AO/AC Trading Zones Strategy [Skyrexio] Overview
AO/AC Trading Zones Strategy leverages the combination of Awesome Oscillator (AO), Acceleration/Deceleration Indicator (AC), Williams Fractals, Williams Alligator and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Combination of AO and AC is used for creating so-called trading zones to create the signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over. In some special cases strategy uses AO and AC combination to trail profit (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Both AC and AO shall print two consecutive increasing values. At the price candle close which corresponds to this condition algorithm opens the first long trade with 10% of capital.
4. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
5. If AO and AC both continue printing the rising values strategy opens the long trade on each candle close with 10% of capital while number of opened trades reaches 5.
6. If AO and AC both has printed 5 rising values in a row algorithm close all trades if candle's low below the low of the 5-th candle with rising AO and AC values in a row.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting:
EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation).
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about the trading zones concept and its signals. To understand this we need to briefly introduce what is AO and AC. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO) , where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now let's discuss the trading zones concept and how it can create the signal. Zones are created by the combination of AO and AC. We can divide three zone types:
Greed zone: when the AO and AC both are rising
Red zone: when the AO and AC both are decreasing
Gray zone: when one of AO or AC is rising, the other is falling
Gray zone is considered as uncertainty. AC and AO are moving in the opposite direction. Strategy skip such price action to decrease the chance to stuck in the losing trade during potential sideways. Red zone is also not interesting for the algorithm because both indicators consider the trend as bearish, but strategy opens only long trades. It is waiting for the green zone to increase the chance to open trade in the direction of the potential uptrend. When we have 2 candles in a row in the green zone script executes a long trade with 10% of capital.
Two green zone candles in a row is considered by algorithm as a bullish trend, but now so strong, that's the reason why trade is going to be closed when the combination of Alligator and Fractals will consider the the trend change from bullish to bearish. If id did not happens, algorithm starts to count the green zone candles in a row. When we have 5 in a row script change the trade closing condition. Such situation is considered is a high probability strong bull market and all trades will be closed if candle's low will be lower than fifth green zone candle's low. This is used to increase probability to secure the profit. If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. Each trade uses 10% of capital.
Why we use trading zones signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC and AO values in the direction of the most likely main trend signaling that we have the high probability of the fastest bullish phase on the market. The main idea is to take part in such rapid moves and add trades if this move continues its acceleration according to indicators.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -9.49%
Maximum Single Profit: +24.33%
Net Profit: +4374.70 USDT (+43.75%)
Total Trades: 278 (39.57% win rate)
Profit Factor: 2.203
Maximum Accumulated Loss: 668.16 USDT (-5.43%)
Average Profit per Trade: 15.74 USDT (+1.37%)
Average Trade Duration: 60 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
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Arpeet MACDOverview
This strategy is based on the zero-lag version of the MACD (Moving Average Convergence Divergence) indicator, which captures short-term trends by quickly responding to price changes, enabling high-frequency trading. The strategy uses two moving averages with different periods (fast and slow lines) to construct the MACD indicator and introduces a zero-lag algorithm to eliminate the delay between the indicator and the price, improving the timeliness of signals. Additionally, the crossover of the signal line and the MACD line is used as buy and sell signals, and alerts are set up to help traders seize trading opportunities in a timely manner.
Strategy Principle
Calculate the EMA (Exponential Moving Average) or SMA (Simple Moving Average) of the fast line (default 12 periods) and slow line (default 26 periods).
Use the zero-lag algorithm to double-smooth the fast and slow lines, eliminating the delay between the indicator and the price.
The MACD line is formed by the difference between the zero-lag fast line and the zero-lag slow line.
The signal line is formed by the EMA (default 9 periods) or SMA of the MACD line.
The MACD histogram is formed by the difference between the MACD line and the signal line, with blue representing positive values and red representing negative values.
When the MACD line crosses the signal line from below and the crossover point is below the zero axis, a buy signal (blue dot) is generated.
When the MACD line crosses the signal line from above and the crossover point is above the zero axis, a sell signal (red dot) is generated.
The strategy automatically places orders based on the buy and sell signals and triggers corresponding alerts.
Advantage Analysis
The zero-lag algorithm effectively eliminates the delay between the indicator and the price, improving the timeliness and accuracy of signals.
The design of dual moving averages can better capture market trends and adapt to different market environments.
The MACD histogram intuitively reflects the comparison of bullish and bearish forces, assisting in trading decisions.
The automatic order placement and alert functions make it convenient for traders to seize trading opportunities in a timely manner, improving trading efficiency.
Risk Analysis
In volatile markets, frequent crossover signals may lead to overtrading and losses.
Improper parameter settings may cause signal distortion and affect strategy performance.
The strategy relies on historical data for calculations and has poor adaptability to sudden events and black swan events.
Optimization Direction
Introduce trend confirmation indicators, such as ADX, to filter out false signals in volatile markets.
Optimize parameters to find the best combination of fast and slow line periods and signal line periods, improving strategy stability.
Combine other technical indicators or fundamental factors to construct a multi-factor model, improving risk-adjusted returns of the strategy.
Introduce stop-loss and take-profit mechanisms to control single-trade risk.
Summary
The MACD Dual Crossover Zero Lag Trading Strategy achieves high-frequency trading by quickly responding to price changes and capturing short-term trends. The zero-lag algorithm and dual moving average design improve the timeliness and accuracy of signals. The strategy has certain advantages, such as intuitive signals and convenient operation, but also faces risks such as overtrading and parameter sensitivity. In the future, the strategy can be optimized by introducing trend confirmation indicators, parameter optimization, multi-factor models, etc., to improve the robustness and profitability of the strategy.
Classic Nacked Z-Score ArbitrageThe “Classic Naked Z-Score Arbitrage” strategy employs a statistical arbitrage model based on the Z-score of the price spread between two assets. This strategy follows the premise of pair trading, where two correlated assets, typically from the same market sector, are traded against each other to profit from relative price movements (Gatev, Goetzmann, & Rouwenhorst, 2006). The approach involves calculating the Z-score of the price spread between two assets to determine market inefficiencies and capitalize on short-term mispricing.
Methodology
Price Spread Calculation:
The strategy calculates the spread between the two selected assets (Asset A and Asset B), typically from different sectors or asset classes, on a daily timeframe.
Statistical Basis – Z-Score:
The Z-score is used as a measure of how far the current price spread deviates from its historical mean, using the standard deviation for normalization.
Trading Logic:
• Long Position:
A long position is initiated when the Z-score exceeds the predefined threshold (e.g., 2.0), indicating that Asset A is undervalued relative to Asset B. This signals an arbitrage opportunity where the trader buys Asset B and sells Asset A.
• Short Position:
A short position is entered when the Z-score falls below the negative threshold, indicating that Asset A is overvalued relative to Asset B. The strategy involves selling Asset B and buying Asset A.
Theoretical Foundation
This strategy is rooted in mean reversion theory, which posits that asset prices tend to return to their long-term average after temporary deviations. This form of arbitrage is widely used in statistical arbitrage and pair trading techniques, where investors seek to exploit short-term price inefficiencies between two assets that historically maintain a stable price relationship (Avery & Sibley, 2020).
Further, the Z-score is an effective tool for identifying significant deviations from the mean, which can be seen as a signal for the potential reversion of the price spread (Braucher, 2015). By capturing these inefficiencies, traders aim to profit from convergence or divergence between correlated assets.
Practical Application
The strategy aligns with the Financial Algorithmic Trading and Market Liquidity analysis, emphasizing the importance of statistical models and efficient execution (Harris, 2024). By utilizing a simple yet effective risk-reward mechanism based on the Z-score, the strategy contributes to the growing body of research on market liquidity, asset correlation, and algorithmic trading.
The integration of transaction costs and slippage ensures that the strategy accounts for practical trading limitations, helping to refine execution in real market conditions. These factors are vital in modern quantitative finance, where liquidity and execution risk can erode profits (Harris, 2024).
