Volatility Bias ModelVolatility Bias Model
Overview
Volatility Bias Model is a purely mathematical, non-indicator-based trading system that detects directional probability shifts during high volatility market phases. Rather than relying on classic tools like RSI or moving averages, this strategy uses raw price behavior and clustering logic to determine potential breakout direction based on recent market bias.
How It Works
Over a defined lookback window (default 10 bars), the strategy counts how many candles closed in the same direction (i.e., bullish or bearish).
Simultaneously, it calculates the price range during that window.
If volatility is above a minimum threshold and a clear directional bias is detected (e.g., >60% of closes are bullish), a trade is opened in the direction of that bias.
This approach assumes that when high volatility is coupled with directional closing consistency, the market is probabilistically more likely to continue in that direction.
ATR-based stop-loss and take-profit levels are applied, and trades auto-exit after 20 bars if targets are not hit.
Key Features
- 100% non-indicator-based logic
- Statistically-driven directional bias detection
- Works across all timeframes (1H, 4H, 1D)
- ATR-based risk management
- No pyramiding, slippage and commissions included
- Compatible with real-world backtesting conditions
Realism & Assumptions
To make this strategy more aligned with actual trading environments, it includes 0.05% commission per trade and a 1-point slippage on every entry and exit.
Additionally, position sizing is set at 10% of a $10,000 starting capital, and no pyramiding is allowed.
These assumptions help avoid unrealistic backtest results and make the performance metrics more representative of live conditions.
Parameter Explanation
Bias Window (10 bars): Number of past candles used to evaluate directional closings
Bias Threshold (0.60): Required ratio of same-direction candles to consider a bias valid
Minimum Range (1.5%): Ensures the market is volatile enough to avoid noise
ATR Length (14): Used to dynamically define stop-loss and target zones
Risk-Reward Ratio (2.0): Take-profit is set at twice the stop-loss distance
Max Holding Bars (20): Trades are closed automatically after 20 bars to prevent stagnation
Originality Note
Unlike common strategies based on oscillators or moving averages, this script is built on pure statistical inference. It models the market as a probabilistic process and identifies directional intent based on historical closing behavior, filtered by volatility. This makes it a non-linear, adaptive model grounded in real-world price structure — not traditional technical indicators.
Disclaimer
This strategy is for educational and experimental purposes only. It does not constitute financial advice. Always perform your own analysis and test thoroughly before applying with real capital.
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MACD + RSI + EMA + BB + ATR Day Trading StrategyEntry Conditions and Signals
The strategy implements a multi-layered filtering approach to entry conditions, requiring alignment across technical indicators, timeframes, and market conditions .
Long Entry Requirements
Trend Filter: Fast EMA (9) must be above Slow EMA (21), price must be above Fast EMA, and higher timeframe must confirm uptrend
MACD Signal: MACD line crosses above signal line, indicating increasing bullish momentum
RSI Condition: RSI below 70 (not overbought) but above 40 (showing momentum)
Volume & Volatility: Current volume exceeds 1.2x 20-period average and ATR shows sufficient market movement
Time Filter: Trading occurs during optimal hours (9:30-11:30 AM ET) when market volatility is typically highest
Exit Strategies
The strategy employs multiple exit mechanisms to adapt to changing market conditions and protect profits :
Stop Loss Management
Initial Stop: Placed at 2.0x ATR from entry price, adapting to current market volatility
Trailing Stop: 1.5x ATR trailing stop that moves up (for longs) or down (for shorts) as price moves favorably
Time-Based Exits: All positions closed by end of trading day (4:00 PM ET) to avoid overnight risk
Best Practices for Implementation
Settings
Chart Setup: 5-minute timeframe for execution with 15-minute chart for trend confirmation
Session Times: Focus on 9:30-11:30 AM ET trading for highest volatility and opportunity
Volatility Pulse with Dynamic ExitVolatility Pulse with Dynamic Exit
Overview
This strategy, Volatility Pulse with Dynamic Exit, is designed to capture impulsive price moves following volatility expansions, while ensuring risk is managed dynamically. It avoids trades during low-volatility periods and uses momentum confirmation to enter positions. Additionally, it features a time-based forced exit system to limit overexposure.
How It Works
A position is opened when the current ATR (Average True Range) significantly exceeds its 20-period average, signaling a volatility expansion.
To confirm the move is directional and not random noise, the strategy checks for momentum: the close must be above/below the close of 20 bars ago.
Low volatility zones are filtered out to avoid chop and poor trade entries.
Upon entry, a dynamic stop-loss is set at 1x ATR, while take-profit is set at 2x ATR, offering a 2:1 reward-to-risk ratio.
If the position remains open for more than 42 bars, it is forcefully closed, even if targets are not hit. This prevents long-lasting, stagnant trades.
Key Features
✅ Volatility-based breakout detection
✅ Momentum confirmation filter
✅ Dynamic stop-loss and take-profit based on real-time ATR
✅ Time-based forced exit (42 bars max holding)
✅ Low-volatility environment filter
✅ Realistic settings with 0.05% commission and slippage included
Parameters Explanation
ATR Length (14): Captures recent volatility over ~2 weeks (14 candles).
Momentum Lookback (20): Ensures meaningful price move confirmation.
Volatility Expansion Threshold (0.5x): Strategy activates only when ATR is at least 50% above its average.
Minimum ATR Filter (1.0x): Avoids entries in tight, compressed market ranges.
Max Holding (42 bars): Trades are closed after 42 bars if no exit signal is triggered.
Risk-Reward (2.0x): Aiming for 2x ATR as profit for every 1x ATR risk.
Originality Note
While volatility and momentum have been used separately in many strategies, this script combines both with a time-based dynamic exit system. This exit rule, combined with an ATR-based filter to exclude low-activity periods, gives the system a practical edge in real-world use. It avoids classic rehashes and integrates real trading constraints for better applicability.
Disclaimer
This is a research-focused trading strategy meant for backtesting and educational purposes. Always use proper risk management and perform due diligence before applying to real funds.
magic wand STSM"Magic Wand STSM" Strategy: Trend-Following with Dynamic Risk Management
Overview:
The "Magic Wand STSM" (Supertrend & SMA Momentum) is an automated trading strategy designed to identify and capitalize on sustained trends in the market. It combines a multi-timeframe Supertrend for trend direction and potential reversal signals, along with a 200-period Simple Moving Average (SMA) for overall market bias. A key feature of this strategy is its dynamic position sizing based on a user-defined risk percentage per trade, and a built-in daily and monthly profit/loss tracking system to manage overall exposure and prevent overtrading.
How it Works (Underlying Concepts):
Multi-Timeframe Trend Confirmation (Supertrend):
The strategy uses two Supertrend indicators: one on the current chart timeframe and another on a higher timeframe (e.g., if your chart is 5-minute, the higher timeframe Supertrend might be 15-minute).
Trend Identification: The Supertrend's direction output is crucial. A negative direction indicates a bearish trend (price below Supertrend), while a positive direction indicates a bullish trend (price above Supertrend).
Confirmation: A core principle is that trades are only considered when the Supertrend on both the current and the higher timeframe align in the same direction. This helps to filter out noise and focus on stronger, more confirmed trends. For example, for a long trade, both Supertrends must be indicating a bearish trend (price below Supertrend line, implying an uptrend context where price is expected to stay above/rebound from Supertrend). Similarly, for short trades, both must be indicating a bullish trend (price above Supertrend line, implying a downtrend context where price is expected to stay below/retest Supertrend).
Trend "Readiness": The strategy specifically looks for situations where the Supertrend has been stable for a few bars (checking barssince the last direction change).
Long-Term Market Bias (200 SMA):
A 200-period Simple Moving Average is plotted on the chart.
Filter: For long trades, the price must be above the 200 SMA, confirming an overall bullish bias. For short trades, the price must be below the 200 SMA, confirming an overall bearish bias. This acts as a macro filter, ensuring trades are taken in alignment with the broader market direction.
"Lowest/Highest Value" Pullback Entries:
The strategy employs custom functions (LowestValueAndBar, HighestValueAndBar) to identify specific price action within the recent trend:
For Long Entries: It looks for a "buy ready" condition where the price has found a recent lowest point within a specific number of bars since the Supertrend turned bearish (indicating an uptrend). This suggests a potential pullback or consolidation before continuation. The entry trigger is a close above the open of this identified lowest bar, and also above the current bar's open.
For Short Entries: It looks for a "sell ready" condition where the price has found a recent highest point within a specific number of bars since the Supertrend turned bullish (indicating a downtrend). This suggests a potential rally or consolidation before continuation downwards. The entry trigger is a close below the open of this identified highest bar, and also below the current bar's open.
Candle Confirmation: The strategy also incorporates a check on the candle type at the "lowest/highest value" bar (e.g., closevalue_b < openvalue_b for buy signals, meaning a bearish candle at the low, suggesting a potential reversal before a buy).
Risk Management and Position Sizing:
Dynamic Lot Sizing: The lotsvalue function calculates the appropriate position size based on your Your Equity input, the Risk to Reward ratio, and your risk percentage for your balance % input. This ensures that the capital risked per trade remains consistent as a percentage of your equity, regardless of the instrument's volatility or price. The stop loss distance is directly used in this calculation.
Fixed Risk Reward: All trades are entered with a predefined Risk to Reward ratio (default 2.0). This means for every unit of risk (stop loss distance), the target profit is rr times that distance.
Daily and Monthly Performance Monitoring:
The strategy tracks todaysWins, todaysLosses, and res (daily net result) in real-time.
