Quantum Flux Universal Strategy Summary in one paragraph
Quantum Flux Universal is a regime switching strategy for stocks, ETFs, index futures, major FX pairs, and liquid crypto on intraday and swing timeframes. It helps you act only when the normalized core signal and its guide agree on direction. It is original because the engine fuses three adaptive drivers into the smoothing gains itself. Directional intensity is measured with binary entropy, path efficiency shapes trend quality, and a volatility squash preserves contrast. Add it to a clean chart, watch the polarity lane and background, and trade from positive or negative alignment. For conservative workflows use on bar close in the alert settings when you add alerts in a later version.
Scope and intent
• Markets. Large cap equities and ETFs. Index futures. Major FX pairs. Liquid crypto
• Timeframes. One minute to daily
• Default demo used in the publication. QQQ on one hour
• Purpose. Provide a robust and portable way to detect when momentum and confirmation align, while dampening chop and preserving turns
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. The novelty sits in the gain map. Instead of gating separate indicators, the model mixes three drivers into the adaptive gains that power two one pole filters. Directional entropy measures how one sided recent movement has been. Kaufman style path efficiency scores how direct the path has been. A volatility squash stabilizes step size. The drivers are blended into the gains with visible inputs for strength, windows, and clamps.
• What failure mode it addresses. False starts in chop and whipsaw after fast spikes. Efficiency and the squash reduce over reaction in noise.
• Testability. Every component has an input. You can lengthen or shorten each window and change the normalization mode. The polarity plot and background provide a direct readout of state.
• Portable yardstick. The core is normalized with three options. Z score, percent rank mapped to a symmetric range, and MAD based Z score. Clamp bounds define the effective unit so context transfers across symbols.
Method overview in plain language
The strategy computes two smoothed tracks from the chart price source. The fast track and the slow track use gains that are not fixed. Each gain is modulated by three drivers. A driver for directional intensity, a driver for path efficiency, and a driver for volatility. The difference between the fast and the slow tracks forms the raw flux. A small phase assist reduces lag by subtracting a portion of the delayed value. The flux is then normalized. A guide line is an EMA of a small lead on the flux. When the flux and its guide are both above zero, the polarity is positive. When both are below zero, the polarity is negative. Polarity changes create the trade direction.
Base measures
• Return basis. The step is the change in the chosen price source. Its absolute value feeds the volatility estimate. Mean absolute step over the window gives a stable scale.
• Efficiency basis. The ratio of net move to the sum of absolute step over the window gives a value between zero and one. High values mean trend quality. Low values mean chop.
• Intensity basis. The fraction of up moves over the window plugs into binary entropy. Intensity is one minus entropy, which maps to zero in uncertainty and one in very one sided moves.
Components
• Directional Intensity. Measures how one sided recent bars have been. Smoothed with RMA. More intensity increases the gain and makes the fast and slow tracks react sooner.
• Path Efficiency. Measures the straightness of the price path. A gamma input shapes the curve so you can make trend quality count more or less. Higher efficiency lifts the gain in clean trends.
• Volatility Squash. Normalizes the absolute step with Z score then pushes it through an arctangent squash. This caps the effect of spikes so they do not dominate the response.
• Normalizer. Three modes. Z score for familiar units, percent rank for a robust monotone map to a symmetric range, and MAD based Z for outlier resistance.
• Guide Line. EMA of the flux with a small lead term that counteracts lag without heavy overshoot.
Fusion rule
• Weighted sum of the three drivers with fixed weights visible in the code comments. Intensity has fifty percent weight. Efficiency thirty percent. Volatility twenty percent.
• The blend power input scales the driver mix. Zero means fixed spans. One means full driver control.
• Minimum and maximum gain clamps bound the adaptive gain. This protects stability in quiet or violent regimes.
Signal rule
• Long suggestion appears when flux and guide are both above zero. That sets polarity to plus one.
• Short suggestion appears when flux and guide are both below zero. That sets polarity to minus one.
• When polarity flips from plus to minus, the strategy closes any long and enters a short.
• When flux crosses above the guide, the strategy closes any short.
What you will see on the chart
• White polarity plot around the zero line
• A dotted reference line at zero named Zen
• Green background tint for positive polarity and red background tint for negative polarity
• Strategy long and short markers placed by the TradingView engine at entry and at close conditions
• No table in this version to keep the visual clean and portable
Inputs with guidance
Setup
• Price source. Default ohlc4. Stable for noisy symbols.
• Fast span. Typical range 6 to 24. Raising it slows the fast track and can reduce churn. Lowering it makes entries more reactive.
• Slow span. Typical range 20 to 60. Raising it lengthens the baseline horizon. Lowering it brings the slow track closer to price.
Logic
• Guide span. Typical range 4 to 12. A small guide smooths without eating turns.
• Blend power. Typical range 0.25 to 0.85. Raising it lets the drivers modulate gains more. Lowering it pushes behavior toward fixed EMA style smoothing.
• Vol window. Typical range 20 to 80. Larger values calm the volatility driver. Smaller values adapt faster in intraday work.
• Efficiency window. Typical range 10 to 60. Larger values focus on smoother trends. Smaller values react faster but accept more noise.
• Efficiency gamma. Typical range 0.8 to 2.0. Above one increases contrast between clean trends and chop. Below one flattens the curve.
• Min alpha multiplier. Typical range 0.30 to 0.80. Lower values increase smoothing when the mix is weak.
• Max alpha multiplier. Typical range 1.2 to 3.0. Higher values shorten smoothing when the mix is strong.
• Normalization window. Typical range 100 to 300. Larger values reduce drift in the baseline.
• Normalization mode. Z score, percent rank, or MAD Z. Use MAD Z for outlier heavy symbols.