References
• Gatev, E., Goetzmann, W. N., & Rouwenhorst, K. G. (2006). Pairs Trading: Performance of a Relative-Value Arbitrage Rule. The Review of Financial Studies, 19(3), 1317-1343.
• Avery, C., & Sibley, D. (2020). Statistical Arbitrage: The Evolution and Practices of Quantitative Trading. Journal of Quantitative Finance, 18(5), 501-523.
• Braucher, J. (2015). Understanding the Z-Score in Trading. Journal of Financial Markets, 12(4), 225-239.
• Harris, L. (2024). Financial Algorithmic Trading and Market Liquidity: A Comprehensive Analysis. Journal of Financial Engineering, 7(1), 18-34.
TradeShields Strategy Builder🛡 WHAT IS TRADESHIELDS?
This no-code strategy builder is designed for traders on TradingView, offering an intuitive platform to create, backtest, and automate trading strategies. While identifying signals is often straightforward, the real challenge in trading lies in managing risk and knowing when not to trade. It equips users with advanced tools to address this challenge, promoting disciplined decision-making and structured trading practices.
This is not just a collection of indicators but a comprehensive toolkit that helps identify high-quality opportunities while placing risk management at the core of every strategy. By integrating customizable filters, robust controls, and automation capabilities, it empowers traders to align their strategies with their unique objectives and risk tolerance.
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🛡 THE GOAL: SHIELD YOUR STRATEGY
The mission is simple: to shield your strategy from bad trades . Whether you're a seasoned trader or just starting, the hardest part of trading isn’t finding signals—it’s avoiding trades that can harm your account. This framework prioritizes quality over quantity , helping filter out suboptimal setups and encouraging disciplined execution.
With tools to manage risk, avoid overtrading, and adapt to changing market conditions, it protects your strategy against impulsive decisions and market volatility.
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🛡 HOW TO USE IT
1. Apply Higher Timeframe Filters
Begin by analyzing broader market trends using tools like the 200 EMA, Ichimoku Cloud, or Supertrend on higher timeframes (e.g., daily or 4-hour charts).
- Example: Ensure the price is above the 200 EMA on the daily chart for long trades or below it for short trades.
2. Identify the Appropriate Entry Signal
Choose an entry signal that aligns with your model and the asset you're trading. Options include:
Supertrend changes for trend reversals.
Bollinger Band touches for mean-reversion trades.
RSI strength/weakness for overbought or oversold conditions.
Breakouts of key levels (e.g., daily or weekly highs/lows) for momentum trades.
MACD and TSI flips.
3. Determine Take-Profit and Stop-Loss Levels
Set clear exit strategies to protect your capital and lock in profits:
Use single, dual, or triple take-profit levels based on percentages or price levels.
Choose a stop-loss type, such as fixed percentage, ATR-based, or trailing stops.
Optionally, set breakeven adjustments after hitting your first take-profit target.
4. Apply Risk Management Filters
Incorporate risk controls to ensure disciplined execution:
Limit the number of trades per day, week, or month to avoid overtrading.
Use time-based filters to trade during specific sessions or custom windows.
Avoid trading around high-impact news events with region-specific filters.
5. Automate and Execute
Leverage the advanced automation features to streamline execution. Alerts are tailored specifically for each supported platform, ensuring seamless integration with tools like PineConnector, 3Commas, Zapier, and more.
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🛡 CORE FOCUS: RISK MANAGEMENT, AUTOMATION, AND DISCIPLINED TRADING
This builder emphasizes quality over quantity, encouraging traders to approach markets with structure and control. Its innovative tools for risk management and automation help optimize performance while reducing effort, fostering consistency and long-term success.
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🛡 KEY FEATURES
General Settings
Theme Customization : Light and dark themes for a tailored interface.
Timezone Adjustment : Align session times and news schedules with your local timezone.
Position Sizing : Define lot sizes to manage risk effectively.
Directional Control : Choose between long-only, short-only, or both directions for trading.
Time Filters
Day-of-Week Selection : Enable or disable trading on specific days.
Session-Based Trading : Restrict trades to major market sessions (Asia, London, New York) or custom windows.
Custom Time Windows : Precisely control the timeframes for trade execution.
Risk Management Tools
Trade Limits : Maximum trades per day, week, or month to avoid overtrading.
Automatic Trade Closures : End-of-session, end-of-day, or end-of-week options.
Duration-Based Filters : Close trades if take-profit isn’t reached within a set timeframe or if they remain unprofitable beyond a specific duration.
Stop-Loss and Take-Profit Options : Fixed percentage or ATR-based stop-losses, single/dual/triple take-profit levels, and breakeven stop adjustments.
Economic News Filters
Region-Specific Filters : Exclude trades around major news events in regions like the USA, UK, Europe, Asia, or Oceania.
News Avoidance Windows : Pause trades before and after high-impact events or automatically close trades ahead of scheduled news releases.
Higher Timeframe Filters
Multi-Timeframe Tools : Leverage EMAs, Supertrend, or Ichimoku Cloud on higher timeframes (Daily, 4-hour, etc.) for trend alignment.
Chart Timeframe Filters
Precision Filtering : Apply EMA or ADX-based conditions to refine trade setups on current chart timeframes.
Entry Signals
Customizable Options : Choose from signals like Supertrend, Bollinger Bands, RSI, MACD, Ichimoku Cloud, or EMA pullbacks.
Indicator Parameter Overrides : Fine-tune default settings for specific signals.
Exit Settings
Flexible Take-Profit Targets : Single, dual, or triple targets. Exit at significant levels like daily/weekly highs or lows.
Stop-Loss Variability : Fixed, ATR-based, or trailing stop-loss options.
Alerts and Automation
Third-Party Integrations : Seamlessly connect with platforms like PineConnector, 3Commas, Zapier, and Capitalise.ai.
Precision-Formatted Alerts : Alerts are tailored specifically for each platform, ensuring seamless execution. For example:
- PineConnector alerts include risk-per-trade parameters.
- 3Commas alerts contain bot-specific configurations.
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🛡 PUBLISHED CHART SETTINGS: 15m COMEX:GC1!
Time Filters : Trades are enabled from Tuesday to Friday, as Mondays often lack sufficient data coming off the weekend, and weekends are excluded due to market closures. Custom time sessions are turned off by default, allowing trades throughout the day.
Risk Filters : Risk is tightly controlled by limiting trades to a maximum of 2 per day and enabling a mechanism to close trades if they remain open too long and are unprofitable. Weekly trade closures ensure that no positions are carried over unnecessarily.
Economic News Filters : By default, trades are allowed during economic news periods, giving traders flexibility to decide how to handle volatility manually. It is recommended to enable these filters if you are creating strategies on lower timeframes.
Higher Timeframe Filters : The setup incorporates confluence from higher timeframe indicators. For example, the 200 EMA on the daily timeframe is used to establish trend direction, while the Ichimoku cloud on the 30-minute timeframe adds additional confirmation.
Entry Signals : The strategy triggers trades based on changes in the Supertrend indicator.
Exit Settings : Trades are configured to take partial profits at three levels (1%, 2%, and 3%) and use a fixed stop loss of 2%. Stops are moved to breakeven after reaching the first take profit level.
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🛡 WHY CHOOSE THIS STRATEGY BUILDER?
This tool transforms trading from reactive to proactive, focusing on risk management and automation as the foundation of every strategy. By helping users avoid unnecessary trades, implement robust controls, and automate execution, it fosters disciplined trading.
Auto Harmonic Pattern - Backtester [Trendoscope]We are finally here with the implementation of backtesting tool for Auto-Harmonic-Pattern-UltimateX .
