Stealth Trigger X🔰 Stealth Trigger X — Smart Divergence & Breakout Strategy with Trend Weakness Exit
Stealth Trigger X is a precision-engineered, non-repainting strategy designed for traders who rely on high-conviction breakouts and trend confirmation. Rather than relying on lagging or oversimplified signals, this strategy fuses divergence logic, volatility detection, volume filtering, and slope-based trend validation into one clean system — making it both responsive and reliable.
📌 Core Components (How It Works):
1. ZLEMA (Zero-Lag Exponential Moving Average):
Used as the primary trend baseline. Unlike a standard EMA, ZLEMA compensates for lag by using a double-smoothing technique that allows the strategy to detect trend direction changes sooner — especially useful in crypto and fast-moving markets.
2. Gradient Filter (Slope of ZLEMA):
Rather than waiting for price to cross a moving average, the strategy measures the slope of the ZLEMA itself. Positive slope = uptrend, negative slope = downtrend. This gives us early trend validation and exit signals based on weakening momentum.
3. Vortex Indicator (Directional Volatility):
A diff-based implementation of the Vortex Indicator is used to validate whether volatility is expanding in favor of the trend. This prevents false entries during indecision phases or low-momentum conditions.
4. White Line Bias Filter (Structural Trend):
The strategy calculates the midpoint of the highest high and lowest low over a user-defined period. This “White Line” serves as a structural trend bias, ensuring entries align with the broader context — not just momentary momentum.
5. Volume Spike Confirmation:
To avoid manipulation and choppy conditions, the strategy confirms breakouts only when the current bar’s volume exceeds the median volume of recent candles by a set multiplier. This filters out noise and ensures only high-conviction moves trigger entries.
6. Breakout with Divergence Timing:
A hybrid logic checks for price breaking previous range highs/lows (breakouts), combined with simulated divergence behavior based on RSI-like momentum. This helps align entry timing with areas where price is likely to accelerate.
⚙️ Trade Management Logic:
Entry Conditions:
Triggered when all conditions align: ZLEMA slope, Vortex confirmation, White Line bias, volume spike, and divergence-based breakout.
Take Profits:
TP1: 50% of position is closed using a limit order
TP2: Remaining 50% closed with another limit order
This split exit approach lets profits run while locking in gains early.
Exits on Trend Weakness:
If trend conditions weaken (slope flip or vortex flip), the position is exited before a full reversal occurs — helping protect capital during exhaustion phases.
Reentry Delay:
Enforces a 1-bar cooldown between exit and new entries to avoid “ping-pong” signals and maintain clean backtest results.
📊 Real-Time Dashboard (On-Chart):
Displays critical stats including:
Current position (Long, Short, or Flat)
Entry price
TP1 and TP2 hit status
Win rate (%)
Profit factor
Bars since entry
This makes live trading or visual backtesting easy to interpret and track.
✅ Key Facts:
Non-Repainting: All signals are calculated using confirmed bar data only. No future bars or security() functions are used.
Original Logic: This is not a generic mashup. Each component (ZLEMA slope, vortex diff, breakout divergence, volume spike filtering, White Line structure) is optimized to work in tandem.
Best Timeframes: 1H – 4H
Markets: Crypto, Forex, Indices — any market with trending behavior and measurable volume
⚠️ Disclaimer:
This strategy is for educational purposes only. It is not financial advice or a recommendation to trade. Past performance does not guarantee future results. Always trade with proper risk management and backtest strategies before live deployment.
🧠 Summary:
Stealth Trigger X is built for traders who want:
Precision entries
Early trend exits
Reliable backtest integrity
Clean logic with no repainting
It is especially effective in breakout environments where volume and momentum align — and excels at avoiding weak or manipulated trends.
Cerca negli script per "momentum"
Multi-EMA Crossover StrategyMulti-EMA Crossover Strategy
This strategy uses multiple exponential moving average (EMA) crossovers to identify bullish trends and execute long trades. The approach involves progressively stronger signals as different EMA pairs cross, indicating increasing bullish momentum. Each crossover triggers a long entry, and the intensity of bullish sentiment is reflected in the color of the bars on the chart. Conversely, bearish trends are represented by red bars.
Strategy Logic:
First Long Entry: When the 1-day EMA crosses above the 5-day EMA, it signals initial bullish momentum.
Second Long Entry: When the 3-day EMA crosses above the 10-day EMA, it confirms stronger bullish sentiment.
Third Long Entry: When the 5-day EMA crosses above the 20-day EMA, it indicates further trend strength.
Fourth Long Entry: When the 10-day EMA crosses above the 40-day EMA, it suggests robust long-term bullish momentum.
The bar colors reflect these conditions:
More blue bars indicate stronger bullish sentiment as more short-term EMAs are above their longer-term counterparts.
Red bars represent bearish conditions when short-term EMAs are below longer-term ones.
Example: Bitcoin Trading on a Daily Timeframe
Bullish Scenario:
Imagine Bitcoin is trading at $30,000 on March 31, 2025:
First Signal: The 1-day EMA crosses above the 5-day EMA at $30,000. This suggests initial upward momentum, prompting a small long entry.
Second Signal: A few days later, the 3-day EMA crosses above the 10-day EMA at $31,000. This confirms strengthening bullish sentiment; another long position is added.
Third Signal: The 5-day EMA crosses above the 20-day EMA at $32,500, indicating further upward trend development; a third long entry is executed.
Fourth Signal: Finally, the 10-day EMA crosses above the 40-day EMA at $34,000. This signals robust long-term bullish momentum; a fourth long position is entered.
Bearish Scenario:
Suppose Bitcoin reverses from $34,000 to $28,000:
The 1-day EMA crosses below the 5-day EMA at $33,500.
The 3-day EMA dips below the 10-day EMA at $32,000.
The 5-day EMA falls below the 20-day EMA at $30,000.
The final bearish signal occurs when the 10-day EMA drops below the 40-day EMA at $28,000.
The bars turn increasingly red as bearish conditions strengthen.
Advantages of This Strategy:
Progressive Confirmation: Multiple crossovers provide layered confirmation of trend strength.
Visual Feedback: Bar colors help traders quickly assess market sentiment and adjust positions accordingly.
Flexibility: Suitable for trending markets like Bitcoin during strong rallies or downturns.
Limitations:
Lagging Signals: EMAs are lagging indicators and may react slowly to sudden price changes.
False Breakouts: Crossovers in choppy markets can lead to whipsaws or false signals.
This strategy works best in trending markets and should be combined with additional risk management techniques, e.g., stop loss or optimal position sizes (Kelly Criterion).
Kinetik Model [NantzOS]Description:
The Kinetik Model is a strategy that reinterprets the traditional stochastic oscillator to take advantage of momentum instead of the standard overbought/oversold reversal approach. Primarily operating upon zero line crosses, what you observe is the difference between the K and D plots. the first unique feature about this system is that the stochastic calculation has been made "boundless" in order to more accurately gauge the rate of momentum. It doesn't consolidate in upper or lower channels. The second feature is the dataset typically known as %K smoothing is set to a fixed value, the %K length and %D smoothing serve as a customizable length and signal. The third is that it takes trades based on the difference between the fixed %K and customizable %D, a reminder that is your oscillator display. This oscillator versus the traditional stochastic is comparable to the MACD histogram versus the MACD line plots. The fourth feature is that the user dynamically tests the upper and lower thresholds, displayed with a color background on the oscillator, to act as a filtration method. The system won't take shorts if momentum is above the upper threshold and won't take longs if it's performing below the lower threshold. Lastly, this system uses a trailing stop exit strategy, which can be deactivated, and the option to test long only.
Features Summarized:
A reimagined stochastic that operates without fixed boundries, offering flexibility for properly observing momentum.
High and low levels act as extreme zones for highlighting strong trends.
Users can modify data length, signal input, and thresholds from the settings to suit their preferred asset and time frame.
A built-in optional stop-loss mechanism with adjustable sensitivity, enabling tighter or more relaxed risk management.
Includes and optional long only setting and candle coloring with signals.
How to Use:
Navigate to the indicator tab in TradingView to search and apply the Kinetik Model.
Access the settings icon on the indicator to navigate the style and settings:
Length: Modifies the amount of data used to calculate the oscillator.
Signal: Further calibrates the sensitivity of the final plot.
High/Low Thresholds: A single filtration method for defining extreme zones of momentum bias, which determines entry/exits along with the zero line crosses.
Remaining Settings: Customize stop loss calibration along with optional features and styling choice.
Oscillators have been a staple in financial analysis since the mid-20th century, with tools like the RSI, MACD, and Stochastic helping gauge overbought and oversold conditions. What makes the latter unique is that the stochastic utilizes highs and lows as opposed to various EMA rates of change. Kinetik's unique boundless stochastic calculation and K/D difference plotting are the heart of this strategy.
EMA RSI Trend Reversal Ver.1Overview:
The EMA RSI Trend Reversal indicator combines the power of two well-known technical indicators—Exponential Moving Averages (EMAs) and the Relative Strength Index (RSI)—to identify potential trend reversal points in the market. The strategy looks for key crossovers between the fast and slow EMAs, and uses the RSI to confirm the strength of the trend. This combination helps to avoid false signals during sideways market conditions.
How It Works:
Buy Signal:
The Fast EMA (9) crosses above the Slow EMA (21), indicating a potential shift from a downtrend to an uptrend.
The RSI is above 50, confirming strong bullish momentum.
Visual Signal: A green arrow below the price bar and a Buy label are plotted on the chart.
Sell Signal:
The Fast EMA (9) crosses below the Slow EMA (21), indicating a potential shift from an uptrend to a downtrend.
The RSI is below 50, confirming weak or bearish momentum.
Visual Signal: A red arrow above the price bar and a Sell label are plotted on the chart.
Key Features:
EMA Crossovers: The Fast EMA crossing above the Slow EMA signals potential buying opportunities, while the Fast EMA crossing below the Slow EMA signals potential selling opportunities.
RSI Confirmation: The RSI helps confirm trend strength—values above 50 indicate bullish momentum, while values below 50 indicate bearish momentum.
Visual Cues: The strategy uses green arrows and red arrows along with Buy and Sell labels for clear visual signals of when to enter or exit trades.
Signal Interpretation:
Green Arrow / Buy Label: The Fast EMA (9) has crossed above the Slow EMA (21), and the RSI is above 50. This is a signal to buy or enter a long position.
Red Arrow / Sell Label: The Fast EMA (9) has crossed below the Slow EMA (21), and the RSI is below 50. This is a signal to sell or exit the long position.
Strategy Settings:
Fast EMA Length: Set to 9 (this determines how sensitive the fast EMA is to recent price movements).
Slow EMA Length: Set to 21 (this smooths out price movements to identify the broader trend).
RSI Length: Set to 14 (default setting to track momentum strength).
RSI Level: Set to 50 (used to confirm the strength of the trend—above 50 for buy signals, below 50 for sell signals).
Risk Management (Optional):
Use take profit and stop loss based on your preferred risk-to-reward ratio. For example, you can set a 2:1 risk-to-reward ratio (2x take profit for every 1x stop loss).
Backtesting and Optimization:
Backtest the strategy on TradingView by opening the Strategy Tester tab. This will allow you to see how the strategy would have performed on historical data.
Optimization: Adjust the EMA lengths, RSI period, and risk-to-reward settings based on your asset and time frame.
Limitations:
False Signals in Sideways Markets: Like any trend-following strategy, this indicator may generate false signals during periods of low volatility or sideways movement.
Not Suitable for All Market Conditions: This indicator performs best in trending markets. It may underperform in choppy or range-bound markets.
Strategy Example:
XRP/USD Example:
If you're trading XRP/USD and the Fast EMA (9) crosses above the Slow EMA (21), while the RSI is above 50, the indicator will signal a Buy.
Conversely, if the Fast EMA (9) crosses below the Slow EMA (21), and the RSI is below 50, the indicator will signal a Sell.
Bitcoin (BTC/USD):
On the BTC/USD chart, when the indicator shows a green arrow and a Buy label, it’s signaling a potential long entry. Similarly, a red arrow and Sell label indicate a short entry or exit from a previous long position.
Summary:
The EMA RSI Trend Reversal Indicator helps traders identify potential trend reversals with clear buy and sell signals based on the EMA crossovers and RSI confirmations. By using green arrows and red arrows, along with Buy and Sell labels, this strategy offers easy-to-understand visual signals for entering and exiting trades. Combine this with effective risk management and backtesting to optimize your trading performance.
VIDYA ProTrend Multi-Tier ProfitHello! This time is about a trend-following system.
VIDYA is quite an interesting indicator that adjusts dynamically to market volatility, making it more responsive to price changes compared to traditional moving averages. Balancing adaptability and precision, especially with the more aggressive short trade settings, challenged me to fine-tune the strategy for a variety of market conditions.
█ Introduction and How it is Different
The "VIDYA ProTrend Multi-Tier Profit" strategy is a trend-following system that combines the VIDYA (Variable Index Dynamic Average) indicator with Bollinger Bands and a multi-step take-profit mechanism.
Unlike traditional trend strategies, this system allows for more adaptive profit-taking, adjusting for long and short positions through distinct ATR-based and percentage-based targets. The innovation lies in its dynamic multi-tier approach to profit-taking, especially for short trades, where more aggressive percentages are applied using a multiplier. This flexibility helps adapt to various market conditions by optimizing trade management and profit allocation based on market volatility and trend strength.
BTCUSD 6hr performance
█ Strategy, How it Works: Detailed Explanation
The core of the "VIDYA ProTrend Multi-Tier Profit" strategy lies in the dual VIDYA indicators (fast and slow) that analyze price trends while accounting for market volatility. These indicators work alongside Bollinger Bands to filter trade entries and exits.
🔶 VIDYA Calculation
The VIDYA indicator is calculated using the following formula:
Smoothing factor (𝛼):
alpha = 2 / (Length + 1)
VIDYA formula:
VIDYA(t) = alpha * k * Price(t) + (1 - alpha * k) * VIDYA(t-1)
Where:
k = |Chande Momentum Oscillator (MO)| / 100
🔶 Bollinger Bands as a Volatility Filter
Bollinger Bands are calculated using a rolling mean and standard deviation of price over a specified period:
Upper Band:
BB_upper = MA + (K * stddev)
Lower Band:
BB_lower = MA - (K * stddev)
Where:
MA is the moving average,
K is the multiplier (typically 2), and
stddev is the standard deviation of price over the Bollinger Bands length.
These bands serve as volatility filters to identify potential overbought or oversold conditions, aiding in the entry and exit logic.
🔶 Slope Calculation for VIDYA
The slopes of both fast and slow VIDYAs are computed to assess the momentum and direction of the trend. The slope for a given VIDYA over its length is:
Slope = (VIDYA(t) - VIDYA(t-n)) / n
Where:
n is the length of the lookback period. Positive slope indicates bullish momentum, while negative slope signals bearish momentum.
LOCAL picture
🔶 Entry and Exit Conditions
- Long Entry: Occurs when the price moves above the slow VIDYA and the fast VIDYA is trending upward. Bollinger Bands confirm the signal when the price crosses the upper band, indicating bullish strength.