• Clamp level. Typical range 2.0 to 4.0. Lower clamps reduce the influence of extreme runs.
Filters
• Efficiency filter is implicit in the gain map. Raising efficiency gamma and the efficiency window increases the preference for clean trends.
• Micro versus macro relation is handled by the fast and slow spans. Increase separation for swing, reduce for scalping.
• Location filter is not included in v1.0. If you need distance gates from a reference such as VWAP or a moving mean, add them before publication of a new version.
Alerts
• This version does not include alertcondition lines to keep the core minimal. If you prefer alerts, add names Long Polarity Up, Short Polarity Down, Exit Short on Flux Cross Up in a later version and select on bar close for conservative workflows.
Strategy has been currently adapted for the QQQ asset with 30/60min timeframe.
For other assets may require new optimization
Properties visible in this publication
• Initial capital 25000
• Base currency Default
• Default order size method percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Honest limitations and failure modes
• Past results do not guarantee future outcomes
• Economic releases, circuit breakers, and thin books can break the assumptions behind intensity and efficiency
• Gap heavy symbols may benefit from the MAD Z normalization
• Very quiet regimes can reduce signal contrast. Use longer windows or higher guide span to stabilize context
• Session time is the exchange time of the chart
• If both stop and target can be hit in one bar, tie handling would matter. This strategy has no fixed stops or targets. It uses polarity flips for exits. If you add stops later, declare the preference
Open source reuse and credits
• None beyond public domain building blocks and Pine built ins such as EMA, SMA, standard deviation, RMA, and percent rank
• Method and fusion are original in construction and disclosure
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Strategy add on block
Strategy notice
Orders are simulated by the TradingView engine on standard candles. No request.security() calls are used.
Entries and exits
• Entry logic. Enter long when both the normalized flux and its guide line are above zero. Enter short when both are below zero
• Exit logic. When polarity flips from plus to minus, close any long and open a short. When the flux crosses above the guide line, close any short
• Risk model. No initial stop or target in v1.0. The model is a regime flipper. You can add a stop or trail in later versions if needed
• Tie handling. Not applicable in this version because there are no fixed stops or targets
Position sizing
• Percent of equity in the Properties panel. Five percent is the default for examples. Risk per trade should not exceed five to ten percent of equity. One to two percent is a common choice
Properties used on the published chart
• Initial capital 25000
• Base currency Default
• Default order size percent of equity with value 5
• Pyramiding 1
• Commission 0.05 percent
• Slippage 10 ticks
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Dataset and sample size
• Test window Jan 2, 2014 to Oct 16, 2025 on QQQ one hour
• Trade count in sample 324 on the example chart
Release notes template for future updates
Version 1.1.
• Add alertcondition lines for long, short, and exit short
• Add optional table with component readouts
• Add optional stop model with a distance unit expressed as ATR or a percent of price
Notes. Backward compatibility Yes. Inputs migrated Yes.
Cari skrip untuk "能做t++0的etf有哪些"
Continuation Suite v1 — 5m/15mContinuation Suite v1 — 5m/15m (Non-Repainting, S/R + Trend Continuation)
What it does
Continuation Suite v1 is a practical intraday toolkit that combines non-repainting trend-continuation signals with auto-built Support/Resistance (S/R) from confirmed pivots. It’s designed for fast, liquid names on 5m charts with an optional 15m higher-timeframe (HTF) overlay. You get: stacked-EMA bias, disciplined pullback+reclaim entries, optional volume/volatility gates, a “Strong” signal tier, solid S/R lines or zones, and a compact dashboard for fast reads.
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Why traders use it
• Clear bias using fast/mid/slow EMA stacking.
• Actionable entries that require a pullback, a reclaim, and (optionally) a minor break of prior extremes.
• Signal quality gates (volume vs SMA, ATR%, ADX/DI alignment, EMA spacing, slope).
• Non-repainting logic when “Confirm on Close” = ON. Intrabar previews show what’s forming, but confirmed signals only print on bar close.
• S/R that matters: confirmed-pivot lines or ATR-sized zones, optional HTF overlay, and auto de-dup to avoid clutter.
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Signal construction (no magic, just rules)
Bullish continuation (base):
1. Trend: EMA fast > EMA mid > EMA slow
2. Pullback: price pulls into the stack (lowest low or close vs EMA fast/mid over a lookback)
3. Reclaim: close > EMA fast and close > open
4. Break filter (optional): current bar takes out the prior bar’s high
5. Filters: volume > SMA (if enabled) and ATR% ≤ max (if enabled)
6. Cooldown: a minimum bar gap between signals
Bearish continuation (base): mirror of the above.
Strong signals: base conditions plus ADX ≥ threshold, DI alignment (DI+>DI- for longs; DI->DI+ for shorts), minimum EMA-spacing %, and minimum fast-EMA slope.
Reference stops:
• Longs: lowest low over the pullback lookback
• Shorts: highest high over the pullback lookback
Alerts are included for: Bullish Continuation, Bearish Continuation, STRONG Bullish, STRONG Bearish.
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S/R engine (current TF + optional HTF)
• Builds S/R from confirmed pivots only (left/right bars).
• Choose Lines (midlines) or Zones (ATR-sized).
• Zones merge when a new pivot lands near an existing zone’s mid (ATR-scaled epsilon).
• Touches counter tracks significance; you can require a minimum to draw.
• HTF overlay (default 15m) draws separate lines/zones with tiny TF tags on the right.
• De-dup option hides current-TF zones that sit too close to HTF zones (ATR-scaled), reducing overlap.
• Freeze on Close (optional) keeps arrays stable intrabar; snapshots show levels immediately as bars open.
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Presets
• Auto: Detects QQQ-like tickers (QQQ, QLD, QID) or SoFi; else defaults to Custom.