CAUTION: THIS IS NOT A STRATEGY AND SHOULD NOT BE FOLLOWED BLINDLY. WE ENCOURAGE USERS TO UTILISE THIS AS BACKTESTING TOOL FOR BUILDING THEIR STRATEGY BASED ON HARMONIC PATTERNS
This script is based on our premium indicator - Auto-Harmonic-Pattern-UltimateX . In this script, along with implementation of scanning harmonic patterns, we provide various options via settings which enables users to build their own strategy based on harmonic patterns, use them with custom coded filters, backtest them on various tickers and timeframes.
Harmonic Patterns is concept and we can trade harmonic pattern in many ways. While general interest around harmonic patterns is to find reversal zones and use them for short term swing trades. But, using it along trend following strategies can also be very rewarding. Here is one of the educational idea I shared about using harmonic patterns for trend following. These are just few possibilities where users can explore further on how they want to trade this. The settings of this script are crafted in such a way that it enables users to explore all these possibilities.
🎲 Components
Chart components of this script is lighter compared to Auto Harmonic Pattern - UltimateX. This is because we want to keep lighter interface in order to support seamless execution of emulator. Since pine strategy framework does most of the things such as calculating profitability, keeping track of trades and results etc, display with respect to - "Closed Trade Stats" are removed from this script and "Open Trade Stats" are made lighter.
🎲 Settings
🎯 Trade Settings : Few important settings under this section are
Due to pine limitations, we will not be able to support both long and short in a same setup. Hence, users need to chose either long or short trade setup.
Entry/Base/Target play important role in defining your strategy.
Confluence is another important factor which lets users use multiple patterns at once as confirmation.
🎯 Zigzag Settings : Zigzag settings determine the size of patterns being formed.
Please note that smaller patterns may not yield very good results and larger patterns may take time to complete trade. Similarly higher depth can cause runtime issues. Recursive zigzag option is alternative to deep search algorithm.
🎯 Filters :
Filters enable users to select trades based on specific conditions. Ability to use external filter even allows writing and using custom filters to be used with this algorithm. Here is a video which explains how this can be done. HOW-TO-Use-external-filters
Pattern filters allow users to pick and chose patterns they want to trade. This can be done either individually or based on category
🎯 Alerts :
Apart from strategy specific alerts, the script also implements customisable alerts via pine alert() function. Alerts can be configured to send upon three conditions
When new pattern is created
When an existing pattern updates entry/stop/target due to safe repaint of D (Only happens when Trail Entry Price is selected)
When a pattern in trade closes either due to hitting stop or target
Important Note: Alerts fired via this method may not match the trades shown on chart as trades which are controlled via pine strategy emulator depends on various other factors such as pyramiding.
Alert template is customisable and users can make use of available placeholders to get dynamic data in alerts. Valid placeholders are
{alertType} - Alert type - New/Update/Close
{id} - Pattern Id
{ticker} - Ticker
{timeframe} - Chart timeframe
{price} - Current price
{patterns} - Identified pattern names
{direction} - Direction - Long/Short
{entry} - Entry Price
{stop} - Stop Price
{target} - Target Price
{orderType} - Limit/Stop - applicable for only New and Update types
{status} - Trade status. Valid values are Pending/Cancelled/Stopped/Success
Template is common for all custom alert types. Hence, updating the template will impact all custom alerts - New/Update/Close
{
"alert" : "{alertType}",
"id" : {id},
"ticker" : "{ticker}",
"timeframe" : "{timeframe}",
"price" : {price},
"patterns" : "{patterns}",
"direction" : "{direction}",
"entry" : {entry},
"stop" : {stop},
"target" : {target},
"orderType" : {orderType}
"status" : {status}
}
Here is a video on how to customise the alerts using templates and placeholders - HOW-TO-Customize-Alerts-With-Placeholders
🎯 Miscellaneous :
These are simple settings to control display and backtest bars. If you are running alerts, we suggest turning of Open Trades and Drawings and limit backtest to minimal value in order to improve efficiency of
🎯 Backtest Engine Parameters :
Default settings are optimised for trend following. Users are encouraged to play around with settings and filters to build strategy out of this tool.
Position sizing is not leveraged. Margin settings makes sure that trades cannot exceed capital.
All measures are taken to avoid repainting. Script does not use request.security and real time bars. This drastically reduces the risk of repainting in scripts.
If you are premium user, please select "Bar Magnifier".
gangood bot for FinandyGangood is a mean reversion algorithm currently optimized for trading the ETH/USDT pair on the 1 hour chart time frame. All indicator inputs use the closing price of the period, and all trades are executed at the open of the period following the period in which the trading signal was generated.
To take into account slippage, the commission costs 0.15%.
Backtest result from 2020.
Result since 2019 2,500,000%, maximum drawdown 18%
This bot uses 11 indicators:
1) ADX
2) RANGE FILTER
3) SAR
4) RSI
5) TWAP
6) JMA
7) MACD
8) VOLUME DELTA
9) VOLUME WEIGHT
10) MA
11) TSI
Pattern 1:
There are 3 main components that make up Gangood: I. Trend Filter. The algorithm uses a version of the ADX indicator as a trend filter to only trade during certain time periods when price is most likely to be range-bound (i.e., average retracement). This indicator consists of a fast ADX and a slow ADX both using the same lookback period.
The ADX is smoothed with a 6-period EMA and the slow ADX is smoothed with a 12-period EMA. When the fast ADX is above the slow ADX , the algorithm does not trade because it indicates that the price is most likely trending, which is bad for a mean reversion system. Conversely, when the fast ADX is below the slow ADX, the price is likely to be in a range, so this is the only time the algorithm is allowed to trade. II. Bollinger Bands When the trend filter allows trading, the algorithm uses Bollinger Bands.
Indicator for opening long and short positions. The Bolliger Bands indicator has a 20 lookback period and a 1.5 standard deviation for both the upper and lower bands. When the price crosses the lower band, a buy signal is generated and a long position is opened. When the price crosses the upper band, a sell signal is generated and a short position is opened.
Pattern 2:
Based on RSI which is commonly used as a trend reversal indicator. However, here it is used as a trend-setting indicator, often with great success. This pattern only takes long trades, which is quite successful in a bull market.
Pattern 3:
Long or short trades are determined by the intersection of the fast EMA with the slow EMA for long positions and vice versa for short positions. Trades should only occur close to intersections. We then use the MACD for the long position. an indicator with a 10-minute time frame where we look for high peaks in negative values for longs and vice versa for shorts. They should be significantly higher than the other peaks.
Capital Management:
The maximum leverage in this strategy, I would recommend 2x, in order to trade without unnecessary risks and keep your nerves in order.
Bot setup:
I use the Finandy terminal, in which you can easily trade with this strategy.
1. We go to binance and turn on the hedging mode, this is necessary so that if tradingview sends a webhook for buying later than for selling.
2. Adding a new signal to Finandy
2.1. Open tab
2.1.1. "Order side" Strategy
2.1.2. "Amount" Balance% x Leverage
2.1.3. We set the percentage of the order two times less than the one you want
2.1.4. "Shoulder" is twice as large as the one you want
2.2.Close tab
2.2.1. "Enebaled" tick
2.2.2. "Reverse / Close" Disable
3. Set a notification for this strategy.
4. Copy "Signal URL" and paste it into webhook on tradingview
5. Copy "Signal Message" and paste it into the message on tradingview
CryptoNite - Machine Learning Strategy (15Min Timeframe)Greeting Traders! I am back with another ML strategy. :D I kept my word with combining my machine learning algorithms from Python and integrating them into Tradingview. Thanks to Tradingview's new release of Pinescript v5 it is now possible. This strategy respects the Sortino Ratio and was created using 2 years of data for 50 different cryptocurrencies. That is a total of 100 years of data and 44,849 trades to create this strategy. Now let me tell you, my computer and I are exhausted. We both been at it non-stop for about two months everyday. I refine the strategy, and the computer runs 24/7 for a few days to spit out the best results into the terminal. It's been a good run so my computer will finally get some sleep tonight.