A "daily profit target" is implemented (day_profit): If the daily net result is very favorable (e.g., res >= 4 with todaysLosses >= 2 or todaysWins + todaysLosses >= 8), the strategy may temporarily halt trading for the remainder of the session to "lock in" profits and prevent overtrading during volatile periods.
A "monthly stop-out" (monthly_trade) is implemented: If the lres (overall net result from all closed trades) falls below a certain threshold (e.g., -12), the strategy will stop trading for a set period (one week in this case) to protect capital during prolonged drawdowns.
Trade Execution:
Entry Triggers: Trades are entered when all buy/sell conditions (Supertrend alignment, SMA filter, "buy/sell situation" candle confirmation, and risk management checks) are met, and there are no open positions.
Stop Loss and Take Profit:
Stop Loss: The stop loss is dynamically placed at the upTrendValue for long trades and downTrendValue for short trades. These values are derived from the Supertrend indicator, which naturally adjusts to market volatility.
Take Profit: The take profit is calculated based on the entry price, the stop loss, and the Risk to Reward ratio (rr).
Position Locks: lock_long and lock_short variables prevent immediate re-entry into the same direction once a trade is initiated, or after a trend reversal based on Supertrend changes.
Visual Elements:
The 200 SMA is plotted in yellow.
Entry, Stop Loss, and Take Profit lines are plotted in white, red, and green respectively when a trade is active, with shaded areas between them to visually represent risk and reward.
Diamond shapes are plotted at the bottom of the chart (green for potential buy signals, red for potential sell signals) to visually indicate when the buy_sit or sell_sit conditions are met, along with other key filters.
A comprehensive trade statistics table is displayed on the chart, showing daily wins/losses, daily profit, total deals, and overall profit/loss.
A background color indicates the active trading session.
Ideal Usage:
This strategy is best applied to instruments with clear trends and sufficient liquidity. Users should carefully adjust the Your Equity, Risk to Reward, and risk percentage inputs to align with their individual risk tolerance and capital. Experimentation with different ATR Length and Factor values for the Supertrend might be beneficial depending on the asset and timeframe.
CANX MA Crossover© CanxStixTrader
Moving average crossover systems measure drift in the market. They are great strategies for time-limited traders. KEEP IT SIMPLE
This strategy works both for buys and sells using the reaction line to guide your position against the reactions.
HOW TO USE THE INDICATOR
1) Choose your market and timeframe.
2) Choose the length.
3) Choose the multiplier.
4) Choose if the strategy is long-only or bidirectional (longs & shorts).
TIPS
The strategy works best in bullish markets as that is the primary direction that market such as stocks, indexes and metals like to move.
- Increase the multiplier to reduce whipsaws
- Increase the length to take fewer trades
- Decrease the length to take more trades
- Try a Long-Only strategy to see if that performs better.
The base set up when you load the indicator is for the 1 minute chart on gold. We found that it also works well on the US Indexes. For other markets you may need to change the length and multiplier to suit the market and back test its results.
EMA 10/20/50 Alignment Strategy### 📘 **Strategy Name**
**EMA 10/20/50 Trend Alignment Strategy**
---
### 📝 **Description (for Publishing)**
This strategy uses the alignment of Exponential Moving Averages (EMAs) to identify strong bullish trends. It enters a long position when the short-term EMA is above the mid-term EMA, which is above the long-term EMA — a classic sign of trend strength.
#### 🔹 Entry Criteria:
* **EMA10 > EMA20 > EMA50**: A bullish alignment that signals momentum in an upward direction.
* The strategy enters a **long position** when this alignment occurs.
#### 🔹 Exit Criteria:
* The long position is closed when the EMA alignment breaks (i.e., the trend weakens or reverses).
#### 🔹 Additional Features:
* Includes a **date range filter**, allowing you to backtest the strategy over a specific period.
* Uses **100% of available capital** for each trade (position size auto-scales with account balance).
* No short positions, stop loss, or take profit are applied — this is a trend-following strategy meant to ride bullish moves.
---
### ✅ Best For:
* Traders looking for a **simple, trend-based entry system**
* Testing price momentum strategies during specific market regimes
* Visualizing EMA stacking patterns in historical data
Breakout Core | by Solid#SignalsBreakout Core | by SolidSignals
General Overview
Breakout Core is an advanced breakout trading strategy designed for Bitcoin (BTC). Optimized for the unique market dynamics following the launch of BlackRock’s Spot ETFs in January 2024, it adapts to Bitcoin’s post-ETF volatility patterns. The strategy’s core strength lies in its low drawdown, achieved through a proprietary time-based signal-filtering algorithm that sets it apart from traditional breakout strategies. Breakout Core offers traders a reliable tool for navigating Bitcoin’s evolving market with reduced risk and enhanced precision.
Mechanisms
Breakout Core combines well-known indicators BB, EMAs, MAs with custom-tuned parameters to improve signal accuracy. Its unique feature is a proprietary time-filter algorithm that prioritizes high-probability breakout signals during specific high-volatility trading hours, derived from market analysis post-ETF launch. This algorithm minimizes false positives, particularly in volatile conditions, by integrating time-based volatility patterns with price action. The result is a robust strategy that optimizes entry and exit points for Bitcoin trading.
Objectives
Breakout Core aims to provide steady returns with controlled risk by targeting Bitcoin’s breakout patterns in the post-ETF market. Its low drawdown, achieved through extensive optimization and proprietary logic, makes it suitable for leverage trading (e.g., 3–5x leverage), balancing growth with capital protection. Tailored for BTC, the strategy equips traders with a precise tool to navigate Bitcoin’s transformed market dynamics.
Backtesting and Parameter Notes
Backtesting was performed using a $10,000 USDT account, risking up to 10% of equity per trade, including 0.06% commission fees and 2-tick slippage, aligned with standard exchange conditions. The strategy report details backtesting results from the launch of BlackRock’s Spot ETFs. These settings are the script’s defaults, ensuring transparency. Traders are encouraged to verify results using TradingView’s Deep Backtest feature to adapt to current market conditions.
Please note: Past performance does not guarantee future results.
Chart and Usage
The chart is clean and intuitive, displaying only Breakout Core’s buy and sell signals for easy interpretation. Parameters are pre-optimized for immediate use, with adjustable Take Profit (TP) and Stop Loss (SL) levels. Traders should validate custom settings via TradingView’s backtesting tools to ensure market compatibility. An integrated Alarm Panel supports API connectivity, providing clear Entry/Exit commands for Long and Short positions, enabling seamless automated trading workflows.
Originality Statement
Breakout Core is an original strategy developed by SolidSignals, leveraging standard indicators (Bollinger Bands, EMAs, MAs) combined with a proprietary time-filter algorithm. No third-party or open-source code is used, ensuring full compliance with TradingView’s originality requirements. The time-filter mechanism, based on post-ETF volatility analysis, distinguishes this strategy from conventional breakout approaches.
Important Disclaimer
Market conditions evolve continuously, and past performance is not indicative of future results. Traders are responsible for validating the strategy’s settings and performance under current market conditions before use.
The VoVix Experiment The VoVix Experiment
The VoVix Experiment is a next-generation, regime-aware, volatility-adaptive trading strategy for futures, indices, and more. It combines a proprietary VoVix (volatility-of-volatility) anomaly detector with price structure clustering and critical point logic, only trading when multiple independent signals align. The system is designed for robustness, transparency, and real-world execution.
Logic:
VoVix Regime Engine: Detects pre-move volatility anomalies using a fast/slow ATR ratio, normalized by Z-score. Only trades when a true regime spike is detected, not just random volatility.
Cluster & Critical Point Filters: Price structure and volatility clustering must confirm the VoVix signal, reducing false positives and whipsaws.
Adaptive Sizing: Position size scales up for “super-spikes” and down for normal events, always within user-defined min/max.
Session Control: Trades only during user-defined hours and days, avoiding illiquid or high-risk periods.
Visuals: Aurora Flux Bands (From another Original of Mine (Options Flux Flow): glow and change color on signals, with a live dashboard, regime heatmap, and VoVix progression bar for instant insight.
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: 15 min (but works on all timeframes)
Order size: Adaptive, 1–2 contracts
Session: 5:00–15:00 America/Chicago (default, fully adjustable)
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 MNQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Forward Testing: (This is no guarantee. I've provided these results to show that executions perform as intended. Test were done on Tradovate)
ALL TRADES
Gross P/L: $12,907.50
# of Trades: 64
# of Contracts: 186
Avg. Trade Time: 1h 55min 52sec
Longest Trade Time: 55h 46min 53sec
% Profitable Trades: 59.38%
Expectancy: $201.68
Trade Fees & Comm.: $(330.95)
Total P/L: $12,576.55
Winning Trades: 59.38%
Breakeven Trades: 3.12%
Losing Trades: 37.50%
Link: www.dropbox.com
Inputs & Tooltips
VoVix Regime Execution: Enable/disable the core VoVix anomaly detector.
Volatility Clustering: Require price/volatility clusters to confirm VoVix signals.
Critical Point Detector: Require price to be at a statistically significant distance from the mean (regime break).
VoVix Fast ATR Length: Short ATR for fast volatility detection (lower = more sensitive).
VoVix Slow ATR Length: Long ATR for baseline regime (higher = more stable).
VoVix Z-Score Window: Lookback for Z-score normalization (higher = smoother, lower = more reactive).
VoVix Entry Z-Score: Minimum Z-score for a VoVix spike to trigger a trade.
VoVix Exit Z-Score: Z-score below which the regime is considered decayed (exit).
VoVix Local Max Window: Bars to check for local maximum in VoVix (higher = stricter).
VoVix Super-Spike Z-Score: Z-score for “super” regime events (scales up position size).