- Short Entry: Happens when the price drops below the slow VIDYA and the fast VIDYA trends downward. The signal is confirmed when the price crosses the lower Bollinger Band, showing bearish momentum.
- Exit: Based on VIDYA slopes flattening or reversing, or when the price hits specific ATR or percentage-based profit targets.
🔶 Multi-Step Take Profit Mechanism
The strategy incorporates three levels of take profit for both long and short trades:
- ATR-based Take Profit: Each step applies a multiple of the ATR (Average True Range) to the entry price to define the exit point.
The first level of take profit (long):
TP_ATR1_long = Entry Price + (2.618 * ATR)
etc.
█ Trade Direction
The strategy offers flexibility in defining the trading direction:
- Long: Only long trades are considered based on the criteria for upward trends.
- Short: Only short trades are initiated in bearish trends.
- Both: The strategy can take both long and short trades depending on the market conditions.
█ Usage
To use the strategy effectively:
- Adjust the VIDYA lengths (fast and slow) based on your preference for trend sensitivity.
- Use Bollinger Bands as a filter for identifying potential breakout or reversal scenarios.
- Enable the multi-step take profit feature to manage positions dynamically, allowing for partial exits as the price reaches specified ATR or percentage levels.
- Leverage the short trade multiplier for more aggressive take profit levels in bearish markets.
This strategy can be applied to different asset classes, including equities, forex, and cryptocurrencies. Adjust the input parameters to suit the volatility and characteristics of the asset being traded.
█ Default Settings
The default settings for this strategy have been designed for moderate to trending markets:
- Fast VIDYA Length (10): A shorter length for quick responsiveness to price changes. Increasing this length will reduce noise but may delay signals.
- Slow VIDYA Length (30): The slow VIDYA is set longer to capture broader market trends. Shortening this value will make the system more reactive to smaller price swings.
- Minimum Slope Threshold (0.05): This threshold helps filter out weak trends. Lowering the threshold will result in more trades, while raising it will restrict trades to stronger trends.
Multi-Step Take Profit Settings
- ATR Multipliers (2.618, 5.0, 10.0): These values define how far the price should move before taking profit. Larger multipliers widen the profit-taking levels, aiming for larger trend moves. In higher volatility markets, these values might be adjusted downwards.
- Percentage Levels (3%, 8%, 17%): These percentage levels define how much the price must move before taking profit. Increasing the percentages will capture larger moves, while smaller percentages offer quicker exits.
- Short TP Multiplier (1.5): This multiplier applies more aggressive take profit levels for short trades. Adjust this value based on the aggressiveness of your short trade management.
Each of these settings directly impacts the performance and risk profile of the strategy. Shorter VIDYA lengths and lower slope thresholds will generate more trades but may result in more whipsaws. Higher ATR multipliers or percentage levels can delay profit-taking, aiming for larger trends but risking partial gains if the trend reverses too early.
RMI Trend Sync - Strategy [presentTrading]█ Introduction and How It Is Different
The "RMI Trend Sync - Strategy " combines the strength of the Relative Momentum Index (RMI) with the dynamic nature of the Supertrend indicator. This strategy diverges from traditional methodologies by incorporating a dual analytical framework, leveraging both momentum and trend indicators to offer a more holistic market perspective. The integration of the RMI provides an enhanced understanding of market momentum, while the Super Trend indicator offers clear insights into the end of market trends, making this strategy particularly effective in diverse market conditions.
BTC 4h long/short performance
█ Strategy: How It Works - Detailed Explanation
- Understanding the Relative Momentum Index (RMI)
The Relative Momentum Index (RMI) is an adaptation of the traditional Relative Strength Index (RSI), designed to measure the momentum of price movements over a specified period. While RSI focuses on the speed and change of price movements, RMI incorporates the direction and magnitude of those movements, offering a more nuanced view of market momentum.
- Principle of RMI
Calculation Method: RMI is calculated by first determining the average gain and average loss over a given period (Length). It differs from RSI in that it uses the price change (close-to-close) rather than absolute gains or losses. The average gain is divided by the average loss, and this ratio is then normalized to fit within a 0-100 scale.
- Momentum Analysis in the Strategy
Thresholds for Decision Making: The strategy uses predetermined thresholds (pmom for positive momentum and nmom for negative momentum) to trigger trading decisions. When RMI crosses above the positive threshold and other conditions align (e.g., a bullish trend), it signals a potential long entry. Similarly, crossing below the negative threshold in a bearish trend may trigger a short entry.
- Super Trend and Trend Analysis
The Super Trend indicator is calculated based on a higher time frame, providing a broader view of the market trend. This indicator uses the Average True Range (ATR) to adapt to market volatility, making it an effective tool for identifying trend reversals.
The strategy employs a Volume Weighted Moving Average (VWMA) alongside the Super Trend, enhancing its capability to identify significant trend shifts.
ETH 4hr long/short performance
█ Trade Direction
The strategy offers flexibility in selecting the trading direction: long, short, or both. This versatility allows traders to adapt to their market outlook and risk tolerance, whether looking to capitalize on bullish trends, bearish trends, or a combination of both.
█ Usage
To effectively use the "RMI Trend Sync" strategy, traders should first set their preferred trading direction and adjust the RMI and Super Trend parameters according to their risk appetite and trading goals.
The strategy is designed to adapt to various market conditions, making it suitable for different asset classes and time frames.
█ Default Settings
RMI Settings: Length: 21, Positive Momentum Threshold: 70, Negative Momentum Threshold: 30
Super Trend Settings: Length: 10, Higher Time Frame: 480 minutes, Super Trend Factor: 3.5, MA Source: WMA
Visual Settings: Display Range MA: True, Bullish Color: #00bcd4, Bearish Color: #ff5252
Additional Settings: Band Length: 30, RWMA Length: 20
Easy Trade Pro [Buy and Sell Strategy + Backtesting System]Hello Traders,
Easy Trade Pro is a comprehensive tool that combines multiple technical indicators into a single customizable one. This tool is the culmination of an extensive trading career, it is designed to help traders navigate the markets in any timeframe and financial asset, like Equities, Futures, Crypto, Forex and Commodities.
Before we deep dive into the comprehensive guide on what Easy Trade Pro is, let's kick off by showcasing the strategy used in this example. Please note, we have adopted an extremely conservative approach strictly following the Tradingview House Rules, which you can review here: www.tradingview.com
The backtest strategy parameters:
Currency pair: EUR USD
Timeframe: 15-min chart
Market: Spot, no leverage
Broker: FXCM
Trading range: 2022-09-01 07:30 — 2023-06-26 20:00
Backtesting range: 2022-08-31 23:00 — 2023-06-26 20:00
Initial Capital: $10,000
Buy Order Size: 20% of the capital, $2,000
Stop Loss: 0.50%
Sell orders: Four different take profits where we unload the position by 25% each time
Broker Fees: Commission set at 0.08$
Slippage: 10 ticks
Understanding FXCM Commissions and Setting Realistic Slippage for EUR/USD Spot Trading:
◉I would like to provide some clarity on the commission structure and slippage setting used in the study for trading the EUR/USD pair on the FXCM spot market. Based on the information available, FXCM charges a commission of $4.00 per standard lot (100,000) on both sides of the trade (meaning at open and close) for the EUR/USD pair. Since the study involve an order size of $2,000 USD, which is equivalent to 0.02 lots, the commission fee for one side of the trade (either buying or selling) would be calculated as $4.00 multiplied by 0.02, which is $0.08. This means that for each individual trade, whether it be a buy or sell, the commission fee would be $0.08.
◉As for slippage, it is crucial to account for the inherent uncertainty in the execution price due to market fluctuations. In the forex market, the EUR/USD pair is quoted with a precision of five decimal places, with the smallest price change being a "pipette" (0.00001). Given that slippage can vary based on market conditions, it is considered fair practice to use a slippage of around 10 ticks under normal market conditions for the EUR/USD pair. This allows for a more realistic representation of the execution price, especially in a liquid and fast-moving market such as forex.
More detailed information about FXCM fees structure in the link below:
docs.fxcorporate.com
Enter a Trade conditions:
For our buy order, we utilize a custom buy signal called 'Bullish Reversal'. A detailed explanation of this and other buy orders can be found later in the guide, specifically in section 1).
To enhance realism in our trading strategy, we have implemented a confirmation mechanism. When utilizing the strategy tester, you have the option to input a value to determine the number of confirmation candles to consider.
For example, if you set the input to 1, the system will check if the next candle following the signal meets the criteria for confirmation. If set to 2, the system will evaluate the second candle, and so on for higher values. The confirmation is determined by comparing the closing or opening price of the selected buy signal candle with the corresponding closing price of the confirmation candle.
In this case we choose as buy signal: 'Bullish Reversal' + 2 candle of confirmation
Exit a trade conditions:
On the sell side, we exit a trade in four different types of sell orders where we take profits. Inside '', you will encounter unique labels attributed to our custom sell signals. A detailed explanation of these sell orders can be found later in the guide, specifically in section 1). We used custom order called:
1TP 'Good Sell'
2TP 'Good Sell'
3TP 'Good Sell'
4TP 'Bearish Reversal' + 4 confirmation candles
Our confirmation logic, for sell signals, is applied only to 'Bearish Reversal' signal. The confirmation is determined by comparing the closing or opening price of the selected 'Bearish Reversal' candle with the corresponding closing price of the confirmation candle. In this case, we wait for the fourth candle from the 'Bearish Reversal' signal to confirm the sell trade.
Protect your capital:
This super-conservative study involves a clear low risk, with the use of $2,000, 20% of our capital. If the stop loss of 0.5% were triggered, we lose 10$, equating to 0.10% of $10,000 - thus affecting only 0.10% of our capital.
Super Conservative Approach & Results:
With 353 closed trades, we achieved a net profit of 2.03%, or $203.34$ relative to our initial $10,000 capital, and a win rate of 73.37%.
Less Conservative Approach & Results:
We could also consider increasing our risk to 0.5% of our capital per trade. We would maintain our stop loss at 0.50%, but we would need to use all our capital to enter the market. If the stop loss of 0.5% will be triggered, we would lose 50$, equating to 0.5% of $10,000.
In this scenario, our net profit would have increased to 10.15%, equivalent to $1015.
Please be aware:
While fully automated strategies can bring considerable advantages, they are not without their cons. For one, relying solely on an automated system may not take into account the potential confluence of other strategies or indicators, such as the significance of support and resistance zones. These elements often require a more nuanced, human understanding of the markets and cannot always be perfectly replicated by an algorithm.
Additionally, it's essential to remember that a significant percentage of traders are not consistently profitable. As such, prudent risk management, a conservative approach, and acceptance of a reasonable profit are crucial aspects of successful trading. While the allure of high returns can be tempting, the sustainability of your trading strategy should always take precedence. Achieving steady, reliable profits over time often outweighs the appeal of a risky, high-return strategy that could potentially lead to substantial losses.
So, while automation can be a powerful tool in your trading arsenal, it's also important to consider other strategies and factors. Always ensure you're managing your risk effectively and approaching trading with a realistic and informed perspective.
------------------------------------------------------------------------ Why Easy Trade Pro is Original? ----------------------------------------------------------------------------------
We developed Easy Trade Pro as a unique and comprehensive solution, and we decided to protect our code to preserve its originality. We invested significant time and effort into making it a realistic trading strategy simulator. The standout features that set Easy Trade Pro apart include:
☀ Versatile Stop Loss Mechanisms: Stop loss execution can be complex and often requires careful coding to work as intended. In most freely available open-source codes, stop losses are implemented using the Average True Range (ATR). ATR can be beneficial but has limitations:
☁ Lagging Indicator - Like most technical indicators, the ATR is a lagging indicator. This means it is based on past data, and so it may not accurately reflect future market volatility. If market conditions change rapidly, the ATR may not adjust quickly enough, potentially leading to suboptimal stop loss levels.
☁ No Directional Information - The ATR measures volatility, but it does not provide any indication of the direction of the trend. Therefore, it should not be used as a standalone tool for making trading decisions, but should be used in conjunction with other technical analysis tools that can provide directional cues.
☁ Inefficiency in Trending Markets - In strongly trending markets, ATR-based stops can sometimes be too far from the current price level. This could lead to larger losses if the price moves against your trade before hitting the stop loss. On the flip side, in less volatile, sideways markets, an ATR-based stop might be set too close to the entry point, leading to premature stop outs.
☁ Overoptimization Risk - If you're backtesting a trading strategy, there's a risk of overoptimizing your stop loss settings by fine-tuning them to past data. The best ATR multiplier that worked in the past might not necessarily work in the future, leading to potential performance issues.
☀ We countered these by implementing four different types of 'protect the trade' mechanisms:
✔ Fixed Percentage Stop Loss
✔ Trailing Stop Loss
✔ Stop Loss Moved to Entry Upon Reaching Certain Gain
✔ Stop Loss Moved to Entry Upon Reaching First Take Profit Order ("Custom Order").
☀ Dual Exit Strategy: We incorporated two distinct methods of exiting a trade. The first uses our custom signals, while the second triggers exit at a certain percentage of gain.
☀ Multiple Take Profit Orders: You have the flexibility to establish up to four different sell orders. This feature enables you to fractionate your exit strategy according to your needs. You can choose to trigger these fractions based on our custom signals or determine your own exit points by setting targeted gains at a fixed percentage.
☀ Confirmation Candle System: This feature enhances trade precision by requiring confirmation candles after a buy or sell signal. This confirmation, dependent on the next candle's closing price, helps reduce false signals and improves entry and exit points. While our confirmation system is applicable to all custom buy signals, it's solely dedicated for the bearish reversal when it comes to sell signals.
☀ Universal Compatibility: Easy Trade Pro's Strategy Tester works perfectly with any asset class. The code can handle different contract types, including the SPX contracts and fractional assets like Bitcoin. It's optimized to ensure proper execution of trades without rounding issues.
☀ Bullish and Bearish Reversal candles: Our method of detecting these pivotal candles combines conditions from buy and sell signals with pertinent divergences in Price, RSI, and Volume (OBV). The distinguishing factor, however, lies in recognizing significant shifts in market structure and liquidity grabs. To further enhance the credibility of our indicator, we've incorporated Bollinger Bands, serving as an additional layer in spotting potential trend reversals, particularly when aligned with long-wick candlesticks, engulfing patterns, and morning or evening star formations.
☀ Non-Repainting Indicator: Our indicator signals are designed not to repaint. Once a signal appears, it stays fixed, offering a reliable tool for your trading decisions.
================================================== EXTENSIVE TECHNICAL DESCRIPTION ====================================================
Easy Trade Pro is versatile, allowing you to analyze market trends across any financial asset. With its rigorous testing, our tool can be used confidently on any timeframe, from 1D to 1min, whether you prefer longer-term or shorter-term trades.
Although we recommend trading on timeframes between 1D and 1min, higher timeframes like 1W chart, can also provide broader insights.
Our study combines a variety of popular technical indicators, such as RSI, Stochastic RSI, MACD, DMI, Bollinger Bands as well as relevant EMAs. On the volume side OBV and MFI. Using a data-driven approach, “Easy Trade Pro” analyzes historical market trends to identify optimal ways to combine these indicators with significant divergences between price and oscillators. On top of that the code considers relevant changes in market structure and liquidity grabs, to generate reliable and accurate signals for potential buy and sell opportunities.