• QQQ: Tighter ATR% and EMA settings geared to index-ETF behavior.
• SoFi: Wider ATR allowances and longer mid/slow for single-name behavior.
• Custom: Expose all key inputs to tune for your product.
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Dashboard (top-right)
• Preset in use
• Bias (Bullish CONT / Bearish CONT / Neutral)
• Strong (Yes/No)
• Volatility (ATR% bucket)
• Trend (ADX bucket)
• HTF timeframe tag
• Volume (bucket or “off”)
• Signals mode (Close-Confirmed vs Intrabar)
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Inputs you’ll actually adjust
Trend/Signals
• Fast/Mid/Slow EMA lengths
• Pullback lookback, Min bars between signals
• Volume filter (vol > SMA N)
• ATR% max filter (cap excessive volatility)
• Require break of prior bar’s high/low
• “Strong” gates: min EMA slope, min EMA spacing %, ADX length & threshold
Support/Resistance
• Lines vs Zones
• Pivot left/right bars
• Extend left/right (bars)
• Max pivots kept (current & HTF)
• Zone width (× ATR), Merge epsilon (× ATR), Min gap (× ATR)
• Min touches, Max zones per side near price
• De-dup current TF vs HTF (× ATR)
Repainting control
• Confirm on Close: when ON, signals/SR finalize on bar close (non-repainting)
• Freeze on Close: freeze S/R intrabar with snapshot updates
• Show previews: translucent intrabar labels for what’s forming
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How to use it (straightforward)
1. Load on 5-minute chart (baseline). Keep Confirm on Close ON if you hate repainting.
2. Use Bias + Strong + S/R context. If a long prints into HTF resistance, you have information.
3. Manage risk off the reference stop (pullback extreme). If ATR% reads “Great,” widen expectations; if “Poor,” size down or pass.
4. Alerts: wire the four alert types to your workflow.
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Notes and constraints
• Designed for liquid symbols. Thin books and synthetic “volume” will degrade the volume gate.
• S/R is pivot-based. On very choppy tape, touch counts help. Increase min touches or switch to Lines to declutter.
• If your chart timeframe isn’t 5m, behavior changes because lengths are in bars, not minutes. Tune lengths accordingly.
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Disclaimers
This is a research tool. No signals are guaranteed. Markets change, outliers happen, slippage is real. Nothing here is financial advice—use your own judgment and risk management.
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Author: DaddyScruff
License: MPL-2.0 (Mozilla Public License 2.0)
Portfolio Simulator & BacktesterMulti-asset portfolio simulator with different metrics and ratios, DCA modeling, and rebalancing strategies.
Core Features
Portfolio Construction
Up to 5 assets with customizable weights (must total 100%)
Support for any tradable symbol: stocks, ETFs, crypto, indices, commodities
Real-time validation of allocations
Dollar Cost Averaging
Monthly or Quarterly contributions
Applies to both portfolio and benchmark for fair comparison
Model real-world investing behavior
Rebalancing
Four strategies: None, Monthly, Quarterly, Yearly
Automatic rebalancing to target weights
Transaction cost modeling (customizable fee %)
Key Metrics Table
CAGR: Annualized compound return (S&P 500 avg: ~10%)
Alpha: Excess return vs. benchmark (positive = outperformance)
Sharpe Ratio: Return per unit of risk (>1.0 is good, >2.0 excellent)
Sortino Ratio: Like Sharpe but only penalizes downside (better metric)
Calmar Ratio: CAGR / Max Drawdown (>1.0 good, >2.0 excellent)
Max Drawdown: Largest peak-to-trough decline
Win Rate: % of positive days (doesn't indicate profitability)
Visualization
Dual-chart comparison - Portfolio vs. Benchmark
Dollar or percentage view toggle
Customizable colors and line width
Two tables: Statistics + Asset Allocation
Adjustable table position and text size
🚀 Quick Start Guide
Enter 1-5 ticker symbols (e.g., SPY, QQQ, TLT, GLD, BTCUSD)
Make sure percentage weights total 100%
Choose date range (ensure chart shows full period - zoom out!)
Configure DCA and rebalancing (optional)
Select benchmark (default: SPX)
Analyze results in statistics table
💡 Pro Tips
Chart data matters: Load SPY or your longest-history asset as main chart
If you select an asset that was not available for the selected period, the chart will not show up! E.g. BTCUSD data: Only available from ~2017 onwards.
Transaction fees: 0.1% default (adjust to match your broker)
⚠️ Important Notes
Requires visible chart data (zoom out to show full date range)
Limited by each asset's historical data availability
Transaction fees and costs are modeled, but taxes/slippage are not
Past performance ≠ future results
Use for research and education only, not financial advice
Let me know if you have any suggestions to improve this simulator.
Recovery StrategyDescription:
The Recovery Strategy is a long-only trading system designed to capitalize on significant price drops from recent highs. It enters a position when the price falls 10% or more from the highest high over a 6-month lookback period and adds positions on further 2% drops, up to a maximum of 5 positions. Each trade is held for 6 months before exiting, regardless of profit or loss. The strategy uses margin to amplify position sizes, with a default leverage of 5:1 (20% margin requirement). All key parameters are customizable via inputs, allowing flexibility for different assets and timeframes. Visual markers indicate recent highs for reference.
How It Works:
Entry: Buys when the closing price drops 10% or more from the recent high (highest high in the lookback period, default 126 bars ~6 months). If already in a position, additional buys occur on further 2% drops (e.g., 12%, 14%, 16%, 18%), up to 5 positions (pyramiding).
Exit: Each trade exits after its own holding period (default 126 bars ~6 months), regardless of profit or loss. No stop loss or take-profit is used.