Min/Max Contracts: Adaptive position sizing range.
Session Start/End Hour: Only trade between these hours (exchange time).
Allow Weekend Trading: Enable/disable trading on weekends.
Session Timezone: Timezone for session filter (e.g., America/Chicago for CME).
Show Trade Labels: Show/hide entry/exit labels on chart.
Flux Glow Opacity: Opacity of Aurora Flux Bands (0–100).
Flux Band EMA Length: EMA period for band center.
Flux Band ATR Multiplier: Width of bands (higher = wider).
Compliance & Transparency
* No hidden logic, no repainting, no pyramiding.
* All signals, sizing, and exits are fully explained and visible.
* Backtest settings are stricter than most real accounts.
* All visuals are directly tied to the strategy logic.
* This is not a mashup or cosmetic overlay; every component is original and justified.
Disclaimer
Trading is risky. This script is for educational and research purposes only. Do not trade with money you cannot afford to lose. Past performance is not indicative of future results. Always test in simulation before live trading.
Proprietary Logic & Originality Statement
This script, “The VoVix Experiment,” is the result of original research and development. All core logic, algorithms, and visualizations—including the VoVix regime detection engine, adaptive execution, volatility/divergence bands, and dashboard—are proprietary and unique to this project.
1. VoVix Regime Logic
The concept of “volatility of volatility” (VoVix) is an original quant idea, not a standard indicator. The implementation here (fast/slow ATR ratio, Z-score normalization, local max logic, super-spike scaling) is custom and not found in public TradingView scripts.
2. Cluster & Critical Point Logic
Volatility clustering and “critical point” detection (using price distance from a rolling mean and standard deviation) are general quant concepts, but the way they are combined and filtered here is unique to this script. The specific logic for “clustered chop” and “critical point” is not a copy of any public indicator.
3. Adaptive Sizing
The adaptive sizing logic (scaling contracts based on regime strength) is custom and not a standard TradingView feature or public script.
4. Time Block/Session Control
The session filter is a common feature in many strategies, but the implementation here (with timezone and weekend control) is written from scratch.
5. Aurora Flux Bands (From another Original of Mine (Options Flux Flow)
The “glowing” bands are inspired by the idea of volatility bands (like Bollinger Bands or Keltner Channels), but the visual effect, color logic, and integration with regime signals are original to this script.
6. Dashboard, Watermark, and Metrics
The dashboard, real-time Sharpe/Sortino, and VoVix progression bar are all custom code, not copied from any public script.
What is “standard” or “common quant practice”?
Using ATR, EMA, and Z-score are standard quant tools, but the way they are combined, filtered, and visualized here is unique. The structure and logic of this script are original and not a mashup of public code.
This script is 100% original work. All logic, visuals, and execution are custom-coded for this project. No code or logic is directly copied from any public or private script.
Use with discipline. Trade your edge.
— Dskyz, for DAFE Trading Systems
REVELATIONS (VoVix - PoC) REVELATIONS (VoVix - POC): True Regime Detection Before the Move
Let’s not sugarcoat it: Most strategies on TradingView are recycled—RSI, MACD, OBV, CCI, Stochastics. They all lag. No matter how many overlays you stack, every one of these “standard” indicators fires after the move is underway. The retail crowd almost always gets in late. That’s never been enough for my team, for DAFE, or for anyone who’s traded enough to know the real edge vanishes by the time the masses react.
How is this different?
REVELATIONS (VoVix - POC) was engineered from raw principle, structured to detect pre-move regime change—before standard technicals even light up. We built, tested, and refined VoVix to answer one hard question:
What if you could see the spike before the trend?
Here’s what sets this system apart, line-by-line:
o True volatility-of-volatility mathematics: It’s not just "ATR of ATR" or noise smoothing. VoVix uses normalized, multi-timeframe v-vol spikes, instantly detecting orderbook stress and "outlier" market events—before the chart shows them as trends.
o Purist regime clustering: Every trade is enabled only during coordinated, multi-filter regime stress. No more signals in meaningless chop.
o Nonlinear entry logic: No trade is ever sent just for a “good enough” condition. Every entry fires only if every requirement is aligned—local extremes, super-spike threshold, regime index, higher timeframe, all must trigger in sync.
o Adaptive position size: Your contracts scale up with event strength. Tiny size during nominal moves, max leverage during true regime breaks—never guesswork, never static exposure.
o All exits governed by regime decay logic: Trades are closed not just on price targets but at the precise moment the market regime exhausts—the hardest part of systemic trading, now solved.
How this destroys the lag:
Standard indicators (RSI, MACD, OBV, CCI, and even most “momentum” overlays) simply tell you what already happened. VoVix triggers as price structure transitions—anyone running these generic scripts will trade behind the move while VoVix gets in as stress emerges. Real alpha comes from anticipation, not confirmation.
The visuals only show what matters:
Top right, you get a live, live quant dashboard—regime index, current position size, real-time performance (Sharpe, Sortino, win rate, and wins). Bottom right: a VoVix "engine bar" that adapts live with regime stress. Everything you see is a direct function of logic driving this edge—no cosmetics, no fake momentum.
Inputs/Signals—explained carefully for clarity:
o ATR Fast Length & ATR Slow Length:
These are the heart of VoVix’s regime sensing. Fast ATR reacts to sharp volatility; Slow ATR is stability baseline. Lower Fast = reacts to every twitch; higher Slow = requires more persistent, “real” regime shifts.
Tip: If you want more signals or faster markets, lower ATR Fast. To eliminate noise, raise ATR Slow.
o ATR StdDev Window: Smoothing for volatility-of-volatility normalization. Lower = more jumpy, higher = only the cleanest spikes trigger.
Tip: Shorten for “jumpy” assets, raise for indices/futures.
o Base Spike Threshold: Think of this as your “minimum event strength.” If the current move isn’t volatile enough (normalized), no signal.
Tip: Higher = only biggest moves matter. Lower for more signals but more potential noise.
o Super Spike Multiplier: The “are you sure?” test—entry only when the current spike is this multiple above local average.
Tip: Raise for ultra-selective/swing-trading; lower for more active style.
Regime & MultiTF:
o Regime Window (Bars):
How many bars to scan for regime cluster “events.” Short for turbo markets, long for big swings/trends only.
o Regime Event Count: Only trade when this many spikes occur within the Regime Window—filters for real stress, not isolated ticks.
Tip: Raise to only ever trade during true breakouts/crashes.
o Local Window for Extremes:
How many bars to check that a spike is a local max.
Tip: Raise to demand only true, “clearest” local regime events; lower for early triggers.
o HTF Confirm:
Higher timeframe regime confirmation (like 45m on an intraday chart). Ensures any event you act on is visible in the broader context.
Tip: Use higher timeframes for only major moves; lower for scalping or fast regimes.
Adaptive Sizing:
o Max Contracts (Adaptive): The largest size your system will ever scale to, even on extreme event.
Tip: Lower for small accounts/conservative risk; raise on big accounts or when you're willing to go big only on outlier events.
o Min Contracts (Adaptive): The “toe-in-the-water.” Smallest possible trade.
Tip: Set as low as your broker/exchange allows for safety, or higher if you want to always have meaningful skin in the game.
Trade Management:
o Stop %: Tightness of your stop-loss relative to entry. Lower for tighter/safer, higher for more breathing room at cost of greater drawdown.
o Take Profit %: How much you'll hold out for on a win. Lower = more scalps. Higher = only run with the best.
o Decay Exit Sensitivity Buffer: Regime index must dip this far below the trading threshold before you exit for “regime decay.”
Tip: 0 = exit as soon as stress fails, higher = exits only on stronger confirmation regime is over.
o Bars Decay Must Persist to Exit: How long must decay be present before system closes—set higher to avoid quick fades and whipsaws.
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.
Tip: Set to 1 for instant regime exit; raise for extra confirmation (less whipsaw risk, exits held longer).
________________________________________
Bottom line: Tune the sensitivity, selectivity, and risk of REVELATIONS by these inputs. Raise thresholds and windows for only the best, most powerful signals (institutional style); lower for activity (scalpers, fast cryptos, signals in constant motion). Sizing is always adaptive—never static or martingale. Exits are always based on both price and regime health. Every input is there for your control, not to sell “complexity.” Use with discipline, and make it your own.
This strategy is not just a technical achievement: It’s a statement about trading smarter, not just more.
* I went back through the code to make sure no the strategy would not suffer from repainting, forward looking, or any frowned upon loopholes.
Disclaimer:
Trading is risky and carries the risk of substantial loss. Do not use funds you aren’t prepared to lose. This is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results.
Expect more: We’ll keep pushing the standard, keep evolving the bar until “quant” actually means something in the public code space.
Use with clarity, use with discipline, and always trade your edge.
— Dskyz , for DAFE Trading Systems
SwingTrade VWAP Strategy[TiamatCrypto]V1.1This Pine Script® code creates a trading strategy called "SwingTrade VWAP Strategy V1.1." This strategy incorporates various trading tools, such as VWAP (Volume Weighted Average Price), ADX (Average Directional Index), and volume signals. Below is an explanation of the components and logic within the script:
### Overview of Features
- **VWAP:** A volume-weighted moving average that assesses price trends relative to the VWAP level.
- **ADX:** A trend strength indicator that helps confirm the strength of bullish or bearish trends.
- **Volume Analysis:** Leverages volume data to gauge momentum and identify volume-weighted buy/sell conditions.
- **Dynamic Entry/Exit Signals:** Combines the above indicators to produce actionable buy/sell or exit signals.
- **Customizable Inputs:** Inputs for tuning parameters like VWAP period, ADX thresholds, and volume sensitivity.