* ☎ --> Please not that MACD, BBs, and EMAs account for a minimal part of our script <--- ☎, If you're looking for a simpler tool, consider checking out our open-source indicator, 'RSI, SRSI, MACD, and DMI cross - Open source code'. You can find it here:
With our customizable system, traders will be able to identify:
1) Three types of buy signals🐂,💰,💎 and sell signals 🐻,🔨,💀
2) Bullish and bearish reversal candles with support and resistance lines
3) Bull and bear momentum signals
4) A function that utilizes Color bars to identify the strength of the trend
5) Three customizable moving averages
6) Alerts direct to your email or phone
7) Advanced and customizable settings menu
8) Our software also includes a backtesting system that that allows users to test their trading strategies on historical data, to check how they would have performed in real-world market conditions. This can help refine a trading strategy and make more informed decisions.
------------------------------------------------------------------------------ 1) BUY AND SELL SIGNALS ---------------------------------------------------------------------------------
Our buy and sell signals are generated using a custom combination of RSI, MFI, and Stochastic RSI levels, as well as relevant MACD and Stochastic RSI crosses. These indicators are carefully analyzed to identify potential trading opportunities and determine optimal entry and exit points for trades.
RSI (Relative strength index) measures the strength of a security's price action, while the SRSI (Stochastic Relative Strength Index) is a momentum oscillator that measures the current price relative to its high and low range over a set period. The Money Flow Index (MFI) is another momentum indicator that uses both price and volume data to measure buying and selling pressure. MACD (Moving Average Convergence Divergence) is a popular technical indicator used in financial markets to analyze price trends and momentum.
▶ With our system, you'll be able to identify three different levels of buy signals:
◉ The first level of buy signal is represented by a 🐂 emoji and is a "Good Buy". This signal indicates a possible buying opportunity. It indicates that could be a good opportunity to enter in a long trade. It's important to note that, the "Good Buy" signal can sometimes be supplemented with a green "Bull" text and a flag plotshape positioned beneath the signal. In these scenarios, we categorize this as a "Good Buy Bull" signal.
◉ The second level of buy signal is represented by a 💰 emoji and is a "Great Buy". This signal indicates a stronger buying opportunity than the "Good Buy" signal.
◉ The third and strongest buy signal is represented by a 💎 emoji and is an "Incredible Buy". This signal indicates a stronger buying opportunity than the "Good Buy" and "Great Buy" signals
▶ With our system, you'll be able to identify three different levels of sell signals:
◉ On the sell side, the first level is represented by a 🐻 emoji and is a "Good Sell". This signal indicates a possible selling opportunity. It indicates that could be a good opportunity to exit a trade or open a short position. It's important to note that, the "Good Sell" signal can occasionally be accompanied by a red "Bear" text and a flag plotshape positioned beneath the signal. In such instances, we refer to this as a "Good Sell Bear" signal.
◉ The second sell signal is represented by a 🔨 emoji and is a "Great Sell". This signal indicates a stronger selling opportunity than the "Good Sell" signal.
◉ The third and strongest sell signal is represented by a 💀 emoji and is an "Incredible Sell". This signal indicates a stronger selling opportunity than the "Good Sell" and "Great Sell" signals.
------------------------------------------2) "BULLISH AND BEARISH REVERSAL CANDLES PLUS SUPPORT AND RESISTANCE LINES" ------------------------------------------------
Bullish and bearish reversal candles are specific candles that have more probability to reverse the trend.
Our trading indicator is designed to identify bullish and bearish reversal candles. Our method of detecting these pivotal candles combines conditions from buy and sell signals with pertinent divergences in Price, RSI, and Volume (OBV). The distinguishing factor, however, lies in recognizing significant shifts in market structure and liquidity grabs. To further enhance the credibility of our indicator, we've incorporated Bollinger Bands, serving as an additional layer in spotting potential trend reversals, particularly when aligned with long-wick candlesticks, engulfing patterns, and morning or evening star formations.
These candles are represented by blue and orange colors respectively by default. Additionally, the indicator also uses lines that are drawn at either the opening or closing of candles to help identify pivot points of support or resistance. These candles, lines color or shape are customizable in the settings menu.
How can I benefit the most from bullish reversal candles? To make the most of bullish reversal candles, a powerful strategy is:
E.g, 1D chart - Wait for the next 1 or 2 candles to close above the support line linked to the bullish reversal candle. For lower timeframes, it is recommended to wait for 2 or 3 candles before making a trading decision. A good tip is also to look for other signals (confluence), like a buy signal. Traders should decide based on their risk tolerance.
Here below we can see an example of a bullish reversal candle in the BTC/USDT, 1D, chart. The system identify a bullish reversal candle (blue color), the next 2 candles are green and closed above the support blue line, in addition we have other bullish signals (confluence).
How can I benefit the most from bullish reversal lines? Bullish reversal lines can help traders to identify key level of support and maintain control of their position until a clear break below occurs.
In the example below we se how the price retrace to the support line:
After touching the price bounce up.
How can I benefit the most from bearish reversal candles? To make the most of bearish reversal candles, a powerful strategy is:
E.g, 1D chart - Wait for the next 1 or 2 candles to close below the resistance line linked to the bearish reversal candle. For lower timeframes, it is recommended to wait for 2 or 3 candles before making a trading decision. Traders should decide based on their risk tolerance.
Here below we can see an example of a bearish reversal candle in the ETH/USDT, 1D, chart. The system identify a bearish reversal candle (orange color), the next candle is red and closes below the resistance orange line. A good tip is also to look for other signals (confluence), like a sell signal.
How can I benefit the most from bearish reversal lines? Bearish reversal lines can help traders to identify key level of resistance and maintain control of their position until a clear break above occurs.
In the example below we se how the price bounce back to the resistance line and get rejected.
------------------------------------------------------------------------- 3) BULL AND BEAR MOMENTUM SIGNALS -----------------------------------------------------------------------
We analyzed factors such as buy or sell signals, long or short confirmation signals, DMI crossup or crossdown and breaks of market structure (BOS) or change of character (CHoCh) to determine the strength and direction of the trend. These study give us bull trend or bear trend signals that can help traders identify potential trading opportunities and make informed decisions.
These conditions are represented by a green word "BULL" and a flag shape below (bull momentum) and by a red word "BEAR" and a flag shape above (bear momentum) respectively by default. These plots shapes are customizable in the settings menu.
How can I benefit the most from bull momentum signals? To make the most of bull momentum signals, a powerful strategy is:
E.g, 1D chart - Look for confluence. If bull signal comes with a "Good Buy 🐂" in the same candle the signal is more strong. Another good combo is to look for a bullish reversal candle prior or after this signal, usually within a range of 1/2 candles. For lower timeframes, it is recommended to wait 2/3 candles before making a trading decision.
In the picture below we can see an example of a bull momentum signal in the US500, 1D, chart.
How can I benefit the most from bear momentum signals? To make the most of bear momentum signals, a powerful strategy is:
E.g, 1D chart - Look for confluence. If bear signal comes with a "Good Sell 🐻" in the same candle the signal is more strong. Another good combo is to look for a bearish reversal candle prior or after this signal, usually within a range of 1/2 candles. For lower timeframes, it is recommended to wait 2/3 candles before making a trading decision.
In the picture below we can see an example of a bear momentum signal in combo with a sell signal, NETFLIX, 1D, chart.
-------------------------------------------------------------- 4) "COLOR BARS THAT INDICATE THE STRENGTH OF THE TREND -----------------------------------------------------
This code is responsible for changing the color of the bars on a chart based on certain conditions. The gradient colors are defined for green and red, and the algorithm checks if the current bar is within a certain range of either a bearish reversal or bullish reversal candle and whether the price is above or below certain exponential moving averages or if important break of market structure occurs.
Ultimately, this feature helps traders visually identify potential trends and market shifts and avoid getting distracted by price fluctuations. Please note that every gradient of color can be customize by the user. We set 3 different bullish colors and 3 different bearish colors.
Below the picture of the settings menu related to the bar color.
----------------------------------------------------------------------5)THREE CUSTOMIZABLE MOVING AVERAGES ----------------------------------------------------------------------
You can choose up to three moving averages, any length and any type like SMA, EMA, WMA, HMA, RMA, SWMA and VWMA. Furthermore, you have the freedom to adjust the color and width of the lines to your preference.
Below the picture of the settings menu related to the moving averages.
----------------------------------------------------------------------6) ALERTS DIRECT TO YOUR EMAIL OR PHONE --------------------------------------------------------------------
Our alert feature sends real-time notifications directly to your email or phone when a signal is generated, allowing you to take immediate action and stay ahead of the market.
With our system, you first establish your own rules for trading in the strategy tester - this includes your criteria for entering and exiting trades.
Once you've defined these conditions, our system will start sending you alerts. These alerts will be triggered whenever your specified conditions are met. So, if the market matches your 'enter trade' conditions, you'll receive an alert prompting. Similarly, when your 'exit trade' conditions are met, you'll receive another alert.
Remember, these alerts are purely based on the conditions you set.
Once the condition is met, you will receive alerts directly to your email or phone when enter and exit a trade based on your custom conditions. To make sure you receive these notifications click on notifications tab.
---------------------------------------------------------------7) ADVANCED AND CUSTOMIZABLE SETTINGS MENU----------------------------------------------------------------------
We designed Easy Trade indicators with traders in mind, so it's user-friendly, easy to navigate and users can customize inputs, style, and colors of every feature in the indicator's settings menu.
-----------------------------------------------------------------------8) EASY TRADE PRO - BACKTESTING SYSTEM----------------------------------------------------------------------
Easy Trade Pro features a highly effective and realistic backtesting system, designed to mirror as closely as possible the real-world scenarios of entering and exiting trades.
Step 1:
Open the settings menu of the Indicator.
Once opened the settings menu click on properties.
Decide on the capital you wish to invest. Choose whether to use contracts or USD and determine the size of your orders. For the sake of realism, we recommend not exceeding 25% of your capital per order. However, if you decide to utilize your entire capital, make sure to adjust your stop loss accordingly. For instance, if you have a capital of 10K and use 10K with a stop loss at 2%, your potential loss would be $200. Conversely, if you use only 2K of your 10K capital with a stop loss at 10%, you would still lose the same 2% of your capital. To make your simulation even more authentic, consider incorporating broker fees or commissions into your calculations. For example, spot market fees are typically around 0.10%. If you're backtesting markets with low liquidity, consider factoring in slippage as well.
Step 2:
Navigate to the 'Inputs' section and scroll down until you come across 'Backtesting System - Strategy Test'. Once you locate this, click on the box and activate the 'USE STRATEGY SYSTEM' option by checking the tick box.
Also You will then need to set a 'Start Date' and 'End Date', establishing a specific time period during which you wish to test your strategy.
Otherwise you can consider to use the deep backtesting feature.
Step 3:
It's now time to establish the conditions for entering a trade. You can choose from five different types of custom buy signals: Good Buy, Good Buy Bull, Great Buy, Incredible Buy, and Bullish Reversal. Note that 'Great Buy' and 'Incredible Buy' are rare signals, so we advise against using them frequently in mechanical strategy tests; instead, consider them more for manual live tests. For more consistent results, we recommend using the other buy signals.
After determining your preferred buy signal, you can choose how many confirmation candles you wish to wait for before entering a trade. A 'confirmation' means that if the next candle closes above the opening or closing price of the chosen buy signal, it's considered a confirmation. This could be the opening or closing price, depending on whether the candle is green (close > open) or red.
You can set the number of confirmation candles in different time frames: below 2h, between 2h and 10h, and above 10h.
Step 4:
It's now time to safeguard your trade by managing risk. You can choose to implement a stop loss, expressed in percentage terms, or opt for a trailing stop. A trailing stop is a type of stop loss order that moves with the market price. It is designed to protect gains by enabling a trade to remain open and continue to profit as long as the market price is moving in a favorable direction. However, the trade closes if the market price changes direction by a specified amount (the 'trailing stop distance').
Additionally, you can minimize losses and move the stop loss to your entry point once the price reaches a certain percentage of profit. This strategy can help secure potential gains while limiting the potential for losses.
Step 5:
Now it's time to set the conditions for exiting the trade. You have the option to divide your exit into a maximum of four parts, with each part representing 25% of the position size. For each take profit point, you can choose from three different custom sell signals: Good Sell, Good Sell Bear, and Bearish Reversal.
Similarly, the concept of confirmation candles also applies here, but in this case, the candles are not closing above. A 'confirmation' for a sell signal means that if the next candle closes below the opening or closing price of the selected sell signal, it's considered a confirmation. This could be the opening or closing price, depending on whether the candle is green (open > close) or red (close < open).
So, when you're looking to sell, a confirmation would occur if the next candlestick's closing price is lower than the opening or closing price of the candlestick that triggered the sell signal. This indicates a potential bearish trend, providing the confirmation to execute the sell order.
Additionally, we've introduced a feature that allows you to move your stop loss to the entry point whenever the first take profit (1TP) is reached, which equates to hitting one custom sell signal.
Step 6:
We've also designed an alternative method for taking profits. With this approach, you can choose to exit your position once a fixed percentage gain from the entry point is reached. For instance, you might decide to exit when a 10% profit is achieved. Similarly to the previous method, this approach allows you to choose up to four exit points and determine the proportion of your position you want to close at each stage.
Conclusion:
Easy Trade Pro provides users with various options for entering and exiting trades. To effectively utilize the indicator, we strongly recommend conducting thorough backtesting and considering the results across your preferred trading pairs. It is advisable to analyze a substantial number of trades, ideally exceeding 100 trades, to obtain reliable insights into the indicator's performance. This approach will help you gain a better understanding of how Easy Trade Pro aligns with your trading strategy and objectives.
❗Keep attention❗
It is important to note that no trading indicator or strategy is foolproof, and there is always a risk of losses in trading. While this indicator may provide useful information for making conclusions, it should not be used as the sole basis for making trading decisions. Traders should always use proper risk management techniques and consider multiple factors when making trading decisions.
It is also important to be aware of the limitations of simulated performance results. Hypothetical or simulated results do not represent actual trading, and since trades have not been executed, results may be over- or under-compensated for market factors such as lack of liquidity. Simulated trading programs are also designed with the benefit of hindsight, and no representation is being made that any account will achieve profits or losses similar to those shown. Therefore, our indicators are for informative purposes only and not intended to be used as financial advice.
We encourage traders to use our indicators as part of a well-rounded trading strategy and to always be aware of the risks involved in trading. Remember that past performance is not indicative of future results and always trade responsibly.
Dskyz (DAFE) GENESIS Dskyz (DAFE) GENESIS: Adaptive Quant, Real Regime Power
Let’s be honest: Most published strategies on TradingView look nearly identical—copy-paste “open-source quant,” generic “adaptive” buzzwords, the same shallow explanations. I’ve even fallen into this trap with my own previously posted strategies. Not this time.
What Makes This Unique
GENESIS is not a black-box mashup or a pre-built template. It’s the culmination of DAFE’s own adaptive, multi-factor, regime-aware quant engine—built to outperform, survive, and visualize live edge in anything from NQ/MNQ to stocks and crypto.