So let's talk a little about the features of the strategy. In the settings window, you'll see the Stoploss, Take Profit Parameters, and Date Range. You can change the Date Range, but I recommend to leave the SL/TP parameters how they are because the machine learning algo chose those input. If you wish to change them you are always welcome to do so but backtest results will change. For the Take Profit parameters you'll see on the left side you something labeled time duration(displayed in minutes) and on the right side you'll see take profit values. Let's talk a little bit how they work.
TP_values = {
"0": 0.102,
"133": 0.051,
"431": 0.039,
"963": 0
}
In python, the table looks like this but it is quite easy to understand in Tradingview.
From 0-133 minutes, the strategy is looking to the reach target point 1 at 10.2% profit.
From 133-431 minutes, the strategy is looking to the reach target point 2 at 5.1% profit.
From 431-963 minutes, the strategy is looking to the reach target point 3 at 3.9% profit.
From 963+ minutes, the strategy is looking to break even at 0% profit on target point 4.
Through each target point a sell trigger is active. It will look for the best time to sell even if TP has not been reached.
This helps the trade not stay open too long.
The last thing I need to mention is the textbox displayed on the right side of your chart. This textbox displays the current Take Profit value in dollar amount. So when you're in a trade you'll know what TP target has to be reached when the open trade is active. Throughout time, the target price changes depending how long the trade has been open. If you have any questions feel free to comment down below, and enjoy this strategy!
hamster-bot HD preset_2presets for users
// DESCRIPTION OF STRATEGY ver. 2
HiDeep Strategy
Author foresterufa
This is a counter-trend strategy that is gradually gaining a position against the trend at the best price.
A prerequisite for completing a position is the price exit from the internal channel on the chart and the appearance of the HiDeep indicator.
The condition for closing the position is touching the opposite side of the internal channel.
A condition for facilitating closure along the middle line of the channel, with high price volatility , is that the price touches the border of the external channel.
Input signals are generated by HiDeep indicators. Closing a position by moving averages.
HigherHigh LowerLow RATALGOHi Traders,
This is Trend following strategy.
This strategy calculates the higher high or lower low of a look back period. If the previous high or low is breached, a signal to enter market is given.
This strategy works well with regular candles and line charts if you find the right settings and chart time frame.
Give it a try with your settings & post your feedback and suggestion if any for improvement.
I had automate this strategy with broker using Trading view Alert feature to get some live results on NSE:Banknifty1!
MTF - Box Trading StrategyMultiTime Frame - Box Trading Strategies (MTF-BT))
How does it work ? The code uses dynamic levels and crossovers on higher time frames to identify trade calls.
Model 1 (Default) Uses a low risk model and Model 2 (Optional) Uses an aggressive model
How to Deploy / Use
As part of the Indicator there are a few choices the user can opt for
Box Resolution - The resolution of the higher time frame for analysis , typically set at 90 , can be customized by the users.
Use Long Strategy 1 - This would add long trades based on Model1 Algorithm for the users
Use Short Strategy 1 - This would add short trades based on Model1 Algorithm for the users
Use Long Strategy 2 - This would add long trades based on Model2 Algorithm for the users
Use Short Strategy 2 - This would add short trades based on Model2 Algorithm for the users
Check Range Val Validate the width of the channel on higher timeframe and trade only when the channel is wider than the value provided ,
The value of 0.14 is determined using series of back test across various assets
Use Stop Loss : Flag to check if Stop Loss should be done by the strategy
Stop Loss Limit : Stop Loss in Absolute terms
Use Profit Booking : Flag to check if Profit Booking should be done by the strategy
Stop Loss Limit : Profit Target in Absolute terms
Do Intraday Exit :Flag to check if trade should be taken as an Intraday only
Exit Window : Session time during which the trade should be closed , like 15:00 - 15:30 for NSE , 22:30 - 23:00 for MCX etc ,
it should be wide enough to accommodate the resolution the use has on the screen
Visual Checks - The user could manually validate the back test results on various assets they would like to use this strategy on before putting it live.
Usage/Markets : Index Trading / Equities and also well with Commodities and Currencies
Time Frame : works well between 3 and 30 , keep the Box resolution to at least 45 for 3/5 mins TF and you could move upto 180 (3 hrs ) for a 30 mins TF.
Strategy Settings Used/Assumed : All of this values are provided in the Properties Tab of the Indicator Settings
and the users can customize it to suit the broker or the product they are charting it against
Initial Capital : 100 000
Order Size : 10 Quantities for Equities , you may change it to 1 lot for Future contracts based on capital deployed
Commission : is set at 0.05%
Slippage : 20 ticks
Recalculate Option : After the Order is filled is selected by default
Disclaimer : There could be scenarios when the breakout/breakdown candle is rejected , especially when it is long one
so it is always recommended to have a confirmation candle that open-closes above the breakout candle / open-closes below the breakdown candle
If you like it and find it useful or if you find a defect or bug , Please let us know in the comments .. that would encouraging !! for us to develop it further
Thank you and have a beautiful and Profitable trading session !
How to get access
Please click on the link / email in the signature or send me a private message to get access
Feedback
Please click on the link/email in the signature or send me a private message for suggestions/feedbacks
GreenCrypto Strategy
This strategy majorly uses MA, Tilson and S&R. MA is used for predicting the trend, Instead of normal cross-over of the MA, we are calculating the trend of the MA itself (whether MA is moving upward or downward by comparing the previous and current value of MA), along with MA we also use Tilson to calculate the MA.
Once we have MA and Tilson we take average and merge both MA and Tilson MA to get a double confirmation on the trend of the market. for entry and exit we use S&R with the merged MA, if the trend change is at the support or resistance level we go for LONG/SHORT respectively. Here we are doing continuous LONG+SHORT position, this provides more opportunity to capture unexpected market trend.
Enter a Long Trade when the script shows "Long" and exit either when you get "Short" signal or when it meets your target.
Parameters:
"Use 1:EST, 2:SST, 3:HST ?" : Select EMA , SMA or HullMA (works best on HullMA)
Length: Length of the EMA / SMA /HullmA
Factor: Used for calculation of Tilson and the Support and resistance .
Date/month/day : for selecting the right backtesting the period (currently it set to Jan 2018 to current day )
for this backtesting i have used 1000$ capital and 0.02% commission for each trade.
This strategy works best on 4H time fram but you can also use it on 1 day or higher timeframe charts
The default config present in this script is designed for ETH but it will also work with other coins)
Config for Specific Crypto coins (Please feel free to try out other configs also) :
ADA, BNB, EOS : "Use 1:EST, 2:SST, 3:HST ?" = 3
"Length" = 8
"Factor" = 0.9
ETC, XLM : "Use 1:EST, 2:SST, 3:HST ?" = 3
"Length" = 8
"Factor" = 0.85
Please DM me if you would like to tryout 7 Days free trail.
The Profit Gate | Tier 1 Script | v1.0.0This script is used to optimized the trend of the stock based on volume , and many kind of moving average. You can use this to swing, or get the idea of long hold play. This work for Crypto as well as penny stock.
This script is best for Penny Stock, Big Cap, Crypto. It is generally based on the idea of averaging move of previous candles as well as current volume . This means if we have our candles at 15m, it will capture bunch of previous candles up to 10 years ahead to get an average move. This will give us a prediction of whether or not a stock will move up (Buy), or go down (Sell).
General Buy|Sell Tier 1
This script is used to optimized the trend of the stock based on volume , and many kind of moving average. You can use this to swing, or get the idea of long hold play. This work for Crypto as well as penny stock.
This script is best for Penny Stock, Big Cap, Crypto. It is generally based on the idea of averaging move of previous candles as well as current volume . This means if we have our candles at 15m, it will capture bunch of previous candles up to 10 years ahead to get an average move. This will give us a prediction of whether or not a stock will move up (Buy), or go down (Sell).