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### **Code Breakdown**
#### **Input Parameters**
The script begins by defining several user-configurable variables under groups. These include indicators' on/off switches (`showVWAP`, `enableADX`, `enableVolume`) and input parameters for VWAP, ADX thresholds, and volume sensitivity:
- **VWAP Period and Threshold:** Controls sensitivity for VWAP signal generation.
- **ADX Settings:** Allows users to configure the ADX period and strength threshold.
- **Volume Ratio:** Detects bullish/bearish conditions based on relative volume patterns.
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#### **VWAP Calculation**
The script calculates VWAP using the formula:
\
Where `P` is the typical price (`(high + low + close)/3`) and `V` is the volume.
- It resets cumulative values (`sumPV` and `sumV`) at the start of each day.
- Delta percentage (`deltaPercent`) is calculated as the percentage difference between the close price and the VWAP.
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#### **Indicators and Signals**
1. **VWAP Trend Signals:**
- Identifies bullish/bearish conditions based on price movement (`aboveVWAP`, `belowVWAP`) and whether the price is crossing the VWAP level (`crossingUp`, `crossingDown`).
- Also detects rising/falling delta changes based on the VWAP threshold.
2. **ADX Calculation:**
- Calculates the directional movement (`PlusDM`, `MinusDM`) and smoothed values for `PlusDI`, `MinusDI`, and `ADX`.
- Confirms strong bullish/bearish trends when ADX crosses the defined threshold.
3. **Volume-Based Signals:**
- Evaluates the ratio of bullish volume (when `close > VWAP`) to bearish volume (when `close < VWAP`) over a specified lookback period.
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#### **Trade Signals**
The buy and sell signals are determined by combining conditions from the VWAP, ADX, and volume signals:
- **Buy Signal:** Triggered when price upward crossover VWAP, delta rises above the threshold, ADX indicates a strong bullish trend, and volume confirms bullish momentum.
- **Sell Signal:** Triggered under inverse conditions.
- Additionally, exit conditions (`exitLong` and `exitShort`) are based on VWAP crossovers combined with the reversal of delta values.
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#### **Plotting and Display**
The strategy plots VWAP on the chart and adds signal markers for:
- **Buy/Long Entry:** Green triangle below bars.
- **Sell/Short Entry:** Red triangle above bars.
- **Exit Signals:** Lime or orange "X" shapes for exits from long/short positions.
- Additionally, optional text labels are displayed to indicate the type of signal.
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#### **Trading Logic**
The script's trading logic executes as follows:
- **Entries:**
- Executes long trades when the `buySignal` condition is true.
- Executes short trades when the `sellSignal` condition is true.
- **Exits:**
- Closes long positions upon `exitLong` conditions.
- Closes short positions upon `exitShort` conditions.
- The strategy calculates profits and visualizes the trade entry, exit, and running profit within the chart.
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#### **Alerts**
Alerts are set up to notify traders via custom signals for buy and sell trades.
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### **Use Case**
This script is suitable for day traders, swing traders, or algorithmic traders who rely on confluence signals from VWAP, ADX, and volume momentum. Its modular structure (e.g., the ability to enable/disable specific indicators) makes it highly customizable for various trading styles and financial instruments.
#### **Customizability**
- Adjust VWAP, ADX, and volume sensitivity levels to fit unique market conditions or asset classes.
- Turn off specific criteria to focus only on VWAP or ADX signals if desired.
#### **Caution**
As with all trading strategies, this script should be used for backtesting and analysis before live implementation. It's essential to validate its performance on historical data while considering factors like slippage and transaction costs.
TLCproTLCpro Trading Strategy
Description
TLCpro is a multi-timeframe trend-following strategy that combines EMA crossovers, MACD filtering, RSI confirmation, and VWAP/Trend EMA as dynamic support/resistance levels. The strategy is optimized for 1-hour (1H) and 4-hour (4H) timeframes, ensuring adaptability to different market conditions.
Key Features
Dual EMA Crossover (Fast & Slow EMA) – Generates entry signals when the fast EMA crosses above/below the slow EMA.
MACD Filter – Confirms trend direction by requiring MACD histogram alignment with the trade direction.
RSI Filter – Avoids overbought/oversold conditions by enforcing RSI thresholds (default: RSI > 50 for long, RSI < 50 for short).
Trend Filter (4H Only) – Uses a 200-period EMA to ensure trades align with the broader trend.
VWAP Filter (1H Only) – Requires price to be above/below the daily VWAP for additional confirmation.
Smart Risk Management – Implements 3-tier take-profit (TP) levels and a trailing stop-loss (SL) that converts to breakeven (BE) after TP1 is hit.
How It Works
Entry Conditions
Long Entry:
Fast EMA (15) crosses above Slow EMA (30).
MACD histogram is positive.
RSI > 50 (configurable).
On 1H: Price above daily VWAP.
On 4H: Price above 200-period Trend EMA.
Short Entry:
Fast EMA (15) crosses below Slow EMA (30).
MACD histogram is negative.
RSI < 50 (configurable).
On 1H: Price below daily VWAP.
On 4H: Price below 200-period Trend EMA.
Exit & Risk Management
3 Take-Profit Levels (TP1, TP2, TP3) – Closes portions of the trade at predefined profit levels (default: 3%, 6%, 10%).
Dynamic Stop-Loss (SL) & Breakeven (BE) Logic:
Initial SL: Fixed at 3% from entry.
After TP1 is hit: SL moves to breakeven (entry price).
After TP2 is hit: SL moves to TP1 level, locking in partial profits.
Visual SL/TP Lines – Drawn on the chart for easy tracking.
Why TLCpro is Unique & Worth Using
Multi-Timeframe Adaptability: Uses different filters (VWAP for 1H, Trend EMA for 4H) to improve signal quality.
Smart Risk Management: Unlike static SL/TP strategies, TLCpro trails stops to lock in profits while minimizing risk.
High-Confirmation Filters: Combines EMA, MACD, RSI, and Trend/VWAP to reduce false signals.
Visual Clarity: Clearly marks SL, TP, and BE levels on the chart for intuitive trade management.
Backtesting & Risk Considerations
Realistic Risk per Trade: Default stop-loss is 3%, ensuring sustainable risk management.
Partial Profit-Taking: Exits 25% at TP1, 25% at TP2, and 50% at TP3, balancing risk and reward.
Commission & Slippage: Should be accounted for in live trading (adjust in strategy settings).
Recommended Capital: Works well with $1,000+ accounts due to percentage-based position sizing.
How to Use
Apply to 1H or 4H charts (optimized for these timeframes).
Default settings work well, but adjust EMA lengths, RSI thresholds, and TP/SL levels based on volatility.
Monitor SL/TP lines – The strategy auto-updates them as price moves.
Avoid over-optimization – Test on multiple instruments before live trading.
Final Notes
TLCpro is designed for swing traders and trend followers who want a systematic, rules-based approach with clear risk management. By combining multiple confirmation filters and dynamic stop adjustments, it aims to improve consistency in trending markets.
PowerHouse SwiftEdge AI v2.10 StrategyOverview
The PowerHouse SwiftEdge AI v2.10 Strategy is a sophisticated trading system designed to identify high-probability trade setups in forex, stocks, and cryptocurrencies. By combining multi-timeframe trend analysis, momentum signals, volume confirmation, and smart money concepts (Change of Character and Break of Structure ), this strategy offers traders a robust tool to capitalize on market trends while minimizing false signals. The strategy’s unique “AI” component analyzes trends across multiple timeframes to provide a clear, actionable dashboard, making it accessible for both novice and experienced traders. The strategy is fully customizable, allowing users to tailor its filters to their trading style.
What It Does
This strategy generates Buy and Sell signals based on a confluence of technical indicators and smart money concepts. It uses:
Multi-Timeframe Trend Analysis: Confirms the market’s direction by analyzing trends on the 1-hour (60M), 4-hour (240M), and daily (D) timeframes.
Momentum Filter: Ensures trades align with strong price movements to avoid choppy markets.
Volume Filter: Validates signals with above-average volume to confirm market participation.
Breakout Filter: Requires price to break key levels for added confirmation.
Smart Money Signals (CHoCH/BOS): Identifies reversals (CHoCH) and trend continuations (BOS) based on pivot points.
AI Trend Dashboard: Summarizes trend strength, confidence, and predictions across timeframes, helping traders make informed decisions without needing to analyze complex data manually.
The strategy also plots dynamic support and resistance trendlines, take-profit (TP) levels, and “Get Ready” signals to alert users of potential setups before they fully develop. Trades are executed with predefined take-profit and stop-loss levels for disciplined risk management.
How It Works
The strategy integrates multiple components to create a cohesive trading system:
Multi-Timeframe Trend Analysis:
The strategy evaluates trends on three timeframes (1H, 4H, Daily) using Exponential Moving Averages (EMA) and Volume-Weighted Average Price (VWAP). A trend is considered bullish if the price is above both the EMA and VWAP, bearish if below, or neutral otherwise.
Signals are only generated when the trend on the user-selected higher timeframe aligns with the trade direction (e.g., Buy signals require a bullish higher timeframe trend). This reduces noise and ensures trades follow the broader market context.
Momentum Filter:
Measures the percentage price change between consecutive bars and compares it to a volatility-adjusted threshold (based on the Average True Range ). This ensures trades are taken only during significant price movements, filtering out low-momentum conditions.
Volume Filter (Optional):
Checks if the current volume exceeds a long-term average and shows positive short-term volume change. This confirms strong market participation, reducing the risk of false breakouts.
Breakout Filter (Optional):
Requires the price to break above (for Buy) or below (for Sell) recent highs/lows, ensuring the signal aligns with a structural shift in the market.