True multi-factor core: Volume/price imbalances, trend shifts, volatility compression/expansion, and RSI all interlock for signal creation.
Adaptive regime logic: Trades only in healthy, actionable conditions—no “one-size-fits-all” signals.
Momentum normalization: Uses rolling, percentile-based fast/slow EMA differentials, ALWAYS normalized, ALWAYS relevant—no “is it working?” ambiguity.
Position sizing that adapts: Not fixed-lot, not naive—not a loophole for revenge trading.
No hidden DCA or pyramiding—what you see is what you trade.
Dashboard and visual system: Directly connected to internal logic. If it’s shown, it’s used—and nothing cosmetic is presented on your chart that isn’t quantifiable.
📊 Inputs and What They Mean (Read Carefully)
Maximum Raw Score: How many distinct factors can contribute to regime/trade confidence (default 4). If you extend the quant logic, increase this.
RSI Length / Min RSI for Shorts / Max RSI for Longs: Fine-tunes how “overbought/oversold” matters; increase the length for smoother swings, tighten floors/ceilings for more extreme signals.
⚡ Regime & Momentum Gates
Min Normed Momentum/Score (Conf): Raise to demand only the strongest trends—your filter to avoid algorithmic chop.
🕒 Volatility & Session
ATR Lookback, ATR Low/High Percentile: These control your system’s awareness of when the market is dead or ultra-volatile. All sizing and filter logic adapts in real time.
Trading Session (hours): Easy filter for when entries are allowed; default is regular trading hours—no surprise overnight fills.
📊 Sizing & Risk
Max Dollar Risk / Base-Max Contracts: All sizing is adaptive, based on live regime and volatility state—never static or “just 1 contract.” Control your max exposures and real $ risk. ATR will effect losses in high volatility times.
🔄 Exits & Scaling
Stop/Trail/Scale multipliers: You choose how dynamic/flexible risk controls and profit-taking need to be. ATR-based, so everything auto-adjusts to the current market mode.
Visuals That Actually Matter
Dashboard (Top Right): Shows only live, relevant stats: scoring, status, position size, win %, win streak, total wins—all from actual trade engine state (not “simulated”).
Watermark (Bottom Right): Momentum bar visual is always-on, regime-aware, reflecting live regime confidence and momentum normalization. If the bar is empty, you’re truly in no-momentum. If it glows lime, you’re riding the strongest possible edge.
*No cosmetics, no hidden code distractions.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Why It Wins
While others put out “AI-powered” strategies with little logic or soul, GENESIS is ruthlessly practical. It is built around what keeps traders alive:
- Context-aware signals, not just patterns
- Tight, transparent risk
- Inputs that adapt, not confuse
- Visuals that clarify, not distract
- Code that runs clean, efficient, and with minimal overfitting risk (try it on QQQ, AMD, SOL, etc. out of the box)
Disclaimer (for TradingView compliance):
Trading is risky. Futures, stocks, and crypto can result in significant losses. Do not trade with funds you cannot afford to lose. This is for educational and informational purposes only. Use in simulation/backtest mode before live trading. No past performance is indicative of future results. Always understand your risk and ownership of your trades.
This will not be my last—my goal is to keep raising the bar until DAFE is a brand or I’m forced to take this private.
Use with discipline, use with clarity, and always trade smarter.
— Dskyz , powered by DAFE Trading Systems.
Dskyz (DAFE) Quantum Sentiment Flux - Beginners Dskyz (DAFE) Quantum Sentiment Flux - Beginners:
Welcome to the Dskyz (DAFE) Quantum Sentiment Flux - Beginners , a strategy and concept that’s your ultimate wingman for trading futures like MNQ, NQ, MES, and ES. This gem combines lightning-fast momentum signals, market sentiment smarts, and bulletproof risk management into a system so intuitive, even newbies can trade like pros. With clean DAFE visuals, preset modes for every vibe, and a revamped dashboard that’s basically a market GPS, this strategy makes futures trading feel like a high-octane sci-fi mission.
Built on the Dskyz (DAFE) legacy of Aurora Divergence, the Quantum Sentiment Flux is designed to empower beginners while giving seasoned traders a lean, sentiment-driven edge. It uses fast/slow EMA crossovers for entries, filters trades with VIX, SPX trends, and sector breadth, and keeps your account safe with adaptive stops and cooldowns. Tuned for more action with faster signals and a slick bottom-left dashboard, this updated version is ready to light up your charts and outsmart institutional traps. Let’s dive into why this strat’s a must-have and break down its brilliance.
Why Traders Need This Strategy
Futures markets are a wild ride—fast moves, volatility spikes (like the April 28, 2025 NQ 1k-point drop), and institutional games that can wreck unprepared traders. Beginners often get lost in complex systems or burned by impulsive trades. The Quantum Sentiment Flux is the antidote, offering:
Dead-Simple Setup: Preset modes (Aggressive, Balanced, Conservative) auto-tune signals, risk, and sizing, so you can trade without a quant degree.
Sentiment Superpower: VIX filter, SPX trend, and sector breadth visuals keep you aligned with market health, dodging chop and riding trends.
Ironclad Safety: Tighter ATR-based stops, 2:1 take-profits, and preset cooldowns protect your capital, even in chaotic sessions.
Next-Level Visuals: Green/red entry triangles, vibrant EMAs, a sector breadth background, and a beefed-up dashboard make signals and context pop.
DAFE Swagger: The clean aesthetics, sleek dashboard—ties it to Dskyz’s elite brand, making your charts a work of art.
Traders need this because it’s a plug-and-play system that blends beginner-friendly simplicity with pro-level market awareness. Whether you’re just starting or scalping 5min MNQ, this strat’s your key to trading with confidence and style.
Strategy Components
1. Core Signal Logic (High-Speed Momentum)
The strategy’s engine is a momentum-based system using fast and slow Exponential Moving Averages (EMAs), now tuned for faster, more frequent trades.
How It Works:
Fast/Slow EMAs: Fast EMA (Aggressive: 5, Balanced: 7, Conservative: 9 bars) and slow EMA (12/14/18 bars) track short-term vs. longer-term momentum.
Crossover Signals:
Buy: Fast EMA crosses above slow EMA, and trend_dir = 1 (fast EMA > slow EMA + ATR * strength threshold).
Sell: Fast EMA crosses below slow EMA, and trend_dir = -1 (fast EMA < slow EMA - ATR * strength threshold).
Strength Filter: ma_strength = fast EMA - slow EMA must exceed an ATR-scaled threshold (Aggressive: 0.15, Balanced: 0.18, Conservative: 0.25) for robust signals.
Trend Direction: trend_dir confirms momentum, filtering out weak crossovers in choppy markets.
Evolution:
Faster EMAs (down from 7–10/21–50) catch short-term trends, perfect for active futures markets.
Lower strength thresholds (0.15–0.25 vs. 0.3–0.5) make signals more sensitive, boosting trade frequency without sacrificing quality.
Preset tuning ensures beginners get optimized settings, while pros can tweak via mode selection.
2. Market Sentiment Filters
The strategy leans hard into market sentiment with a VIX filter, SPX trend analysis, and sector breadth visuals, keeping trades aligned with the big picture.
VIX Filter:
Logic: Blocks long entries if VIX > threshold (default: 20, can_long = vix_close < vix_limit). Shorts are always allowed (can_short = true).
Impact: Prevents longs during high-fear markets (e.g., VIX spikes in crashes), while allowing shorts to capitalize on downturns.
SPX Trend Filter:
Logic: Compares S&P 500 (SPX) close to its SMA (Aggressive: 5, Balanced: 8, Conservative: 12 bars). spx_trend = 1 (UP) if close > SMA, -1 (DOWN) if < SMA, 0 (FLAT) if neutral.
Impact: Provides dashboard context, encouraging trades that align with market direction (e.g., longs in UP trend).
Sector Breadth (Visual):
Logic: Tracks 10 sector ETFs (XLK, XLF, XLE, etc.) vs. their SMAs (same lengths as SPX). Each sector scores +1 (bullish), -1 (bearish), or 0 (neutral), summed as breadth (-10 to +10).
Display: Green background if breadth > 4, red if breadth < -4, else neutral. Dashboard shows sector trends (↑/↓/-).
Impact: Faster SMA lengths make breadth more responsive, reflecting sector rotations (e.g., tech surging, energy lagging).
Why It’s Brilliant:
- VIX filter adds pro-level volatility awareness, saving beginners from panic-driven losses.
- SPX and sector breadth give a 360° view of market health, boosting signal confidence (e.g., green BG + buy signal = high-probability trade).
- Shorter SMAs make sentiment visuals react faster, perfect for 5min charts.
3. Risk Management
The risk controls are a fortress, now tighter and more dynamic to support frequent trading while keeping accounts safe.
Preset-Based Risk:
Aggressive: Fast EMAs (5/12), tight stops (1.1x ATR), 1-bar cooldown. High trade frequency, higher risk.
Balanced: EMAs (7/14), 1.2x ATR stops, 1-bar cooldown. Versatile for most traders.
Conservative: EMAs (9/18), 1.3x ATR stops, 2-bar cooldown. Safer, fewer trades.
Impact: Auto-scales risk to match style, making it foolproof for beginners.
Adaptive Stops and Take-Profits:
Logic: Stops = entry ± ATR * atr_mult (1.1–1.3x, down from 1.2–2.0x). Take-profits = entry ± ATR * take_mult (2x stop distance, 2:1 reward/risk). Longs: stop below entry, TP above; shorts: vice versa.
Impact: Tighter stops increase trade turnover while maintaining solid risk/reward, adapting to volatility.
Trade Cooldown:
Logic: Preset-driven (Aggressive/Balanced: 1 bar, Conservative: 2 bars vs. old user-input 2). Ensures bar_index - last_trade_bar >= cooldown.
Impact: Faster cooldowns (especially Aggressive/Balanced) allow more trades, balanced by VIX and strength filters.
Contract Sizing:
Logic: User sets contracts (default: 1, max: 10), no preset cap (unlike old 7/5/3 suggestion).
Impact: Flexible but risks over-leverage; beginners should stick to low contracts.
Built To Be Reliable and Consistent:
- Tighter stops and faster cooldowns make it a high-octane system without blowing up accounts.
- Preset-driven risk removes guesswork, letting newbies trade confidently.
- 2:1 TPs ensure profitable trades outweigh losses, even in volatile sessions like April 27, 2025 ES slippage.
4. Trade Entry and Exit Logic
The entry/exit rules are simple yet razor-sharp, now with VIX filtering and faster signals:
Entry Conditions:
Long Entry: buy_signal (fast EMA crosses above slow EMA, trend_dir = 1), no position (strategy.position_size = 0), cooldown passed (can_trade), and VIX < 20 (can_long). Enters with user-defined contracts.
Short Entry: sell_signal (fast EMA crosses below slow EMA, trend_dir = -1), no position, cooldown passed, can_short (always true).
Logic: Tracks last_entry_bar for visuals, last_trade_bar for cooldowns.
Exit Conditions:
Stop-Loss/Take-Profit: ATR-based stops (1.1–1.3x) and TPs (2x stop distance). Longs exit if price hits stop (below) or TP (above); shorts vice versa.
No Other Exits: Keeps it straightforward, relying on stops/TPs.
5. DAFE Visuals
The visuals are pure DAFE magic, blending clean function with informative metrics utilized by professionals, now enhanced by faster signals and a responsive breadth background:
EMA Plots:
Display: Fast EMA (blue, 2px), slow EMA (orange, 2px), using faster lengths (5–9/12–18).
Purpose: Highlights momentum shifts, with crossovers signaling entries.
Sector Breadth Background:
Display: Green (90% transparent) if breadth > 4, red (90%) if breadth < -4, else neutral.
Purpose: Faster breadth_sma_len (5–12 vs. 10–50) reflects sector shifts in real-time, reinforcing signal strength.
- Visuals are intuitive, turning complex signals into clear buy/sell cues.
- Faster breadth background reacts to market rotations (e.g., tech vs. energy), giving a pro-level edge.
6. Sector Breadth Dashboard
The new bottom-left dashboard is a game-changer, a 3x16 table (black/gray theme) that’s your market command center:
Metrics:
VIX: Current VIX (red if > 20, gray if not).
SPX: Trend as “UP” (green), “DOWN” (red), or “FLAT” (gray).
Trade Longs: “OK” (green) if VIX < 20, “BLOCK” (red) if not.
Sector Breadth: 10 sectors (Tech, Financial, etc.) with trend arrows (↑ green, ↓ red, - gray).
Placeholder Row: Empty for future metrics (e.g., ATR, breadth score).
Purpose: Consolidates regime, volatility, market trend, and sector data, making decisions a breeze.
- VIX and SPX metrics add context, helping beginners avoid bad trades (e.g., no longs if “BLOCK”).
Sector arrows show market health at a glance, like a cheat code for sentiment.
Key Features
Beginner-Ready: Preset modes and clear visuals make futures trading a breeze.
Sentiment-Driven: VIX filter, SPX trend, and sector breadth keep you in sync with the market.
High-Frequency: Faster EMAs, tighter stops, and short cooldowns boost trade volume.
Safe and Smart: Adaptive stops/TPs and cooldowns protect capital while maximizing wins.
Visual Mastery: DAFE’s clean flair, EMAs, dashboard—makes trading fun and clear.
Backtestable: Lean code and fixed qty ensure accurate historical testing.
How to Use
Add to Chart: Load on a 5min MNQ/ES chart in TradingView.
Pick Preset: Aggressive (scalping), Balanced (versatile), or Conservative (safe). Balanced is default.
Set Contracts: Default 1, max 10. Stick low for safety.
Check Dashboard: Bottom-left shows preset, VIX, SPX, and sectors. “OK” + green breadth = strong buy.
Backtest: Run in strategy tester to compare modes.
Live Trade: Connect to Tradovate or similar. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Try April 28, 2025 NQ drop to see VIX filter and stops in action.
Why It’s Brilliant
The Dskyz (DAFE) Quantum Sentiment Flux - Beginners is a masterpiece of simplicity and power. It takes pro-level tools—momentum, VIX, sector breadth—and wraps them in a system anyone can run. Faster signals and tighter stops make it a trading machine, while the VIX filter and dashboard keep you ahead of market chaos. The DAFE visuals and bottom-left command center turn your chart into a futuristic cockpit, guiding you through every trade. For beginners, it’s a safe entry to futures; for pros, it’s a scalping beast with sentiment smarts. This strat doesn’t just trade—it transforms how you see the market.
Final Notes
This is more than a strategy—it’s your launchpad to mastering futures with Dskyz (DAFE) flair. The Quantum Sentiment Flux blends accessibility, speed, and market savvy to help you outsmart the game. Load it, watch those triangles glow, and let’s make the markets your canvas!
Official Statement from Pine Script Team
(see TradingView help docs and forums):
"This warning may appear when you call functions such as ta.sma inside a request.security in a loop. There is no runtime impact. If you need to loop through a dynamic list of tickers, this cannot be avoided in the present version... Values will still be correct. Ignore this warning in such contexts."
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade fast, trade bold.