Margin: Uses leverage to control larger positions (default 20% margin, 5:1 leverage). The order size is a percentage of equity (default 100%), adjustable via inputs.
Visualization: Displays blue markers (without text) at new recent highs to highlight reference levels.
Inputs:
Lookback Period for High Peak (bars): Number of bars to look back for the recent high (default: 126, ~6 months on daily charts).
Initial Drop Percentage to Buy (%): Percentage drop from recent high to trigger the first buy (default: 10.0%).
Additional Drop Percentage to Buy (%): Further drop percentage to add positions (default: 2.0%).
Holding Period (bars): Number of bars to hold each position before selling (default: 126, ~6 months).
Order Size (% of Equity): Percentage of equity used per trade (default: 100%).
Margin for Long Positions (%): Percentage of position value covered by equity (default: 20%, equivalent to 5:1 leverage).
Usage:
Timeframe: Designed for daily charts (126 bars ~6 months). Adjust Lookback Period and Holding Period for other timeframes (e.g., 1008 hours for hourly charts, assuming 8 trading hours/day).
Assets: Suitable for stocks, ETFs, or other assets with significant price volatility. Test thoroughly on your chosen asset.
Settings: Customize inputs in the strategy settings to match your risk tolerance and market conditions. For example, lower Margin for Long Positions (e.g., to 10% for 10:1 leverage) to increase position sizes, but beware of higher risk.
Backtesting: Use TradingView’s Strategy Tester to evaluate performance. Check the “List of Trades” for skipped trades due to insufficient equity or margin requirements.
Risks and Considerations:
No Stop Loss: The strategy holds trades for the full 6 months without a stop loss, exposing it to significant drawdowns in prolonged downtrends.
Margin Risk: Leverage (default 5:1) amplifies both profits and losses. Ensure sufficient equity to cover margin requirements to avoid skipped trades or simulated margin calls.
Pyramiding: Up to 5 positions can be open simultaneously, increasing exposure. Adjust pyramiding in the code if fewer positions are desired (e.g., change to pyramiding=3).
Market Conditions: Performance depends on price drops and recoveries. Test on historical data to assess effectiveness in your market.
Broker Emulator: TradingView’s paper trading simulates margin but does not execute real margin trading. Results may differ in live trading due to broker-specific margin rules.
How to Use:
Add the strategy to your chart in TradingView.
Adjust input parameters in the settings panel to suit your asset, timeframe, and risk preferences.
Run a backtest in the Strategy Tester to evaluate performance.
Monitor open positions and margin levels in the Trading Panel to manage risk.
For live trading, consult your broker’s margin requirements and leverage policies, as TradingView’s simulation may not match real-world conditions.
Disclaimer:
This strategy is for educational purposes only and does not constitute financial advice. Trading involves significant risk, especially with leverage and no stop loss. Always backtest thoroughly and consult a financial advisor before using any strategy in live trading.
Fear & Greed [theUltimator5]This indicator attempts to replicate CNN's Fear & Greed Index methodology to measure market sentiment on a scale from 0-100. It combines seven key market components into a single sentiment score, where lower values indicate fear and higher values indicate greed.
Note: It is impossible to perfectly replicate the true Fear & Greed indicator due to data limitations, so this indicator attempts to best replicate the output for each of the (7) components using available data.
The uniqueness of this indicator comes from the calculation methods for the 7 components as well as the visual representation of the data, which includes a table and selectable plots for each of the 7 components which make up the overall sentiment. Existing variants of the Fear & Greed Index have substantial flaws in the calculations of several of the components which result in warped final sentiment numbers. This indicator attempts to better track all 7 components and provide a closer model to the actual Fear & Greed index.
Here are the seven components and a brief description of how each are calculated:
1. Market Momentum
Calculation: S&P 500 current price vs. 125-day moving average
Measures how far the market has moved from its long-term trend
Uses CNN-style Z-score normalization over 252 trading days
Higher values indicate strong upward momentum (greed)
Lower values suggest declining momentum (fear)
2. Stock Strength
Calculation: S&P 500 RSI scaled to 252-day range
Uses 14-period RSI of the S&P 500 index
Normalizes RSI values based on their 252-day minimum and maximum
Measures overbought/oversold conditions relative to recent history
Higher values indicate overbought conditions (greed)
Lower values suggest oversold conditions (fear)
3. Price Breadth
Calculation: Modified McClellan Oscillator
Primary: Uses NYSE advancing vs. declining issues with 7-day smoothing
Fallback: Compares sector performance (QQQ, IWM vs. SPY)
Measures how many stocks participate in market moves
Broader participation indicates healthier trends
Narrow breadth suggests selective or weak trends
4. Put/Call Ratio
Calculation: Inverted CBOE Put/Call ratios
Primary: CBOE Equity-only Put/Call ratio (more sensitive)
Fallback: CBOE Total Put/Call ratio
Uses 5-day average and applies CNN normalization
Higher put/call ratios indicate fear (inverted to lower scores)
Lower put/call ratios suggest complacency (higher scores)
5. Market Volatility
Calculation: VIX relative to its 50-day average
Compares current VIX level to its 50-day moving average
Measures deviation from normal volatility expectations
Higher VIX relative to average indicates fear (lower scores)
Lower relative VIX suggests complacency (higher scores)
6. Safe Haven Demand
Calculation: Stock returns vs. bond yield changes
Compares 20-day smoothed S&P 500 returns to Treasury yield changes
When stocks outperform bonds, indicates risk appetite (higher scores)
When bonds outperform stocks, suggests risk aversion (lower scores)
Uses Treasury 10-year yields as the safe haven benchmark
7. Junk Bond Demand
Calculation: High-yield bond spread analysis
Measures yield spread between junk bonds (JNK ETF) and Treasuries
Compares current spread to its 5-day average
Narrowing spreads indicate risk appetite (higher scores)
Widening spreads suggest risk aversion (lower scores)
The combined sentiment is plotted as a single line which changes color based on the current sentiment value.
