_bar_close)
//#endregion }
// ——————————— <↑↑↑ G_SCRIPT03 ↑↑↑>
// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © TraderHalai
// This script was born out of my quest to be able to display strategy back test statistics on charts to allow for easier backtesting on devices that do not natively support backtest engine (such as mobile phones, when I am backtesting from away from my computer). There are already a few good ones on TradingView, but most / many are too complicated for my needs.
//
//Found an excellent display backtest engine by 'The Art of Trading'. This script is a snippet of his hard work, with some very minor tweaks and changes. Much respect to the original author.
//
//Full credit to the original author of this script. It can be found here: www.tradingview.com
//
// This script can be copied and airlifted onto existing strategy scripts of your own, and integrates out of the box without implementation of additional functions. I've also added Max Runup, Average Win and Average Loss per trade to the orignal script.
//
//Will look to add in more performance metrics in future, as I further develop this script.
//
//Feel free to use this display panel in your scripts and strategies.
//Thanks and enjoy! :)
//@version=5
//strategy("Strategy BackTest Display Statistics - TraderHalai", overlay=true, default_qty_value= 5, default_qty_type = strategy.percent_of_equity, initial_capital=10000, commission_type=strategy.commission.percent, commission_value=0.1)
//DEMO basic strategy - Use your own strategy here - Jaws Mean Reversion from my profile used here
//source = input(title = "Source", defval = close)
///////////////////////////// --- BEGIN TESTER CODE --- ////////////////////////
// COPY below into your strategy to enable display
////////////////////////////////////////////////////////////////////////////////
// Declare performance tracking variables
drawTester = input.bool(false, "Strategy Performance", group='Dashboards', inline="Show Dashboards")
var balance = strategy.initial_capital
var drawdown = 0.0
var maxDrawdown = 0.0
var maxBalance = 0.0
var totalWins = 0
var totalLoss = 0
// Prepare stats table
var table testTable = table.new(position.top_right, 5, 2, border_width=1)
f_fillCell(_table, _column, _row, _title, _value, _bgcolor, _txtcolor) =>
_cellText = _title + "\n" + _value
table.cell(_table, _column, _row, _cellText, bgcolor=_bgcolor, text_color=_txtcolor)
// Custom function to truncate (cut) excess decimal places
//truncate(_number, _decimalPlaces) =>
// _factor = math.pow(10, _decimalPlaces)
// int(_number * _factor) / _factor
// Draw stats table
var bgcolor = color.new(color.black,0)
if drawTester and tradeDateIsAllowed
if barstate.islastconfirmedhistory
// Update table
dollarReturn = strategy.netprofit
f_fillCell(testTable, 0, 0, "Total Trades:", str.tostring(strategy.closedtrades), bgcolor, color.white)
f_fillCell(testTable, 0, 1, "Win Rate:", str.tostring(truncate((strategy.wintrades/strategy.closedtrades)*100,2)) + "%", bgcolor, color.white)
f_fillCell(testTable, 1, 0, "Starting:", "$" + str.tostring(strategy.initial_capital), bgcolor, color.white)
f_fillCell(testTable, 1, 1, "Ending:", "$" + str.tostring(truncate(strategy.initial_capital + strategy.netprofit,2)), bgcolor, color.white)
f_fillCell(testTable, 2, 0, "Avg Win:", "$"+ str.tostring(truncate(strategy.grossprofit / strategy.wintrades, 2)), bgcolor, color.white)
f_fillCell(testTable, 2, 1, "Avg Loss:", "$"+ str.tostring(truncate(strategy.grossloss / strategy.losstrades, 2)), bgcolor, color.white)
f_fillCell(testTable, 3, 0, "Profit Factor:", str.tostring(truncate(strategy.grossprofit / strategy.grossloss,2)), strategy.grossprofit > strategy.grossloss ? color.green : color.red, color.white)
f_fillCell(testTable, 3, 1, "Max Runup:", str.tostring(truncate(strategy.max_runup, 2 )), bgcolor, color.white)
f_fillCell(testTable, 4, 0, "Return:", (dollarReturn > 0 ? "+" : "") + str.tostring(truncate((dollarReturn / strategy.initial_capital)*100,2)) + "%", dollarReturn > 0 ? color.green : color.red, color.white)
f_fillCell(testTable, 4, 1, "Max DD:", str.tostring(truncate((strategy.max_drawdown / strategy.equity) * 100 ,2)) + "%", color.red, color.white)
// --- END TESTER CODE --- ///////////////
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © niceGear68734
//@version=5
//strategy("Table to filter trades per day", overlay=true, use_bar_magnifier = true, initial_capital = 5000, calc_on_every_tick = true, calc_on_order_fills = true, commission_type = strategy.commission.cash_per_contract)
//~ ___________________________________________________________________________
//~ !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
//~ !!!!!!!!!!!!!!!_________________ START _________________!!!!!!!!!!!!!!!!!