Smart Money Concepts (CHoCH/BOS):
Change of Character (CHoCH): Detects potential reversals when the price crosses under a recent pivot high (for Sell) or over a recent pivot low (for Buy) with a bearish or bullish candle, respectively.
Break of Structure (BOS): Confirms trend continuations when the price breaks below a recent pivot low (for Sell) or above a recent pivot high (for Buy) with strong momentum.
These signals are plotted as horizontal lines with labels, making it easy to visualize key levels.
AI Trend Dashboard:
Combines trend direction, momentum, and volatility (ATR) across timeframes to calculate a trend score. Scores above 0.5 indicate an “Up” trend, below -0.5 indicate a “Down” trend, and otherwise “Neutral.”
Displays a table summarizing trend strength (as a percentage), AI confidence (based on trend alignment), and Cumulative Volume Delta (CVD) for market context.
A second table (optional) shows trend predictions for 1H, 4H, and Daily timeframes, helping traders anticipate future market direction.
Dynamic Trendlines:
Plots support and resistance lines based on recent swing lows and highs within user-defined periods (shortTrendPeriod, longTrendPeriod). These lines adapt to market conditions and are colored based on trend strength.
Why This Combination?
The PowerHouse SwiftEdge AI v2.10 Strategy is original because it seamlessly integrates traditional technical analysis (EMA, VWAP, ATR, volume) with smart money concepts (CHoCH, BOS) and a proprietary AI-driven trend analysis. Unlike standalone indicators, this strategy:
Reduces False Signals: By requiring confluence across trend, momentum, volume, and breakout filters, it minimizes trades in choppy or low-conviction markets.
Adapts to Market Context: The ATR-based momentum threshold adjusts dynamically to volatility, ensuring signals remain relevant in both trending and ranging markets.
Simplifies Decision-Making: The AI dashboard distills complex multi-timeframe data into a user-friendly table, eliminating the need for manual analysis.
Leverages Smart Money: CHoCH and BOS signals capture institutional price action patterns, giving traders an edge in identifying reversals and continuations.
The combination of these components creates a balanced system that aligns short-term trade entries with longer-term market trends, offering a unique blend of precision, adaptability, and clarity.
How to Use
Add to Chart:
Apply the strategy to your TradingView chart on a liquid symbol (e.g., EURUSD, BTCUSD, AAPL) with a timeframe of 60 minutes or lower (e.g., 15M, 60M).
Configure Inputs:
Pivot Length: Adjust the number of bars (default: 5) to detect pivot highs/lows for CHoCH/BOS signals. Higher values reduce noise but may delay signals.
Momentum Threshold: Set the base percentage (default: 0.01%) for momentum confirmation. Increase for stricter signals.
Take Profit/Stop Loss: Define TP and SL in points (default: 10 each) for risk management.
Higher/Lower Timeframe: Choose timeframes (60M, 240M, D) for trend filtering. Ensure the chart timeframe is lower than or equal to the higher timeframe.
Filters: Enable/disable momentum, volume, or breakout filters to suit your trading style.
Trend Periods: Set shortTrendPeriod (default: 30) and longTrendPeriod (default: 100) for trendline plotting. Keep below 2000 to avoid buffer errors.
AI Dashboard: Toggle Enable AI Market Analysis to show/hide the prediction table and adjust its position.
Interpret Signals:
Buy/Sell Labels: Green "Buy" or red "Sell" labels indicate trade entries with predefined TP/SL levels plotted.
Get Ready Signals: Yellow "Get Ready BUY" or orange "Get Ready SELL" labels warn of potential setups.
CHoCH/BOS Lines: Aqua (CHoCH Sell), lime (CHoCH Buy), fuchsia (BOS Sell), or teal (BOS Buy) lines mark key levels.
Trendlines: Green/lime (support) or fuchsia/purple (resistance) dashed lines show dynamic support/resistance.
AI Dashboard: Check the top-right table for trend strength, confidence, and CVD. The optional bottom table shows trend predictions (Up, Down, Neutral).
Backtest and Trade:
Use TradingView’s Strategy Tester to evaluate performance. Adjust TP/SL and filters based on results.
Trade manually based on signals or automate with TradingView alerts (set alerts for Buy/Sell labels).
Originality and Value
The PowerHouse SwiftEdge AI v2.10 Strategy stands out by combining multi-timeframe analysis, smart money concepts, and an AI-driven dashboard into a single, user-friendly system. Its adaptive momentum threshold, robust filtering, and clear visualizations empower traders to make confident decisions without needing advanced technical knowledge. Whether you’re a day trader or swing trader, this strategy provides a versatile, data-driven approach to navigating dynamic markets.
Important Notes:
Risk Management: Always use appropriate position sizing and risk management, as the strategy’s TP/SL levels are customizable.
Symbol Compatibility: Test on liquid symbols with sufficient historical data (at least 2000 bars) to avoid buffer errors.
Performance: Backtest thoroughly to optimize settings for your market and timeframe.
AccumulationPro Money Flow StrategyAccumulationPro Money Flow Strategy identifies stock trading opportunities by analyzing money flow and potential long-only opportunities following periods of increased money inflow. It employs proprietary responsive indicators and oscillators to gauge the strength and momentum of the inflow relative to previous periods, detecting money inflow, buying/selling pressure, and potential continuation/reversals, while using trailing stop exits to maximize gains while minimizing losses, with careful consideration of risk management and position sizing.
Setup Instructions:
1. Configuring the Strategy Properties:
Click the "Settings" icon (the gear symbol) next to the strategy name.
Navigate to the "Properties" tab within the Settings window.
Initial Capital: This value sets the starting equity for the strategy backtesting. Keep in mind that you will need to specify your current account size in the "Inputs" settings for position sizing.
Base Currency: Leave this setting at its "Default" value.
Order Size: This setting, which determines the capital used for each trade during backtesting, is automatically calculated and updated by the script. You should leave it set to "1 Contract" and the script will calculate the appropriate number of contracts based on your risk per trade, account size, and stop-loss placement.
Pyramiding: Set this setting at 1 order to prevent the strategy from adding to existing positions.
Commission: Enter your broker's commission fee per trade as a percentage, some brokers might offer commission free trading. Verify Price for limit orders: Keep this value as 0 ticks.
Slippage: This value depends on the instrument you are trading, If you are trading liquid stocks on a 1D chart slippage might be neglected. You can Keep this value as 1 ticks if you want to be conservative.
Margin for long positions/short positions: Set both of these to 100% since this strategy does not employ leverage or margin trading.
Recalculate:
Select the "After order is filled" option.
Select the "On every tick" option.
Fill Orders: Keep “Using bar magnifier” unselected.
Select "On bar close". Select "Using standard OHLC"
2. Configuring the Strategy Inputs:
Click the "Inputs" tab in the Settings window.
From/Thru (Date Range): To effectively backtest the strategy, define a substantial period that includes various bullish and bearish cycles. This ensures the testing window captures a range of market conditions and provides an adequate number of trades. It is usually favorable to use a minimum of 8 years for backtesting. Ensure the "Show Date Range" box is checked.
Account Size: This is your actual current Account Size used in the position sizing table calculations.
Risk on Capital %: This setting allows you to specify the percentage of your capital you are willing to risk on each trade. A common value is 0.5%.
3. Configuring Strategy Style:
Select the "Style" tab.
Select the checkbox for “Stop Loss” and “Stop Loss Final” to display the black/red Average True Range Stop Loss step-lines
Make sure the checkboxes for "Upper Channel", "Middle Line", and "Lower Channel" are selected.
Select the "Plots Background" checkboxes for "Color 0" and "Color 1" so that the potential entry and exit zones become color-coded.
Having the checkbox for "Tables" selected allows you to see position sizing and other useful information within the chart.
Have the checkboxes for "Trades on chart" and "Signal Labels" selected for viewing entry and exit point labels and positions.
Uncheck* the "Quantity" checkbox.
Precision: select “Default”.
Check “Labels on price scale”
Check “Values in status line”
Strategy Application Guidelines:
Entry Conditions:
The strategy identifies long entry opportunities based on substantial money inflow, as detected by our proprietary indicators and oscillators. This assessment considers the strength and momentum of the inflow relative to previous periods, in conjunction with strong price momentum (indicated by our modified, less-lagging MACD) and/or a potential price reversal (indicated by our modified, less-noisy Stochastic). Additional confirmation criteria related to price action are also incorporated. Potential entry and exit zones are visually represented by bands on the chart.
A blue upward-pointing arrow, accompanied by the label 'Long' and green band fills, signifies a long entry opportunity. Conversely, a magenta downward-pointing arrow, labeled 'Close entry(s) order Long' with yellow band fills, indicates a potential exit.
Take Profit:
The strategy employs trailing stops, rather than fixed take-profit levels, to maximize gains while minimizing losses. Trailing stops adjust the stop-loss level as the stock price moves in a favorable direction. The strategy utilizes two types of trailing stop mechanisms: one based on the Average True Range (ATR), and another based on price action, which attempts to identify shifts in price momentum.
Stop Loss:
The strategy uses an Average True Range (ATR)-based stop-loss, represented by two lines on the chart. The black line indicates the primary ATR-based stop-loss level, set upon trade entry. The red line represents a secondary ATR stop-loss buffer, used in the position sizing calculation to account for potential slippage or price gaps.
To potentially reduce the risk of stop-hunting, discretionary traders might consider using a market sell order within the final 30 to 60 minutes of the main session, instead of automated stop-loss orders.
Order Types:
Market Orders are intended for use with this strategy, specifically when the candle and signal on the chart stabilize within the final 30 to 60 minutes of the main trading session.