0-25: Extreme Fear (Red) - Market panic, oversold conditions
26-45: Fear (Orange) - Cautious sentiment, bearish bias
46-55: Neutral (Yellow) - Balanced market sentiment
56-75: Greed (Light Green) - Optimistic sentiment, bullish bias
76-100: Extreme Greed (Green) - Market euphoria, potentially overbought
There are dashed lines to represent the threshold values for each of the sentiments to better visualize transitions.
The table displays each of the (7) components of the index and their respective values. The table can be toggled on/off and the position can be moved.
An optional secondary line can be toggled on to display (1) of the (7) components as a unique color and the component name and value will highlight on the table. The secondary line can be used to dig into the main driving forces behind the overall index value.
Real-Time FTFC Dashboard (Styled)Full Time Frame Continuity dashboard that monitors real-time market direction across multiple timeframes for any stock, ETF, or index. Uses green, red, and pause emojis to visually indicate bullish, bearish, or inactive periods, helping traders quickly assess overall market alignment.
200 SMA (5%/-3% Buffer) for SPY & QQQ In my testing TQQQ is an absolute monster of an ETF that performs extremely well even from a buy and hold standpoint over long periods of time, its largest drawback is the massive drawdown exposure that it faces which can be easily sidestepped with this strategy.
This strategy is meant to basically abuse TQQQ's insane outperformance while augmenting the typical 200SMA strategy in a way that uses all of its strengths while avoiding getting whipsawed in sideways markets.
The strategy BUYS when price crosses 5% over the 200SMA and then SELLS when price drops 3% below the 200SMA. Between trades I'll be parking my entire account in SGOV.
So maximizing profit while minimizing risk.
You use the strategy based off of QQQ and then make the trades on TQQQ when it tells you to BUY/SELL.
Here are some reasons why I will be using this strategy:
Simple emotionless BUY and SELL signals where I don't care who the president is, what is happening in the world, who is bombing who, who the leadership team is, no attachment to individual companies and diversified across the NASDAQ.
~85% win percentage and when it does lose the loses are nothing compared to the wins and after a loss you're basically set up for a massive win in the next trade.
Max drawdown of around 53% when using TQQQ
You benefit massively when the market is doing well and when there is a recession you basically sit in SGOV for a year and then are set up for a monster recovery with a clear easy BUY signal. So as long as you're patient you win regardless of what happens.
The trades are often very long term resulting in you taking advantage of Long Term Capital Gains tax advantage which could mean saving up to 15-20% in taxes.
With only a few trades you can spend time doing other stuff and don't have to track or pay attention to anything that is happening.
Simple, easy, and massively profitable.
Options Strategy V1.3📈 Options Strategy V1.3 — EMA Crossover + RSI + ATR + Opening Range
Overview:
This strategy is designed for short-term directional trades on large-cap stocks or ETFs, especially when trading options. It combines classic trend-following signals with momentum confirmation, volatility-based risk management, and session timing filters to help identify high-probability entries with predefined stop-loss and profit targets.
🔍 Strategy Components:
EMA Crossover (Fast/Slow)
Entry signals are triggered by the crossover of a short EMA above or below a long EMA — a traditional trend-following method to detect shifts in momentum.
RSI Filter
RSI confirms the signal by avoiding entries in overbought/oversold zones unless certain momentum conditions are met.
Long entry requires RSI ≥ Long Threshold
Short entry requires RSI ≤ Short Threshold
ATR-Based SL & TP
Stop-loss is set dynamically as a multiple of ATR below (long) or above (short) the entry price.
Take-profit is placed as a ratio (TP/SL) of the stop distance, ensuring consistent reward/risk structure.
Opening Range Filter (Optional)
If enabled, the strategy only triggers trades after price breaks out of the 09:30–09:45 EST range, ensuring participation in directional moves.
Session Filters
No trades from 04:00 to 09:30 and from 16:00 to 20:00 EST, avoiding low-liquidity periods.
All open trades are closed at 15:55 EST, to avoid overnight risk or expiration issues for options.
⚙️ Built-in Presets:
You can choose one of the built-in ticker-specific presets for optimal conditions:
Ticker EMAs RSI (Long/Short) ATR SL×ATR TP/SL
SPY 8/28 56 / 26 14 1.4× 4.0×
TSLA 23/27 56 / 33 13 1.4× 3.6×
AAPL 6/13 61 / 26 23 1.4× 2.1×
MSFT 25/32 54 / 26 14 1.2× 2.2×
META 25/32 53 / 26 17 1.8× 2.3×
AMZN 28/32 55 / 25 16 1.8× 2.3×
You can also choose "Custom" to fully configure all parameters to your own market and strategy preferences.
📌 Best Use Case:
This strategy is especially suited for intraday options trading, where timing and risk control are critical. It works best on liquid tickers with strong trends or clear breakout behavior.
Mongoose Conflict Risk Radar v1.1 (Separate Panel) description
The Mongoose Capital: Risk Rotation Index is a macro market sentiment tool designed to detect elevated risk conditions by aggregating signals across key asset classes.
This script evaluates trend strength across 8 ETFs representing major risk-on and risk-off flows:
GLD – Gold
VIXY – Volatility
TLT – Long-Term Bonds
SPY – S&P 500
UUP – U.S. Dollar Index
EEM – Emerging Markets
SLV – Silver
FXI – China Large-Cap
Each asset is assigned a binary signal based on price position vs. its 21-period SMA (or a crossover for bonds). The signals are then totaled into a composite Risk Rotation Score, plotted as a bar graph.
