Trend Strategy + Impulse FilterThis is a Trend Strategy + Impulse Filter designed for trading in a dynamic market using both Simple Moving Average (SMA) and MACD indicators for trend and momentum analysis. The strategy includes risk management features like Stop Loss, Take Profit, and Trailing Stop to secure gains and limit losses. Additionally, it uses a Breakout Filter for confirmation, ensuring trades are taken only when the price breaks out from a specified range.
Key Features:
Trend Filter: Enter long when the price is above the SMA and MACD line crosses above the signal line. Enter short when the price is below the SMA and MACD line crosses below the signal line.
Breakout Filter: Only takes trades if the price breaks the previous high (for long) or low (for short) within a defined lookback period.
Risk Management: Set stop-loss and take-profit levels based on ATR for dynamic risk management.
Trailing Stop: Locks profits as the price moves in favor of the trade.
Position Sizing: Trade size is based on a percentage of the current equity.
Customizable Parameters: All indicators and risk management settings are adjustable to fit individual preferences.
This strategy is suitable for traders looking for a comprehensive approach that combines trend-following, momentum, and breakout filtering with solid risk management.
Ukrainian Description:
Це стратегія Trend + Impulse Filter, розроблена для торгівлі на динамічному ринку, використовуючи індикатори Простого ковзаючого середнього (SMA) та MACD для аналізу тренду та імпульсу. Стратегія включає в себе функції управління ризиками, такі як Stop Loss, Take Profit та Trailing Stop, щоб забезпечити прибутки та обмежити збитки. Крім того, вона використовує Breakout Filter для підтвердження, забезпечуючи виконання угод лише тоді, коли ціна пробиває визначений діапазон.
Основні характеристики:
Фільтр тренду: Вхід у лонг, коли ціна вище SMA, і MACD лінія перетинає сигнальну лінію знизу вгору. Вхід у шорт, коли ціна нижча за SMA, і MACD лінія перетинає сигнальну лінію зверху вниз.
Фільтр пробою: Торгові угоди відкриваються лише в разі пробою попереднього максимуму (для лонга) або мінімуму (для шорта) протягом заданого періоду.
Управління ризиками: Стоп-лосс та тейк-профіт визначаються на основі ATR для динамічного управління ризиками.
Trailing Stop: Фіксує прибутки, коли ціна рухається в бік угоди.
Розмір позиції: Розмір угоди залежить від відсотка від поточного балансу.
Налаштовувані параметри: Усі індикатори та налаштування управління ризиками можна відкоригувати відповідно до індивідуальних уподобань.
Ця стратегія підходить для трейдерів, які шукають комплексний підхід, що поєднує слідкування за трендом, імпульсом та фільтрацією пробоїв із надійним управлінням ризиками.
Médias Móveis
Blood IndicatorBlood Indicator
Weekly (FRED:TB3MS / FRED:BAMLH0A0HYM2) plotted against the 100 WK MA. If red be ready for a sell off. Use Confluence in price action to confirm trades.
Combined + Reversal By DemirkanThis indicator is a comprehensive tool designed to identify potential trend reversals, trend direction, and entry/exit points by combining multiple technical analysis instruments. It includes the following components:
Two Reversal Lines (Based on Donchian Channel): Two lines with different periods indicate potential support/resistance levels and trend changes.
Hull Moving Average (HMA): A smoother, less lagging moving average helps determine trend direction and short-term momentum.
Fibonacci Level: A dynamic Fibonacci retracement level, calculated based on the highest high and lowest low over a specific period, serves as a potential support or area of interest.
Signal Generation: Produces Buy/Sell signals based on the crossovers and conditions of these components.
Visual Aids: Enhances interpretation by coloring the area between lines, coloring candlesticks, and adding labels.
Detailed Component Description:
Input Parameters (Settings):
Reversal Line 1 Length (Default: 100): The period (number of bars) used to calculate the first reversal line. Longer periods capture slower, more significant trends.
Reversal Line 2 Length (Default: 33): The period used to calculate the second reversal line. Shorter periods react to faster, shorter-term changes.
HMA Length (Default: 100): The period for calculating the Hull Moving Average.
Source (Default: close): The price source used for all calculations (close, open, high, low, etc.).
Reversal Line Bar Offset (Default: 3): Determines how many bars forward the Reversal Lines are shifted on the chart. This can make signals appear slightly earlier (or later, depending on the strategy). 0 means no shift.
Fibonacci Level (Default: 0.382): Specifies the Fibonacci retracement level (between 0.0 and 1.0). Common levels like 0.382, 0.5, 0.618 can be used.
Lookback Period (Default: 20): The period (number of bars) over which to look back for the highest high and lowest low to calculate the Fibonacci level.
Price Margin (Default: 0.005): Tolerance (as a percentage) determining how close the price needs to be to the Fibonacci level to be considered "at the level". E.g., 0.005 = 0.5%. If the price is within 0.5% of the calculated Fibonacci level, the condition is met.
Calculations:
donchian(len) Function: Calculates the average (math.avg) of the highest high (ta.highest) and lowest low (ta.lowest) over a specific period (len). This is effectively the midline of a classic Donchian Channel and is used here as the "Reversal Line".
Reversal Lines (conversionLine1, conversionLine2): Calculated using the donchian function based on the user-defined conversionPeriods1 and conversionPeriods2 lengths.
Hull Moving Average (hullMA): Calculated using the hma function. This function uniquely combines Weighted Moving Averages (WMA) to achieve less lag.
Fibonacci Level Calculation (fibLevel1, isAtFibLevel): Finds the highest high and lowest low within the lookbackPeriod, calculates the range (priceRange). fibLevel1 is determined by subtracting priceRange * fibLevel from the highest high (representing a retracement level). isAtFibLevel checks if the current closing price is within the priceMargin tolerance of the calculated fibLevel1.
Visual Elements (Plots/Drawing):
plot(conversionLine1 , ...): Plots the first reversal line in blue, shifted forward by barOffset.
plot(conversionLine2 , ...): Plots the second reversal line in black, shifted forward by barOffset.
plot(hullMA, ...): Plots the Hull Moving Average in orange.
plot(fibLevel1, ...): Plots the calculated Fibonacci level as a light blue, dashed line.
fill(...): Fills the area between the two (shifted) reversal lines. The area is colored blue if conversionLine1 > conversionLine2 (often interpreted as bullish) and red otherwise (bearish). The color transparency is set to 90 (almost opaque).
label.*: Adds labels at trend change points. A "Buy" label appears when the area turns blue (Line 1 crosses above Line 2), and a "Sell" label appears when it turns red (Line 1 crosses below Line 2). Labels appear once when the trend starts and are updated/deleted when the trend changes.
plotshape(...): Plots shapes (arrows/labels) on the chart when specific conditions are met:
Reversal Crossover Signals: A green up arrow (shape.labelup) appears when conversionLine2 crosses above conversionLine1 (Buy Signal - buySignal). A red down arrow (shape.labeldown) appears when conversionLine1 crosses below conversionLine2 (Sell Signal - sellSignal).
Hull MA Signals: A green up arrow (hullBuySignal) appears when the price closes above the HMA after being below it. A red down arrow (hullSellSignal) appears when the price closes below the HMA after being above it.
Fibonacci Buy Signal: A purple up arrow (fibBuySignal) appears when both the price is near the calculated Fibonacci level (isAtFibLevel) and a Hull MA Buy signal (hullBuySignal) occurs simultaneously. This signifies a "confluence" signal.
barcolor(...): Changes the color of the candlesticks. Bars turn blue on a Hull MA Buy signal (hullBuySignal) and red on a Hull MA Sell signal (hullSellSignal). Otherwise, the bar color remains the default chart color.
How to Use / Interpret:
Trend Direction:
Observe the color of the filled area between the reversal lines (Blue = Uptrend, Red = Downtrend).
Note whether the price is above or below the Hull MA.
Consider the slope of the Hull MA (upward or downward).
Entry/Exit Signals:
Aggressive: Use the crossovers of the reversal lines (buySignal, sellSignal). Green arrow suggests buy, red arrow suggests sell.
Trend Following: Use the HMA crossovers (hullBuySignal, hullSellSignal). Green arrow suggests buy, red arrow suggests sell. The bar colors also confirm these signals visually.
Confirmed Buy: Look for the Fibonacci Buy Signal (Purple arrow). When the price reaches a potential support level (Fibonacci) and simultaneously gets an HMA Buy signal, it can be considered a stronger buy indication.
Support/Resistance:
The reversal lines themselves can act as dynamic support/resistance levels.
The plotted Fibonacci level (fibLevel1) can be monitored as a potential retracement and support zone.
Strategy:
Confluence (multiple signals aligning) can increase confidence. For example, a buySignal or hullBuySignal occurring while the HMA is pointing up and the fill area is blue might be considered stronger.