i_showweeklyPerformance = input.bool(false, 'Weekly Performance', group='Dashboards', inline="Show Dashboards")
//__________________________ User Inputs ___________________________________
var const string g_table = "Table Settings"
i_table_pos = "Top Left" //input.string(defval = "Top Left", title = "Position", options = , group = g_table, inline = "1", tooltip = "It sets the location of the table")
i_text_size = "Normal" //input.string(defval = "Normal", title = "Set the size of text", options = , tooltip = "This option is used to change the size of the text in the table")
var const string g_general = "General Settings"
i_check_open_close = "Opened" //input.string("Opened", "Check when the trade :", , group = g_general, tooltip = "This parameter defines what to check for. If opened is selected, the results will show the trades that opened on that day. If closed is selected, the results will show the trades that closed on that day")
i_timezone = "Exchange" //input.string("Exchange", title = "Set the Timezone", options = , group = g_general, tooltip = "You can use this setting whenever you want to change the time that the trade has closed/opened")
//~_____________________________ Switches ___________________________________
table_pos = switch i_table_pos
"Bottom Right" => position.bottom_right
"Bottom Left" => position.bottom_left
"Top Right" => position.top_right
"Top Left" => position.top_left
timezone_setting = i_timezone == "Exchange" ? syminfo.timezone : i_timezone
text_size = switch i_text_size
"Small" => size.small
"Normal" => size.normal
"Large" => size.large
//__________________________ Array Declaration _____________________________
var string t_column_names = array.from( "", "Sun", "Mon", "Tue", "Wed", "Thur", "Fri", "Sat") // Columns header names
var string t_row_names = array.from("", "Total Trades", "Loss", "Win", "Win Rate" ) // Rows header names
var t_column_size = array.size(t_column_names)
var t_row_size = array.size(t_row_names)
var string a_closed_trades = array.new_string() // Save the total number of trades
var string a_loss_trades = array.new_string() // Save the number of losing trades
var string a_win_trades = array.new_string() // Save the number of winning trades
var _a_day_week = array.new_int() // Save the day of the week to split data
// __________________________ Custom Functions ________________________________
//~ create a counter so that it gives a number to strategy.closed_trades.entry_time(counter)
var trade_number = -1
if strategy.closedtrades > strategy.closedtrades
trade_number += 1
f_strategy_closedtrades_hour() =>
switch
i_check_open_close =="Closed" => dayofweek(strategy.closedtrades.exit_time(trade_number), timezone_setting)
i_check_open_close =="Opened" => dayofweek(strategy.closedtrades.entry_time(trade_number), timezone_setting)
f_data(_i) =>
var _closed_trades = 0
var _loss_trades = 0
var _win_trades = 0
var _txt_closed_trades = ""
var _txt_loss_trades = ""
var _txt_win_trades = ""
if strategy.closedtrades > strategy.closedtrades and f_strategy_closedtrades_hour() == _i
_closed_trades += 1
_txt_closed_trades := str.tostring(_closed_trades)
if strategy.losstrades > strategy.losstrades and f_strategy_closedtrades_hour() == _i
_loss_trades += 1
_txt_loss_trades := str.tostring(_loss_trades)
if strategy.wintrades > strategy.wintrades and f_strategy_closedtrades_hour() == _i
_win_trades += 1
_txt_win_trades := str.tostring(_win_trades)
//__________________________
var string array1 = array.new_string(5)
var string array2 = array.new_string(5)
var string array3 = array.new_string(5)
var string array4 = array.new_string(5)
var string array5 = array.new_string(5)
var string array6 = array.new_string(5)
var string array7 = array.new_string(5)
f_pass_data_to_array(_i, _array) =>
= f_data(_i)
array.set(_array,1 , cl)
array.set(_array,2,loss)
array.set(_array,3,win)
if cl != ""
array.set(_array,4,str.tostring(str.tonumber(win) / str.tonumber(cl) * 100 , "##") + " %")
if cl != "" and win == ""
array.set(_array,4,"0 %")
for i = 1 to 7
switch
i == 1 => f_pass_data_to_array(i,array1)
i == 2 => f_pass_data_to_array(i,array2)
i == 3 => f_pass_data_to_array(i,array3)
i == 4 => f_pass_data_to_array(i,array4)
i == 5 => f_pass_data_to_array(i,array5)
i == 6 => f_pass_data_to_array(i,array6)
i == 7 => f_pass_data_to_array(i,array7)
f_retrieve_data_to_table(_i, _j) =>
switch
_i == 1 => array.get(array1, _j)
_i == 2 => array.get(array2, _j)
_i == 3 => array.get(array3, _j)
_i == 4 => array.get(array4, _j)
_i == 5 => array.get(array5, _j)
_i == 6 => array.get(array6, _j)
_i == 7 => array.get(array7, _j)
//~ ___________________________ Create Table ________________________________
create_table(_col, _row, _txt) =>
var table _tbl = table.new(position = table_pos, columns = t_column_size , rows = t_row_size, border_width=1)
color _color = _row == 0 or _col == 0 ? color.rgb(3, 62, 106) : color.rgb(2, 81, 155)
table.cell(_tbl, _col, _row, _txt, bgcolor = _color, text_color = color.white, text_size = text_size)
//~___________________________ Fill With Data _______________________________
if barstate.islastconfirmedhistory and i_showweeklyPerformance and tradeDateIsAllowed
for i = 0 to t_column_size - 1 by 1
for j = 0 to t_row_size - 1 by 1
_txt = ""
if i >= 0 and j == 0
_txt := array.get(t_column_names, i)
if j >= 0 and i == 0
_txt := array.get(t_row_names, j)
if i >= 1 and j >= 1 and j <= 5
_txt := f_retrieve_data_to_table( i , j)
create_table(i ,j , _txt)
//~ ___________________________ Notice ______________________________________
if timeframe.in_seconds() > timeframe.in_seconds("D")
x = table.new(position.middle_center,1,1,color.aqua)
table.cell_set_text(x,0,0,"Please select lower timeframes (Daily or lower)")
//~ !!!!!!!!!!!!!!!_________________ STOP _________________!!!!!!!!!!!!!!!!!!