Position Sizing:
A key aspect of this strategy is that its position size is calculated and displayed in a table on the chart. The position size is calculated based on stop-loss placement, including the stop-loss buffer, and the capital at risk per trade which is commonly set around 0.5% Risk on Capital per Trade.
Backtesting:
The backtesting results presented below the chart are for informational purposes only and are not intended to predict future performance. Instead, they serve as a tool for identifying instruments with which the strategy has historically performed well.
It's important to note that the backtester utilizes a tiny portion of the capital for each trade while our strategy relies on a diversified portfolio of multiple stocks or instruments being traded at once.
Important Considerations:
Volume data is crucial; the strategy will not load or function correctly without it. Ensure that your charts include volume data, preferably from a centralized exchange.
Our system is designed for trading a portfolio. Therefore, if you intend to use our system, you should employ appropriate position sizing, without leverage or margin, and seek out a variety of long opportunities, rather than opening a single trade with an excessively large position size.
If you are trading without automated signals, always allow the chart to stabilize. Refrain from taking action until the final 1 hour to 30 minutes before the end of the main trading session to minimize the risk of acting on false signals.
To align with the strategy's design, it's generally preferable to enter a trade during the same session that the signal appears, rather than waiting for a later session.
Disclaimer:
Trading in financial markets involves a substantial degree of risk. You should be aware of the potential for significant financial losses. It is imperative that you trade responsibly and avoid overtrading, as this can amplify losses. Remember that market conditions can change rapidly, and past performance is not indicative of future results. You could lose some or all of your initial investment. It is strongly recommended that you fully understand the risks involved in trading and seek independent financial advice from a qualified professional before using this strategy.
Alpha Trigger CoreAlpha Trigger Core — Trend Momentum Strategy with Dual Take Profit System
Alpha Trigger Core is a precision-engineered trend-following strategy developed for crypto and altcoin markets. Unlike simple indicator mashups, this system was built from the ground up with a specific logic framework that integrates trend, momentum, volatility, and structure validation into a single unified strategy.
It is not a random combination of indicators, but rather a coordinated system of filters that work together to increase signal quality and minimize false positives. This makes it especially effective on trending assets like BTC, ETH, AVAX, and SOL on the 1-hour chart.
🔍 How It Works
This strategy fuses multiple advanced filters into a cohesive signal engine:
🔹 Trend Identification
A hybrid model combining:
Kalman Filter — Smooths price noise with predictive tracking.
SuperTrend Overlay — Confirms directional bias using ATR.
ZLEMA Envelope — Defines dynamic upper/lower bounds based on price velocity.
🔹 Momentum Filter
Uses a ZLEMA-smoothed CCI to identify accelerating moves.
Long entries require a rising 3-bar CCI sequence.
Short entries require a falling 3-bar CCI sequence.
🔹 Volatility Strength Filter (Vortex Indicator)
Validates entries only when Vortex Diff exceeds a customizable threshold.
Prevents low-volatility "chop zone" trades.
🔹 Wick Trap Filter
Filters out false breakouts driven by liquidity wicks.
Validates that body structure supports the breakout.
📈 Entry & Exit Logic
Long Entry: All trend, momentum, volatility filters must align bullishly and wick traps must be absent.
Short Entry: All filters must align bearishly, with no wick rejection.
Early Exit: Uses ZLEMA slope crossover to exit before a full trend reversal is confirmed.
🎯 Take Profit System
TP1: Takes 50% profit at a user-defined % target.
TP2: Closes remaining 100% at second target.
Cooldown: Prevents immediate reentry and ensures clean position transitions.
📊 Real-Time Strategy Dashboard
Tracks and displays:
Position status (Long, Short, Flat)
Entry Price
TP1/TP2 Hit status
Win Rate (%)
Profit Factor
Bars Since Entry
Fully customizable position & font size
🤖 Bot-Ready Multi-Exchange Alerts
Compatible with WonderTrading, 3Commas, Binance, Bybit, and more.
Customizable comment= tags for entry, exit, TP1, and TP2.
Fully alert-compatible for webhook integrations.
📌 Suggested Use
Best used on trending crypto pairs with moderate-to-high volatility. Recommended on the 1H timeframe for altcoins and majors. Can be used for manual confirmation or automated trading.
🔒 Script Transparency
This is a closed-source script. However, the description above provides a transparent breakdown of the strategy’s core logic, filters, and execution model — ensuring compliance with TradingView’s publishing guidelines.
⚠️ Trading Disclaimer
This script is for educational purposes only and is not financial advice. Always conduct your own analysis before making investment decisions. Past performance does not guarantee future results. Use this strategy at your own risk.
TASC 2025.05 Trading The Channel█ OVERVIEW
This script implements channel-based trading strategies based on the concepts explained by Perry J. Kaufman in the article "A Test Of Three Approaches: Trading The Channel" from the May 2025 edition of TASC's Traders' Tips . The script explores three distinct trading methods for equities and futures using information from a linear regression channel. Each rule set corresponds to different market behaviors, offering flexibility for trend-following, breakout, and mean-reversion trading styles.
█ CONCEPTS
Linear regression
Linear regression is a model that estimates the relationship between a dependent variable and one or more independent variables by fitting a straight line to the observed data. In the context of financial time series, traders often use linear regression to estimate trends in price movements over time.
The slope of the linear regression line indicates the strength and direction of the price trend. For example, a larger positive slope indicates a stronger upward trend, and a larger negative slope indicates the opposite. Traders can look for shifts in the direction of a linear regression slope to identify potential trend trading signals, and they can analyze the magnitude of the slope to support trading decisions.
One caveat to linear regression is that most financial time series data does not follow a straight line, meaning a regression line cannot perfectly describe the relationships between values. Prices typically fluctuate around a regression line to some degree. As such, analysts often project ranges above and below regression lines, creating channels to model the expected extent of the data's variability. This strategy constructs a channel based on the method used in Kaufman's article. It measures the maximum distances from points on the linear regression line to historical price values, then adds those distances and the current slope to the regression points.
Depending on the trading style, traders might look for prices to move outside an established channel for breakout signals, or they might look for price action to reach extremes within the channel for potential mean reversion opportunities.
█ STRATEGY CALCULATIONS
Primary trade rules
This strategy implements three distinct sets of rules for trend, breakout, and mean-reversion trades based on the methods Kaufman describes in his article:
Trade the trend (Rule 1) : Open new positions when the sign of the slope changes, indicating a potential trend reversal. Close short trades and enter a long trade when the slope changes from negative to positive, and do the opposite when the slope changes from positive to negative.
Trade channel breakouts (Rule 2) : Open new positions when prices cross outside the linear regression channel for the current sample. Close short trades and enter a long trade when the price moves above the channel, and do the opposite when the price moves below the channel.
Trade within the channel (Rule 3) : Open new positions based on price values within the channel's range. Close short trades and enter a long trade when the price is near the channel's low, within a specified percentage of the channel's range, and do the opposite when the price is near the channel's high. With this rule, users can also filter the trades based on the channel's slope. When the filter is active, long positions are allowed only when the slope is positive, and short positions are allowed only when it is negative.
Position sizing
Kaufman's strategy uses specific trade sizes for equities and futures markets:
For an equities symbol, the number of shares traded is $10,000 divided by the current price.
For a futures symbol, the number of contracts traded is based on a volatility-adjusted formula that divides $25,000 by the product of the 20-bar average true range and the instrument's point value.
By default, this script automatically uses these sizes for its trade simulation on equities and futures symbols and does not simulate trading on other symbols. However, users can control position sizes from the "Settings/Properties" tab and enable trade simulation on other symbol types by selecting the "Manual" option in the script's "Position sizing" input.
Stop-loss
This strategy includes the option to place an accompanying stop-loss order for each trade, which users can enable from the "SL %" input in the "Settings/Inputs" tab. When enabled, the strategy places a stop-loss order at a specified percentage distance from the closing price where the entry order occurs, allowing users to compare how the strategy performs with added loss protection.
█ USAGE
This strategy adapts its display logic for the three trading approaches based on the rule selected in the "Trade rule" input:
For all rules, the script plots the linear regression slope in a separate pane. The plot is color-coded to indicate whether the current slope is positive or negative.
When the selected rule is "Trade the trend", the script plots triangles in the separate pane to indicate when the slope's direction changes from positive to negative or vice versa. Additionally, it plots a color-coded SMA on the main chart pane, allowing visual comparison of the slope to directional changes in a moving average.
When the rule is "Trade channel breakouts" or "Trade within the channel", the script draws the current period's linear regression channel on the main chart pane, and it plots bands representing the history of the channel values from the specified start time onward.
When the rule is "Trade within the channel", the script plots overbought and oversold zones between the bands based on a user-specified percentage of the channel range to indicate the value ranges where new trades are allowed.
Users can customize the strategy's calculations with the following additional inputs in the "Settings/Inputs" tab:
Start date : Sets the date and time when the strategy begins simulating trades. The script marks the specified point on the chart with a gray vertical line. The plots for rules 2 and 3 display the bands and trading zones from this point onward.
Period : Specifies the number of bars in the linear regression channel calculation. The default is 40.
Linreg source : Specifies the source series from which to calculate the linear regression values. The default is "close".
Range source : Specifies whether the script uses the distances from the linear regression line to closing prices or high and low prices to determine the channel's upper and lower ranges for rules 2 and 3. The default is "close".
Zone % : The percentage of the channel's overall range to use for trading zones with rule 3. The default is 20, meaning the width of the upper and lower zones is 20% of the range.