Adjust the barOffset parameter to fine-tune the timing of the visual signals according to your trading style.
Use the Fibonacci Buy signal to potentially find entry points after pullbacks in an uptrend or near potential bottoms after a decline.
Important Notes:
No single indicator provides 100% accurate signals. It's crucial to use this indicator in conjunction with other analysis methods (price action, chart patterns, volume, etc.) and sound risk management strategies.
The indicator's performance might vary in different market conditions (trending, sideways) and across different timeframes. Backtesting before live trading is recommended.
The barOffset value shifts the plotting of the lines forward visually but does not change the time at which the underlying calculation occurs (it's still based on the data up to the current closing bar).
Dskyz Adaptive Futures Edge (DAFE)imgur.com/a/igj9lFj
Dskyz Adaptive Futures Edge (DAFE) is a futures trading strategy designed to adapt dynamically to market volatility and price action using a blend of technical indicators. The strategy combines adaptive moving averages, optional RSI filtering, candlestick pattern recognition, and multi-timeframe trend analysis to generate long and short trade signals. It incorporates robust risk management techniques including ATR-based stop-losses and trailing stops, ensuring trades are sized and managed within sustainable risk limits.
Key Components and Logic
-Adaptive Moving Averages
Dynamic Calculation: Fast and slow Simple Moving Averages (SMAs) adapt to changing volatility, making them sensitive to high-momentum shifts and smoothing during quieter price action.
Signal Generation: Entry signals are triggered when the fast SMA crosses the slow SMA in conjunction with price direction confirmation (e.g., price above both for long positions).
-RSI Filtering (Optional)
Momentum Confirmation: The RSI filter provides momentum confirmation to avoid overextended entries. It can be toggled on or off for both long and short conditions.
User Control: Adjustable parameters such as lookback period, oversold/overbought thresholds, and enable/disable switches give full control over its influence.
-Candlestick Pattern Recognition
Engulfing Logic: Recognizes strong bullish or bearish engulfing patterns with configurable strength criteria like range and volume. Patterns are filtered by trend direction and strength for confirmation.
Signal Conflict Handling: When both bullish and bearish engulfing patterns occur within the lookback window, the strategy avoids entry to reduce whipsaws in indecisive markets.
-Multi-Timeframe Trend Filter
Higher Timeframe Filtering: Incorporates 15-minute trend direction as a macro-level filter to align intrabar trades with larger trend momentum.
Smoothed Entry Logic: Prevents entering trades that go against the broader market structure, reducing false signals in choppy or low-conviction moves.
-Trade Execution and Risk Management
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Entry Logic
Priority System: Users can define whether moving average signals or candlestick patterns should take priority when both are present.
Volume & Volatility Checks: Ensures sufficient market participation and action before entering a position, improving the odds of reliable follow-through.
Stop-Loss and Trailing Exit
ATR-Based Initial Stops: Dynamically adjusts stop-loss distance based on market volatility using a multiple of ATR (Average True Range), keeping risk proportional to price swings.
Trailing Stop: Protects open profits and enables winners to run by following price action at a set distance (also ATR-based).
-Cooldown Period & Minimum Bar Hold (Trade Discipline Logic)
Cooldown Bars: After an exit, the strategy imposes a mandatory pause before opening a new position.
Why: This avoids rapid-fire re-entries triggered by minor fluctuations that could lead to overtrading and degradation of profitability.
Minimum Bar Hold: A trade must be held for a minimum number of bars before it can be exited.
Why: This prevents the strategy from immediately exiting trades due to fleeting volatility spikes, which previously caused premature exits that often reversed back in favor of the original signal. This ensures trades have adequate time to develop, filtering out noise from true reversals.
-Visual Elements and Transparency Tools
Chart Overlays: Moving averages, RSI values, and trade entry/exit points are shown directly on the chart for complete visibility.
Dashboard UI: Displays critical live metrics—current position, PnL, time held, ATR values, etc.
Debug Logs: Optional toggles allow verbose condition tracking for deep inspection into why a trade occurred (or didn't), useful for both live optimization and debugging.
-Input Parameter Reference Guide
Input Name Function & Suggested Use
Use RSI Filter - Enables or disables RSI-based entry confirmation. Disable if price action alone is desired for entry decisions.
RSI Length - RSI lookback period. Lower values (e.g., 7–14) are more responsive; higher values reduce false signals.
Overbought / Oversold Levels - Used to detect exhaustion zones. E.g., avoid long entries above 70 or short entries below 30.
Use Candlestick Patterns - Enable detection of bullish/bearish engulfing patterns as trade signals. Disable to rely only on trend/MA.
Pattern Strength Thresholds (Range, Volume) - Filters out weak engulfing signals. Higher values require stronger patterns to trigger.
Use 15min Trend Filter - Adds multi-timeframe trend confirmation. Recommended for filtering entries against larger trend direction.
Fast MA - Base Length for fast adaptive moving average. Suggested: 10–25.
Slow MA - Base length for slow adaptive moving average. Suggested: 30–60.
Volatility Sensitivity Multiplier - Multiplies volatility adjustments for adaptive MA length. Higher = more reactive to volatility.
Entry Volume Filter - Filters out trades during low volume. Recommended to prevent entries in illiquid conditions.
ATR Length - Lookback period for ATR calculation. Suggested: 14.
Trailing Stop ATR Offset - Defines how far the stop-loss is from entry. 1.5–2.5 is typical for medium-volatility environments.
Trailing Stop ATR Multiplier - Determines trailing stop distance. 1.5 is tight; 3+ gives more room for trending trades.
Cooldown Bars After Exit - Prevents immediate re-entries. Suggested: 3–10 bars depending on timeframe.
Minimum Bars to Hold Trade - Ensures trades are held long enough to avoid knee-jerk exits. Suggested: 5–10 for intraday strategies.
Trading Hours (Start / End) - Sets the window of allowed trading. Prevents entries outside key session times (e.g., avoid pre-market).
Enable Logging / Debugging - Shows internal trade decision data for tuning and understanding the logic.
Compliance with TradingView Regulations
Realistic Backtesting: The strategy uses proper initial capital, fixed trade quantities, and risk parameters to reflect realistic scenarios.
Transparent Trade Logic: Every condition used for signal generation is documented and controllable by the user. Users can view each signal's rationale.
Risk Mitigation: Cooldown bars, ATR stops, and minimum trade duration ensure the strategy behaves predictably and prevents reckless trade behavior.
Customization: Full control over each module (MA, RSI, Candlestick, Trend, etc.) gives users the ability to tailor the strategy to suit various futures contracts or timeframes.
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Summary
DAFE was built for high-stakes micro futures trading environments such as the MNQ, where milliseconds of volatility matter. This strategy's modular architecture, adaptive logic, and advanced risk controls make it an ideal framework for scalpers and swing traders alike.
BTCUSDT.P
Backtesting: www.dropbox.com
Deep Backtesting:
www.dropbox.com
****Currently testing on a prop account.
Caution Statement
This strategy is designed for educational and experimental purposes and should not be considered financial advice or a guaranteed method of profitability. While the DAFE (Dskyz Adaptive Futures Edge) strategy incorporates advanced filters, adaptive logic, and volatility-based risk management, its performance is subject to market conditions, data accuracy, and user configuration.
Futures trading involves substantial risk, and the leverage inherent in futures contracts can amplify both gains and losses. This strategy may execute trades rapidly and frequently under certain conditions—particularly when filters are disabled or thresholds are set too tightly—potentially leading to increased slippage, commissions, or unanticipated losses.
Users are strongly advised to:
Backtest thoroughly across various market regimes.
Adjust parameters responsibly and understand the implication of each input.
Paper trade in a simulated environment before going live.
Monitor trades actively and use discretion when market volatility increases.
-By using this strategy, you accept all risks and responsibility for any trading decisions made based on its output.
SEMA JMA | QuantEdgeB
📈 Introducing SEMA JMA by QuantEdgeB
🛠️ Overview
SEMA JMA is a precision-engineered, dual-signal trend indicator that blends Jurik Moving Average (JMA) logic with Double Exponential Moving Average (DEMA) smoothing and normalized statistical filters.
This advanced indicator is built for high-quality trend detection, reducing false signals by confirming momentum through both price-based SD bands and normalized JMA logic. The result is a powerful, noise-filtered tool ideal for directional trading in volatile and ranging environments.
SEMA JMA offers adaptive volatility bands, backtest-ready analytics, and dynamic signal labeling, making it a favorite for traders demanding speed, precision, and strategic clarity.
✨ Key Features
🔹 Hybrid JMA + DEMA Core
Combines the ultra-smooth JMA with lag-reducing DEMA for exceptional trend clarity.
🔹 Volatility-Based SD Band Filtering
Uses rolling standard deviation on JMA for adaptive long/short bands that respond to market dynamics.