//~ !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
//~ ___________________________________________________________________________
// Global Dashboard Variables
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
// Dashboard Table Text Size
i_tableTextSize = "Normal" //input.string(title="Dashboard Size", defval="Normal", options= , group="Dashboards")
table_text_size(s) =>
switch s
"Auto" => size.auto
"Huge" => size.huge
"Large" => size.large
"Normal" => size.normal
"Small" => size.small
=> size.tiny
tableTextSize = table_text_size(i_tableTextSize)
// Monthly Table Performance Dashboard By @QuantNomad
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
i_showMonthlyPerformance = input.bool(false, 'Monthly Performance', group='Dashboards', inline="Show Dashboards")
i_monthlyReturnPercision = 2
if i_showMonthlyPerformance and tradeDateIsAllowed
new_month = month(time) != month(time )
new_year = year(time) != year(time )
eq = strategy.equity
bar_pnl = eq / eq - 1
cur_month_pnl = 0.0
cur_year_pnl = 0.0
// Current Monthly P&L;
cur_month_pnl := new_month ? 0.0 :
(1 + cur_month_pnl ) * (1 + bar_pnl) - 1
// Current Yearly P&L;
cur_year_pnl := new_year ? 0.0 :
(1 + cur_year_pnl ) * (1 + bar_pnl) - 1
// Arrays to store Yearly and Monthly P&Ls;
var month_pnl = array.new_float(0)
var month_time = array.new_int(0)
var year_pnl = array.new_float(0)
var year_time = array.new_int(0)
last_computed = false
if (not na(cur_month_pnl ) and (new_month or barstate.islastconfirmedhistory))
if (last_computed )
array.pop(month_pnl)
array.pop(month_time)
array.push(month_pnl , cur_month_pnl )
array.push(month_time, time )
if (not na(cur_year_pnl ) and (new_year or barstate.islastconfirmedhistory))
if (last_computed )
array.pop(year_pnl)
array.pop(year_time)
array.push(year_pnl , cur_year_pnl )
array.push(year_time, time )
last_computed := barstate.islastconfirmedhistory ? true : nz(last_computed )
// Monthly P&L; Table
var monthly_table = table(na)
if (barstate.islastconfirmedhistory)
monthly_table := table.new(position.bottom_right, columns = 14, rows = array.size(year_pnl) + 1, border_width = 1)
table.cell(monthly_table, 0, 0, "", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 1, 0, "Jan", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 2, 0, "Feb", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 3, 0, "Mar", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 4, 0, "Apr", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 5, 0, "May", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 6, 0, "Jun", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 7, 0, "Jul", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 8, 0, "Aug", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 9, 0, "Sep", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 10, 0, "Oct", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 11, 0, "Nov", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 12, 0, "Dec", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 13, 0, "Year", bgcolor = #999999, text_size=tableTextSize)
for yi = 0 to array.size(year_pnl) - 1
table.cell(monthly_table, 0, yi + 1, str.tostring(year(array.get(year_time, yi))), bgcolor = #cccccc, text_size=tableTextSize)
y_color = array.get(year_pnl, yi) > 0 ? color.new(color.teal, transp = 40) : color.new(color.gray, transp = 40)
table.cell(monthly_table, 13, yi + 1, str.tostring(math.round(array.get(year_pnl, yi) * 100, i_monthlyReturnPercision)), bgcolor = y_color, text_color=color.new(color.white, 0),text_size=tableTextSize)
for mi = 0 to array.size(month_time) - 1
m_row = year(array.get(month_time, mi)) - year(array.get(year_time, 0)) + 1
m_col = month(array.get(month_time, mi))
m_color = array.get(month_pnl, mi) > 0 ? color.new(color.teal, transp = 40) : color.new(color.maroon, transp = 40)
table.cell(monthly_table, m_col, m_row, str.tostring(math.round(array.get(month_pnl, mi) * 100, i_monthlyReturnPercision)), bgcolor = m_color, text_color=color.new(color.white, 0), text_size=tableTextSize)
hide = timeframe.isintraday
// Input for EMA period
emaPeriod = 48 //input.int(48, title="EMA Period")
emaPeriod2 = 2 //input.int(2, title="EME Period 2")
emaPeriod3 = 21 //input.int(21, title="EMA Period")
// Input to toggle EMA Cloud
showcloud = input.bool(false, title="Plot EMA?", group='EMA & ATR', inline="Show EMA's & ATR")
useHTF = input.bool(true, title = "Use Higher Time Frame?")