SL% : If the checkbox is selected, the strategy adds a stop-loss to each trade at the specified percentage distance away from the closing price where the entry order occurs. The checkbox is deselected by default, and the default percentage value is 5.
Position sizing : Determines whether the strategy uses Kaufman's predefined trade sizes ("Auto") or allows user-defined sizes from the "Settings/Properties" tab ("Manual"). The default is "Auto".
Long trades only : If selected, the strategy does not allow short positions. It is deselected by default.
Trend filter : If selected, the strategy filters positions for rule 3 based on the linear regression slope, allowing long positions only when the slope is positive and short positions only when the slope is negative. It is deselected by default.
NOTE: Because of this strategy's trading rules, the simulated results for a specific symbol or channel configuration might have significantly fewer than 100 trades. For meaningful results, we recommend adjusting the start date and other parameters to achieve a reasonable number of closed trades for analysis.
Additionally, this strategy does not specify commission and slippage amounts by default, because these values can vary across market types. Therefore, we recommend setting realistic values for these properties in the "Cost simulation" section of the "Settings/Properties" tab.
Titan X 📈 Titan X – Optimized Trend Strategy with Gradient ZLEMA, RMI, CCI, ROC, and Volume Confirmation
Titan X is a precision-engineered trend-following strategy designed for crypto markets and high-volatility assets. It is not just a combination of indicators, but a carefully constructed, non-repainting system where each component plays a specific role in confirming high-probability trade setups. The strategy detects strong directional moves, confirms them with momentum and volume, and manages trade exits without relying on traditional stop losses.
🔍 How the Indicators Work Together
✅ 1. ZLEMA Baseline + Gradient Filter
A Zero Lag Exponential Moving Average (ZLEMA) is used to track directional trend with minimal lag.
A gradient (slope) is calculated from the ZLEMA to measure trend acceleration. This confirms whether a trend is gaining strength or losing momentum.
Entries are only taken when the ZLEMA gradient exceeds a user-defined threshold, ensuring trades are only taken in strong, developing trends.
✅ 2. RMI – Relative Momentum Index (with Memory)
RMI captures sustained momentum direction over time.
It helps validate that price isn't just spiking, but truly trending.
Titan X uses RMI as a trend memory filter, requiring consistent momentum alignment before entry.
✅ 3. Momentum Timing – ROC + CCI
The Rate of Change (ROC) determines the strength and direction of recent momentum.
The Commodity Channel Index (CCI) checks price deviation from a moving average baseline, identifying whether momentum is aligned with market structure.
This combo prevents trades in weak, flat, or conflicting conditions.
✅ 4. Volume Spike Confirmation
Titan X uses a relative volume filter, requiring the current bar’s volume to exceed a moving average threshold.
This ensures trades are only triggered when there is clear breakout interest from market participants, helping avoid fakeouts and low-volume moves.
🎯 Trade Entry & Exit Rules
✅ Entry Conditions:
All five filters must align:
Trend direction (ZLEMA slope)
Momentum (ROC & CCI)
Trend memory (RMI)
Volume (Spike filter)
Trades are entered on the next bar after all confirmations, ensuring 100% non-repainting behavior.
✅ Take Profit System (Multi-Level TP):
TP1: Closes 50% of the position at a user-defined % gain (default: 2%)
TP2: Closes the remaining 50% of the position at a higher % gain (default: 4%)
Each TP is executed via limit order to ensure realistic and backtestable fills.
❌ No Stop Loss Used
Instead of using fixed stop losses, Titan X closes positions early when trend conditions weaken.
This dynamic exit logic is based on a reversal in ZLEMA gradient, which serves as a weak trend detection system.
⏱️ Cooldown Logic
A 1-bar cooldown is enforced between trades to avoid same-bar exit/entry violations on TradingView.
This improves execution accuracy and avoids overtrading on choppy price action.
📊 Real-Time Strategy Dashboard
Titan X includes a live dashboard that provides full transparency:
Current Position (Long / Short / Flat)
Entry Price
TP1 Hit? / TP2 Hit?
Bars Since Entry
Win Rate (%)
Profit Factor
Ideal for both manual monitoring and automated bot strategies.
🔔 Bot-Ready Multi-Exchange Alerts
Alerts can be configured for:
ENTER-LONG, ENTER-SHORT
EXIT-LONG, EXIT-SHORT
TP1 / TP2 targets
Messages are fully customizable and designed for platforms like:
WonderTrading
3Commas
TradingConnector
⚙️ Designed For:
Timeframes: 1H and 4H (optimized for crypto)
Markets: Altcoins, BTC/ETH, high-volatility pairs
Traders: Trend-followers, momentum scalpers, algo bot users
Goal: High accuracy entries, structured exits, zero repainting, and flexible trade management
⚠️ TradingView Disclosure
This strategy is provided for educational purposes only. It does not constitute investment advice, nor does it guarantee any returns. Trading carries risk; test thoroughly before using in live environments.
VBSMI Strategy by QTX Algo SystemsVolatility Based SMI Strategy by QTX Algo Systems
Overview
The Volatility Based SMI Strategy transforms our popular VBSMI with Dynamic Bands indicator into a fully automated strategy that traders can backtest inside TradingView. It retains all core logic from the indicator—including adaptive volatility scaling and trend-based overbought/oversold thresholds—but adds two configurable entry methods, exit conditions, and a dual-mode trade execution engine.
This script is published separately from the VBSMI indicator because some traders use VBSMI as a confluence tool within their existing system, while others prefer a rules-based strategy that can be simulated, optimized, and tracked over time. This script serves the latter use case.
How It Works
Like the original indicator, this strategy uses:
Double-Smoothed SMI Calculation: Based on smoothed momentum using EMA of the relative and full range.
Adaptive Volatility Scaling: Uses a normalized BBWP-based factor to reflect current market volatility.
Dynamic Band Adjustment: Trend direction and strength shift overbought/oversold levels upward or downward.
Band Tilt & Compression Controls: Inputs allow users to define how aggressively the bands shift with trend conditions.
What’s different is the strategy layer—you now choose from two types of entry and exit logic, and two execution styles.
🛠️ Entry & Exit Modes
There are two logic modes for both entry and exit, allowing you to adapt the strategy to your own philosophy:
Cross Mode (SMI Crosses EMA):
Entry: Buy when SMI crosses above its EMA
Exit: Close when SMI crosses below its EMA
Exit OB/OS Mode (Band Exit Logic):
Entry: Buy when price exits dynamic oversold zone (crosses back above tilted oversold band)
Exit: Close when price exits dynamic overbought zone (crosses back below tilted overbought band)
You can mix and match the modes (e.g., enter on Cross, exit on Band Exit).
⚙️ Spot vs. Leverage Mode
Spot Mode
Designed for traders who prefer long-only setups
Enters a long position and holds until the exit condition is met
Prevents overlapping trades—ensures only one position at a time
Leverage Mode
Designed for those testing bi-directional systems (e.g., long/short switching)
Automatically flips between long and short entries depending on the signals
Useful for testing symmetrical strategies or inverse conditions
Both modes work across any asset class and timeframe.
Customization Options
Users can adjust:
Smoothing K/D: Controls how fast or slow the momentum reacts
SMI EMA Length: Determines the responsiveness of the signal line
Trend Lookback Period: Influences how stable the dynamic band tilt is
Band Tilt & Compression Strengths: Refines how far bands adjust based on trend
Entry/Exit Logic Type: Choose between “Cross” or “Exit OB/OS” logic
Trading Mode: Select either "Spot" or "Leverage" depending on your use case
Why It’s Published Separately
This script is not a cosmetic or minor variation of the original indicator. It introduces:
Entry/exit logic
Order execution
Strategy testing capabilities
Mode selection (Spot vs. Leverage)
Signal logic control (Cross vs. Band Exit)
Because the original VBSMI indicator is widely used as a charting and confirmation tool, converting it into a strategy changes how it functions. This version is intended for strategy evaluation and automation, while the original remains available for discretionary and visual use.
Use Cases
This strategy is best suited for:
Evaluating VBSMI-based signals in backtests
Comparing entry and exit logic over time
Testing setups on different assets and timeframes
Automating VBSMI-based logic in a structured and risk-aware framework
Disclaimer
This strategy is for educational purposes only. It does not guarantee future results or profitability. Always test in simulation before using any strategy live, and use proper risk management and trade discipline.
AI Volume StrategyAI Volume Strategy detects significant volume spikes and combines them with trend direction and candlestick color to generate buy and sell signals. The strategy uses an Exponential Moving Average (EMA) of volume to identify abnormal volume spikes that may indicate strong market activity. Additionally, it uses a 50-period EMA of price to filter the trend and decide on entry direction.
Key Features:
Volume Spike Detection: The strategy detects when the current volume exceeds the EMA of volume by a user-defined multiplier, signaling abnormal increases in market activity.
Trend Direction Filter: The strategy uses a 50-period EMA of price to determine the market trend. Buy signals are generated when the price is above the EMA (uptrend), and sell signals are generated when the price is below the EMA (downtrend).
Candle Color Filter: The strategy generates a buy signal only when the current candle is bullish (green) and a sell signal only when the current candle is bearish (red).
Exit after X Bars: The strategy automatically closes the position after a specified number of bars (default is 5 bars), but the exit condition can be adjusted based on user preference, timeframe, and backtesting results. The default exit is after 5 bars, but users can set it to 1 bar or any other number depending on their preferences and strategy.
Signals:
Buy Signal: Generated when a volume spike occurs, the trend is upward, and the current candle is bullish.
Sell Signal: Generated when a volume spike occurs, the trend is downward, and the current candle is bearish.