How to Use
0–2 = Low risk-on behavior
3–4 = Caution / Mixed regime
5–8 = Elevated conflict or macro stress
Use this as a macro confirmation layer for trend entries, risk reduction, or allocation shifts.
Alerts
Set alerts when the index exceeds 5 to track major rotations into defensive assets.
Out of the Noise Intraday Strategy with VWAP [YuL]This is my (naive) implementation of "Beat the Market An Effective Intraday Momentum Strategy for S&P500 ETF (SPY)" paper by Carlo Zarattini, Andrew Aziz, Andrea Barbon, so the credit goes to them.
It is supposed to run on SPY on 30-minute timeframe, there may be issues on other timeframes.
I've used settings that were used by the authors in the original paper to keep it close to the publication, but I understand that they are very aggressive and probably shouldn't be used like that.
Results are good, but not as good as they are stated in the paper (unsurprisingly?): returns are smaller and Sharpe is very low (which is actually weird given the returns and drawdown ratio), there are also margin calls if you enable margin check (and you should).
I have my own ideas of improvements which I will probably implement separately to keep this clean.
Options Betting Range - FixedOptions Betting Range
Options Betting Range is a powerful TradingView indicator designed to streamline options trading by visualizing high-probability price ranges for key symbols. With automated trendlines and clear labels, it empowers traders to make precise, data-driven decisions based on customizable prediction and execution dates.
## Key Features
Broad S&P 500 Coverage: Supports most S&P 500 stock symbols, excluding those with insufficient options volume for reliable data, alongside major ETFs and indices like SPY, IWM, QQQ, DIA, TLT, ^GSPC, ^IXIC, ^RUT, ^NDX, and ^SOX.
Automated Trendlines: Plots dashed and solid trendlines to mark high/low price boundaries, triggered only on specified prediction dates for clean, uncluttered charts.
Customizable Inputs: Configure prediction and execution dates to align with your trading strategy.
Clear Visuals: Color-coded labels (green for highs, purple for lows) display price ranges and percentage spreads for rapid decision-making.
Single-Execution Logic: Draws trendlines once per prediction date, ensuring chart clarity and efficiency.
## How It Works
Based on the latest daily open interest data, the indicator calculates swing ranges for different strike dates, drawing trendlines and labels to visualize potential price boundaries for options trading.
## Why Use It?
Streamlined Analysis: Automates range visualization, saving time and reducing manual charting.
Strategic Clarity: Objective price levels minimize emotional bias and enhance trade planning.
Versatile Application: Ideal for day traders, swing traders, and options strategists across multiple markets.
## Tips for Best Use
Regular Updates: To maintain the accuracy of options betting ranges, periodically update the indicator. On the view page, hover over the indicator name and click the blue whirlwind icon to complete the update.
## Get Started
Add Options Betting Range to your TradingView chart, select a supported symbol, and customize your prediction/execution dates. Leverage the visualized price ranges to execute precise options trading strategies with confidence.
Period High/Low Percentage DifferenceCheck for price away from 200 days high/low and from recent high and low. Found it difficult to keep switching from regular to percentage in chart. I use it for ETF investing.
Sector Relative StrengthDescription
This script compares sector performance relative to the S&P 500. Sector price levels or charts alone can mislead, because they tend to move with the broader market. An increase in a sector’s price does not necessarily indicate strength, as it may simply be following the index.
For more a more reliable picture, the script calculates a ratio between each sector ETF and SPY. If the ratio has increased, the sector has outperformed the index. In case it has declined, the sector has underperformed. If the value is near zero, the sector has moved in line with the index. The sectors are presented in a table and sorted on relative performance.
Calculation Method
The performance is expressed as a percentage change in the ratio over a user-defined lookback period. The default lookback is set to 21 bars, which corresponds to one month on a daily chart. This value can be adopted in the settings to match preferred time period.
Z-Score
In addition to the percentage change, the script calculates a Z-score of the ratio, which measures how far the current value deviates from its recent mean. A high positive Z-score indicates that the ratio is significantly above its average, while a negative value indicates it is below. This normalization allows for comparison between sectors with different price levels or volatility profiles.
Table Columns
- Relative %: The sector's performance relative to SPY over the selected lookback period
- Z-Score: Standardized measure of current performance ratio is relative to its average
- Trend Arrow: Indicates the direction of relative performance up down or flat
Example Interpretation
For example, if XLK shows a 3.7% change, it has outperformed SPY over the selected period. Another sector might show a -2.1% change, which indicates underperformance. While both values shows relative strength or weakness, the Z-score is optional and can provide additional context based on how unusual that performance is compared to the sector's own recent behavior.
Use Case
This approach helps evaluate overall market conditions and supports a top-down method. By starting with sector performance, it becomes easier to identify where the market is showing leadership or weakness. This allows the stock selection process to be more deliberate and can help refine or customize screeners based on certain sectors.
SPY Trend-Based Buy Signals🔹 Overview
This indicator identifies potential buy signals on any asset by combining MACD and Stochastic Oscillator crossovers, while using the SPY’s trend (via exponential moving averages) as a broader market filter.
It helps traders stay aligned with macro momentum and avoid counter-trend entries.