We also use Binary entropy function to optimize the original MACD .
This indicator should be able to tell you where to get in, out, or start to set trailing stop loss on the current position. I will constantly update this algorithm.
Trend analysis, This is ridge model that take in past data from the nearest certain number of candles then predict the next trend by an algorithm.
We also have standard deviation so we can apply it to find the best strike price with the highest probability to get ITM
Please DM me for access to this script
TC Chart Score StrategyThis is My Call Confidence Strategy
The Strategy is designed to help confirm a bullish reversal after a downtrend.
This uses custom weighted algorithm
The Algorithm combines directional movement, volume over average, and moving averages to formulate a score.
The score is then used in conjunction with a smoothed score of the same criteria to initiate a buy signal on a cross over.
The settings are designed to help you customize how you weight directional movement, and the moving averages to further finetune the algorithm to your timelines.
The default settings are designed to be used on a 1 hour time frame.
You can change the settings for other time frames to further increase effectiveness.
This script will be updated as needed if a better algorithm is designed.
RAT Moving Average Crossover StrategyThis is based on general moving average crossovers but some modifications made to generate buy sell signals.
[B] hamster-bot ZZ Breakout reversal strategyAttention! This is a beta version of the strategy script >> <<
A backtest should only be done if you understand how the options work. Otherwise, do a test in the release version
Wildfire [v1]Lower time frame trading strategy with a very simple algorithm and adjustable parameters.
Backtest result shown is from 1st Jan 2018.
Tested with BTCUSD 30m Bitfinex and ETHUSD 30m. Approaches to addressing the drawdown are in development, however the algo in general seems very workable. Prelim tests in other markets encouraging. I have another bot called WARBASTARD which operates in higher timeframes (4hrs) and has far more acceptable drawdown figures.
Invite only, sorry.
CEO Synapse v1.0CEO Synapse — Uyarlanabilir Rejim Stratejisi
This script is invite-only.
What Does This Strategy Do?
Markets are complex systems requiring various expertise. The "CEO Synapse" strategy adopts a "digital dashboard" approach based on the reality that a single viewpoint is insufficient. The strategy combines multiple analytical engines, each developed by me, analyzing different aspects of the market (structure, momentum, rhythm). It detects trend and momentum deviations in markets. A trading decision is made only when there is consensus among these expert engines. The "Synapse Engine" uses adaptive filtering and consensus logic for position management based on market regime (trend/range).
It eliminates the problem of traditional indicators generating misleading signals alone and failing to adapt to volatility and regime changes. Its dynamic threshold mechanism, adaptive periods, and special noise filters reduce unnecessary trades.
Original Methodology and Proprietary Logic: This algorithm does not rely on or copy any open source strategy code. The system uses commonly accepted indicators' mathematical principles such as ADX, EMA, SMA, ATR, True Range, etc., as data sources. The author's methodology combines dynamic period EMA, multi-filter consensus, adaptive threshold, and regime-based execution.
Though our strategy creates an original decision-making mechanism, it leverages foundational building blocks of technical analysis. The traditional indicators we use and their purposes are:
ADX (Average Directional Index): This indicator measures a trend’s strength, not its direction. Our strategy uses ADX as a filter to open positions only under sufficiently strong and distinct trend market conditions. This largely prevents misleading signals in weak or sideways markets.
Moving Averages (EMA and SMA): They form the backbone to determine the main trend direction. By smoothing price data, they reduce noise and reveal the market's general trend. But our strategy processes their outputs not as traditional crossover signals, but as input to an advanced consensus logic with dynamically adjusted periods based on market rhythm combined with other filters.
ATR (Average True Range): This indicator does not produce direct buy-sell signals but measures current market volatility. Especially in "Sideways Market" regime, take profit and stop loss levels are dynamically set based on ATR instead of fixed values, enabling risk management to adapt to market conditions.
Bollinger Band Logic (using Standard Deviation): Though the strategy does not plot Bollinger Bands directly, it uses Standard Deviation, the underlying mathematical concept, to detect excessive price deviations and volatility spikes, producing critical signals for the AMF PG core engine.
"Synapse Engine" consists of two layers: Decision Center (Dynamic Threshold) which automatically adjusts risk appetite based on performance and regime; and Filter Committee (Consensus Score) which weights separate filters to produce a single score. This combination is not reproducible and commercially valuable. Closed source is mandatory.
No classic open source code used. Only publicly available indicators are used. Parameters, order, and usage are fully customized.
Generated Signals: Trend/range entry/exit (long/short), adaptive trailing stop position management, additional risk control signals with Shock Absorber and Quantum Filter.
Purpose: Detect trend breaks and momentum deviations. Components: Volatility filters, adaptive signal weighting, EMA/SMA. Methodology: Combines price and volume change rates via dynamic weighting functions.
What Problem Does CEO Synapse Solve?
CEO Synapse addresses three main issues caused by traditional technical analysis and single indicator usage:
Problem: Misleading Signals and Market Noise
Traditional indicators (MACD, RSI, etc.) generate many "false" buy-sell signals, especially in sideways and choppy markets, causing traders to constantly enter and exit positions (whipsaw) and incur losses.
CEO Synapse Solution: The strategy never relies on a single signal. The Consensus-Based Decision Mechanism ensures no position is opened unless different analytical engines (structural, momentum, rhythm) agree. This "board of directors" approach filters market noise, processing only high-probability signals.
Problem: Static Analysis and Changing Market Conditions
Markets constantly change character; sometimes strong trend, sometimes narrow range. Most strategies try to function with fixed parameters across all conditions, leading to failure.
CEO Synapse Solution: The strategy has Adaptive Regime Switching. It actively analyzes whether the market is in "Trend Mode" or "Sideways Market Mode" and automatically adjusts entry/exit rules and risk management (take profit/stop loss) to the current regime, allowing chameleon-like adaptation to conditions.
Problem: Fixed Parameters and Declining Performance
Many traders believe they find the "best" settings and never change them for months or years. But as market volatility and cycles change, fixed settings lose effectiveness.
CEO Synapse Solution: The strategy operates on Full Adaptation principle.
Market Rhythm Adaptation: Dynamically adjusts analysis speed (e.g., EMA periods) according to market’s natural cycles.
Performance Adaptation: Continuously optimizes risk appetite (signal threshold) based on recent strategy performance, becoming bolder with gains and more cautious with losses.
In summary, CEO Synapse simplifies decision-making, eliminates market noise, and smartly adapts to changing market conditions, protecting the user from common mistakes.
Why "Invite-Only"?
Offering CEO Synapse as "Invite-Only" is a strategic decision to protect the strategy's commercial value and intellectual property and to provide users with the highest quality experience. Key reasons:
Protection of Proprietary IP:
CEO Synapse is the result of hundreds of hours of research, development, and testing. Its consensus logic, adaptive threshold mechanism, and engine integration are unique and patented. Open sourcing it would instantly destroy this trade secret and competitive edge.
Maintaining Performance Integrity and Effectiveness:
Uncontrolled distribution could lead to misuse or signal theft and sale by malicious actors. The invite-only model preserves the strategy’s integrity and ensures access only for serious investors.
Quality User Experience and Support:
Controlled distribution allows better user experience. High-quality documentation explaining features and best practices can be provided, and future updates and support services can be managed better for a limited user base.
Business Model:
CEO Synapse is positioned as a premium analysis tool. Invite-only access reflects its value and compensates the developer for ongoing maintenance, support, and future improvements.
Usage: Available on all timeframes.
Based entirely on my own adaptive filtering methodology.
Proprietary logic: The algorithm’s unique, non-reproducible logic and methodology. Example: Multi-filter consensus + adaptive threshold + regime-based execution.
Why Is This a Premium Tool?