matimeframe = useHTF ? my_time1 : ''
// EMA calculations
ema = request.security(syminfo.tickerid, matimeframe, ta.ema(close, emaPeriod))
ema2 = request.security(syminfo.tickerid, matimeframe, ta.ema(close,emaPeriod2))
ema3 = request.security(syminfo.tickerid, matimeframe,ta.ema(close, emaPeriod3))
emaColor = close > ema3 ? color.new(color.rgb(56, 142, 60, 63), 50) : color.new(color.rgb(147, 40, 51, 38), 50)
// Plotting EMA's
// plot_ema1 = plot(hide ? ema : na, style=plot.style_line, color=color.new(color.rgb(255, 255, 255, 100), 50), title="EMA", linewidth=2)
// plot_ema2 = plot(hide ? ema2 : na, style=plot.style_line, color=color.new(color.rgb(255, 255, 255, 100), 50), title="EMA", linewidth=1)
// plot_ema3 = plot(ema3, style=plot.style_line, color=emaColor, title="EMA", linewidth=1)
// EMA Cloud
cloudColor = ema2 > ema ? color.new(#0f8513, 80) : color.new(#a81414, 80)
cloudColor2 = ema2 > ema3 ? color.new(#0f8513, 50) : color.new(#a81414, 50)
cloudColor := showcloud ? cloudColor : na
// fill(plot_ema1, plot_ema2, color=cloudColor, title="EMA Cloud")
// fill(plot_ema3, plot_ema2, color=cloudColor, title="EMA Cloud")
/////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © BackQuant
import TradingView/ta/4 as ta
//@version=5
//indicator(
// title="DEMA Adjusted Average True Range ",
// shorttitle = "DEMA ATR ",
// overlay=true,
// timeframe="",
// timeframe_gaps=true
// )
// Define User Inputs
simple bool showAtr = input.bool(false, "Plot Dema?", group='EMA & ATR', inline="Show EMA's & ATR")
simple bool haCandles = true //input.bool(true, "Use HA Candles?")
simple int periodDema = 7 //input.int(7, "Dema Period", group = "Dema Atr")
series float sourceDema = close //input.source(close, "Calculation Source", group = "Dema Atr")
simple int periodAtr = 14 //input.int(14, "Period", group = "Dema Atr")
simple float factorAtr = 1.7 //input.float(1.7, "Factor", step = 0.01, group = "Dema Atr")
simple color longColour = #66bb6a
simple color shortColour = #f23645
/////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
// Use HA Candles?
heikinashi_close = request.security(
symbol = ticker.heikinashi(syminfo.tickerid),
timeframe = timeframe.period,
expression = close,
gaps = barmerge.gaps_off,
lookahead = barmerge.lookahead_on
)
var series float source = close
if haCandles == true
source := heikinashi_close
if haCandles == false
source := sourceDema
/////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
// Function
DemaAtrWithBands(periodDema, source, lookback, atrFactor)=>
ema1 = ta.ema(source, periodDema)
ema2 = ta.ema(ema1, periodDema)
demaOut = 2 * ema1 - ema2
atr = ta.atr(lookback)
trueRange = atr * atrFactor
DemaAtr = demaOut
DemaAtr := nz(DemaAtr , DemaAtr)
trueRangeUpper = demaOut + trueRange
trueRangeLower = demaOut - trueRange
if trueRangeLower > DemaAtr
DemaAtr := trueRangeLower
if trueRangeUpper < DemaAtr
DemaAtr := trueRangeUpper
DemaAtr
// Function Out
DemaAtr = DemaAtrWithBands(periodDema, source, periodAtr, factorAtr)
/////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
// Conditions
DemaAtrLong = DemaAtr > DemaAtr
DemaAtrShort = DemaAtr < DemaAtr
// Colour Condtions
var color Trendcolor = #ffffff
if DemaAtrLong
Trendcolor := longColour
if DemaAtrShort
Trendcolor := shortColour
// Plotting
plot( showAtr ? DemaAtr : na, "ATR", color=Trendcolor, linewidth = 2 )
import DevLucem/ZigLib/1 as ZigZag
////////
// Fetch Ingredients
//
// ////////
// // Bake it with a simple oven this time
= ZigZag.zigzag(low, high, Depth, Deviation, Backstep)
string nowPoint = ""
var float lastPoint = z1.price
if bool(ta.change(direction))
lastPoint := z1.price
// ////////
// // Let it Cool And Serve
line zz = na
label point = na
if repaint
zz := line.new(z1, z2, xloc.bar_time, extend? extend.right: extend.none, color.new(direction>0? upcolor: dncolor, lines), width=line_thick)
nowPoint := direction<0? (z2.pricelastPoint? "HH": "LH")
point := label.new(z2, nowPoint, xloc.bar_time, yloc.price,
color.new(direction<0? upcolor: dncolor, labels), direction>0? label.style_label_down: label.style_label_up, color.new(direction>0? upcolor: dncolor, labels), label_size)
if direction == direction
line.delete(zz )
label.delete(point )
else
line.set_extend(zz , extend.none)
else
if direction != direction
zz := line.new(z1 , z2 , xloc.bar_time, extend.none, color.new(direction>0? upcolor: dncolor, lines), width=line_thick)
nowPoint := direction <0? (z2.price lastPoint ? "HH": "LH")
point := label.new(z2 , nowPoint, xloc.bar_time, yloc.price,