🔍 How it works
SPY Trend Filter (Daily Timeframe):
Pulls SPY (S&P 500 ETF) data using EMAs (5, 20, 80)
Categorizes SPY market trend with color codes:
🟢 Green: Strong uptrend (EMA5 > EMA20 > EMA80)
🟡 Yellow: Potential uptrend / early momentum (EMA5 < EMA20 > EMA80)
🔴 Red: Downtrend (EMA5 < EMA20 < EMA80)
🔵 Blue: Possible trend reversal or mixed trend (EMA5 > EMA20 < EMA80)
Buy Signal Conditions (Combined Logic):
A signal is only triggered when:
- SPY trend is either yellow or blue (indicating a neutral-to-bullish or early recovery environment)
-The Stochastic Oscillator's %D line is below 50, showing possible upside
- A bullish MACD crossover occurs on the current symbol
🟢 Green signal: MACD crossover occurs below 0 (early reversal)
🟠 Orange signal: MACD crossover occurs above 0 (momentum continuation)
📈 Visual Output
🟢 Green label below the bar when an early reversal setup occurs
🟠 Orange label above the bar when a trend continuation signal appears
✅ Best Use Case
Ideal for:
Swing traders and position traders
LEAPS (long-term options) traders aligning entries with SPY trend
Anyone seeking clean, contextual entries filtered by market momentum
⚠️ Note: This indicator is most effective when used on fundamentally strong stocks that are sector leaders with solid earnings growth and market presence. Use technical signals as a complement to quality fundamentals.
ℹ️ Clarification: The moving averages displayed on the chart (e.g., on QQQ) are for visual reference only, to help users understand the color logic of the SPY trend filter. The actual logic and signals are based on SPY’s moving averages, regardless of the charted symbol.
Retirement Portfolio Dashboard1. Set It Up
Paste the script into the Pine Script editor in TradingView
Add to chart (use a daily chart for any TSX ticker)
Configure the inputs on the right panel:
Choose your ETF tickers (default: VFV, XAW, XIC)
Enter your target allocations (U.S., Global, Canada, Cash)
Set your current portfolio value and contribution plan
Adjust your expected return and rebalance trigger
📊 2. What It Tracks
💼 Allocation Overview
Target vs. actual % for each asset class
CAD value of each component
Performance YTD based on Jan 2nd start
Drift % to see how far each asset has deviated
📈 Growth Forecast
Future value projection with contributions
Weighted return (based on typical historical returns)
Inflation-adjusted real return (assuming 2% inflation)
⚠ Rebalancing
If any drift exceeds your set threshold (e.g., 5%), the script:
Highlights the issue in red
Displays "⚠ Rebalance Suggested"
Triggers a TradingView alert if you've activated it
🔔 3. Set Up Alerts
Go to Alerts > Create Alert
Choose your script from the dropdown
Under Condition, select "Rebalance Alert"
Choose your desired alert type (popup, email, webhook, etc.)
✅ 4. How to Use It Effectively
Task What to Do
Monitor allocations Check dashboard weekly or monthly
Spot imbalances Use Drift % and Status (green/red)
Forecast retirement growth Adjust contributions, return rate, and horizon
Prepare to rebalance Use alerts when drift > threshold
Tune assumptions Change expected returns or inflation rate as needed
💡 Tips
You can edit return assumptions (e.g., make Global equity more conservative)
Use this on a “blank” ticker (like TSX:XIC) so you don't overlay the chart
Copy values from your broker or retirement account to update real allocations
Bottom and Top finder [theUltimator5]🧭 Bottom and Top Finder — Multi-Symbol Momentum Divergence Detector
The Bottom and Top Finder by theUltimator5 is a highly configurable, momentum-based indicator designed to identify potential market reversal points using a multi-symbol relative strength comparison framework. It evaluates Directional Movement Index (DMI) values from up to three correlated or macro-influential assets to determine when the current instrument may be approaching a bottom (oversold exhaustion) or a top (overbought exhaustion).
🧠 How It Works
This script computes both the +DI (positive directional index) and -DI (negative directional index) for:
The currently selected chart symbol
Up to three user-defined reference symbols (e.g., sector leaders, macro ETFs, currencies, volatility proxies)
It uses a logarithmic percent-change approach to normalize all movement metrics, ensuring results are scale-invariant and price-neutral — meaning it works consistently whether a stock trades at $1 or $100,000. This makes the comparison between different assets meaningful, even if they trade on different scales or volatility levels.
The indicator then:
Compares the +DI values of the reference symbols to the current symbol’s +DI → seeking bottoming signals (suggesting the current symbol is unusually weak).
Compares the -DI values of the reference symbols to the current symbol’s -DI → seeking topping signals (suggesting the current symbol is unusually strong on the downside).
These comparisons are aggregated using a weighted average, where you control the influence (multiplier) of each reference symbol.
🔁 Trigger Logic
The indicator generates two dynamic lines:
Bot Line (Bottom Line): Based on reference +DI vs. current +DI
Top Line: Based on reference -DI vs. current -DI
If the Bot Line rises above the user-defined threshold, it may signal that capitulation or oversold conditions are developing. Similarly, if the Top Line rises above its threshold, it may indicate a blow-off top or overbought selling pressure.
To avoid false positives, a second smoothing-based condition must also be met:
The line must significantly exceed its moving average, confirming momentum divergence.
When both conditions are true, the indicator highlights the background in light red (bottom alert) or green (top alert) for easy visual scanning.
🔧 Key Inputs & Customization
You can fine-tune this tool using the following parameters:
Smoothing Length: Controls how smooth or sensitive the DI values are.
Reference Symbols: Up to 3 assets (default: RSP, HYG, DXY) — customizable for sector, macro, or inverse relationships.
Influence Multipliers: Adjust the weight each symbol has on the overall signal.
Display Options:
Toggle to highlight the chart background during trigger conditions.
Toggle to display a real-time table of reference symbols and their influence levels.
📈 Visual Output
Two plotted lines: One for bottoms and one for tops
Dynamically colored based on how far they exceed thresholds
Background highlights to mark trigger zones
Optional table displaying the current reference symbol setup and weights
🛠 Best Use Cases
This tool is ideal for:
Identifying short-term tops or bottoms using momentum exhaustion
Spotting divergences between an asset and broader market or sector health
Macro analysis with assets like SPY, QQQ, GME, MSFT, BTC, etc...