🔹 Normalized Price Filter Confirmation
A second JMA stream is normalized against price and filtered via SD for added trend confirmation and false signal suppression.
🔹 Backtest Integration & Equity Curve Plotting
Built-in compatibility with QuantEdgeB/BacktestingIndV2, delivering historical metrics, equity visualization, and strategic evaluation.
🔹 Fully Customizable UI
Includes label toggles, signal overlays, visual themes, and backtest table position selection.
📊 How It Works
1️⃣ JMA-DEMA Hybrid Trend Engine
The foundation of SEMA JMA lies in a custom-built JMA engine, enhanced by a DEMA smoothing layer to:
• Minimize lag without losing trend integrity.
• Maintain responsiveness in noisy or low-volume environments.
• Create a central trend structure used by both raw price and normalized filters.
2️⃣ Standard Deviation Band Filtering
SEMA JMA applies a rolling SD filter over the JMA signal. This creates adaptive upper and lower bands:
• Long Signal = Price > Upper Band
• Short Signal = Price < Lower Band
These bands adjust based on price volatility, offering a dynamic alternative to traditional fixed thresholds.
3️⃣ Normalized JMA for Momentum Confirmation
A second JMA-DEMA structure is normalized by dividing by price, then smoothed:
• If the normalized signal rises above -1, it suggests upside pressure.
• If it drops below -1, it signals momentum decay.
Only when both raw and normalized signals agree does the indicator issue a trade trigger.
✅ Signal Logic
📌 Long Signal →
🔹 Price breaks above volatility-adjusted upper SD band
🔹 AND Normalized JMA rises above -1
📌 Short Signal →
🔹 Price breaks below lower SD band
🔹 AND Normalized JMA falls below -1
⚙️ SEMA JMA stays in its active trend state until an opposing signal triggers, enabling tren riding while filtering short lived swings.
👥 Who Should Use It?
✅ Swing & Trend Traders → Ride strong directional moves with reduced whipsaws
✅ Volatility-Adaptive Systems → Filter trades using rolling SD-based thresholds
✅ Quantitative Strategy Builders → Deploy within algo-driven strategies using backtest-ready metrics
✅ Risk-Aware Traders → Use dual confirmation to minimize signal risk
⚙️ Customization & Default Settings
🔧 Core Settings:
• JMA Length (Default: 35) → Defines JMA sensitivity.
• DEMA Length (Default: 20) → Smoothing after JMA to refine structure.
• Normalized JMA Lengths → Control confirmation layer smoothness (default: 1 for short and long).
• Standard Deviation Length (Default: 30) → Determines the volatility lookback.
• SD Weight Factors → Separate values for long (default: 1.0) and short (default: 1.002) bands.
📊 Backtest Mode
SEMA JMA includes an optional backtest table, enabling traders to assess its historical effectiveness before applying it in live trading conditions.
🔹 Backtest Metrics Displayed:
• Equity Max Drawdown → Largest historical loss from peak equity.
• Profit Factor → Ratio of total profits to total losses, measuring system efficiency.
• Sharpe Ratio → Assesses risk-adjusted return performance.
• Sortino Ratio → Focuses on downside risk-adjusted returns.
• Omega Ratio → Evaluates return consistency & performance asymmetry.
• Half Kelly → Optimal position sizing based on risk/reward analysis.
• Total Trades & Win Rate → Assess historical success rate.
📌 Disclaimer:
Backtest results are based on past performance and do not guarantee future success. Always incorporate real-time validation and risk management in live trading.
🚀 Why This Matters?
✅ Strategy Validation → Gain insight into historical trend accuracy.
✅ Customization Insights → See how different settings impact performance.
✅ Risk Awareness → Understand potential drawdowns before deploying capital.
📌 How to Use SEMA JMA
🌀 Trend-Following Strategy
✔ Go Long: When price breaks above SD band and normalized momentum rises
✔ Go Short: When price breaks below SD band and normalized momentum falls
✔ Stay in position: Until signal reversal confirms
⚙️ Volatility-Adaptive Configuration
✔ Tune w1 (Long SD weight) and w2 (Short SD weight) for responsiveness
✔ Increase SD length in noisy markets for smoother bands
📌 Conclusion
SEMA JMA by QuantEdgeB delivers surgical precision trend signals using a dual-layer approach:
• JMA + DEMA core smoothing
• Statistical SD breakout filters
• Normalized confirmation logic
It’s a versatile indicator suited for trend-following, volatility tracking, and system-based signal generation—engineered for clarity, confidence, and adaptability.
🔹 Key Takeaways:
1️⃣ Multi-Filter Trend Logic – JMA + DEMA + Normalized filtering for high-confidence signals
2️⃣ SD-Based Volatility Control – Reduces noise, avoids ATR limitations
3️⃣ Quant-Ready System – Includes full backtesting
📌 Master your market edge with precision – SEMA JMA | QuantEdgeB
🔹 Disclaimer: Past performance is not indicative of future results.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
14 EMA & RSI Combo with First Buy/SellEMA14 & RSI stratergy - Used as a indication for BUY and Sell based on EMA 14 and RSI. Chk for higher timeframe trend and stick to the entries that are following the trend
50 EMA Crossover With Monthly DCARecommended Chart Interval = 1W
Overview:
This strategy combines trend-following principles with dollar-cost averaging (DCA), aiming to efficiently deploy capital while minimizing market timing risk.
How It Works:
When the Long Condition is Not Met (i.e., Price < 50 EMA):
- If the price is below the 50 EMA, a fixed DCA amount is added to a cash reserve every month.
- This ensures that capital is consistently accumulated, even when the strategy isn't in a long position.
When the Long Condition is Met (i.e., Price > 50 EMA):
- A long position is opened when the price is above the 50 EMA.
- At this point, the entire capital, including the accumulated cash reserve, is deployed into the market.
- While the strategy is long, a DCA buy order is placed every month using the set DCA amount, continuously investing as the market conditions allow.
Exit Strategy:
If the price falls below the 50 EMA, the strategy closes all positions, and the cash reserve accumulation process begins again.
Key Benefits:
✔ Systematic Investing: Ensures consistent capital deployment while following trend signals.
✔ Cash Efficiency: Accumulates uninvested funds when conditions aren’t met and deploys them at optimal moments.
✔ Risk Management: Exits when the price trend weakens, protecting capital.
Conclusion:
This method allows for efficient capital growth by combining a trend-following approach with disciplined DCA, ensuring risk is managed while capital is deployed systematically at optimal points in the market. 🚀
Trailing Monster StrategyTrailing Monster Strategy
This is an experimental trend-following strategy that incorporates a custom adaptive moving average (PKAMA), RSI-based momentum filtering, and dynamic trailing stop-loss logic. It is designed for educational and research purposes only, and may require further optimization or risk management considerations prior to live deployment.
Strategy Logic
The strategy attempts to participate in sustained price trends by combining:
- A Power Kaufman Adaptive Moving Average (PKAMA) for dynamic trend detection,
- RSI and Simple Moving Average (SMA) filters for market condition confirmation,
- A delayed trailing stop-loss to manage exits once a trade is in profit.
Entry Conditions
Long Entry:
- RSI exceeds the overbought threshold (default: 70),
- Price is trading above the 200-period SMA,
- PKAMA slope is positive (indicating upward momentum),
- A minimum number of bars have passed since the last entry.
Short Entry:
- RSI falls below the oversold threshold (default: 30),
- Price is trading below the 200-period SMA,
- PKAMA slope is negative (indicating downward momentum),
-A minimum number of bars have passed since the last entry.
Exit Conditions
- A trailing stop-loss is applied once the position has been open for a user-defined number of bars.
- The trailing distance is calculated as a fixed percentage of the average entry price.
Technical Notes
This script implements a custom version of the Power Kaufman Adaptive Moving Average (PKAMA), conceptually inspired by alexgrover’s public implementation on TradingView .
Unlike traditional moving averages, PKAMA dynamically adjusts its responsiveness based on recent market volatility, allowing it to better capture trend changes in fast-moving assets like altcoins.
Disclaimer
This strategy is provided for educational purposes only.
It is not financial advice, and no guarantee of profitability is implied.
Always conduct thorough backtesting and forward testing before using any strategy in a live environment.
Adjust inputs based on your individual risk tolerance, asset class, and trading style.
Feedback is encouraged. You are welcome to fork and modify this script to suit your own preferences and market approach.
Scalping all timeframe EMA & RSIEMA 50 and EMA 100 combined with RSI 14
Should also be accompanied by the RSI 14 chart.
With the following conditions:
IF the EMAs are close but not crossing:
* Be prepared to take a Sell position if the first Bearish Candlestick crosses the lowest EMA, and the RSI value is equal to or below 40.
* Be prepared to take a Buy position if the first Bullish Candlestick crosses the highest EMA, and the RSI value is equal to or above 60.