color.new(direction <0? upcolor: dncolor, labels), direction >0? label.style_label_down: label.style_label_up, color.new(direction >0? upcolor: dncolor, labels), label_size)
bgcolor(direction<0? color.new(dncolor, background): color.new(upcolor, background), title='Direction Background', display = display.none)
plotarrow(direction, "direction", display=display.status_line)
// ////////
// // Declare Meal Was Sweet By Force
alertcondition(nowPoint == "HH" and z2.price != z2.price , "New Higher High", 'Zigzag on {{ticker}} higher higher high detected at {{time}}')
alertcondition(nowPoint == "LH" and z2.price != z2.price , "New Lower High", 'Zigzag on {{ticker}} higher lower high detected at {{time}}')
alertcondition(nowPoint == "HL" and z2.price != z2.price , "New Higher Low", 'Zigzag on {{ticker}} higher lower low detected at {{time}}')
alertcondition(nowPoint == "LL" and z2.price != z2.price , "New Lower Low", 'Zigzag on {{ticker}} lower low detected at {{time}}')
alertcondition(direction != direction , 'Direction Changed', 'Zigzag on {{ticker}} direction changed at {{time}}')
alertcondition(direction != direction and direction>0, 'Bullish Direction', 'Zigzag on {{ticker}} bullish direction at {{time}}')
alertcondition(direction != direction and direction<0, 'Bearish Direction', 'Zigzag on {{ticker}} bearish direction at {{time}}')
if direction != direction
alert((direction<0? "Bearish": "Bullish") + " Direction Final ", alert.freq_once_per_bar_close)
MSG = "MARKET STRUCTURE"
VBG = "VOLUMETRIC ORDER BLOCKS"
MST = "Limit market structure calculation to improve memory speed time"
SLT = " Limit swing structure to tot bars back"
IDT = " Start date of the internal structure"
CST = "Color candle based on trend detection system"
OBT = "Display internal buy and sell activity"
OBD = "Show Last number of orderblock"
OBMT = " Use Length to adjust cordinate of the orderblocks\n Use whole candle body"
_ ='
------------
–––––––––––––––––––––––––– INPUTS –––––––––––––––––––––––––––
------------ '//{
bool windowsis = input.bool(true, "Window", inline="kla", group=MSG)
int mswindow = input.int(5000, "", tooltip=MST,group=MSG, inline="kla", minval=1000)
bool showSwing = input.bool(true, "Swing", inline="scss", group=MSG)
int swingLimit = input.int(100, "", tooltip=SLT, inline="scss", group=MSG, minval=10, maxval=200)
color swingcssup = input.color(#f7525f, "", inline="scss", group=MSG)
color swingcssdn = input.color(#66bb6a, "", inline="scss", group=MSG)
bool showMapping = input.bool(false, "Mapping Structure", inline="mapping", group=MSG)
string mappingStyle = input.string("----", "", options= , inline="mapping", group=MSG)
color mappingcss = input.color(color.silver, "", tooltip="Display Mapping Structure", inline="mapping", group=MSG)
bool candlecss = input.bool(false, "Color Candles", tooltip=CST, group=MSG, inline="txt")
string mstext = input.string("Tiny", "", options= ,
inline="txt", group=MSG)
string msmode = input.string("Adjusted Points", "Algorithmic Logic", options=
, inline="node", group=MSG)
int mslen = input.int(5, "", inline="node", group=MSG, minval=2)
bool buildsweep = input.bool(true, "Build Sweep (x)", "Build sweep on market structure", "znc", MSG)
bool msbubble = input.bool(true, "Bubbles", tooltip="Display Circle Bubbles", inline="bubbles", group=MSG)
bool obshow = input.bool(true, "Show Last", tooltip=OBD, group=VBG, inline="obshow")
int oblast = input.int(5, "", group=VBG, inline="obshow", minval=0)
color obupcs = input.color(color.new(#089981, 90), "", inline="obshow", group=VBG)
color obdncs = input.color(color.new(#f23645, 90), "", inline="obshow", group=VBG)
bool obshowactivity = input.bool(true, "Show Buy/Sell Activity", inline="act", group=VBG, tooltip=OBT)
color obactup = input.color(color.new(#089981, 50), "", inline="act", group=VBG)
color obactdn = input.color(color.new(#f23645, 50), "", inline="act", group=VBG)
obshowbb = input.bool(false, "Show Breakers", inline="bb", group=VBG, tooltip="Display Breakers")
color bbup = input.color(color.new(#089981, 100), "", inline="bb", group=VBG)
color bbdn = input.color(color.new(#f23645, 100), "", inline="bb", group=VBG)
obmode = input.string("Length", "Construction", options= , tooltip=OBMT, inline="atr", group=VBG)
len = input.int(5, "", inline="atr", group=VBG, minval=1)
obmiti = input.string("Close", "Mitigation Method", options= ,
tooltip="Mitigation method for when to trigger order blocks", group=VBG)
obtxt = input.string("Normal", "Metric Size", options= ,
tooltip="Order block Metrics text size", inline="txt", group=VBG)