"CEO Synapse"’s value stems from being a proprietary, integrated system beyond free standard indicators:
Advanced Noise Filtering: Not just reduces noise but adjusts filter sensitivity to current market character. Inspired by public mathematical concepts (cycle analysis, statistical filtering) but uniquely combined with proprietary weighting mechanisms and adaptive consensus logic forming the strategy's commercial value. Core indicators (EMA, ATR, ADX, DMI, etc.) are uniquely processed inside this proprietary system.
Full Adaptation: Instead of fixed parameters, the strategy continuously adapts to the market's natural rhythm, volatility, and past performance.
Consensus-Based Decision Making: Relies on collective intelligence of multiple analytical engines, not a single failure point.
These features substantially increase the ability to extract meaningful, actionable insights from raw market data, making it premium. It improves signal accuracy, reduces risk, and adapts to regime shifts. The dynamic threshold mechanism continuously adjusts risk appetite based on recent performance (profitability) and market regime.
By using this script, you agree not to redistribute, sell, or reverse engineer the source code.
This strategy is for educational purposes only. Past performance does not guarantee future results. Always apply proper risk management and protect your capital.
Risk Management: Maximum Drawdown Protection
The strategy includes a built-in capital protection mechanism. Users can specify the percentage drop from peak capital they tolerate. If the capital hits this drawdown limit, protection activates, closing all open positions and blocking new trades, acting as an emergency brake to guard capital against unexpected market conditions.
Automation Ready: Customizable Webhook Alerts
Fully Compatible Automation (JSON): The strategy outputs fully configurable JSON-formatted alert messages for buy, sell, and close actions. This allows connecting CEO Synapse signals to automation platforms like 3Commas and PineConnector for fully automated trading. Dynamic values like position size ({{strategy.order.contracts}}) are automatically included in alerts.
Strategy Backtest Information
Please remember past performance is not indicative of future results. The published chart and report are based on the BTCUSD pair in a 3-hour timeframe with the following settings:
Test Period: January 1, 2018 – November 3, 2025
Default Position Size: 15% of capital
Pyramiding: Off
Commission: 0.0008
Slippage: 2 ticks
Test Approach: The published test contains 201 trades and is statistically significant. Performing your own tests on different assets and timeframes is strongly recommended. Default settings are a template and should be adjusted per your analysis.
QV 4D BX ReversalThis algorithm excels in long-term trading and identifying momentum reversals on higher timeframes. To maximize profits, you can then leverage the QV 2H/4D 2BX & FVB Strategy algorithm, switching to a lower timeframe for precise short-term trades.
### Overview of the Strategy
The "QV 4D BX Reversal" is a Pine Script (version 5) trading strategy for TradingView, designed as a reversal-based system using a custom momentum oscillator called "B-Xtrender" on a higher timeframe (default 4-day). It supports user-selected long-only or short-only trading, entering on signs of momentum reversal or continuation in the oscillator's direction. The strategy uses 5% of equity per trade, with no commissions, and focuses on simple entry/exit rules based on the oscillator's value, changes, and thresholds. It's plotted in a separate pane as a colored histogram (green for positive/uptrending, red for negative/downtrending), with a centerline at 0. This script is suited for trend-reversal trading in assets like stocks, forex, or crypto, emphasizing higher-timeframe signals for reduced noise.
The name likely refers to:
- **QV**: QuantVault (the creator).
- **4D**: Default 4-day timeframe for the oscillator.
- **BX**: B-Xtrender oscillator.
- **Reversal**: Focus on detecting momentum shifts for entries and exits.
It's licensed under Mozilla Public License 2.0, making it open-source friendly.
### Key Indicators and Calculations
The core of the strategy is a single indicator fetched from a higher timeframe:
1. **B-Xtrender Oscillator (shortTermXtrender)**:
- Formula: `RSI(EMA(close, short_l1) - EMA(close, short_l2), short_l3) - 50`.
- Defaults: L1=5, L2=20, L3=5.
- This measures momentum in the difference between a fast and slow EMA, normalized via RSI, and centered around 0 (positive = bullish, negative = bearish).
- Fetched via `request.security` from the input timeframe (TF1, default "4D").
- Plotted as a histogram:
- Green (lime if increasing, darker if decreasing) when >0.
- Red (bright if increasing toward 0, darker if decreasing) when <0.
- A dashed gray hline at 0 acts as a centerline for crossovers.
No other indicators like ATR or bands are used—it's purely oscillator-driven.
### How the Strategy Works: Entries
Entries trigger on momentum shifts or continuations in the B-Xtrender, filtered by the selected trade direction. Only one direction is active at a time (no hedging).
- **Long Direction**:
- **Entry Condition** (`long_entry`): Triggers if either:
- Crossover above 0 (from below) AND the value is increasing (current > previous).
- OR simply increasing (current > previous), regardless of level.
- On entry, it records if the oscillator was below the exit level (exit_lvl, default 3.5) via `entryBelowExit` for a special exit rule.
- Enters a long position with 5% of equity.
- **Short Direction**:
- **Entry Condition** (`short_entry`): Triggers if either:
- Crossunder below 0 (from above) AND the value is decreasing (current < previous).
- OR simply decreasing (current < previous), regardless of level.
- Enters a short position with 5% of equity.
No pyramiding or position sizing variations—entries are straightforward and can re-enter immediately after exits if conditions met. No additional filters like volume or price action.
### How the Strategy Works: Exits
Exits close the entire position based on adverse momentum signals, with combined rules for robustness. Exits are direction-specific and only trigger if in a position.
- **Long Exits** (`long_exit`): Closes the long if any of:
- Crossunder below the exit level (default 3.5).
- Oscillator is red (<=0) AND decreasing for 2 consecutive bars (current < prev, prev < prev ).
- If entry was below exit level (`entryBelowExit` true), crossunder below 0.
- Comment on close indicates the reason (e.g., "Cross below 3.5" or "Red + 2-bar decline").
- Resets `entryBelowExit` after exit.
- **Short Exits** (`short_exit`): Closes the short if any of:
- Crossover above the negative exit level (-3.5).
- Oscillator is green (>=0) AND increasing for 2 consecutive bars (current > prev, prev > prev ).
- Comment on close indicates the reason (e.g., "Cross above -3.5" or "Green + 2-bar increase").
This setup aims to exit on weakening momentum or threshold breaches, protecting against reversals. No partial exits or trailing stops—full close only.
### Alerts
The script includes alert conditions for key events, which can be set up in TradingView for notifications:
- Long Entry (Crossover): "B-Xtrender crossed above 0 and is rising → LONG".
- Long Entry (Increasing): "B-Xtrender TF1 is increasing → LONG".
- Long Exit (Red + 2-Bar Decline): "B-Xtrender is red and decreased for 2 bars → EXIT LONG".
- Short Entry (Crossunder): "B-Xtrender crossed below 0 and is falling → SHORT".
- Short Entry (Decreasing): "B-Xtrender TF1 is decreasing → SHORT".
- Short Exit (Green + 2-Bar Increase): "B-Xtrender is green and increased for 2 bars → EXIT SHORT".
These use `alertcondition` for easy setup.
### Additional Notes
- **Customization**: Inputs allow tweaking EMA lengths, timeframe, exit level, and direction. Best for higher TFs like 4D to capture multi-day reversals.
- **Risk Management**: Relies on equity percentage sizing; no built-in stops beyond oscillator exits. Users should backtest for drawdowns.
- **Limitations**: Single-timeframe focus may miss broader trends; no volume or volatility filters. Assumes chart TF is lower than "4D" for accurate security requests.
- **Performance**: Suited for ranging or reversing markets where momentum shifts are frequent. In strong trends, it might enter/exit prematurely.
This strategy provides a simple, momentum-based reversal system, ideal for beginners or as a building block for more complex setups.
Mario vr SIT MC Utilizar en el gráfico
4
1
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🧠 Market Structure Pro System – MVR
Market Structure Pro System – MVR is an advanced trading strategy designed to detect key reversal and trend-break zones with high precision.