IF the EMAs are overlapping and crossing:
* Be prepared to take a Sell position if the first Bearish Candlestick crosses both EMAs, and the RSI value crosses below 50.
*Be prepared to take a Buy position if the first Bullish Candlestick crosses both EMAs, and the RSI value crosses above 50.
P-Motion Trend | QuantEdgeB⚡ Introducing P-Motion Trend (PMT) by QuantEdgeB
🧭 Overview
P-Motion Trend is a refined trend-following framework built for modern market dynamics. It combines DEMA filtering, percentile-based smoothing, and volatility-adjusted envelopes to create a clear, noise-filtered trend map directly on your chart.
This overlay indicator is engineered to detect breakout zones, trend continuation setups, and market regime shifts with maximum clarity and minimum lag.
Whether you're swing trading crypto, managing intraday FX moves, or positioning in equities — P-Motion Trend adapts, aligns, and simplifies.
🧠 Core Logic
1️⃣ DEMA Filtering Core
The input source is processed through a Double EMA to reduce lag while retaining trend sensitivity.
2️⃣ Percentile Median Smoothing
To eliminate short-lived spikes, the DEMA output is passed through a percentile median rank — effectively smoothing without distortion.
3️⃣ Volatility Envelope with EMA Basis
An exponential moving average (EMA) is applied to the smoothed median, and standard deviation bands are wrapped around it:
• ✅ Long Signal → Price closes above the upper band
• ❌ Short Signal → Price closes below the lower band
• ➖ Inside Band = Neutral
These bands expand/contract with market volatility — protecting against false breakouts in quiet regimes and adapting quickly to strong moves.
📊 Visual & Analytical Layers
• 🎯 Bar Coloring: Color-coded candles highlight trend state at a glance.
• 📈 EMA Ribbon Overlay: A dynamic ribbon of EMAs helps confirm internal momentum and detect transitions (trend decay or acceleration).
• 🔹Gradient Fill Zones: Visually communicates squeeze vs. expansion phases based on band width.
⚙️ Custom Settings
• EMA Length – Defines the core trend path (default: 21)
• SD Length – Controls volatility band smoothing (default: 30)
• SD Mult Up/Down – Sets thresholds for breakout confirmation (default: 1.5)
• DEMA Filter Source – Raw input used for trend processing
• DEMA Filter Length – Sets DEMA smoothing (default: 7)
• Median Length – Percentile-based smoothing window (default: 2)
📌 Use Cases
✅ Trend Confirmation
Use PMT to confirm whether the price action is structurally valid for trend continuation. A close above the upper band signals entry alignment.
🛡️ Reversal Guard
Avoid early reversion entries. PMT keeps you in-trend until price truly breaks structure.
🔍 Momentum Visualizer
With multiple EMA bands, the indicator also functions as a momentum envelope to spot divergence between price and smoothed trend flow.
🔚 Conclusion
P-Motion Trend is a hybrid volatility + trend system built with precision smoothing, dynamic filtering, and clean visual output. It balances agility with stability, helping you:
• Filter out price noise
• Enter with structure
• Stay in trades longer
• Exit with confidence
🧩 Summary of Benefits
• 🔹 Lag-minimized trend structure via DEMA core
• 🔹 Real-time volatility band adaptation
• 🔹 Gradient visual feedback on compression/expansion
• 🔹 EMA ribbon assists in phase detection
• 🔹 Suitable for all markets & timeframes
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
DEGA RMA | QuantEdgeB🧠 Introducing DEGA RMA (DGR ) by QuantEdgeB
🛠️ Overview
DEGA RMA (DGR) is a precision-engineered trend-following system that merges DEMA, Gaussian kernel smoothing, and ATR-based envelopes into a single, seamless overlay indicator. Its mission: to filter out market noise while accurately capturing directional bias using a layered volatility-sensitive trend core.
DGR excels at identifying valid breakouts, sustained momentum conditions, and trend-defining price behavior without falling into the trap of frequent signal reversals.
🔍 How It Works
1️⃣ Double Exponential Moving Average (DEMA)
The system begins by applying a DEMA to the selected price source. DEMA responds faster than a traditional EMA, making it ideal for capturing transitions in momentum.
2️⃣ Gaussian Filtering
A custom Gaussian kernel is used to smooth the DEMA signal. The Gaussian function applies symmetrical weights, centered around the most recent bar, effectively softening sharp price oscillations while preserving the underlying trend structure.
3️⃣ Recursive Moving Average (RMA) Core
The filtered Gaussian output is then processed through an RMA to generate a stable dynamic baseline. This baseline becomes the foundation for the final trend logic.
4️⃣ ATR-Scaled Breakout Zones
Upper and lower trend envelopes are calculated using a custom ATR filter built on DEMA-smoothed volatility.
• ✅ Long Signal when price closes above the upper envelope
• ❌ Short Signal when price closes below the lower envelope
• ➖ Neutral when inside the band (no signal noise)
✨ Key Features
🔹 Multi-Layer Trend Model
DEMA → Gaussian → RMA creates a signal structure that is both responsive and robust.
🔹 Volatility-Aware Entry System
Adaptive ATR bands adjust in real-time, expanding during high volatility and contracting during calm periods.
🔹 Noise-Reducing Gaussian Kernel
Sigma-adjustable kernel ensures signal smoothness without introducing excessive lag.
🔹 Clean Visual System
Candle coloring and band fills make trend state easy to read and act on at a glance.
⚙️ Custom Settings
• DEMA Source – Input source for trend core (default: close)
• DEMA Length – Length for initial smoothing (default: 30)
• Gaussian Filter Length – Determines smoothing depth (default: 4)
• Gaussian Sigma – Sharpness of Gaussian curve (default: 2.0)
• RMA Length – Core baseline smoothing (default: 12)
• ATR Length – Volatility detection period (default: 40)
• ATR Mult Up/Down – Controls the upper/lower threshold range for signals (default: 1.7)
📌 How to Use
1️⃣ Trend-Following Mode
• Go Long when price closes above the upper ATR band
• Go Short when price closes below the lower ATR band
• Remain neutral otherwise
2️⃣ Breakout Confirmation Tool
DGR’s ATR-based zone logic helps validate price breakouts and filter out false signals that occur inside compressed ranges.
3️⃣ Volatility Monitoring
Watch the ATR envelope width — a narrowing band often precedes expansion and potential directional shifts.
📌 Conclusion
DEGA RMA (DGR) is a thoughtfully constructed trend-following framework that goes beyond basic moving averages. Its Gaussian smoothing, adaptive ATR thresholds, and layered filtering logic provide a versatile solution for traders looking for cleaner signals, less noise, and real-time trend awareness.
Whether you're trading crypto, forex, or equities — DGR adapts to volatility while keeping your chart clean and actionable.
🔹 Summary
• ✅ Advanced Smoothing → DEMA + Gaussian + RMA = ultra-smooth trend core
• ✅ Volatility-Adjusted Zones → ATR envelope scaling removes whipsaws
• ✅ Fully Customizable → Tailor to any asset or timeframe
• ✅ Quant-Inspired Structure → Built for clarity, consistency, and confidence
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Gaussian Smooth Trend | QuantEdgeB🧠 Introducing Gaussian Smooth Trend (GST) by QuantEdgeB
🛠️ Overview
Gaussian Smooth Trend (GST) is an advanced volatility-filtered trend-following system that blends multiple smoothing techniques into a single directional bias tool. It is purpose-built to reduce noise, isolate meaningful price shifts, and deliver early trend detection while dynamically adapting to market volatility.
GST leverages the Gaussian filter as its core engine, wrapped in a layered framework of DEMA smoothing, SMMA signal tracking, and standard deviation-based breakout thresholds, producing a powerful toolset for trend confirmation and momentum-based decision-making.
🔍 How It Works
1️⃣ DEMA Smoothing Engine
The indicator begins by calculating a Double Exponential Moving Average (DEMA), which provides a responsive and noise-resistant base input for subsequent filtering.
2️⃣ Gaussian Filter
A custom Gaussian kernel is applied to the DEMA signal, allowing the system to detect smooth momentum shifts while filtering out short-term volatility.
This is especially powerful during low-volume or sideways markets where traditional MAs struggle.
3️⃣ SMMA Layer with Z-Filtering
The filtered Gaussian signal is then passed through a custom Smoothed Moving Average (SMMA). A standard deviation envelope is constructed around this SMMA, dynamically expanding/contracting based on market volatility.
4️⃣ Signal Generation
• ✅ Long Signal: Price closes above Upper SD Band
• ❌ Short Signal: Price closes below Lower SD Band
• ➖ No trade: Price stays within the band → market indecision
✨ Key Features
🔹 Multi-Stage Trend Detection
Combines DEMA → Gaussian Kernel → SMMA → SD Bands for robust signal integrity across market conditions.