showmetric = input.bool(true, "Show Metrics", group=VBG)
showline = input.bool(true, "Show Mid-Line", group=VBG)
overlap = input.bool(true, "Hide Overlap", group=VBG, inline="ov")
wichlap = input.string("Recent", "", options= , inline="ov", group=VBG)
fvg_enable = input.bool(false, "", inline="1", group="FAIR VALUE GAP", tooltip="Display fair value gap")
what_fvg = input.string("FVG", "", inline="1", group="FAIR VALUE GAP", tooltip="Display fair value gap",
options= )
fvg_num = input.int(5, "Show Last", inline="1a", group="FAIR VALUE GAP", tooltip="Number of fvg to show", minval=0)
fvg_upcss = input.color(color.new(#089981, 80), "", inline="1", group="FAIR VALUE GAP")
fvg_dncss = input.color(color.new(#f23645, 80), "", inline="1", group="FAIR VALUE GAP")
fvgbbup = input.color(color.new(#089981, 100), "", inline="1", group="FAIR VALUE GAP")
fvgbbdn = input.color(color.new(#f23645, 100), "", inline="1", group="FAIR VALUE GAP")
fvg_src = input.string("Close", "Mitigation",
inline="3",
group="FAIR VALUE GAP",
tooltip=" Use the close of the body as trigger\n\n Use the extreme point of the body as trigger",
options= )
fvgthresh = input.float(0, "Threshold", tooltip="Filter out non significative FVG", group="FAIR VALUE GAP",
inline="asd", minval=0, maxval=2, step=0.1)
fvgoverlap = input.bool(true, "Hide Overlap", "Hide overlapping FVG", group="FAIR VALUE GAP")
fvgline = input.bool(true, "Show Mid-Line", group="FAIR VALUE GAP")
fvgextend = input.bool(false, "Extend FVG", group="FAIR VALUE GAP")
dispraid = input.bool(false, "Display Raids", inline="raid", group="FAIR VALUE GAP")
//}
_ ='
------------
–––––––––––––––––––––––––– UDT –––––––––––––––––––––––––––
------------ '//{
type hqlzone
box pbx
box ebx
box lbx
label plb
label elb
label lbl
type Zphl
line top
line bottom
label top_label
label bottom_label
bool stopcross
bool sbottomcross
bool itopcross
bool ibottomcross
string txtup
string txtdn
float topy
float bottomy
float topx
float bottomx
float tup
float tdn
int tupx
int tdnx
float itopy
float itopx
float ibottomy
float ibottomx
float uV
float dV
type entered
bool normal = false
bool breaker = false
type store
line ln
label lb
box bx
linefill lf
type structure
int zn
float zz
float bos
float choch
int loc
int temp
int trend
int start
float main
int xloc
bool upsweep
bool dnsweep
string txt = na
type drawms
int x1
int x2
float y
string txt
color css
string style
type ob
bool bull
float top
float btm
float avg
int loc
color css
float vol
int dir
int move
int blPOS
int brPOS
int xlocbl
int xlocbr
bool isbb = false
int bbloc
type FVG
float top = na
float btm = na
int loc = bar_index
bool isbb = false
int bbloc = na
bool israid = false
float raidy = na
int raidloc = na
int raidx2 = na
bool active = false
color raidcs = na
type SFP
float y
int loc
float ancor
type sfpbuildlbl
int x
float y
string style
color css
string txt
type sfpbuildline
int x1
int x2
float y
color css
float ancor
int loc
type equalbuild
int x1
float y1
int x2
float y2
color css
string style
type equalname
int x
float y
string txt
color css
string style
type ehl
float pt
int t
float pb
int b
type sellbuyside
float top
float btm
int loc
color css
string txt
float vol
type timer
bool start = false
int count = 0
//}
_ ='
------------
–––––––––––––––––––––––––– SETUP –––––––––––––––––––––––––––
------------ '//{
var store bin = store.new(
array.new< line >()
, array.new< label >()
, array.new< box >()
, array.new()
)
var entered blobenter = entered.new()
var entered brobenter = entered.new()
var entered blfvgenter = entered.new()
var entered brfvgenter = entered.new()
var entered blarea = entered.new()
var entered brarea = entered.new()
var timer lc = timer.new ()
if barstate.islast
for obj in bin.ln
obj.delete()
for obj in bin.lb
obj.delete()
for obj in bin.bx
obj.delete()
for obj in bin.lf
obj.delete()
bin.ln.clear()
bin.lb.clear()
bin.bx.clear()
bin.lf.clear()
invcol = #ffffff00
float atr = (ta.atr(200) / (5/len))
//}
_ ='
------------
–––––––––––––––––––––––––– UTILITY –––––––––––––––––––––––––––
------------ '//{
method txSz(string s) =>
out = switch s
"Tiny" => size.tiny
"Small" => size.small
"Normal" => size.normal
"Large" => size.large
"Huge" => size.huge
"Auto" => size.auto
out
method lstyle(string style) =>
out = switch style
'⎯⎯⎯⎯' => line.style_solid
'----' => line.style_dashed
'····' => line.style_dotted
ghl() => [high , low , close , open , close, open, high, low, high , low , ta.atr(200)]
method IDMIDX(bool use_max, int loc) =>
min = 99999999.