It combines multiple professional tools within a single algorithm — integrating market structure, dynamic channels, volatility filters, and trend confirmations — making it ideal for scalping and swing trading across different markets (Forex, indices, cryptocurrencies, or stocks).
⚙️ How it works
The algorithm performs a complete structural analysis of the market through several technical layers:
🔹 1. Price Structure (BOS, Supply & Demand)
The system automatically detects:
Order Blocks
Supply and Demand Zones
Break of Structure (BOS) to identify market structure shifts
This allows traders to recognize where price is likely to react or break a trend, anticipating major market movements.
🔹 2. Keltner Channels and Linear Regression
The strategy uses multiple Keltner Channels with different settings to measure volatility expansion and contraction.
In combination, a dynamic linear regression line shows the overall market direction, helping confirm whether price is trending or ranging.
🔹 3. Volatility and Trend Filters
It integrates several complementary systems:
ATR (Average True Range): measures the strength and volatility of price movement.
PSAR (Parabolic SAR): identifies potential trend reversals.
Supertrend: acts as the main trend filter and confirmation tool.
These filters work together to avoid false signals in ranging or low-volatility conditions.
🔹 4. Swing Highs / Lows and Dynamic Lines
The indicator also marks swing high and low points, helping visualize dynamic support and resistance levels and potential price reversal areas.
📈 Signal Interpretation
BUY signals:
Occur when price breaks a demand zone or bearish structure, while trend filters (Supertrend / PSAR) confirm bullish direction.
SELL signals:
Trigger when price breaks a supply zone or bullish structure, with bearish confirmation from the trend filters.
These conditions can be further validated by visual confirmations from the Keltner Channel or a color change in the linear regression.
Script protegido
Este script se publica como código cerrado. Sin embargo, puede utilizarlo libremente y sin limitaciones: obtenga más información aquí.
mariovr_usd
Exención de responsabilidad
La información y las publicaciones que ofrecemos, no implican ni constituyen un asesoramiento financiero, ni de inversión, trading o cualquier otro tipo de consejo o recomendación emitida o respaldada por TradingView. Puede obtener información adicional en las Condiciones de uso.
1 comentario
AI-JX Strategy### 🤖 Core Features
AI-JX v3.3 is an AI-powered comprehensive trading strategy system developed with PineScript v6, integrating multiple advanced technical analysis tools and machine learning algorithms.
### 📊 Main Functional Modules 1. AI Learning System
- Adaptive Parameter Optimization : Automatically learns and adjusts trading parameters
- Three Strategy Modes : Conservative (ranging markets), Aggressive (trending markets), Balanced (universal)
- Dynamic Weight Adjustment : Intelligently allocates weights to different strategies based on market conditions
- Learning Memory Mechanism : Records historical trading data for continuous strategy optimization 2. Technical Indicator System
- SuperTrend Indicator : ATR-based trend following system
- Heikin Ashi Smoothing : Reduces market noise for clearer trend signals
- Standard Deviation Channels : Multi-level support and resistance analysis
- Trend Distribution Profile : Visualizes price distribution and trend strength
- Multi-Timeframe Analysis : Comprehensive analysis across 5m, 15m, and 1h timeframes 3. Intelligent Signal Generation
- Traditional Signals : Classic buy/sell signals based on SuperTrend
- AI Smart Signals : Comprehensive scoring system combining RSI, MACD, and ATR
- False Breakout Detection : Identifies and filters fake breakout signals
- Price Confirmation Mechanism : Ensures signal validity and reliability 4. Risk Management System
- Dynamic Stop Loss/Take Profit : Long 3% TP/1.5% SL, Short 2:1 risk-reward ratio
- Slippage Monitoring : Real-time market slippage risk assessment
- Volatility Filtering : Adjusts trading strategy based on ATR
- Position Management : Smart capital allocation and risk control 5. Visualization Panels
- Statistics Panel : Displays key data like trade count, win rate, current strategy
- AI Learning Panel : Shows strategy weights and learning progress
- Prediction Panel : Real-time AI analysis and trading recommendations
- Chart Markers : Clear buy/sell signals and trend line displays 6. Alert System
- Multiple Alert Types : Buy, sell, take profit, and stop loss notifications
- Personalized Messages : Fun "WangWang" themed alert messages
- Real-time Notifications : Precise alerts with maximum one per bar frequency
### 🎯 Key Advantages
- AI-Driven : Machine learning optimization for better performance
- Multi-Strategy : Adapts to different market conditions automatically
- Risk-Controlled : Comprehensive risk management with dynamic adjustments
- User-Friendly : Intuitive interface with detailed visualization panels
- Highly Customizable : Extensive parameter settings for different trading styles
TTE Elite Market SignalsWelcome to TTE Elite Market Signals Your very own personal trading assistant
Trading today demands more than intuition—it requires exclusive access to elite-level market intelligence and the discipline to act on high-probability signals. Every professional trader seeks that decisive advantage: the clarity and confidence that separates consistent profitability from market uncertainty. The financial markets show no mercy, demanding precision, logic, and strategy grounded in institutional-grade analysis.
Human judgment, while powerful, can be compromised by fatigue and emotion, leading to costly trading errors. This is precisely where TTE Elite Market Signals excels. Our sophisticated platform combines proven trading methodologies with advanced signal generation technology, delivering market intelligence that empowers you to identify optimal entry and exit opportunities while maintaining complete control over your trading decisions.
Revolutionary Signal Intelligence
TTE Elite Market Signals features adaptive learning technology that evolves with market conditions. It continuously refines its analysis, helping you identify higher-probability setups while providing the market intelligence needed for superior risk management.
Elite Analysis Modes
Our platform adapts its signal generation to match market personalities:
- Institutional Flow Mode (MM-hybrid): Identifies manipulation patterns and tracks smart money movement with exclusive institutional-grade precision
- Momentum Adaptive Mode: Rapidly adjusts analysis when volatility and momentum shift
- Conservative Precision Mode: Steady, risk-conscious signals for consistent performance
- Adaptive Intelligence Mode: Self-refining system that enhances signal quality over time from past trades (long term of use)
Comprehensive Signal Intelligence
TTE Elite Market Signals integrates multiple sophisticated analytical systems:
- Volume Profile analysis for exclusive institutional-level market insights
- Pattern recognition enhanced by machine learning algorithms
- Intelligent exit timing that identifies optimal profit-taking opportunities
- Protection against market manipulation tactics
- Position sizing guidance that scales with trading success
- Fibonacci based reversal logic
Perfect for Your Trading Evolution
Experienced traders appreciate our sophisticated market intelligence and institutional-grade analytics that provide genuine competitive advantages.
Developing traders benefit from intelligent signal analysis that handles complex market calculations while teaching professional-level market interpretation and risk management principles via visuals on chart and descriptive panel.
All timeframes supported—from scalping to swing trading, TTE Elite Market Signals adapts to your preferred trading style via several user input selections.
Two Elite Service Modes
1. Signal Intelligence Mode: Real-time market signals with AI-driven analysis and detailed trade rationale
2. Alert Precision Mode: High-probability setup notifications with comprehensive market context and risk parameters
The Exclusive Learning Advantage
What makes TTE Elite Market Signals exceptional: it maintains a comprehensive trade memory and identifies the highest-probability signals, adapts to changing volatility patterns, and continuously refines(does not repaint) its analysis to enhance your profit potential and trading accuracy.
Built-in Professional Protection
- Advanced manipulation detection safeguards against institutional market maker(MM) tactics
- Intelligent risk assessment adjusts signal confidence based on market conditions
- Progressive scaling guidance maximizes winners while minimizing losses(educational)
- Comprehensive oversight with customizable risk parameters
Experience the Elite Difference
TTE gives you visuals on the chart of past trades and live metrics results to see what actually work and what fails, to minimize unrealistic expectations. Just sit back and watch sophisticated algorithms work tirelessly on your behalf, identifying opportunities that others miss and alerting you as signals are generated. Transforming the stressful, emotional battlefield of trading into a systematic analytical approach.