🔹 Gaussian Adaptive Filtering
Applies a tunable sigma parameter for the Gaussian kernel, enabling you to fine-tune smoothness vs. responsiveness.
🔹 Volatility-Aware Trend Zones
Price must close outside of dynamic SD envelopes to trigger signals — reducing whipsaws and increasing signal quality.
🔹 Dynamic Color-Coded Visualization
Candle coloring and band fills reflect live trend state, making the chart intuitive and fast to read.
⚙️ Custom Settings
• DEMA Source: Price stream used for smoothing (default: close)
• DEMA Length: Period for initial exponential smoothing (default: 7)
• Gaussian Length / Sigma: Controls smoothing strength of kernel filter
• SMMA Length: Final smoothing layer (default: 12)
• SD Length: Lookback period for standard deviation filtering (default: 30)
• SD Mult Up / Down: Adjusts distance of upper/lower breakout zones (default: 2.5 / 1.8)
• Color Modes: Six distinct color palettes (e.g., Strategy, Warm, Cool)
• Signal Labels: Toggle on/off entry markers ("𝓛𝓸𝓷𝓰", "𝓢𝓱𝓸𝓻𝓽")
📌 Trading Applications
✅ Trend-Following → Enter on confirmed breakouts from Gaussian-smoothed volatility zones
✅ Breakout Validation → Use SD bands to avoid false breakouts during chop
✅ Volatility Compression Monitoring → Narrowing bands often precede large directional moves
✅ Overlay-Based Confirmation → Can complement other QuantEdgeB indicators like K-DMI, BMD, or Z-SMMA
📌 Conclusion
Gaussian Smooth Trend (GST) delivers a precision-built trend model tailored for modern traders who demand both clarity and control. The layered signal architecture, combined with volatility awareness and Gaussian signal enhancement, ensures accurate entries, clean visualizations, and actionable trend structure — all in real-time.
🔹 Summary Highlights
1️⃣ Multi-stage Smoothing — DEMA → Gaussian → SMMA for deep signal integrity
2️⃣ Volatility-Aware Filtering — SD bands prevent false entries
3️⃣ Visual Trend Mapping — Gradient fills + candle coloring for clean charts
4️⃣ Highly Customizable — Adapt to your timeframe, style, and volatility
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Z SMMA | QuantEdgeB📈 Introducing Z-Score SMMA (Z SMMA) by QuantEdgeB
🛠️ Overview
Z SMMA is a momentum-driven oscillator designed to track the standardized deviation of a Smoothed Moving Average (SMMA). By applying Z-score normalization, this tool dynamically adapts to price volatility, enabling traders to detect meaningful directional shifts and trend changes with enhanced clarity.
It serves both as a trend-following and mean-reversion system, identifying opportunities through standardized thresholds while remaining robust across volatile and calm market conditions.
✨ Key Features
🔹 Z-Score Normalization Engine
Applies Z-score to a custom SMMA baseline, allowing traders to compare price action relative to its recent volatility-adjusted mean.
🔹 Dynamic Trend Detection
Generates actionable long/short signals based on customizable Z-thresholds, making it adaptable across different asset classes and timeframes.
🔹 Overbought/Oversold Zones
Highlight reversion and profit-taking zones (default OB: +2 to +4, OS: -2 to -4), great for counter-trend or mean-reversion strategies.
🔹 Visual Reinforcement Tools
Includes candle coloring, gradient fills, and optional ALMA/EMA band overlays to visualize trend regime transitions.
🔍 How It Works
1️⃣ Z-Score SMMA Calculation
The core is a custom Smoothed Moving Average (SMMA) that is normalized by its standard deviation over a lookback period.
Final Formula:
Z = (SMMA - Mean) / StdDev
2️⃣ Signal Generation
• ✅ Long Bias: Z-Score > Long Threshold (default: 0)
• ❌ Short Bias: Z-Score < Short Threshold (default: 0)
3️⃣ Visual Aids
• Candle Color → Shows trend bias
• Band Fills → Highlight trend strength
• Overlays → Optional ALMA/EMA bands for structure analysis
⚙️ Custom Settings
• SMMA Length → Default: 12
• Z-Score Lookback → Default: 30
• Long Threshold → Default: 0
• Short Threshold → Default: 0
• Color Themes → Choose from 6 visual modes
• Extra Plots → Toggle advanced overlays (ALMA, EMA, bands)
• Label Display → Show/hide “𝓛𝓸𝓷𝓰” & “𝓢𝓱𝓸𝓻𝓽” markers
👥 Who Should Use It?
✅ Trend Traders → For early entries with confirmation from Z-score expansion
✅ Quantitative Analysts → Standardized deviation enables comparison across assets
✅ Mean-Reversion Traders → Use OB/OS zones to fade parabolic spikes
✅ Swing & Systematic Traders → Identify momentum shifts with optional ALMA/EMA overlays
📌 Conclusion
Z SMMA offers a smart, adaptive framework for tracking deviation from equilibrium in a quant-friendly format. Whether you're looking to follow trends or catch exhaustion points, Z SMMA provides a clear, standardized view of momentum and price extremes.
🔹 Key Takeaways:
1️⃣ Z-Score standardization ensures dynamic range awareness
2️⃣ SMMA base filters out noise, offering smoother signals
3️⃣ Color-coded visuals support faster reaction and cleaner charts
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before
Quantile DEMA Trend | QuantEdgeB🚀 Introducing Quantile DEMA Trend (QDT) by QuantEdgeB
🛠️ Overview
Quantile DEMA Trend (QDT) is an advanced trend-following and momentum detection indicator designed to capture price trends with superior accuracy. Combining DEMA (Double Exponential Moving Average) with SuperTrend and Quantile Filtering, QDT identifies strong trends while maintaining the ability to adapt to various market conditions.
Unlike traditional trend indicators, QDT uses percentile filtering to adjust for volatility and provides dynamic thresholds, ensuring consistent signal performance across different assets and timeframes.
✨ Key Features
🔹 Trend Following with Adaptive Sensitivity
The DEMA component ensures quicker responses to price changes while reducing lag, offering a real-time reflection of market momentum.
🔹 Volatility-Adjusted Filtering
The SuperTrend logic incorporates quantile percentile filters and ATR (Average True Range) multipliers, allowing QDT to adapt to fluctuating market volatility.
🔹 Clear Signal Generation
QDT generates clear Long and Short signals using percentile thresholds, effectively identifying trend changes and market reversals.
🔹 Customizable Visual & Signal Settings
With multiple color modes and customizable settings, you can easily align the QDT indicator with your trading strategy, whether you're focused on trend-following or volatility adjustments.
📊 How It Works
1️⃣ DEMA Calculation
DEMA is used to reduce lag compared to traditional moving averages. It is calculated by applying a Double Exponential Moving Average to price data. This smoother trend-following mechanism ensures responsiveness to market movements without introducing excessive noise.
2️⃣ SuperTrend with Percentile Filtering
The SuperTrend component adapts the trend-following signal by incorporating quantile percentile filters. It identifies dynamic support and resistance levels based on historical price data:
• Upper Band: Calculated using the 75th percentile + ATR (adjusted with multiplier)
• Lower Band: Calculated using the 25th percentile - ATR (adjusted with multiplier)
These dynamic bands adjust to market conditions, filtering out noise while identifying the true direction.
3️⃣ Signal Generation
• Long Signal: Triggered when price crosses below the SuperTrend Lower Band
• Short Signal: Triggered when price crosses above the SuperTrend Upper Band
The indicator provides signals with corresponding trend direction based on these crossovers.
👁 Visual & Custom Features
• 🎨 Multiple Color Modes: Choose from "Strategy", "Solar", "Warm", "Cool", "Classic", and "Magic" color palettes to match your charting style.
• 🏷️ Long/Short Signal Labels: Optional labels for visual cueing when a long or short trend is triggered.
• 📉 Bar Color Customization: Bar colors dynamically adjust based on trend direction to visually distinguish the market bias.
👥 Who Should Use QDT?
✅ Trend Followers: Use QDT as a dynamic tool to confirm trends and capture profits in trending markets.
✅ Swing Traders: Use QDT to time entries based on confirmed breakouts or breakdowns.
✅ Volatility Traders: Identify market exhaustion or expansion points, especially during volatile periods.
✅ Systematic & Quant Traders: Integrate QDT into algorithmic strategies to enhance market detection with adaptive filtering.
⚙️ Customization & Default Settings
- DEMA Length(30): Controls the lookback period for DEMA calculation
- Percentile Length(10): Sets the lookback period for percentile filtering
- ATR Length(14): Defines the length for calculating ATR (used in SuperTrend)
- ATR Multiplier(1.2 ): Multiplier for ATR in SuperTrend calculation
- SuperTrend Length(30):Defines the length for SuperTrend calculations
📌 How to Use QDT in Trading
1️⃣ Trend-Following Strategy
✔ Enter Long positions when QDT signals a bullish breakout (price crosses below the SuperTrend lower band).