max = 0.
idx = 0
if use_max
for i = 0 to (bar_index - loc)
max := math.max(high , max)
min := max == high ? low : min
idx := max == high ? i : idx
else
for i = 0 to (bar_index - loc)
min := math.min(low , min)
max := min == low ? high : max
idx := min == low ? i : idx
idx
SFPData() => [high, high , high , low, low , low , close, volume, time, bar_index , time ]
SFPcords() =>
RealTF = barstate.isrealtime ? 0 : 1
= SFPData()
[h , h1 , h2 , l , l1 , l2 , c , v , t , n , t1 ]
method find(structure ms, bool use_max, bool sweep, bool useob) =>
min = 99999999.
max = 0.
idx = 0
if not sweep
if ((bar_index - ms.loc) - 1) > 0
if use_max
for i = 0 to (bar_index - ms.loc) - 1
max := math.max(high , max)
min := max == high ? low : min
idx := max == high ? i : idx
if useob
if high
SMA25 vs SMA150 – Reentry nur bei Gap-Expansion version 1📈 Strategy: SMA25 vs. SMA150 – Reentry with Gap Expansion
This trend-following strategy trades long positions only during strong uptrends.
It combines mid-term trend confirmation (SMA150) with short-term momentum (SMA25), and includes strict entry, reentry, and exit conditions to capture sustained bullish phases while cutting weak setups early.
🟢 Entry Rules
A long position is opened only if all of the following conditions are met:
Trend filter: The closing price is above SMA150 → confirms an uptrend.
Bullish candle: Current candle closes higher than it opens.
SMA range: SMA25 is 8% to 60% above SMA150.
Momentum slope: SMA25 has increased more strongly than SMA150 over the last 5 candles and is rising.
Trend confirmation: SMA25 has remained above SMA150 for at least 5 candles.
Price distance: The close is at least 0.5% above SMA25.
Stability: The previous two candles also closed above SMA25.
Short-term breakout: Current close is higher than the last 3 closes.
Reentry condition: Allowed only after 20 candles since the last exit and only if a gap expansion occurs above the previous high.
🔴 Exit Rules
A trade is closed as soon as any of the following conditions is triggered:
Dynamic trailing exit:
Close falls 3% below the highest SMA25 value since entry.
Hard stop-loss:
The low of the candle falls 5% or more below the entry price (intrabar trigger).
Early weakness filter:
If any of the first 3 candles after entry closes below the entry price, the trade is exited immediately.
⚙️ Additional Details
Long trades only (no shorts)
No pyramiding – only one position open at a time
Chart background color:
Green = position open
Red = no position
This system targets clean, established uptrends, avoids premature entries, and exits quickly when momentum fades.
It’s designed for swing and position traders who prefer systematic, trend-based setups with tight risk control and clear structure.
SulLaLuna 💵 Trend Mastery:The Calzolaio Way🚀SulLaLuna 💵 Trend Mastery:The Calzolaio Way🚀
🌕 Find the God Candele. Capture the gains. Create passive income.
Fellow F.I.R.E. Decibels, disciples of the Calzolaio Way—welcome to the sacred toolkit. This indicator, "SulLaLuna 💵 Trend Mastery:The Calzolaio Way🚀," is forged from the elite SulLaLuna stack, drawing wisdom from Market Wizards like Michael Marcus (who turned $30k into $80M through disciplined trend riding) and Oliver Velez's pristine strategies for profiting on every trade. It's not just lines on a chart—it's your architectural blueprint for financial sovereignty, where data meets divine timing to build the cathedral of Project Calzolaio.
We trade math, not emotion. We honor timeframes. Confluence is King. This indicator deploys the Zero-Lag SMA (ZLSMA), Hull-based M2 (global money supply as a macro trend oracle), ATR-smart stops, and multi-TF alignments to ritualize God Candle setups. Backtested across asset classes, it's modular for your playbooks—small risks, compounding gains, passive income streams.
Why This Indicator is Awesome: The Divine Confluence Engine
In the spirit of "Use Only the Best," this tool synthesizes proven SulLaLuna indicators like ZLSMA, Adaptive Trend Finder, and Momentum HUD with Velez's lessons on trend reversals, support/resistance, and psychology of fear. Here's why it reigns supreme:
1. Global M2 Hull: Macro Trend Oracle
Scaled M2 (summed from major economies like US, EU, JP) via Hull MA captures the "big picture" (Velez Ch. 2). It flips colors as S/R—green for support (bullish bounce zones), red for resistance (bearish ceilings), orange neutral. Like Marcus spotting commodity booms, it signals when liquidity sweeps ignite God Candles. Extend it for future price projections, honoring "How a Trend Ends" (Velez Ch. 5).