BONK 1H Long Volatility StrategyGrok 1hr bonk strategy:
Key Changes and Why They’re Made
1. Indicator Adjustments
Moving Averages:
Fast MA: Changed to 5 periods (from, e.g., 9 on a higher timeframe).
Slow MA: Changed to 13 periods (from, e.g., 21).
Why: Shorter periods make the moving averages more sensitive to quick price changes on the 1-hour chart, helping identify trends faster.
ATR (Average True Range):
Length: Set to 10 periods (down from, e.g., 14).
Multiplier: Reduced to 1.5 (from, e.g., 2.0).
Why: A shorter ATR length tracks recent volatility better, and a lower multiplier lets the strategy catch smaller price swings, which are more common hourly.
RSI:
Kept at 14 periods with an overbought level of 70.
Why: RSI stays the same to filter out overbought conditions, maintaining consistency with the original strategy.
2. Entry Conditions
Trend: Requires the fast MA to be above the slow MA, ensuring a bullish direction.
Volatility: The candle’s range (high - low) must exceed 1.5 times the ATR, confirming a significant move.
Momentum: RSI must be below 70, avoiding entries at potential peaks.
Price: The close must be above the fast MA, signaling a pullback or trend continuation.
Why: These conditions are tightened to capture frequent volatility spikes while filtering out noise, which is more prevalent on a 1-hour chart.
3. Exit Strategy
Profit Target: Default is 5% (adjustable from 3-7%).
Stop-Loss: Default is 3% (adjustable from 1-5%).
Why: These levels remain conservative to lock in gains quickly and limit losses, suitable for the faster pace of a 1-hour timeframe.
4. Risk Management
The strategy may trigger more trades on a 1-hour chart. To avoid overtrading:
The ATR filter ensures only volatile moves are traded.
Trading fees (e.g., 0.5% on Coinbase) reduce the net profit to ~4% on winners and -3.5% on losers, requiring a win rate above 47% for profitability.
Suggestion: Risk only 1-2% of your capital per trade to manage exposure.
5. Visuals and Alerts
Plots: Blue fast MA, red slow MA, and green triangles for buy signals.
Alerts: Trigger when an entry condition is met, so you don’t need to watch the chart constantly.
How to Use the Strategy
Setup:
Load TradingView, select BONK/USD on the 1-hour chart (Coinbase pair).
Paste the script into the Pine Editor and add it to your chart.
Customize:
Adjust the profit target (e.g., 5%) and stop-loss (e.g., 3%) to your preference.
Tweak ATR or MA lengths if BONK’s volatility shifts.
Trade:
Look for green triangle signals and confirm with market context (e.g., volume or news).
Enter trades manually or via TradingView’s broker tools if supported.
Exit when the profit target or stop-loss is hit.
Test:
Use TradingView’s Strategy Tester to backtest on historical data and refine settings.
Benefits of the 1-Hour Timeframe
Faster Opportunities: Captures shorter-term uptrends in BONK’s volatile price action.
Responsive: Adjusted indicators react quickly to hourly changes.
Conservative: Maintains the 3-7% profit goal with tight risk control.
Potential Challenges
Noise: The 1-hour chart has more false signals. The ATR and MA filters help, but caution is needed.
Fees: Frequent trading increases costs, so ensure each trade’s potential justifies the expense.
Volatility: BONK can move unpredictably—monitor broader market trends or Solana ecosystem news.
Final Thoughts
Switching to a 1-hour timeframe makes the strategy more active, targeting shorter volatility spikes while keeping profits conservative at 3-7%. The adjusted indicators and conditions balance responsiveness with reliability. Backtest it on TradingView to confirm it suits BONK’s behavior, and always use proper risk management, as meme coins are highly speculative.
Disclaimer: This is for educational purposes, not financial advice. Cryptocurrency trading, especially with assets like BONK, is risky. Test thoroughly and trade responsibly.
Smart Money Breakout & Order Block StrategySmart Money Breakout & Order Block Strategy
Created by Shubham
This strategy was developed by Shubham, designed to provide traders with a structured approach to smart money trading by combining breakout entries and order block reversals. It focuses on liquidity zones, volatility filters, and ATR-based stop management to adapt to different market conditions.
🔹 Strategy Overview
The Smart Money Breakout & Order Block Strategy is built for traders who want to identify institutional moves while avoiding false breakouts. This non-repainting strategy helps traders detect:
✅ Momentum Breakouts – Price breaking key support & resistance levels.
✅ Order Block Reversals – Institutional buying & selling zones.
✅ Dynamic Stop Management – No fixed SL/TP; uses ATR-based trailing stops.
✅ Volatility Filtering – Avoids choppy market conditions.
🔹 Trading Logic
1️⃣ Breakout Trading (Momentum Entries)
Long Entry: When price breaks above resistance with high volatility.
Short Entry: When price breaks below support with high volatility.
2️⃣ Order Block Reversals (Liquidity Entries)
Bullish Order Block: A strong price rejection after consecutive bearish candles signals smart money accumulation, triggering a long trade.
Bearish Order Block: A strong price rejection after consecutive bullish candles signals smart money distribution, triggering a short trade.
3️⃣ Volatility Filter (False Signal Prevention)
Uses normalized volatility to ensure breakouts are backed by strong momentum.
Helps filter out low-volume, choppy market conditions.
4️⃣ ATR-Based Position Management (Dynamic Stops & Trailing Stop)
No fixed SL/TP → Uses ATR-based stop-loss to adapt to market volatility.
Implements a trailing stop for maximizing potential profits in trending markets.
🔹 Key Features
✔️ Developed by Shubham – Designed for precision trading with institutional techniques.
✔️ Smart Money Concept – Identifies liquidity zones, breakouts, and order blocks.
✔️ Volatility Filter – Prevents false breakouts by analyzing market momentum.
✔️ ATR-Based Dynamic Stops – No fixed SL/TP, making it more adaptive.
✔️ Trailing Stop Functionality – Allows profits to run while reducing risk.
✔️ Fully Automated Execution – Uses TradingView’s strategy functions for automatic trade placement and exits.
✔️ Commission-Adjusted Backtesting – Includes realistic commission settings to ensure accurate results.
📊 Backtesting & Realistic Expectations
✅ Best for Higher Timeframes (1H, 4H, Daily) – Avoids market noise.
✅ Most Effective in Trending & Volatile Markets – Crypto, forex, indices, and commodities.
✅ Performance Varies with Market Conditions – Works best in strong trends.
✅ No Unrealistic Promises – Strategy performance is dependent on market behavior and risk management.
📌 IMPORTANT DISCLAIMER:
This strategy is provided for educational purposes only and should not be considered financial advice. Past performance in backtesting does not guarantee future results. Users should conduct their own research before applying this strategy in live markets.
🚀 Developed by Shubham – Test it yourself and see how it performs! 🚀
Qullamaggie [Modified] | FractalystWhat's the purpose of this strategy?
The strategy aims to identify high-probability breakout setups in trending markets, inspired by Kristjan "Qullamaggie" Kullamägi’s approach.
It focuses on capturing explosive price moves after periods of consolidation, using technical criteria like moving averages, breakouts, trailing stop-loss and momentum confirmation.
Ideal for swing traders seeking to ride strong trends while managing risk.
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How does the strategy work?
The strategy follows a systematic process to capture high-momentum breakouts:
Pre-Breakout Criteria:
Prior Price Surge: Identifies stocks that have rallied 30-100%+ in recent month(s), signaling strong underlying momentum (per Qullamaggie’s volatility expansion principles).
Consolidation Phase: Looks for a tightening price range (e.g., flag, pennant, or tight base), indicating a potential "coiling" before continuation.
Trend Confirmation: Uses moving averages (e.g., 20/50/200 EMA) to ensure the stock is trading above key averages on the daily chart, confirming an uptrend.
Price Break: Enters when price clears the consolidation high with conviction.
Risk Management:
Initial Stop Loss: Placed below the consolidation low or a recent swing point to limit downside.
Break-Even Adjustment: Moves stop loss to breakeven once the trade reaches 1.5x risk-to-reward (RR), securing a "free trade" while letting winners run.
Trailing Stop (Unique Edge):
Market Structure Trailing: Instead of trailing via moving averages, the stop is dynamically adjusted using structural invalidation level. This adapts to price action, allowing the trade to stay open during volatile retracements while locking in gains as new structure forms.
Why This Matters: Most strategies use rigid trailing stops (e.g., below the 10EMA), which often exit prematurely in choppy markets. By trailing based on structure, this strategy avoids "noise" and captures larger trends, directly boosting overall returns.
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What markets or timeframes is this suited for?
This is a long-only strategy designed for trending markets, and it performs best in:
Markets: Stocks (especially high-growth, liquid equities), cryptocurrencies (major pairs with strong volatility), commodities (e.g., oil, gold), and futures (index/commodity futures).
Timeframes: Primarily daily charts for swing trades (1-30 day holds), though weekly charts can help confirm broader trends.
Key Advantage: The TradingView script allows instant backtesting with adjustable parameters
You can:
- Test historical performance across multiple markets to identify which assets align best with the strategy.
- Optimize settings (e.g., trailing stop sensitivity, moving averages etc.) to match a market’s volatility profile.
Build a diversified portfolio by filtering for markets that show consistent profitability in backtests.
For example, you might discover cryptos require tighter trailing stops due to volatility, while stocks thrive with wider structural stops. The script automates this analysis, letting you to trade confidently.
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What indicators or tools does the strategy use?
The strategy combines customizable technical tools with strict anti-lookahead safeguards:
Core Indicators:
Moving Averages: Adjustable periods (e.g., 20/50/200 EMA or SMA) and timeframes (daily/weekly) to confirm trend alignment. Users can test combinations (e.g., 10EMA vs. 20EMA) to optimize for specific markets.
Breakout Parameters:
Consolidation Length: Adjustable window to define the "tightness" of the pre-breakout pattern.
Entry Models: Flexible entry logics (Breakouts and fractals)
Anti-Lookahead Design:
All calculations (e.g., moving averages, consolidation ranges, volume averages) use only closed/confirmed data available at the time of the signal.
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How do I manage risk with this strategy?
The strategy prioritizes customizable risk controls to align with your trading style and account size:
User-Defined Risk Inputs:
Risk Per Trade: Set a % of Equity (e.g., 1-2%) to determine position size. The strategy auto-calculates shares/contracts to match your selected risk per trade.
Flexibility: Choose between fixed risk or equity-based scaling.
The script adjusts position sizing dynamically based on your selection.
Pyramiding Feature:
Customizable Entries: Adjust the number of pyramiding trades allowed (e.g., 1-3 additional positions) in the strategy settings. Each new entry is triggered only if the prior trade hits its 1.5x RR target and the trend remains intact.
Risk-Scaled Additions: New positions use profits from prior trades, compounding gains without increasing initial risk.
Risk-Free Trade Mechanic:
Once a trade reaches 1.5x RR, the stop loss is moved to breakeven, eliminating downside risk.
The strategy then opens a new position (if pyramiding is enabled) using a portion of the locked-in profit. This "snowballs" winners while keeping total capital exposure stable.
Impact on Net Profit & Drawdown:
Net Profit Boost: Pyramiding lets you ride multi-leg trends aggressively. For example, a 100% runner could generate 2-3x more profit vs. a single-entry approach.
Controlled Drawdowns: Since new positions are funded by profits (not initial capital), max drawdown stays anchored to your original risk per trade (e.g., 1-2% of account). Even if later entries fail, the breakeven stop on prior trades protects overall equity.
Why This Works: Most strategies either over-leverage (increasing drawdowns) or exit too early. By recycling profits into new positions only after securing risk-free capital, this approach mimics hedge fund "scaling in" tactics while staying retail-trader friendly.
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How does the strategy identify market structure for its trailing stoploss?
The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
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What are the underlying calculations?
The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
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What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
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What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
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What type of break-even method is used in this strategy? What are the underlying calculations?
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
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What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What Makes This Strategy Unique?
This strategy combines flexibility, smart risk management, and momentum focus in a way that’s rare and practical:
1. Adapts to Any Market Rhythm
Works on daily, weekly, or intraday charts without code changes.
Uses two entry types: classic breakouts (like trending stocks) or fractal patterns (to avoid false starts).
2. Smarter Stop-Loss System
No rigid rules: Stops adjust based on price structure (e.g., new “higher lows”), not fixed percentages.
Avoids whipsaws: Tightens stops only when the trend strengthens, not in choppy markets.
3. Safe Profit-Boosting Pyramiding
Adds new positions only after prior trades are risk-free (stops moved above breakeven).
Scales up using locked-in profits, not new capital, to grow gains safely.
4. Built-In Momentum Check
Tracks 1/3/6-month price growth to spotlight stocks with strong, lasting momentum.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Scalping Strategy Signal v2 by [INFINITYTRADER]Overview
This Pine Script (v6) implements a scalping strategy that uses higher timeframe data (default: 4H) to generate entry and exit signals, originally designed for the 15-minute timeframe with an option for 30-minute charts. The "Scalping Strategy Signal v2 by " integrates moving averages, RSI, volume, ATR, and candlestick patterns to identify trading opportunities. It features adjustable risk management with ATR-based stop-loss, take-profit, and trailing stops, plus dynamic position sizing based on user-set capital. Trades trigger only on the higher timeframe candle close (e.g., 4H) to limit activity within the same period. This closed-source script offers a structured scalping approach, blending multiple entry methods and risk controls for adaptability across market conditions.
What Makes It Unique
Unlike typical scalping scripts relying on single-indicator triggers (e.g., RSI alone or basic MA crossovers), this strategy combines four distinct entry methods—standard MA crossovers, RSI-based momentum shifts, trend-following shorts, and candlestick pattern logic—evaluated on a 4H timeframe for confirmation. This multi-layered design, paired with re-entry logic after losses and a mix of manual, ATR-based, and trailing exits, aims to balance trade frequency and reliability. The higher timeframe filter adds precision not commonly found in simpler scalping tools, while the 30-minute option enhances consistency by reducing noise.
How It Works
Timeframe Logic
Runs on a base timeframe (designed for 15-minute charts, with a 30-minute option) while pulling data from a user-chosen higher timeframe (default: 4H) for signal accuracy.
Limits entries to the close of each 4H candle, ensuring one trade per period to avoid over-trading in volatile conditions.
Indicators and Data
Moving Averages : Employs 21-period and 50-period simple moving averages on the higher timeframe to detect trends and signal entries/exits.
Volume : Requires volume to exceed 70% of its 20-period average on the higher timeframe for momentum confirmation.
RSI : Uses a 14-period RSI for overbought/oversold filtering and a 6-period RSI for precise entry timing.
ATR : Applies a 14-period Average True Range on the higher timeframe to set adaptive stop-loss and take-profit levels.
Candlestick Patterns : Analyzes consecutive green or red 4H bars for trend continuation signals.
Why These Indicators
The blend of moving averages, RSI, volume, ATR, and candlestick patterns forms a robust scalping framework. Moving averages establish trend context, RSI filters momentum and avoids extremes, volume confirms market activity, ATR adjusts risk to volatility, and candlestick patterns enhance entry timing with price action insights. Together, they target small, frequent moves in flat or trending markets, with the 4H filter reducing false signals common in lower-timeframe scalping.