✔ Enter Short positions when QDT signals a bearish breakdown (price crosses above the SuperTrend upper band).
✔ Hold positions as long as QDT continues to provide the same direction.
2️⃣ Reversal Strategy
✔ Take profits when price reaches extreme levels (upper or lower percentile zones) that may indicate trend exhaustion or reversion.
3️⃣ Volatility-Driven Entries
✔ Use the percentile filtering to enter positions based on mean-reversion logic or breakout setups in volatile markets.
🧠 Why It Works
QDT combines the DEMA’s quick response to price changes with SuperTrend's volatility-adjusted thresholds, ensuring a responsive and adaptive indicator. The use of percentile filters and ATR multipliers helps adjust to varying market conditions, making QDT suitable for both trending and range-bound environments.
🔹 Conclusion
The Quantile DEMA Trend (QDT) by QuantEdgeB is a powerful, adaptive trend-following and momentum detection system. By integrating DEMA, SuperTrend, and quantile percentile filtering, it provides accurate and timely signals while adjusting to market volatility. Whether you are a trend follower or volatility trader, QDT offers a robust solution to identify high-probability entry and exit points.
🔹 Key Takeaways:
1️⃣ Trend Confirmation – Uses DEMA and SuperTrend for dynamic trend detection
2️⃣ Volatility Filtering – Adjusts to varying market conditions using percentile logic
3️⃣ Clear Signal Generation – Easy-to-read signals and visual cues for strategy implementation
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
EMA Crossover (Short Focus with Trailing Stop)This strategy utilizes a combination of Exponential Moving Averages (EMA) and Simple Moving Averages (SMA) to generate entry and exit signals for both long and short positions. The core of the strategy is based on the 13-period EMA (short EMA) crossing the 33-period EMA (long EMA) for entering long trades, while a 13-period EMA crossing the 25-period EMA (mid EMA) generates short trade signals. The 100-period SMA and 200-period SMA serve as additional trend indicators to provide context for the market conditions. The strategy aims to capitalize on trend reversals and momentum shifts in the market.
The strategy is designed to execute trades swiftly with an emphasis on entering positions when conditions align in real time. For long entries, the strategy initiates a buy when the 13 EMA is greater than the 33 EMA, indicating a bullish trend. For short entries, the 13 EMA crossing below the 33 EMA signals a bearish trend, prompting a short position. Importantly, the code includes built-in exit conditions for both long and short positions. Long positions are exited when the 13 EMA falls below the 33 EMA, while short positions are closed when the 13 EMA crosses above the 25 EMA.
A key feature of the strategy is the use of trailing stops for both long and short positions. This dynamic exit method adjusts the stop level as the market moves in favor of the trade, locking in profits while reducing the risk of losses. The trailing stop for long positions is based on the high price of the current bar, while the trailing stop for short positions is set using the low price, providing more flexibility in managing risk. This trailing stop mechanism helps to capture profits from favorable market moves while ensuring that positions are exited if the market moves against them.
This strategy works best on the daily timeframe and is optimized for major cryptocurrency pairs. The daily chart allows for the EMAs to provide more reliable signals, as the strategy is designed to capture broader trends rather than short-term market fluctuations. Using it on major crypto pairs increases its effectiveness as these assets tend to have strong and sustained trends, providing better opportunities for the strategy to perform well.
TP/SL Percentage & RR Visual ToolThis tool is designed to help traders visually and statistically assess their trade setup by calculating Stop Loss (SL), Take Profit (TP), and Risk-to-Reward (RR) based on percentage inputs from the current price.
🔧 How It Works:
Uses the current candle’s close price as your entry.
Calculates TP and SL as percentage-based levels (e.g., 1% SL, 1.5% TP).
Displays horizontal lines and labels on the chart for TP and SL (only on the latest candle to reduce clutter).
Shows a compact table in the top-right corner with all key values:
Entry Price
Current Price
TP Price (+%)
SL Price (-%)
TP Distance from current price
RR Ratio (e.g., 1:1.5)
💡 Use Cases:
Quickly validate if a trade setup meets your desired RR profile (e.g., 1:2).
Perfect for scalpers, swing traders, and position traders who rely on structured risk management.
Combine with your entry signal strategy to visualize targets and stops without manual calculations.
⚙️ Inputs:
Stop Loss % – Sets how far your SL is from the entry.
Take Profit % – Sets how far your TP is from the entry.
Coppock Curve
The Coppock Curve is a long-term momentum indicator, also known as the "Coppock Guide," used to identify potential long-term market turning points, particularly major downturns and upturns, by smoothing the sum of 14-month and 11-month rates of change with a 10-month weighted moving average.
Here's a more detailed breakdown:
What it is:
The Coppock Curve is a technical indicator designed to identify long-term buy and sell signals in major stock market indices and related ETFs.
How it's calculated:
Rate of Change (ROC): The indicator starts by calculating the rate of change (ROC) for 14 and 11 periods (usually months).
Sum of ROCs: The ROC for the 14-period and 11-period are summed.
Weighted Moving Average (WMA): A 10-period weighted moving average (WMA) is then applied to the sum of the ROCs.
Interpreting the Curve:
Buy Signals: A buy signal is often generated when the Coppock Curve crosses above the zero line, suggesting a potential transition from a bearish to a bullish phase.
Sell Signals: While primarily designed to identify market bottoms, some traders may interpret a cross below the zero line as a sell signal or a bearish warning.
Origin and Purpose:
The Coppock Curve was introduced by economist Edwin Coppock in 1962.
It was originally designed to help investors identify opportune moments to enter the market.
Coppock's inspiration came from the Episcopal Church's concept of the average mourning period, which he believed mirrored the stock market's recovery period.
Limitations:
The Coppock Curve is primarily used for long-term analysis and may not be as effective for short-term or intraday trading.
It may lag in rapidly changing markets, and its signals may not always be reliable.
Volume Spikes Pro - relative volume comparisonThe Enhanced Volume Spike Detector builds on the basic relative volume comparison by adding price direction analysis and more sophisticated categorization of volume events.
Directional Analysis
This indicator doesn't just identify volume spikes, but categorizes them as:
- **Bullish**: Volume spike with upward price movement
- **Bearish**: Volume spike with downward price movement
- **Neutral**: Volume spike with minimal price change
- **Strong**: Exceptional volume spike (2.5x+ default) regardless of direction
Visual Classification
Different color schemes instantly communicate the volume spike type:
- Green for bullish volume (price rising)
- Red for bearish volume (price falling)
- Dark Green for strong bullish volume
- Dark Red for strong bearish volume (price falling)
Customization Tips
- For day trading or short timeframes: Consider reducing MA length to 10-15
- For swing trading: The default 20 is appropriate
- For position trading or longer timeframes: Consider increasing to 30-50
- For more selective signals: Increase multiplier to 2.0 or higher
- For more comprehensive detection: Decrease multiplier to 1.3-1.4
Volume Flow with Bollinger Bands and EMA Cross SignalsThe Volume Flow with Bollinger Bands and EMA Cross Signals indicator is a custom technical analysis tool designed to identify potential buy and sell signals based on several key components:
Volume Flow: This component combines price movement and trading volume to create a signal that indicates the strength or weakness of price movements. When the price is rising with increasing volume, it suggests strong buying activity, whereas falling prices with increasing volume indicate strong selling pressure.
Bollinger Bands: Bollinger Bands consist of three lines:
The Basis (middle line), which is a Simple Moving Average (SMA) of the price over a set period.
The Upper Band, which is the Basis plus a multiple of the standard deviation (typically 2).
The Lower Band, which is the Basis minus a multiple of the standard deviation. Bollinger Bands help identify periods of high volatility and potential overbought/oversold conditions. When the price touches the upper band, it might indicate that the market is overbought, while touching the lower band might indicate oversold conditions.
EMA Crossovers: The script includes two Exponential Moving Averages (EMAs):
Fast EMA: A shorter-term EMA, typically more sensitive to price changes.
Slow EMA: A longer-term EMA, responding slower to price changes. The crossover of the Fast EMA crossing above the Slow EMA (bullish crossover) signals a potential buy opportunity, while the Fast EMA crossing below the Slow EMA (bearish crossover) signals a potential sell opportunity.
Background Color and Candle Color: The indicator highlights the chart's background with specific colors based on the signals:
Green background for buy signals.
Yellow background for sell signals. Additionally, the candles are colored green for buy signals and yellow for sell signals to visually reinforce the trade opportunities.
Buy/Sell Labels: Small labels are placed on the chart:
"BUY" label in green is placed below the bar when a buy signal is generated.
"SELL" label in yellow is placed above the bar when a sell signal is generated.