2. ZLSMA + ATR Smart Stops: Surgical Precision
Zero-Lag SMA (faster than standard MAs) crosses M2 for entries, with ATR bands for initial stops (2x mult) and trails (1x mult). This embodies "Trade Small. Lose Smaller."—risk ≤1-2% per trade, pre-planned exits. Flip markers (↑/↓) alert divine timing, filtering noise like Velez's "First Pullback" setups.
3. HTF & Multi-TF Dashboard: Timeframe Alignments are Sacred
Show HTF M2 (e.g., Daily) with custom styles/colors. Multi-TF lines (4H, D, W, M) dash across your chart, labeled right-edge with 🚀 (bull) or 🛸 (bear). A confluence table (top-right) scores alignments: Strong Bull (≥3 green), Strong Bear, or Mixed. This is "Confluence is King"—no single signal rules; seek 4+ star scores like Rogers buying value in hysteria.
4. Background & Ribbon: Visual Divine Guidance
Slope-based bgcolor (green bull, red bear) for at-a-glance bias. M2 Ribbon (EMA cloud) flips triangles for macro shifts, ritualizing climactic reversals (Velez Ch. 7).
5. Composite Probability: High-Prob God Candle Hunter
Scores (0-100%) blend 8 factors: price/ZLSMA vs M2, TF slopes, ribbon. Threshold (70%) + pivot zone (near M2/ATR) + optional cross filters for HP signals. Labels show "%" dynamically—alerts fire when confluence ≥4, echoing Schwartz's champion edge: "Everybody Gets What They Want" (Seykota wisdom).
6. Alerts & Rituals Built-In
M2 flips, entries/exits, HP longs/shorts—log them in your journal. Weekly reviews dissect anomalies, as per our Operational Framework.
This isn't hype—it's audited excellence. Backtest it: High confluence crushes drawdowns, compounding like Bielfeldt's T-bond mastery from Peoria. We build together; share wins in the F.I.R.E. Decibel forum.
Suggested Strategy: The SulLaLuna M2 Confluence Playbook
Honor the Risk Triad: Position ↓ if leverage/timeframe ↑; scale ↑ only on ≥4 confluence. Align with "God Candele" hunts—rare explosives reverse-engineered for passive streams.
1. Pre-Trade Checklist (Before Every Entry)
- Trend Alignment: D/4H/1H M2 slopes agree? Table shows Strong Bull/Bear?
- Signal on 15m: ZLSMA crosses M2 in confluence zone (near pivot/ATR bands).
- Volume + Divergence**: Supported by volume (use HUD if added); score ≥70%.
- SL/TP Setup: ATR-based stop; TP at structure/2-3R reward (Velez Reward:Risk).
- HTF Agrees: Monthly bull for longs; avoid counter-trend unless climactic (Ch. 7).
Confluence Score: Rate 1-5 stars. <3? Stand aside. Log emotional state—no adrenaline.
2. Execution Protocol
- Entry: On HP Long/Short triangle (e.g., ZLSMA > M2, score 80%+, monthly bull). Use limits; favor longs above M2 support.
- Position Size: ≤1-2% risk. Example: $10k account, 1% risk = $100 SL distance → size accordingly.
- Trail Stops: Move to trail band after 1R profit; let winners run like Kovner's world trades.
- Asset Classes**: Forex/stocks/crypto—test M2's macro edge on EURUSD or NASDAQ (Velez Ch. 6 reviews).
Ritualize: "When we find the God Candele, we don’t just ride it—we ritualize it." Screenshot + reason.
3. Post-Trade Ritual
- Document: Result, confluence score, lessons. Update journal.
- Exits: Hit stop/exit cross? Or trail locks gains.
- Weekly Audit: Wins/losses, anomalies. Adjust params (e.g., M2 length 55 default).
4. Risk Triad in Action
- Low TF (15m)? Smaller size.
- High Leverage? Tiny positions.
- Confluence ≥4 + HTF support? Scale hold for passive compounding.
Example Setup: God Candle Long
- Chart: 15m EURUSD.
- M2 Hull green (support), ZLSMA crossover, 4H/D/W bull (table: Strong Bull).
- HP Long (85% score) near pivot.
- Entry: Limit at cross; SL below ATR lower; TP at next resistance.
- Outcome: Capture 2R gain; trail for more if trend day (Velez Ch. 5).
Community > Ego: Test, share signals in Discord. Backtest in Pine Script for algo evolution.
We are architects of redemption. Each trade bricks the cathedral. Trade the micro, flow with the macro. When alignments converge, we act—with discipline, data, and divine purpose.
🗣️ “Confluence is King. Honor the Timeframes. Track the God Candele.”
Master Strategy Guidebook. Rise as F.I.R.E. Decibels! 🚀