Entry Conditions
Four entry methods are evaluated at the 4H candle close:
Standard Long Entry: Price crosses above the 21-period moving average, volume exceeds 70% of its 20-period average, and the 1H 14-period RSI is below 70—confirms uptrend momentum.
Special Long Entry: The 6-period RSI crosses above 23, price is more than 1.5 times the ATR from the 21-period moving average, and price exceeds its prior close—targets oversold bounces with a stop-loss at the 4H candle’s low.
Short Entries:
- RSI-Based: The 6-period RSI crosses below 68 with volume support—catches overbought pullbacks.
- Trend-Based: Price crosses below the 21-period moving average, volume is above 70% of its average, and the 1H 14-period RSI is above 30—confirms downtrends.
Red/Green Bar Logic: Two consecutive green 4H bars for longs or red 4H bars for shorts—uses candlestick patterns for continuation, with a tight stop-loss from the base timeframe candle.
Re-Entry Logic
Long : After a losing special long, triggers when the 6-period RSI crosses 27 and price crosses the 21-period moving average.
Short : After a losing short, triggers when the 6-period RSI crosses 50 and price crosses below the 21-period moving average.
Purpose: Offers recovery opportunities with stricter conditions.
Exit Conditions
Manual Exits: Longs close if the 21-period MA crosses below the 50-period MA or the 1H 14-period RSI exceeds 68; shorts close if the 21-period MA crosses above the 50-period MA or RSI drops below 25.
ATR-Based TP/SL: Stop-loss is entry price ± ATR × 1.5 (default); take-profit is ± ATR × 4 (default), checked at 4H close.
Trailing Stop: Adjusts ±6x ATR from peak/trough, closing if price retraces within 1x ATR.
Special/Tight SL: Special longs exit if price opens below the 4H candle’s low; 4th method entries use the base timeframe candle’s low/high, checked every bar.
Position Sizing
Bases trade value on user-set capital (default: 100 USDT), dividing by the higher timeframe close price for dynamic sizing.
Visualization
Displays a table at the bottom-right with current/previous signals, TP/SL levels, equity, trading pair, and trade size—color-coded for clarity (green for buy, red for sell).
Inputs
Initial Capital (USDT): Sets trade value (default: 100, min: 1).
ATR Stop-Loss Multiplier: Adjusts SL distance (default: 1.5, min: 1).
ATR Take-Profit Multiplier: Adjusts TP distance (default: 4, min: 1).
Higher Timeframe: Selects analysis timeframe (options: 1m, 5m, 15m, 30m, 1H, 4H, D, W; default: 4H).
Usage Notes
Intended Timeframe: Designed for 15-minute charts with 4H confirmation for precision and frequency; 30-minute charts improve consistency by reducing noise.
Backtesting: Adjust ATR multipliers and capital to match your asset’s volatility and risk tolerance.
Risk Management: Combines manual, ATR, and trailing exits—monitor to avoid overexposure.
Limitations: 4H candle-close dependency may delay entries in fast markets; RSI/volume filters can reduce trades in low-momentum periods.
Backtest Observations
Tested on BTC/USDT (4H higher timeframe, default settings: Initial Capital: 100 USDT, ATR SL: 1.5x, ATR TP: 4x) across market conditions, comparing 15-minute and 30-minute charts:
Bull Market (Jul 2023 - Dec 2023):
15-Minute: 277 long, 219 short; Win Rate: 42.74%; P&L: 108%; Drawdown: 1.99%; Profit Factor: 3.074.
30-Minute: 257 long, 215 short; Win Rate: 49.58%; P&L: 116.85%; Drawdown: 2.34%; Profit Factor: 3.14.
Notes: Moving average crossovers and green bar patterns suited this bullish phase; 30-minute improved win rate and P&L by filtering weaker signals.
Bear Market (Jan 2022 - Jun 2022):
15-Minute: 262 long, 211 short; Win Rate: 44.4%; P&L: 239.80%; Drawdown: 3.74%; Profit Factor: 3.419.
30-Minute: 250 long, 200 short; Win Rate: 52.22%; P&L: 258.77%; Drawdown: 5.34%; Profit Factor: 3.461.
Notes: Red bar patterns and RSI shorts thrived in the downtrend; 30-minute cut choppy reversals for better consistency.
Flat Market (Jan 2021 - Jun 2021):
15-Minute: 280 long, 208 short; Win Rate: 51.84%; P&L: 340.33%; Drawdown: 9.59%; Profit Factor: 2.924.
30-Minute: 270 long, 209 short; Win Rate: 55.11%; P&L: 315.42%; Drawdown: 7.21%; Profit Factor: 2.598.
Notes: High trade frequency and P&L showed strength in ranges; 30-minute lowered drawdown for better risk control.
Results reflect historical performance on BTC/USDT with default settings—users should test on their assets and timeframes. Past performance does not guarantee future results and is shared only to illustrate the strategy’s behavior.
Why It Works Well in Flat Markets
A "flat market" lacks strong directional trends, with price oscillating around moving averages, as in Jan 2021 - Jun 2021 for BTC/USDT. This strategy excels here because its crossover-based entries trigger frequently in tight ranges. In trending markets, an exit might not be followed by a new entry without a pullback, but flat markets produce multiple crossovers, enabling more trades. ATR-based TP/SL and trailing stops capture these small swings, while RSI and volume filters ensure momentum, driving high P&L and win rates.
Technical Details
Built in Pine Script v6 for TradingView compatibility.
Prevents overlapping trades with long/short checks.
Handles edge cases like zero division and auto-detects the trading pair’s base currency (e.g., BTC from BTCUSDT).
This strategy suits scalpers seeking structured entries and risk management. Test on 15-minute or 30-minute charts to match your style and market conditions.
QuantJazz Turbine Trader BETA v1.17QuantJazz Turbine Trader BETA v1.17 - Strategy Introduction and User Guide
Strategy Introduction
Welcome to the QuantJazz Turbine Trader BETA v1.17, a comprehensive trading strategy designed for TradingView. This strategy is built upon oscillator principles, drawing inspiration from the Turbo Oscillator by RedRox, and incorporates multiple technical analysis concepts including RSI, MFI, Stochastic oscillators, divergence detection, and an optional FRAMA (Fractal Adaptive Moving Average) filter.
The Turbine Trader aims to provide traders with a flexible toolkit for identifying potential entry and exit points in the market. It presents information through a main signal line oscillator, a histogram, and various visual cues like dots, triangles, and divergence lines directly on the indicator panel. The strategy component allows users to define specific conditions based on these visual signals to trigger automated long or short trades within the TradingView environment.
This guide provides an overview of the strategy's components, settings, and usage. Please remember that this is a BETA version (v1.17). While developed with care, it may contain bugs or behave unexpectedly.
LEGAL DISCLAIMER: QuantJazz makes no claims about the fitness or profitability of this tool. Trading involves significant risk, and you may lose all of your invested capital. All trading decisions made using this strategy are solely at the user's discretion and responsibility. Past performance is not indicative of future results. Always conduct thorough backtesting and risk assessment before deploying any trading strategy with real capital.
This work is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International.
Core Concepts and Visual Elements
The Turbine Trader indicator displays several components in its own panel below the main price chart:
1. Signal Line (Avg & Avg2): This is the primary oscillator. It's a composite indicator derived from RSI, MFI (Money Flow Index), and Stochastic calculations, smoothed using an EMA (Exponential Moving Average).
Avg: The faster smoothed signal line.
Avg2: The slower smoothed signal line.
Color Coding: The space between Avg and Avg2 is filled. The color (Neon Blue/gColor or Neon Purple/rColor) indicates the trend based on the relationship between Avg and Avg2. Blue suggests bullish momentum (Avg > Avg2), while Purple suggests bearish momentum (Avg2 > Avg).
Zero Line Crosses: Crossovers of the Avg line with the zero level can indicate shifts in momentum.
2. Histogram (resMfi): This histogram is based on smoothed and transformed MFI calculations (Fast MFI and Slow MFI).
Color Coding: Bars are colored Neon Blue (histColorUp) when above zero, suggesting bullish pressure, and Neon Purple (histColorDn) when below zero, suggesting bearish pressure. Transparency is applied.
Zero Line Crosses: Crossovers of the histogram with the zero level can signal potential shifts in money flow.
3. Reversal Points (Dots): Dots appear on the Signal Line (specifically on Avg2) when the color changes (i.e., Avg crosses Avg2).
Small Dots: Appear when a reversal occurs while the oscillator is in an "extreme" zone (below -60 for bullish reversals, above +60 for bearish reversals).
Large Dots: Appear when a reversal occurs outside of these extreme zones.
Colors: Blue (gRdColor) for bullish reversals (Avg crossing above Avg2), Purple (rRdColor) for bearish reversals (Avg crossing below Avg2).
4. Take Profit (TP) Signals (Triangles): Small triangles appear above (+120) or below (-120) the zero line.
Bearish Triangle (Down, Purple rTpColor): Suggests a potential exit point for long positions or an entry point for short positions, based on the oscillator losing upward momentum above the 50 level.
Bullish Triangle (Up, Blue gTpColor): Suggests a potential exit point for short positions or an entry point for long positions, based on the oscillator losing downward momentum below the -50 level.
5. Divergence Lines: The strategy automatically detects and draws potential regular and hidden divergences between the price action (highs/lows) and the Signal Line (Avg).
Regular Bullish Divergence (White bullDivColor line, ⊚︎ label): Price makes a lower low, but the oscillator makes a higher low. Suggests potential bottoming.
Regular Bearish Divergence (White bearDivColor line, ⊚︎ label): Price makes a higher high, but the oscillator makes a lower high. Suggests potential topping.
Hidden Bullish Divergence (bullHidDivColor line, ⊚︎ label): Price makes a higher low, but the oscillator makes a lower low. Suggests potential continuation of an uptrend.
Hidden Bearish Divergence (bearHidDivColor line, ⊚︎ label): Price makes a lower high, but the oscillator makes a higher high. Suggests potential continuation of a downtrend.
Delete Broken Divergence Lines: If enabled, newer divergence lines originating from a similar point will replace older ones.
6. Status Line: A visual bar at the top (95 to 105) and bottom (-95 to -105) of the indicator panel. Its color intensity reflects the confluence of signals:
Score Calculation: +1 if Avg > Avg2, +1 if Avg > 0, +1 if Histogram > 0.
Top Bar (Bullish): Bright Blue (gStatColor) if score is 3, Faded Blue if score is 2, Black otherwise.
Bottom Bar (Bearish): Bright Purple (rStatColor) if score is 0, Faded Purple if score is 1, Black otherwise.
Strategy Settings Explained
The strategy's behavior is controlled via the settings panel (gear icon).
1. Date Range:
Start Date, End Date: Define the period for backtesting. Trades will only occur within this range.
2. Optional Webhook Configuration: (For Automation)
3C Email Token, 3C Bot ID: Enter your 3Commas API credentials if you plan to automate trading using webhooks. The strategy generates JSON alert messages compatible with 3Commas. You can go ahead and just leave the text field as defaulted, "TOKEN HERE" / "BOT ID HERE" if not using any bot automations at this time. You can always come back later and automate it. More info can be made available from QuantJazz should you need automation assistance with custom indicators and trading strategies.
3. 🚀 Signal Line:
Turn On/Off: Show or hide the main signal lines (Avg, Avg2).
gColor, rColor: Set the colors for bullish and bearish signal line states.
Length (RSI): The lookback period for the internal RSI calculation. Default is 2.
Smooth (EMA): The smoothing period for the EMAs applied to the composite signal. Default is 9.
RSI Source: The price source used for RSI calculation (default: close).
4. 📊 Histogram:
Turn On/Off: Show or hide the histogram.
histColorUp, histColorDn: Set the colors for positive and negative histogram bars.
Length (MFI): The base lookback period for MFI calculations. Default is 5. Fast and Slow MFI lengths are derived from this.
Smooth: Smoothing period for the final histogram output. Default is 1 (minimal smoothing).
5.💡 Other:
Show Divergence Line: Toggle visibility of regular divergence lines.
bullDivColor, bearDivColor: Colors for regular divergence lines.
Show Hidden Divergence: Toggle visibility of hidden divergence lines.
bullHidDivColor, bearHidDivColor: Colors for hidden divergence lines.
Show Status Line: Toggle visibility of the top/bottom status bars.
gStatColor, rStatColor: Colors for the status line bars.
Show TP Signal: Toggle visibility of the TP triangles.
gTpColor, rTpColor: Colors for the TP triangles.
Show Reversal points: Toggle visibility of the small/large dots on the signal line.
gRdColor, rRdColor: Colors for the reversal dots.
Delete Broken Divergence Lines: Enable/disable automatic cleanup of older divergence lines.
6. ⚙️ Strategy Inputs: (CRITICAL for Trade Logic)
This section defines which visual signals trigger trades. Each signal (Small/Large Dots, TP Triangles, Bright Bars, Signal/Histogram Crosses, Signal/Histogram Max/Min, Divergences) has a dropdown menu:
Long: This signal can trigger a long entry.
Short: This signal can trigger a short entry.
Disabled: This signal will not trigger any entry.
Must Be True Checkbox: If checked for a specific signal, that signal's condition must be met for any trade (long or short, depending on the dropdown selection for that signal) to be considered. Multiple "Must Be True" conditions act as AND logic – all must be true simultaneously.
How it Works:
The strategy first checks if all conditions marked as "Must Be True" (for the relevant trade direction - long or short) are met.
If all "Must Be True" conditions are met, it then checks if at least one of the conditions not marked as "Must Be True" (and set to "Long" or "Short" respectively) is also met.
If both steps pass, and other filters (like Date Range, FRAMA) allow, an entry order is placed.
Example: If "Large Bullish Dot" is set to "Long" and "Must Be True" is checked, AND "Bullish Divergence" is set to "Long" but "Must Be True" is not checked: A long entry requires BOTH the Large Bullish Dot AND the Bullish Divergence to occur simultaneously. If "Large Bullish Dot" was "Long" but not "Must Be True", then EITHER a Large Bullish Dot OR a Bullish Divergence could trigger a long entry (assuming no other "Must Be True" conditions are active).
Note: By default, the strategy is configured for long-only trades (strategy.risk.allow_entry_in(strategy.direction.long)). To enable short trades, you would need to comment out or remove this line in the Pine Script code and configure the "Strategy Inputs" accordingly.
7. 💰 Take Profit Settings:
Take Profit 1/2/3 (%): The percentage above the entry price (for longs) or below (for shorts) where each TP level is set. (e.g., 1.0 means 1% profit).
TP1/2/3 Percentage: The percentage of the currently open position to close when the corresponding TP level is hit. The percentages should ideally sum to 100% if you intend to close the entire position across the TPs.
Trailing Stop (%): The percentage below the highest high (for longs) or above the lowest low (for shorts) reached after the activation threshold, where the stop loss will trail.
Trailing Stop Activation (%): The minimum profit percentage the trade must reach before the trailing stop becomes active.
Re-entry Delay (Bars): The minimum number of bars to wait after a TP is hit before considering a re-entry. Default is 1 (allows immediate re-entry on the next bar if conditions met).