Working of the Indicator:
Volume Flow Calculation: The Volume Flow is calculated by multiplying the price change (current close minus the previous close) with the volume. This product is then smoothed with a Simple Moving Average (SMA) over a user-defined period (length). The result is then multiplied by a multiplier to adjust its sensitivity.
Price Change = close - close
Volume Flow = Price Change * Volume
Smoothed Volume Flow = SMA(Volume Flow, length)
The Volume Flow Signal is then: Smooth Volume Flow * Multiplier
This calculation represents the buying or selling pressure in the market.
Bollinger Bands: Bollinger Bands are calculated using the Simple Moving Average (SMA) of the closing price (basis) and the Standard Deviation (stdev) of the price over a period defined by the user (bb_length).
Basis (Middle Band) = SMA(close, bb_length)
Upper Band = Basis + (bb_std_dev * Stdev)
Lower Band = Basis - (bb_std_dev * Stdev)
The upper and lower bands are plotted alongside the price to identify the price's volatility. When the price is near the upper band, it could be overbought, and near the lower band, it could be oversold.
EMA Crossovers: The Fast EMA and Slow EMA are calculated using the Exponential Moving Average (EMA) function. The crossovers are detected by checking:
Buy Signal (Bullish Crossover): When the Fast EMA crosses above the Slow EMA.
Sell Signal (Bearish Crossover): When the Fast EMA crosses below the Slow EMA.
The long_condition variable checks if the Fast EMA crosses above the Slow EMA, and the short_condition checks if it crosses below.
Visual Signals:
Background Color: The background is colored green for a buy signal and yellow for a sell signal. This gives an immediate visual cue to the trader.
Bar Color: The candles are colored green for buy signals and yellow for sell signals.
Labels:
A "BUY" label in green appears below the bar when the Fast EMA crosses above the Slow EMA.
A "SELL" label in yellow appears above the bar when the Fast EMA crosses below the Slow EMA.
Summary of Buy/Sell Logic:
Buy Signal:
The Fast EMA crosses above the Slow EMA (bullish crossover).
Volume flow is positive, indicating buying pressure.
Background turns green and candles are colored green.
A "BUY" label appears below the bar.
Sell Signal:
The Fast EMA crosses below the Slow EMA (bearish crossover).
Volume flow is negative, indicating selling pressure.
Background turns yellow and candles are colored yellow.
A "SELL" label appears above the bar.
Usage of the Indicator:
This indicator is designed to help traders identify potential entry (buy) and exit (sell) points based on:
The interaction of Exponential Moving Averages (EMAs).
The strength and direction of Volume Flow.
Price volatility using Bollinger Bands.
By combining these components, the indicator provides a comprehensive view of market conditions, helping traders make informed decisions on when to enter and exit trades.
FUMO GHOST V1.1FUMO GHOST V1.0 is a high-precision trend-following strategy that identifies explosive price continuations using EMA + Supertrend logic, filtered through Heikin Ashi confirmation candles.
This strategy is designed to operate across timeframes — from scalping (1M) to swing trading (1H+) — using adaptive auto-settings for sensitivity.
It’s built to be minimal, efficient, and bold — just like the #FUMO mindset.
🔍 Core Logic:
Supertrend (ATR-based) defines trend direction
EMA is used as a momentum baseline
Heikin Ashi logic filters entries:
Long: price above EMA, trend up, HA candle strong (open == low)
Short: price below EMA, trend down, HA candle weak (open == high)
Exit: triggered automatically on Supertrend reversal
This system is designed to stay in the trend as long as it’s valid — no scalping in/out or rapid re-entries.
⚙ Strategy Settings:
Auto-adjusts EMA & ATR parameters by timeframe (1M to 1D)
Manual override available (use_custom = true)
“Silent Mode” hides all visuals for minimal charting
Uses internal Heikin Ashi logic, regardless of visible candles
🧪 Backtest Notes:
Backtest is powered by TradingView’s built-in strategy() engine
Default risk: 10% equity per trade
For accurate simulation, enable “Use standard OHLC” in strategy settings — this ensures reliable backtest when internal Heikin Ashi logic is used
🔒 Why is the code protected?
This script uses:
A unique combination of Supertrend + EMA + Heikin Ashi filters
Internal timeframe-aware parameter scaling
Logic tuned specifically for explosive trend continuations
While freely available for public use, the source code is closed to protect the inner mechanism and prevent reverse engineering.
FUMO GHOST V1.0 is built for clarity, conviction, and confidence.
Make your next trade bold.
Make Fuck U Money — 24/7.
MARKET SYNERGY ANALYZER# MARKET SYNERGY ANALYZER v2.0
Current Date and Time (UTC): 2025-04-04 00:20:33
Author: Timur İnci
## INTRODUCTION
The Market Synergy Analyzer is an advanced technical analysis tool designed to bridge the gap between traditional market analysis and cross-market correlation studies. This sophisticated indicator provides traders and analysts with a comprehensive view of market relationships, particularly focusing on the synergy between BIST (Borsa Istanbul) indices and cryptocurrency markets.
### Core Purpose
- Identifies market correlations across different asset classes
- Tracks relative strength between markets
- Provides normalized price comparison
- Offers multi-timeframe analysis through customizable EMAs
## DEVELOPMENT
### Technical Implementation
1. **Multi-Market Data Processing**
- Real-time data fetching from BIST indices
- Cryptocurrency market integration
- Cross-market price normalization
2. **Advanced Technical Indicators**
- Four-layer EMA system (5, 14, 34, 233 periods)
- Normalized price ratios
- Percentage difference calculations
- Real-time market synergy detection
3. **Visualization Components**
- Color-coded EMA lines for trend identification
- Normalized candlestick charts
- Visual correlation indicators
### Key Features
- **Market Coverage:**
- 30+ BIST indices including XU100, XU030, XU050
- Major cryptocurrency pairs (BTC/USD, BTC/TRY, BTC/EUR)
- Sector-specific indices
- **Analysis Tools:**
- Relative strength comparison
- Cross-market correlation metrics
- Trend deviation alerts
- Multi-timeframe analysis
## CONCLUSION
### Practical Applications
1. **For Traders:**
- Identify market leading sectors
- Spot divergences between markets
- Time entry and exit points
- Track relative market strength
2. **For Portfolio Managers:**
- Monitor sector rotations
- Assess market correlations
- Optimize portfolio diversification
- Track market breadth
3. **For Risk Managers:**
- Monitor market relationships
- Track systemic risk indicators
- Identify potential market disruptions
- Assess cross-market impacts
### Benefits
- **Enhanced Decision Making:**
- Data-driven market analysis
- Reduced emotional bias
- Systematic approach to market analysis
- Comprehensive market view
- **Risk Management:**
- Early warning system for market changes
- Cross-market risk assessment
- Trend deviation alerts
- Portfolio exposure monitoring
- **Market Insights:**
- Deep market understanding
- Sector rotation identification
- Correlation analysis
- Market leadership tracking
### Target Users
1. Professional Traders
2. Portfolio Managers
3. Market Analysts
4. Risk Managers
5. Institutional Investors
## TECHNICAL REQUIREMENTS
- Platform: TradingView
- Pine Script Version: 6.0
- Data Feed: Real-time market data
- Recommended Timeframes: All
- Memory Usage: Optimized (500 bars back)
## FUTURE DEVELOPMENTS
1. Machine Learning Integration
2. Advanced Pattern Recognition
3. Additional Market Coverage
4. Enhanced Alert System
5. Custom Reporting Features
Normalized Mean ReversionA script that can help identify potential mean reversion opportunities using a Simple Moving Average (SMA) as the mean. This script will plot the SMA and highlight when the price deviates significantly from it, which could indicate a potential mean reversion setup.
NasyI## NasyI - Multi-Timeframe Technical Analysis Toolkit
### English Description
**NasyI** is a comprehensive technical analysis indicator designed to provide traders with a complete view of market dynamics across multiple timeframes. This indicator combines the power of Exponential Moving Averages (EMAs), Simple Moving Averages (MAs), Volume Weighted Average Price (VWAP), and key support/resistance levels to help traders identify trend direction, potential reversal points, and optimal entry/exit opportunities.