Alerts:
Buy Alert: Alerts the user when a buy signal is triggered.
Sell Alert: Alerts the user when a sell signal is triggered.
Visualization:
Buy Signal: A green label appears below the bar when the buy conditions are met.
Sell Signal: A red label appears above the bar when the sell conditions are met.
Volume EMA: Optionally, the Volume EMA line can be plotted on the chart to visualize volume trends.
This strategy helps traders identify potential entry points based on increased volume activity while considering trend direction and candlestick patterns. With the ability to adjust the exit condition, users can fine-tune the strategy to their specific needs and backtest results.
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.
Trend MatrixFinal TradingView-Compliant Description for Trend Matrix
Trend Matrix is a precision-engineered trend-following strategy built for high-confidence entries and tactical trade management.
This strategy combines multiple non-repainting filters, each with a distinct role, to form a unified "trend matrix" that confirms directional bias, volume commitment, and momentum strength — all before entry is considered.
🔍 Core Components & Why They’re Used
🧠 Gaussian Filter (Custom)
A smoothed Gaussian-weighted moving average is used to detect trend direction changes. Unlike standard EMAs, this filter minimizes lag while retaining smooth transitions — ideal for confirming trend shifts without false reversals.
📈 RMI Trend Memory
A Relative Momentum Index is used to validate trend direction persistence. RMI's ability to filter out short-term oscillations makes it ideal for confirming whether a trend is still active.
📊 Gradient Filter (ZLEMA-based)
Measures the slope of a ZLEMA-smoothed close. If slope flips, it signals a potential trend weakness. This provides real-time confirmation for entry or exit bias.
📉 Volume Spike Detection
Confirms that breakouts or trend continuations are supported by volume commitment. Uses a dynamic SMA-based volume filter with a user-defined multiplier.
🟦 White Line (Bias Midpoint)
This structural component calculates the midpoint of the highest high and lowest low over a range — providing directional context and helping eliminate trades in consolidation zones.
🎯 Entry Conditions
Long entries require:
Gaussian trend flip to the upside
RMI > 50 (bullish memory)
Volume spike confirmation
Positive gradient (ZLEMA slope)
Price above White Line (bias filter)
Short entries use the inverse logic.
All entries enforce a cooldown bar to prevent same-bar reversals or whipsaw trades.
🎯 Exit Conditions
Take Profit 1: 50% of position at +2%
Take Profit 2: Remaining 50% at +4%
Early Exit on Trend Weakness:
Position closes fully if the trend weakens (RMI flip or gradient reversal)
📊 Dashboard + Performance Tracking
The built-in dashboard shows:
Current Position
Entry Price
TP1/TP2 Hit Status
Bars Since Entry
Win Rate (%)
Profit Factor
Useful for manual tracking or live trading review.
🌐 Multi-Exchange Bot Compatibility
Trend Matrix is built with universal trade alerts using customizable comment= fields. This makes it compatible with any exchange-connected bot platform such as:
WunderTrading
3Commas
Alertatron
Cornix
Or any webhook-based trading system
Alerts are sent using the {{strategy.order.comment}} placeholder, allowing you to route entries and exits through your preferred exchange account on Binance, Bybit, OKX, Kraken, and others.
🛠️ Customization
All components are modular:
TP1/TP2 levels
Gaussian length & sigma
Volume spike filter sensitivity
Gradient & White Line length
RMI settings
You can tailor the strategy for different assets or timeframes — optimized for crypto 1H, but works with stocks, FX, or lower timeframes with adjusted parameters.
✅ Final Notes
Trend Matrix is not just a mashup — it's a synchronized system of filters with clear roles, designed to maximize trade confidence and minimize noise. Every layer of confirmation serves a purpose, making this a highly adaptive trend-following tool for any market environment.
⚠️ Disclaimer (as required by TradingView)
This script is for educational purposes only and does not constitute financial advice. Use at your own risk. Always test strategies thoroughly before applying them in live trading environments. Past performance is not indicative of future results.
Dkoderweb repainting issue fix strategyHarmonic Pattern Recognition Trading Strategy
This TradingView strategy called "Dkoderweb repainting issue fix strategy" is designed to identify and trade harmonic price patterns with optimized entry and exit points using Fibonacci levels. The strategy implements various popular harmonic patterns including Bat, Butterfly, Gartley, Crab, Shark, ABCD, and their anti-patterns.
Key Features
Pattern Recognition: Identifies 17+ harmonic price patterns including standard and anti-patterns
Fibonacci-Based Entries and Exits: Uses customizable Fibonacci levels for precision entries, take profits, and stop losses
Alternative Timeframe Analysis: Option to use higher timeframes for pattern identification
Heiken Ashi Support: Optional use of Heiken Ashi candles instead of regular candlesticks
Visual Indicators:
Pattern visualization with ZigZag indicator
Buy/sell signal markers
Color-coded background to highlight active trade zones
Customizable Fibonacci level display
How It Works
The strategy uses a ZigZag-based pattern identification system to detect pivot points
When a valid harmonic pattern forms, the strategy calculates the optimal entry window using the specified Fibonacci level (default 0.382)
Entries trigger when price returns to the entry window after pattern completion
Take profit and stop loss levels are automatically set based on customizable Fibonacci ratios
Visual alerts notify you of entries and exits
The strategy tracks active trades and displays them with background color highlights
Customizable Settings
Trade size
Entry window Fibonacci level (default 0.382)
Take profit Fibonacci level (default 0.618)
Stop loss Fibonacci level (default -0.618)
Alert messages for entries and exits
Display options for specific Fibonacci levels
Alternative timeframe selection
This strategy is designed to fix repainting issues that are common in harmonic pattern strategies, ensuring more reliable signals and backtesting results.
NY First Candle Break and RetestStrategy Overview
Session and Time Parameters:
The strategy focuses on the New York trading session, starting at 9:30 AM and lasting for a predefined session length, typically 3 to 4 hours. This timing captures the most active market hours, providing ample trading opportunities.
Strategy Parameters:
Utilizes the Average True Range (ATR) to set dynamic stop-loss levels, ensuring risk is managed according to market volatility.
Employs a reward-to-risk ratio to determine take profit levels, aiming for a balanced approach between potential gains and losses.
Strategy Settings:
Incorporates simple moving averages (EMA) and the Volume Weighted Average Price (VWAP) to identify trend direction and price levels.
Volume confirmation is used to validate breakouts, ensuring trades are based on significant market activity.
Trade Management:
Features a trailing stop mechanism to lock in profits as the trade moves in favor, with multiple take profit levels to secure gains incrementally.
The strategy is designed to handle both long and short positions, adapting to market conditions.
Alert Settings:
Provides alerts for key events such as session start, breakout, retest, and entry signals, helping traders stay informed and act promptly.
Visual cues on the chart highlight entry and exit points, making it easier for beginners to follow the strategy.
This strategy is particularly suited for the current volatile market environment, where simplicity and clear guidelines can help beginner traders navigate the complexities of trading. It emphasizes risk management and uses straightforward indicators to make informed trading decisions.
I put together this Trading View scalping strategy for futures markets with some help from Claude AI. Shoutout to everyone who gave me advice along the way—I really appreciate it! I’m sure there’s room for improvement, so feel free to share your thoughts… just go easy on me. :)
BB Breakout + Momentum Squeeze [Strategy]This Strategy is Based on 3 free indicators
- Bollinger Bands Breakout Oscillator: Link
- TTM Squeeze Pro: Link
- Rolling ATR Bands: Link
Bollinger Bands Breakout Oscillator - This tool shows how strong a market trend is by measuring how often prices move outside their normal Bollinger bands range. It helps you see whether prices are strongly moving in one direction or just moving sideways. By looking at how much and how frequently prices push beyond their typical boundaries, you can identify which direction the market is heading over your selected time period.
TM Squeeze Pro - This is a custom version of the TTM Squeeze indicator.
It's designed to help traders spot consolidation phases in the market (when price is coiling or "squeezing") and to catch breakouts early when volatility returns. The logic is based on the relationship between Bollinger Bands and Keltner Channels, combined with a momentum oscillator to show direction and strength.
Rolling ATR Bands - This indicator combines volatility bands (ATR) with momentum and trend signals to show where the market might be breaking out, retesting, or trending. It's highly visual and helpful for traders looking to time entries/exits during trending or volatile moves.
Logic Of the Strategy:
We are going to use the Bollinger Bands Breakout to determine the direction of the market. Than check the Volatility of the price by looking at the TTM Squeeze indicator. And use the ATR Bands to determine dynamic Stop Losses and based on the calculate the Take Profit targets and quantity for each position dynamically.
For the Long Setup:
1. We need to see the that Bull Power (Green line of the Bollinger Bands Breakout Oscilator) is crossing the level of 50.
2. Check the presence of volatility (Green dot based on the TTM Squeeze indicator)
For the Short Setup:
1. We need to see the that Bear Power (Red line of the Bollinger Bands Breakout Oscilator) is crossing the level of 50.
2. Check the presence of volatility (Green dot based on the TTM Squeeze indicator)
Stop Loss is determined by the Lower ATR Band (for the Long entry) and Upper ATR Band (For the Short entry)
Take Profit is 1:1.5 risk reward ration, which means if the Stop loss is 1% the TP target will be 1.5%
Move stop Loss to Breakeven: If the price will go in the direction of the trade for at least half of the Risk Reward target then the stop will automatically be adjusted to the entry price. For Example: the Stop Loss is 1%, the price has move at least 0.5% in the direction of your trade and that will move the Stop Loss level to the Entry point.
You can Adjust the parameters for each indicator used in that script and also adjust the Risk and Money management block to see how the PnL will change.