Re-entry Price Offset (%): The percentage the price must move beyond the previous TP level before a re-entry is allowed. This prevents immediate re-entry if the price hovers around the TP level.
8. 📈 FRAMA Filter: (Optional Trend Filter)
Use FRAMA Filter: Enable or disable the filter.
FRAMA Source, FRAMA Period, FRAMA Fast MA, FRAMA Slow MA: Parameters for the FRAMA calculation. Defaults provided are common starting points.
FRAMA Filter Type:
FRAMA > previous bars: Allows trades only if FRAMA is significantly above its recent average (defined by FRAMA Percentage and FRAMA Lookback). Typically used to confirm strong upward trends for longs.
FRAMA < price: Allows trades only if FRAMA is below the current price (framaSource). Can act as a baseline trend filter.
FRAMA Percentage (X), FRAMA Lookback (Y): Used only for the FRAMA > previous bars filter type.
How it Affects Trades: If Use FRAMA Filter is enabled:
Long entries require the FRAMA filter condition to be true.
Short entries require the FRAMA filter condition to be false (as currently coded, this acts as an inverse filter for shorts if enabled).
How to Use the Strategy
1. Apply to Chart: Open your desired chart on TradingView. Click "Indicators", find "QuantJazz Turbine Trader BETA v1.17" (you might need to add it via Invite-only scripts or if published publicly), and add it to your chart. The oscillator appears below the price chart, and the strategy tester panel opens at the bottom.
2. Configure Strategy Properties: In the Pine Script code itself (or potentially via the UI if supported), adjust the strategy() function parameters like initial_capital, default_qty_value, commission_value, slippage, etc., to match your account, broker fees, and risk settings. The user preferences provided (e.g., 1000 initial capital, 0.1% commission) are examples. Remember use_bar_magnifier is false by default in v1.17.
3. Configure Inputs (Settings Panel):
Set the Date Range for backtesting.
Crucially, configure the ⚙️ Strategy Inputs. Decide which signals should trigger entries and whether they are mandatory ("Must Be True"). Start simply, perhaps enabling only one or two signals initially, and test thoroughly. Remember the default long-only setting unless you modify the code.
Set up your 💰 Take Profit Settings, including TP levels, position size percentages for each TP, and the trailing stop parameters. Decide if you want to use the re-entry feature.
Decide whether to use the 📈 FRAMA Filter and configure its parameters if enabled.
Adjust visual elements (🚀 Signal Line, 📊 Histogram, 💡 Other) as needed for clarity.
4. Backtest: Use the Strategy Tester panel in TradingView. Analyze the performance metrics (Net Profit, Max Drawdown, Profit Factor, Win Rate, Trade List) across different assets, timeframes, and setting configurations. Pay close attention to how different "Strategy Inputs" combinations perform.
5. Refine: Based on backtesting results, adjust the input settings, TP/SL strategy, and signal combinations to optimize performance for your chosen market and timeframe, while being mindful of overfitting.
6. Automation (Optional): If using 3Commas or a similar platform:
Enter your 3C Email Token and 3C Bot ID in the settings.
Create alerts in TradingView (right-click on the chart or use the Alert panel).
Set the Condition to "QuantJazz Turbine Trader BETA v1.17".
In the "Message" box, paste the corresponding placeholder, which will pass the message in JSON from our custom code to TradingView to pass through your webhook: {{strategy.order.alert_message}}.
In the next tab, configure the Webhook URL provided by your automation platform. Put a Whale sound, while you're at it! 🐳
When an alert triggers, TradingView will send the pre-formatted JSON message from the strategy code to your webhook URL.
Final Notes
The QuantJazz Turbine Trader BETA v1.17 offers a wide range of customizable signals and strategy logic. Its effectiveness heavily depends on proper configuration and thorough backtesting specific to the traded asset and timeframe. Start with the default settings, understand each component, and methodically test different combinations of signals and parameters. Remember the inherent risks of trading and never invest capital you cannot afford to lose.
Bull Flag (9:30-12:00 Only) [One-Liner Fix]🚀 Bull Flag Breakout Strategy | Intraday Momentum (9:30-12:00) 🔥📈
💡 Designed for Intraday Traders who love momentum breakouts and want to automate Bull Flag setups with volume confirmation! This strategy detects strong bullish moves, measures pullbacks, and triggers trades when the first candle makes a new high—ensuring maximum momentum.
⸻
🏆 Why This Strategy?
✅ Bull Flag Pattern Automation – No need to manually spot pullbacks! 🎯
✅ Smart Volume Confirmation – Only enter trades when breakout volume is strong! 📊
✅ Morning Session Focused (9:30 - 12:00 EST) – Trade when momentum is at its peak! ⏰
✅ Customizable ATR & Risk Settings – Adjust pullback %, stop-loss, and take-profit! 🛠️
✅ Backtest-Friendly – See how the strategy performs over time! 🔍
⸻
🎯 How It Works
📌 Step 1: Detects a Bullish Impulse Bar
🔹 Large green candle 🚀
🔹 Candle range > ATR multiplier
🔹 Volume > Average volume threshold
📌 Step 2: Confirms a Valid Pullback
🔸 Pullback must stay within % range of the impulse move 📉
🔸 If the pullback is too deep or takes too long, the setup is ignored ⛔
📌 Step 3: First Candle to Make a New High 📈
🔹 When a candle breaks the previous high and volume confirms, go long! 💰
🔹 Stop-Loss set at pullback low
🔹 Take-Profit at Risk:Reward (R:R) Target 🎯
⸻
🔥 Best For
💎 Scalpers & Day Traders – Capture short-term breakout momentum! ⚡
📊 Backtesters – Optimize ATR, volume, and pullback rules for best performance! 🧪
⏳ Morning Momentum Traders – Focus on 9:30-12:00 AM EST for higher probability setups!
⸻
🚨 Important Notes
🔹 This strategy is not financial advice! 📜
🔹 Always backtest & paper trade before using real money! 📉📈
🔹 Volatility varies – Customize settings based on your trading style! 🔧
🚀 Like this script? Give it a try & let us know how it works for you! 🔥👊
⸻
Pure Price Action StrategyTest Price Action Strategy from Lux Pure Price Action Indicator
How This Strategy Works:
Recognizing Trends & Reversals:
Break of Structure (BOS): A bullish signal indicating a trend continuation.
Market Structure Shift (MSS): A bearish signal indicating a potential reversal.
Analyzing Market Momentum:
It uses recent highs and lows to confirm whether the price is making higher highs (bullish) or lower lows (bearish).
Customizing Visualization Styles:
Buy signals (BUY Signal) are plotted as green upward arrows.
Sell signals (SELL Signal) are plotted as red downward arrows.
Stop-Loss (SL) & Take-Profit (TP): Configurable via percentage input.
TSI Long/Short for BTC 2HThe TSI Long/Short for BTC 2H strategy is an advanced trend-following system designed specifically for trading Bitcoin (BTC) on a 2-hour timeframe. It leverages the True Strength Index (TSI) to identify momentum shifts and executes both long and short trades in response to dynamic market conditions.
Unlike traditional moving average-based strategies, this script uses a double-smoothed momentum calculation, enhancing signal accuracy and reducing noise. It incorporates automated position sizing, customizable leverage, and real-time performance tracking, ensuring a structured and adaptable trading approach.
🔹 What Makes This Strategy Unique?
Unlike simple crossover strategies or generic trend-following approaches, this system utilizes a customized True Strength Index (TSI) methodology that dynamically adjusts to market conditions.
🔸 True Strength Index (TSI) Filtering – The script refines the TSI by applying double exponential smoothing, filtering out weak signals and capturing high-confidence momentum shifts.
🔸 Adaptive Entry & Exit Logic – Instead of fixed thresholds, it compares the TSI value against a dynamically determined high/low range from the past 100 bars to confirm trade signals.
🔸 Leverage & Risk Optimization – Position sizing is dynamically adjusted based on account equity and leverage settings, ensuring controlled risk exposure.
🔸 Performance Monitoring System – A built-in performance tracking table allows traders to evaluate monthly and yearly results directly on the chart.
📊 Core Strategy Components
1️⃣ Momentum-Based Trade Execution
The strategy generates long and short trade signals based on the following conditions:
✅ Long Entry Condition – A buy signal is triggered when the TSI crosses above its 100-bar highest value (previously set), confirming bullish momentum.
✅ Short Entry Condition – A sell signal is generated when the TSI crosses below its 100-bar lowest value (previously set), indicating bearish pressure.
Each trade execution is fully automated, reducing emotional decision-making and improving trading discipline.
2️⃣ Position Sizing & Leverage Control
Risk management is a key focus of this strategy:
🔹 Dynamic Position Sizing – The script calculates position size based on:
Account Equity – Ensuring trade sizes adjust dynamically with capital fluctuations.
Leverage Multiplier – Allows traders to customize risk exposure via an adjustable leverage setting.
🔹 No Fixed Stop-Loss – The strategy relies on reversals to exit trades, meaning each position is closed when the opposite signal appears.
This design ensures maximum capital efficiency while adapting to market conditions in real time.
3️⃣ Performance Visualization & Tracking
Understanding historical performance is crucial for refining strategies. The script includes:
📌 Real-Time Trade Markers – Buy and sell signals are visually displayed on the chart for easy reference.
📌 Performance Metrics Table – Tracks monthly and yearly returns in percentage form, helping traders assess profitability over time.
📌 Trade History Visualization – Completed trades are displayed with color-coded boxes (green for long trades, red for short trades), visually representing profit/loss dynamics.
📢 Why Use This Strategy?
✔ Advanced Momentum Detection – Uses a double-smoothed TSI for more accurate trend signals.
✔ Fully Automated Trading – Removes emotional bias and enforces discipline.
✔ Customizable Risk Management – Adjust leverage and position sizing to suit your risk profile.
✔ Comprehensive Performance Tracking – Integrated reporting system provides clear insights into past trades.
This strategy is ideal for Bitcoin traders looking for a structured, high-probability system that adapts to both bullish and bearish trends on the 2-hour timeframe.
📌 How to Use: Simply add the script to your 2H BTC chart, configure your leverage settings, and let the system handle trade execution and tracking! 🚀
FRAMA-LRO📌 FRAMA × LRO Auto-Trading Strategy - Adaptive Trend & Momentum System
Overview
This Pine Script provides an automated trading strategy that combines FRAMA (Fractal Adaptive Moving Average) and LRO (Linear Regression Oscillator) to enhance trend detection and momentum analysis. Unlike traditional moving averages, FRAMA dynamically adjusts to price volatility, while LRO effectively measures momentum for high-precision entries.
📌 Key Features
1. Dynamic Trend & Momentum Synergy
FRAMA: Detects price trends by adjusting to market conditions using fractal dimensions.
LRO: Filters trades based on linear regression slope momentum.
Breakout Confirmation: Entry is validated when price breaks FRAMA bands with LRO support.
2. Realistic Backtesting Settings
Initial Capital: $5,000 (more in line with retail traders).
Risk Management: 5% equity per trade.
Slippage & Commission: Adjusted to realistic values (1 pip slippage, 94 pips spread per trade).
Backtest Data: Covers at least 100 trades for statistical significance.
3. Clear Trade Logic
Long Entry: Price breaks above FRAMA upper band & LRO > 0.
Short Entry: Price breaks below FRAMA lower band & LRO < 0.
Stop-Loss: Dynamic ATR-based calculation.
Take-Profit: Fixed risk-reward ratio (1:2).
📌 How It Works
The system identifies trend strength with FRAMA, then confirms momentum shifts with LRO before executing trades. This ensures higher accuracy and filters false breakouts.
📌 Visual Aids for Clarity
Color-Coded Candles:
🟢 Uptrend (LRO > 0)
🔵 Downtrend (LRO < 0)
⚪ Neutral (LRO ≈ 0)
Chart Annotations: Clearly marked trade signals for easy reference.
📌 Risk Management & Automation
Fully automated execution of entries, stop-loss, and take-profit.
ATR-based volatility adaptation for dynamic SL adjustments.
Customizable parameters (period, volatility settings, risk percentage).
📌 Originality & Enhancements
This script is not just a combination of FRAMA & LRO, but an optimized system designed to:
Improve signal accuracy using adaptive trend detection.
Eliminate noise with LRO-based momentum filtering.
Implement dynamic risk management via ATR-based SL.
Influences & Acknowledgments
This strategy builds on methodologies inspired by ChartPrime and BigBeluga, refining their concepts for a systematic approach.
📌 Disclaimer
This script is for educational purposes only. Past performance does not guarantee future results. Always manage risk appropriately.
Dynamic Ticks Oscillator Model (DTOM)The Dynamic Ticks Oscillator Model (DTOM) is a systematic trading approach grounded in momentum and volatility analysis, designed to exploit behavioral inefficiencies in the equity markets. It focuses on the NYSE Down Ticks, a metric reflecting the cumulative number of stocks trading at a lower price than their previous trade. As a proxy for market sentiment and selling pressure, this indicator is particularly useful in identifying shifts in investor behavior during periods of heightened uncertainty or volatility (Jegadeesh & Titman, 1993).
Theoretical Basis
The DTOM builds on established principles of momentum and mean reversion in financial markets. Momentum strategies, which seek to capitalize on the persistence of price trends, have been shown to deliver significant returns in various asset classes (Carhart, 1997). However, these strategies are also susceptible to periods of drawdown due to sudden reversals. By incorporating volatility as a dynamic component, DTOM adapts to changing market conditions, addressing one of the primary challenges of traditional momentum models (Barroso & Santa-Clara, 2015).
Sentiment and Volatility as Core Drivers
The NYSE Down Ticks serve as a proxy for short-term negative sentiment. Sudden increases in Down Ticks often signal panic-driven selling, creating potential opportunities for mean reversion. Behavioral finance studies suggest that investor overreaction to negative news can lead to temporary mispricings, which systematic strategies can exploit (De Bondt & Thaler, 1985). By incorporating a rate-of-change (ROC) oscillator into the model, DTOM tracks the momentum of Down Ticks over a specified lookback period, identifying periods of extreme sentiment.
In addition, the strategy dynamically adjusts entry and exit thresholds based on recent volatility. Research indicates that incorporating volatility into momentum strategies can enhance risk-adjusted returns by improving adaptability to market conditions (Moskowitz, Ooi, & Pedersen, 2012). DTOM uses standard deviations of the ROC as a measure of volatility, allowing thresholds to contract during calm markets and expand during turbulent ones. This approach helps mitigate false signals and aligns with findings that volatility scaling can improve strategy robustness (Barroso & Santa-Clara, 2015).
Practical Implications
The DTOM framework is particularly well-suited for systematic traders seeking to exploit behavioral inefficiencies while maintaining adaptability to varying market environments. By leveraging sentiment metrics such as the NYSE Down Ticks and combining them with a volatility-adjusted momentum oscillator, the strategy addresses key limitations of traditional trend-following models, such as their lagging nature and susceptibility to reversals in volatile conditions.
References
• Barroso, P., & Santa-Clara, P. (2015). Momentum Has Its Moments. Journal of Financial Economics, 116(1), 111–120.