#### Key Features
1. **Multi-Timeframe Analysis System**
- 2-minute EMAs (13, 48) for ultra-short-term trend identification
- 5-minute EMAs (9, 13, 21, 48, 200) for short-term trend confirmation
- Daily EMAs (5, 13, 21, 48, 100, 200) and MAs (20, 50, 100, 200) for longer-term perspective
- Color-coded bands between key EMAs to visually identify trend strength and direction
2. **Advanced VWAP Integration**
- Daily VWAP for intraday support/resistance
- Weekly VWAP for medium-term price reference
- Monthly VWAP for long-term institutional price levels
- All VWAPs properly reset at their respective time period boundaries
3. **Critical Price Level Identification**
- Previous day high/low lines for identifying key breakout and breakdown levels
- Pre-market high/low tracking to identify potential intraday support/resistance zones
- All levels displayed with distinct line styles for easy identification
4. **Dynamic Trend Analysis**
- Color-coded bands between EMAs display trend strength and direction:
- Green bands indicate uptrend conditions (9 EMA > 21 EMA > 48 EMA)
- Red bands indicate downtrend conditions (9 EMA < 21 EMA < 48 EMA)
- Yellow bands indicate neutral/confused market conditions
- Visual representation makes trend changes immediately apparent
5. **Comprehensive Customization Options**
- Fully customizable colors for all indicators and bands
- Adjustable transparency settings for visual clarity
- Optional price labels with customizable placement and appearance
- Ability to show/hide specific components based on trading preferences
#### Trading Applications
This indicator is particularly valuable for:
1. **Day Trading & Scalping**: The 2-minute and 5-minute EMAs with color bands provide clear short-term trend direction and potential reversal signals.
2. **Swing Trading**: Daily EMAs and MAs offer perspective on the larger trend, helping to align short-term trades with the broader market direction.
3. **Gap Trading**: Previous day and pre-market levels help identify potential gap fill scenarios and breakout/breakdown opportunities.
4. **VWAP Trading Strategies**: Multiple timeframe VWAPs allow for identifying institutional participation levels and potential reversal zones.
5. **EMA Cross Systems**: The various EMAs can be used to identify golden crosses and death crosses across multiple timeframes.
#### How the Components Work Together
The power of NasyI comes from the integration of these different technical elements:
1. The short-timeframe EMAs (2m, 5m) provide immediate trend information, while the daily EMAs/MAs provide context about the larger market structure.
2. The color bands between EMAs offer instant visual confirmation of trend alignment or divergence across timeframes.
3. Previous day and pre-market levels add horizontal support/resistance zones to complement the dynamic moving averages.
4. Multiple timeframe VWAPs provide additional confirmation of institutional activity levels and potential reversal points.
By combining these elements, traders can develop a comprehensive market view that integrates price action, trend direction, and key support/resistance levels all in one indicator.
#### Usage Instructions
1. Apply the NasyI indicator to your chart (works best on intraday timeframes from 1-minute to 30-minute).
2. Observe the relationship between price and the various EMAs:
- Price above the 2m/5m EMAs with green bands indicates bullish short-term conditions
- Price below the 2m/5m EMAs with red bands indicates bearish short-term conditions
3. Use the daily EMAs/MAs and VWAPs as targets for potential price movements and reversal zones.
4. Previous day and pre-market high/low lines provide key levels to watch for breakouts or breakdowns.
5. Customize the appearance according to your preferences using the extensive settings options.
This indicator represents a unique approach to technical analysis by combining multiple timeframe perspectives into a single, visually intuitive display that helps traders make more informed decisions based on a comprehensive view of market conditions.
### 中文描述
**NasyI** 是一个全面的技术分析指标，旨在为交易者提供跨多个时间周期的完整市场动态视图。该指标结合了指数移动平均线（EMA）、简单移动平均线（MA）、成交量加权平均价格（VWAP）和关键支撑/阻力水平的力量，帮助交易者识别趋势方向、潜在反转点和最佳进出场机会。
#### 主要特点
1. **多时间周期分析系统**
- 2分钟EMAs（13，48）用于超短期趋势识别
- 5分钟EMAs（9，13，21，48，200）用于短期趋势确认
- 日线EMAs（5，13，21，48，100，200）和MAs（20，50，100，200）用于更长期的视角
- 关键EMAs之间的彩色带状区域直观显示趋势强度和方向
2. **高级VWAP整合**
- 日内VWAP作为日内支撑/阻力
- 周内VWAP作为中期价格参考
- 月内VWAP作为长期机构价格水平
- 所有VWAP在各自的时间周期边界正确重置
3. **关键价格水平识别**
- 前一交易日高点/低点线用于识别关键突破和跌破水平
- 盘前高点/低点跟踪用于识别潜在的日内支撑/阻力区域
- 所有水平以不同的线条样式显示，便于识别
4. **动态趋势分析**
- EMAs之间的彩色带状区域显示趋势强度和方向：
- 绿色带状区域表示上升趋势（9 EMA > 21 EMA > 48 EMA）
- 红色带状区域表示下降趋势（9 EMA < 21 EMA < 48 EMA）
- 黄色带状区域表示中性/混乱市场条件
- 视觉表示使趋势变化立即显现
5. **全面的自定义选项**
- 所有指标和带状区域的颜色完全可定制
- 可调节的透明度设置，提高视觉清晰度
- 可选的价格标签，带有可定制的位置和外观
- 能够根据交易偏好显示/隐藏特定组件
#### 交易应用
此指标对以下方面特别有价值：
1. **日内交易和短线交易**：2分钟和5分钟EMAs与色带提供清晰的短期趋势方向和潜在反转信号。
2. **摇摆交易**：日线EMAs和MAs提供对更大趋势的视角，帮助将短期交易与更广泛的市场方向对齐。
3. **缺口交易**：前一日和盘前水平帮助识别潜在的缺口填充情况和突破/跌破机会。
4. **VWAP交易策略**：多时间周期VWAP允许识别机构参与水平和潜在反转区域。
5. **EMA交叉系统**：各种EMAs可用于识别跨多个时间周期的黄金交叉和死亡交叉。
#### 组件如何协同工作
NasyI的强大之处在于这些不同技术元素的集成：
1. 短时间周期EMAs（2m，5m）提供即时趋势信息，而日线EMAs/MAs提供关于更大市场结构的背景。
2. EMAs之间的色带提供趋势对齐或跨时间周期分歧的即时视觉确认。
3. 前一日和盘前水平添加水平支撑/阻力区域，补充动态移动平均线。
4. 多时间周期VWAP提供机构活动水平和潜在反转点的额外确认。
通过结合这些元素，交易者可以发展出全面的市场视图，整合价格行动、趋势方向和关键支撑/阻力水平于一个指标中。
#### 使用说明
1. 将NasyI指标应用到您的图表上（最适合1分钟至30分钟的日内时间周期）。
2. 观察价格与各种EMAs之间的关系：
- 价格位于2m/5m EMAs之上，带有绿色带状区域，表示看涨的短期条件
- 价格位于2m/5m EMAs之下，带有红色带状区域，表示看跌的短期条件
3. 使用日线EMAs/MAs和VWAPs作为潜在价格移动和反转区域的目标。
4. 前一日和盘前高点/低点线提供需要关注的突破或跌破的关键水平。
5. 使用广泛的设置选项根据您的偏好自定义外观。
这个指标代表了一种独特的技术分析方法，将多个时间周期的视角结合到一个单一的、视觉直观的显示中，帮助交易者基于对市场条件的全面视图做出更明智的决策。
3SMA +30 Stan Weinstein +200WMA +alert-crossingIndicator Description: Stan Weinstein Strategy + Key Moving Averages
🔹 Introduction
This indicator combines the Classic Stan Weinstein Strategy with a modern update based on the author’s latest recommendations. It includes key moving averages that help identify trends and potential entry or exit points in the market.
📊 Included Moving Averages (Fully Customizable)
All moving averages in this indicator have modifiable parameters, allowing users to adjust values in the input settings.
1️⃣ 30-Week SMA (Stan Weinstein): A long-term trend indicator defining the asset’s main trend.
2️⃣ 40-Week SMA (Weinstein Update): An adjusted version recommended by the author in his recent updates.
3️⃣ 10-Day SMA: Displays short-term price action and helps confirm trend changes.
4️⃣ 100-Day SMA: A medium-term trend measure used by traders to assess trend strength.
5️⃣ 200-Day WMA (Weighted Moving Average): A very long-term indicator that filters market noise and confirms solid trends.
🔍 How to Interpret It
✔️ 30/40-Week SMA in an uptrend → Confirms an accumulation phase or an upward price trend.
✔️ Price above the 200-WMA → Indicates a strong and healthy long-term trend.
✔️ 10-SMA crossing other moving averages → Can signal an early entry or exit opportunity.
✔️ 100-SMA vs. 200-WMA → A breakout of the 100-SMA above the 200-WMA may signal a new bullish phase.
🚨 Built-in Alerts (Key Crossovers)
The indicator includes automatic alerts to notify traders when key moving averages cross, allowing timely reactions:
🔔 10-SMA crossing the 40-SMA → Possible medium-term trend shift.
🔔 10-SMA crossing the 200-WMA → Confirmation of a stronger trend.
🔔 40-SMA crossing the 200-WMA → Long-term trend reversal signal.
💡 Customization: All moving average periods can be adjusted in the input settings, making the indicator flexible for different trading strategies.