Let the System Do the Heavy Lifting
While others struggle with analysis paralysis and emotional decision-making, you'll have access to signals that have already processed hundreds of data points, identified institutional patterns, and calculated optimal risk-reward scenarios for a far less stressful trading experience.
What Elite Traders Should Know
TTE Elite Market Signals represents cutting-edge signal generation technology designed for serious market education and skill development, but it is not a black box, nor perfect for all markets. It must be adjusted to yield optimal results. While our advanced capabilities and institutional-grade features provide significant analytical advantages, trading success requires discipline and proper execution. Markets evolve, and optimal results demand understanding of signal context.
Success with TTE Elite Market Signals comes from mastering our analytical modes and using the proper entry types such as breakout entry, machine learning(ML) entry etc, utilizing and selecting the most effective risk control to optimize it, and maintaining disciplined risk management.
Join the Elite Trading Revolution
This isn't just another signal service—it equips you with the tools to do proper market analysis displaying price movement and volume profile designed for serious traders who understand that consistent profitability comes from discipline, superior market intelligence and proper interpretation, not luck.
Trade smart, stay profitable, and achieve trading excellence.
Best TTE Settings
Trade Entry Types:
1st Best Breakout Entry(out perform all others when used alone)
2nd Best ML Entry by itself or + Pattern Entry Combined
Risk Management:
ATR Multiplier 2
Enable Master Size Control
Master Size Mode
Max Risk Per Trade % 2.5
Max Multiplier Cap 1.5
Enable Growth Scaling
Growth Scaling Mode-set to Time Based or Performance
Risk Management System- set to Hybrid
Enable ML System
ML Mode-set to Auto or Quantum Learning
ML Application Strategy-set to Universal All Entries
Enable Trend Continuation
Mode- Set to Standard
Independent Entry-stays unchecked(off)
Best Performing Instruments on TTE (will update list as more are adjusted and tested)
NVDA
AMD
AMZN
TSLA
SPY
QQQ
PLTR
Setup: Smooth Gaussian + Adaptive Supertrend (Manual Vol)Overview
This strategy combines two powerful trend-based tools originally developed by Algo Alpha: the Smooth Gaussian Trend (simulated) and the Adaptive Supertrend. The objective is to capture sustained bullish movements in periods of controlled volatility by filtering for high-probability entries.
Entry Logic
Long Entry Conditions:
The closing price is above the Smooth Gaussian Trend line (with length = 75), and
The volatility setting from the Adaptive Supertrend is manually defined as either 2 or 3
Exit Condition:
The closing price falls below the Smooth Gaussian Trend line
This script uses a simulated version of the Gaussian Trend line via double-smoothed SMA, as the original Algo Alpha indicator is protected and cannot be accessed directly in code.
Features
Plots entry and exit signals directly on the chart
Manual toggle to enable or disable the volatility filter
Lightweight design to allow flexible backtesting even without access to proprietary indicators
Important Note
This strategy does not connect to the actual Adaptive Supertrend from Algo Alpha. Users must manually input the volatility level based on what they observe on the chart when the original indicator is also applied. The Smooth Gaussian Trend is approximated and may differ slightly from the original.
Suggested Use
Recommended timeframes: 1H, 4H, or Daily
Best used alongside the original indicators displayed on the chart
Consider incorporating additional structure, momentum, or volume filters to enhance performance
If you have suggestions or would like to contribute improvements, feel free to reach out or fork the script.
Long-Leg Doji Breakout StrategyThe Long-Leg Doji Breakout Strategy is a sophisticated technical analysis approach that capitalizes on market psychology and price action patterns.
Core Concept: The strategy identifies Long-Leg Doji candlestick patterns, which represent periods of extreme market indecision where buyers and sellers are in equilibrium. These patterns often precede significant price movements as the market resolves this indecision.
Pattern Recognition: The algorithm uses strict mathematical criteria to identify authentic Long-Leg Doji patterns. It requires the candle body to be extremely small (≤0.1% of the total range) while having long wicks on both sides (at least 2x the body size). An ATR filter ensures the pattern is significant relative to recent volatility.
Trading Logic: Once a Long-Leg Doji is identified, the strategy enters a "waiting mode," monitoring for a breakout above the doji's high (long signal) or below its low (short signal). This confirmation approach reduces false signals by ensuring the market has chosen a direction.
Risk Management: The strategy allocates 10% of equity per trade and uses a simple moving average crossover for exits. Visual indicators help traders understand the pattern identification and trade execution process.
Psychological Foundation: The strategy exploits the natural market cycle where uncertainty (represented by the doji) gives way to conviction (the breakout), creating high-probability trading opportunities.
The strength of this approach lies in its ability to identify moments when market sentiment shifts from confusion to clarity, providing traders with well-defined entry and exit points while maintaining proper risk management protocols.
How It Works
The strategy operates on a simple yet powerful principle: identify periods of market indecision, then trade the subsequent breakout when the market chooses direction.
Step 1: Pattern Detection
The algorithm scans for Long-Leg Doji candles, which have three key characteristics:
Tiny body (open and close prices nearly equal)
Long upper wick (significant rejection of higher prices)
Long lower wick (significant rejection of lower prices)
Step 2: Confirmation Wait
Once a doji is detected, the strategy doesn't immediately trade. Instead, it marks the high and low of that candle and waits for a definitive breakout.
Step 3: Trade Execution
Long Entry: When price closes above the doji's high
Short Entry: When price closes below the doji's low
Step 4: Exit Strategy
Positions are closed when price crosses back through a 20-period moving average, indicating potential trend reversal.
Market Psychology Behind It
A Long-Leg Doji represents a battlefield between bulls and bears that ends in a stalemate. The long wicks show that both sides tried to push price in their favor but failed. This creates a coiled spring effect - when one side finally gains control, the move can be explosive as trapped traders rush to exit and momentum traders jump aboard.
Key Parameters
Doji Body Threshold (0.1%): Ensures the body is truly small relative to the candle's range
Wick Ratio (2.0): Both wicks must be at least twice the body size
ATR Filter: Uses Average True Range to ensure the pattern is significant in current market conditions
Position Size: 10% of equity per trade for balanced risk management
Pros:
High Probability Setups: Doji patterns at key levels often lead to significant moves as they represent genuine shifts in market sentiment.
Clear Rules: Objective criteria for entry and exit eliminate emotional decision-making and provide consistent execution.
Risk Management: Built-in position sizing and exit rules help protect capital during losing trades.
Market Neutral: Works equally well for long and short positions, adapting to market direction rather than fighting it.
Visual Confirmation: The strategy provides clear visual cues, making it easy to understand when patterns are forming and trades are triggered.
Cons:
False Breakouts: In choppy or ranging markets, price may break the doji levels only to quickly reverse, creating whipsaws.
Patience Required: Traders must wait for both pattern formation and breakout confirmation, which can test discipline during active market periods.
Simple Exit Logic: The moving average exit may be too simplistic, potentially cutting profits short during strong trends or holding losers too long during reversals.
Volatility Dependent: The strategy relies on sufficient volatility to create meaningful doji patterns - it may underperform in extremely quiet markets.
Lagging Entries: Waiting for breakout confirmation means missing the very beginning of moves, reducing potential profit margins.
Best Market Conditions
The strategy performs optimally during periods of moderate volatility when markets are making genuine directional decisions rather than just random noise. It works particularly well around key support/resistance levels where the market's indecision is most meaningful.
Optimization Considerations
Consider combining with additional confluence factors like volume analysis, support/resistance levels, or other technical indicators to improve signal quality. The exit strategy could also be enhanced with trailing stops or multiple profit targets to better capture extended moves while protecting gains.
Best for Index option,
Enjoy !!