• Carhart, M. M. (1997). On Persistence in Mutual Fund Performance. The Journal of Finance, 52(1), 57–82.
• De Bondt, W. F., & Thaler, R. (1985). Does the Stock Market Overreact? The Journal of Finance, 40(3), 793–805.
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65–91.
• Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time Series Momentum. Journal of Financial Economics, 104(2), 228–250.
Volatility-Adjusted Rate of Change (VARC) ModelThe Volatility-Adjusted Rate of Change (VARC) Model is a dynamic trading strategy designed to identify potential market opportunities by incorporating volatility and skewness data. The model relies on the CBOE Skew Index (CBOE:SKEW) and adjusts the traditional Rate of Change (ROC) indicator based on market volatility, offering a more refined approach to trading based on price momentum.
1. CBOE Skew Index (SKEW) and ROC Calculation
At its core, the VARC model uses the CBOE Skew Index as a measure of market sentiment. The SKEW index represents the perceived risk of extreme negative movements in the S&P 500, providing insight into the balance of risks in the market (CBOE, 2021). This sentiment-based index is often used by traders and analysts to gauge the likelihood of a market downturn.
The Rate of Change (ROC) is applied to the Skew Index, calculated over a specified lookback period (rocLength = 29). The ROC measures the percentage change in price from one period to another and is widely used to gauge the momentum of an asset (Chande & Kroll, 1994). In the VARC model, the ROC of the Skew Index is employed to assess shifts in market sentiment that may signal turning points or potential volatility.
2. Volatility Adjustment
Volatility plays a significant role in market behavior and risk management. The VARC model uses a volatility-adjusted threshold to dynamically adjust the sensitivity of the trading signals. This is achieved by calculating the standard deviation of the ROC over a defined volatility lookback period (volatilityLookback = 20) and applying a volatility multiplier (volatilityMultiplier = 1.5). These parameters define upper and lower thresholds for trade entry and exit.
The model adjusts the sensitivity of the ROC signals based on market volatility, ensuring that the strategy adapts to changing market conditions. When volatility is high, the thresholds are widened, allowing the model to filter out noise and avoid unnecessary trades. Conversely, during periods of low volatility, the thresholds tighten, enabling the model to capture smaller price movements.
3. Entry and Exit Conditions
The VARC model generates trading signals based on the behavior of the ROC relative to the dynamically adjusted volatility thresholds. A long position is initiated when the ROC crosses below the lower threshold, indicating that the market is becoming oversold or showing signs of excessive pessimism. The position is closed when the ROC exceeds the upper threshold, signaling a potential reversal or a return to normal market conditions. These entry and exit conditions are defined as follows:
• Long Condition: The ROC is below the lower threshold (roc < dynamicThresholdLow).
• Exit Condition: The ROC is above the upper threshold (roc > dynamicThresholdHigh).
This approach provides a systematic method for entering and exiting positions based on volatility-adjusted momentum, helping traders to capitalize on shifts in market sentiment.
4. Visualization and Signal Highlighting
The model includes several visual aids to help traders interpret the signals. The ROC, dynamic thresholds, and a zero line are plotted on the chart to provide a clear representation of market momentum and the current trading range. Furthermore, a background color is used to highlight periods when a position is open, visually reinforcing the model’s decisions.
5. Conclusion
The VARC model offers a robust framework for trading by combining momentum (through the ROC) with a volatility-adjusted approach that refines trade signals based on market conditions. The use of the CBOE Skew Index adds an additional layer of market sentiment analysis, providing context to the ROC values. This volatility-adaptive strategy offers traders a more nuanced way to navigate the markets, making it suitable for both short-term and longer-term trading horizons.
References:
• CBOE. (2021). CBOE Skew Index (SKEW). Chicago Board Options Exchange. Retrieved from www.cboe.com
• Chande, T., & Kroll, J. (1994). The New Technical Trader: Boost Your Profit by Plugging into the Latest Indicators. Wiley.
This model can be particularly useful in volatile markets, where traditional fixed thresholds may not perform as well. By adjusting the thresholds dynamically based on the underlying volatility, the VARC model offers a more flexible and responsive approach to market trading.
Up Gap Strategy with DelayThis strategy, titled “Up Gap Strategy with Delay,” is based on identifying up gaps in the price action of an asset. A gap is defined as the percentage difference between the current bar’s open price and the previous bar’s close price. The strategy triggers a long position if the gap exceeds a user-defined threshold and includes a delay period before entering the position. After entering, the position is held for a set number of periods before being closed.
Key Features:
1. Gap Threshold: The strategy defines an up gap when the gap size exceeds a specified threshold (in percentage terms). The gap threshold is an input parameter that allows customization based on the user’s preference.
2. Delay Period: After the gap occurs, the strategy waits for a delay period before initiating a long position. This delay can help mitigate any short-term volatility that might occur immediately after the gap.
3. Holding Period: Once the position is entered, it is held for a user-defined number of periods (holdingPeriods). This is to capture the potential post-gap trend continuation, as gaps often indicate strong directional momentum.
4. Gap Plotting: The strategy visually plots up gaps on the chart by placing a green label beneath the bar where the gap condition is met. Additionally, the background color turns green to highlight up-gap occurrences.
5. Exit Condition: The position is exited after the defined holding period. The strategy ensures that the position is closed after this time, regardless of whether the price is in profit or loss.
Scientific Background:
The gap theory has been widely studied in financial literature and is based on the premise that gaps in price often represent areas of significant support or resistance. According to research by Kaufman (2002), gaps in price action can be indicators of future price direction, particularly when they occur after a period of consolidation or a trend reversal. Moreover, Gaps and their Implications in Technical Analysis (Murphy, 1999) highlights that gaps can reflect imbalances between supply and demand, leading to high momentum and potential price continuation or reversal.
In trading strategies, utilizing gaps with specific conditions, such as delay and holding periods, can enhance the ability to capture significant price moves. The strategy’s delay period helps avoid potential market noise immediately after the gap, while the holding period seeks to capitalize on the price continuation that often follows gap formation.
This methodology aligns with momentum-based strategies, which rely on the persistence of trends in financial markets. Several studies, including Jegadeesh & Titman (1993), have documented the existence of momentum effects in stock prices, where past price movements can be predictive of future returns.
Conclusion:
This strategy incorporates gap detection and momentum principles, supported by empirical research in technical analysis, to attempt to capitalize on price movements following significant gaps. By waiting for a delay period and holding the position for a specified time, it aims to mitigate the risk associated with early volatility while maximizing the potential for sustained price moves.
DCA Alpha 1.0 Trading Tool for Dollar-Cost Averaging
Description:
DCA Alpha 1.0 is a precision-engineered trading tool designed to assist traders and investors in accumulating assets during market downturns. Using proprietary algorithms that combine momentum decay, extreme price deviation metrics, trend dynamics, divergence analysis, and mean regression, it identifies potential bottom extreme zones in various asset classes such as indices, stocks, crypto, and commodities.
This indicator highlights market conditions where assets are oversold, undervalued, or experiencing capitulation—providing disciplined, unleveraged dollar-cost averaging (DCA) opportunities. Ideal for long-term growth strategies, DCA Alpha 1.0 helps cut through market noise, pinpointing moments of peak fear and maximum reward potential.
Whether navigating volatile crypto markets, timing corrections in indices, or accumulating commodities, DCA Alpha 1.0 serves as a vital tool for mastering the art of buying low and building your assets up strategically.
Instructions:
Getting Started:
Add the Indicator:
Install DCA Alpha 1.0 on your TradingView chart.
Select your preferred asset class: stocks, indices, crypto, or commodities.
Choose an appropriate timeframe (e.g., daily or weekly for long-term DCA strategies).
Customize Inputs: Adjust the following settings to align with your strategy:
Percentage of Equity to Trade: Define the portion of your portfolio to allocate per signal (default: 1% equity).
Profit Target Percentages: Set thresholds for locking in gains (default: 50% on lower timeframes, 500% on higher timeframes).
Zones and Signals:
Extreme Negative Zones:
What It Represents:
These zones highlight conditions where prices are deeply oversold, indicating extreme bearish sentiment. The market is likely nearing a bottom, offering high-probability buying opportunities.
Entry Signals:
When the price enters these extreme negative zones, visual markers (e.g., green triangles or other indicators) will signal a potential buying opportunity. These moments are indicative of market exhaustion, signaling that a reversal could be imminent.
Momentum Decay & Divergence:
Momentum decay occurs when price movement slows over time. In extreme negative zones, if prices continue to fall but at a diminishing rate (e.g., decreased volume or a fading oscillator), it suggests weakening bearish momentum. This, coupled with bullish divergence (oscillator forming higher lows while price makes lower lows), signifies a reversal, making it an ideal point to consider dollar-cost averaging into the asset.
Neutral Zones:
What It Represents:
The neutral zone is a state of market equilibrium, where prices are neither overbought nor oversold. The market is in a balanced state, with no strong trend emerging.
Mean Regression:
In a neutral zone, the market is reverting to its mean or average price after overreacting in either direction. A price transition from extreme zones (overbought/oversold) to the neutral zone suggests a reversion to the market's long-term average, making this a period of reduced volatility and uncertainty.
Entering or Exiting Neutral Zones:
Traders should avoid entering or exiting positions during neutral zone conditions unless transitioning from an extreme zone (negative or positive). Transitioning from an extreme negative zone to neutral may suggest an opportunity to accumulate assets gradually, while a shift from neutral to an extreme negative zone may indicate a deeper correction and warrant caution.
Momentum Decay & Divergence (Exiting Neutral Zone):
If prices are rising but the oscillator shows lower highs (bearish divergence), and momentum is fading, this could signal a pullback. A transition out of the neutral zone in this context may prompt traders to hold off on new positions or consider profit-taking.
Extreme Positive Zones:
What It Represents:
Markets can also become overbought or overvalued. When price enters extreme positive zones, the asset may be overvalued, suggesting potential selling or a waiting period.
Exit Signals:
Red triangle indicators signal potential exit points when prices reach overbought conditions, signaling a time to lock in profits and reduce exposure.
Momentum Decay & Divergence (Exiting Positive Zone):
When prices are making new highs but momentum is weakening (momentum decay) and the oscillator is showing lower highs (bearish divergence), this could indicate a faltering rally. Such conditions represent an ideal time to reduce exposure or exit positions.
Key Inputs for Customization:
Percentage of Equity to Trade:
This setting allows you to allocate a portion of your total portfolio per buy signal. By default, 1% of equity is used per signal, but this can be adjusted based on your risk tolerance and strategy.
Profit Target Percentages:
These thresholds help lock in gains once the price moves a set percentage in your favor.
Lower Timeframes: Default profit target of 50%.
Higher Timeframes: Default profit target of 500%.
These settings can be customized for specific risk/reward preferences.
Warning!!! : Aggressive Mode
Aggressive Mode is an advanced feature designed for traders who want to increase the frequency of signals during periods of market volatility. This mode will trigger more frequent entries, even into slightly less extreme zones, capturing short-term reversals.
What Aggressive Mode Does:
It amplifies signals by allowing the tool to identify more frequent price reversals, including brief market corrections, increasing trade frequency. While this can offer more trading opportunities, it also exposes you to higher risk.
Warning:
Aggressive Mode should be used only by experienced traders familiar with short-term volatility. The increased frequency of signals could lead to higher risk exposure. Ensure robust risk management practices, such as stop-loss orders and profit-taking strategies, are in place before activating this mode.
Default Setting:
Aggressive Mode is disabled by default. It can be activated at your discretion based on your experience level and risk appetite.
Best Practices:
Focus on High-Quality Assets: Prioritize assets with strong recovery potential (e.g., major indices, blue-chip cryptocurrencies).
Use Longer Timeframes: Minimize market noise and optimize your DCA strategy by focusing on higher timeframes (e.g., daily or weekly charts).
Review Trading Inputs: Regularly adjust your inputs to ensure they align with your financial goals and risk tolerance.
Implement Risk Management: Use stop-loss orders and profit targets to manage risk, especially when using Aggressive Mode.
Disclaimer:
DCA Alpha 1.0 is designed specifically for unleveraged, long-term dollar-cost averaging strategies. It is not intended for day trading or leveraged positions. The tool excels at identifying market dips but cannot guarantee success. Users are fully responsible for their own risk management, including the use of stop-losses, profit targets, and position sizing.
Aggressive Mode increases trade frequency and may lead to higher exposure and potential losses. Only experienced traders should consider using this mode. Always understand the risks involved before incorporating this tool into your trading strategy.
DAILY Supertrend + EMA Crossover with RSI FilterThis strategy is a technical trading approach that combines multiple indicators—Supertrend, Exponential Moving Averages (EMAs), and the Relative Strength Index (RSI)—to identify and manage trades.
Core Components:
1. Exponential Moving Averages (EMAs):
Two EMAs, one with a shorter period (fast) and one with a longer period (slow), are calculated. The idea is to spot when the faster EMA crosses above or below the slower EMA. A fast EMA crossing above the slow EMA often suggests upward momentum, while crossing below suggests downward momentum.
2. Supertrend Indicator:
The Supertrend uses Average True Range (ATR) to establish dynamic support and resistance lines. These lines shift above or below price depending on the prevailing trend. When price is above the Supertrend line, the trend is considered bullish; when below, it’s considered bearish. This helps ensure that the strategy trades only in the direction of the overall trend rather than against it.
3. RSI Filter:
The RSI measures momentum. It helps avoid buying into markets that are already overbought or selling into markets that are oversold. For example, when going long (buying), the strategy only proceeds if the RSI is not too high, and when going short (selling), it only proceeds if the RSI is not too low. This filter is meant to improve the quality of the trades by reducing the chance of entering right before a reversal.
4. Time Filters:
The strategy only triggers entries during user-specified date and time ranges. This is useful if one wants to limit trading activity to certain trading sessions or periods with higher market liquidity.
5. Risk Management via ATR-based Stops and Targets:
Both stop loss and take profit levels are set as multiples of the ATR. ATR measures volatility, so when volatility is higher, both stops and profit targets adjust to give the trade more breathing room. Conversely, when volatility is low, stops and targets tighten. This dynamic approach helps maintain consistent risk management regardless of market conditions.
Overall Logic Flow:
- First, the market conditions are analyzed through EMAs, Supertrend, and RSI.
- When a buy (long) condition is met—meaning the fast EMA crosses above the slow EMA, the trend is bullish according to Supertrend, and RSI is below the specified “overbought” threshold—the strategy initiates or adds to a long position.
- Similarly, when a sell (short) condition is met—meaning the fast EMA crosses below the slow EMA, the trend is bearish, and RSI is above the specified “oversold” threshold—it initiates or adds to a short position.
- Each position is protected by an automatically calculated stop loss and a take profit level based on ATR multiples.
Intended Result:
By blending trend detection, momentum filtering, and volatility-adjusted risk management, the strategy aims to capture moves in the primary trend direction while avoiding entries at excessively stretched prices. Allowing multiple entries can potentially amplify gains in strong trends but also increases exposure, which traders should consider in their risk management approach.
In essence, this strategy tries to ride established trends as indicated by the Supertrend and EMAs, filter out poor-quality entries using RSI, and dynamically manage trade risk through ATR-based stops and targets.