Pair trading signals or market breadth confirmation/disagreement
It complements other technical indicators like RSI, MACD, Bollinger Bands, or price structure patterns (double bottoms/tops, etc.)
HBND ReferenceChart the HBND as an index based on weighting found on the HBND Etf website. For best results display the adjusted close since HBND is a high yielding fund. The weightings have to be updated manually.
There are three display options:
1. Normalize the index relative to the symbol on the chart (presumably HBND) and this is the default.
2. Percentage change relative to the first bar of the index
3. The raw value which will be the tlt price * tlt percentage weighting + vglt price * vglt percentage weighting + edv percentage weighting * edv price.
[SHORT ONLY] Internal Bar Strength (IBS) Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "Internal Bar Strength (IBS) Strategy" is a mean-reversion strategy designed to identify trading opportunities based on the closing price's position within the daily price range. It enters a short position when the IBS indicates overbought conditions and exits when the IBS reaches oversold levels. This strategy is Short-Only and was designed to be used on the Daily timeframe for Stocks and ETFs.
█ WHAT IS INTERNAL BAR STRENGTH (IBS)?
Internal Bar Strength (IBS) measures where the closing price falls within the high-low range of a bar. It is calculated as:
IBS = (Close - Low) / (High - Low)
- Low IBS (≤ 0.2) : Indicates the close is near the bar's low, suggesting oversold conditions.
- High IBS (≥ 0.8) : Indicates the close is near the bar's high, suggesting overbought conditions.
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The IBS value rises to or above the Upper Threshold (default: 0.9).
The Closing price is greater than the previous bars High (close>high ).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
An exit Signal is generated when the IBS value drops to or below the Lower Threshold (default: 0.3). This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Upper Threshold: The IBS level at which the strategy enters trades. Default is 0.9.
Lower Threshold: The IBS level at which the strategy exits short positions. Default is 0.3.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for Stocks and ETFs markets and performs best when prices frequently revert to the mean.
The strategy can be optimized further using additional conditions such as using volume or volatility filters.
It is sensitive to extreme IBS values, which help identify potential reversals.
Backtesting results should be analyzed to optimize the Upper/Lower Thresholds for specific instruments and market conditions.
IronCondor 10am 30TF by RMThe IronCondor 10am 30TF indicator shows Iron Condor trades win rate over a large number of days.
The default ETFs in this indicators are "QQQ", "SPY", "RUT" , "CBTX" and "SPX", other entries have not been tested.
Iron Condor quick explanation:
- Iron Condors trades have four options, generally, are based around a Midpoint price (Current Market Price Strike) and
- Two equally distances Strikes for the SELL components (called the Body of the Iron Condor)
- Further away from the two SELLs, another Two BUYs for protection (not considered in this indicator)
- Iron Condors are used for Passive Income based on small gains most of the time.
The IronCondor 10am 30TF has its logic created based on the premises that:
- Most days the market prices stay within a range.
- As example the S&P market prices would stay within 1% on about 80% of the time
- The moving markets (bullish or bearish) occur about 20% of the time
- The biggest market price volatility generally occurs before market opens and then around the first hour or so of trade in the day.
- After the first hour or so of the market the prices would be most likely to stay within a range.
The operation is simple:
- At the Trade Star time in the day (say 10:30 Hrs.) draws a vertical yellow line, then
- Creates two blue horizontal lines for the SELL limits in the Iron Condor Body, at +/- 1% price boundary (check Ticker list below for values)
- At the Trade End time (say 16:00 Hrs.) checks that none of the SELL limits have been broken by highs or lows during the trade day
(The check is done calculating at Trade End time the high/lows 10 bars back for 30 min TF - timeframe)
- There is a label at each Trade End time with Win/Loss and Body value.
- There is one final label with overall calculated past performance in Win percentage out of 'n' trades
Defaults and User Entries:
- The User can modify the Midpoint price called 'IronCondor Midpoint STRIKE' (default is the Candle Close at the selected time)
- The User can modify the Body value called 'IronCondor Body' (default is the Ticker's selected value as per list below)
"QQQ" or "SPY" Body = 5
"RUT" or "CBTX" Body = 20
"SPX" Body = 60
* Disclaimer: This is not a Financial tool, it cannot used as any kind of advice to invest or risk moneys in any market,
Markets are volatile in nature - with little or no warning - and will drain your account if you are not careful.
Use only as an academic demonstrator => * Use at your own risk *
Sharpe and Sortino Ratios with Date RangeThis indicator calculates the Sharpe and Sortino ratios using a chart symbol's periodic price returns.
I added the ability to calculate SORTINO and Sharpe based on CUSTOM DATES within the option menu.
It builds on the script here: by adding this feature.
A little about the Sortino Ratio.
www.nasdaq.com
I want equity market returns, but I don’t want equity market volatility. This is the sentiment many investors naturally feel. This sentiment often grows stronger as one approaches or is in the phase where they desire distributions from their savings to improve lifestyle. This is why there is a need for active management in the investment arena. The desire to control downside volatility, but also participate in the upside growth is a very fundamental human desire. The Sortino Ratio measures how well a particular investment meets this fundamental human desire.
There is the old adage, “volatility is the price you pay for returns.” However, what if we could measure the historical performance of an investment and see if it has given above average returns compared to the downside volatility. This is a simple division problem. It will tell us if the volatility “price we are paying for returns” is good. We can then compare that to other investments to see how they compare.
Let us take the return and subtract the risk-free interest rate and then simply divide that by the downside movement from the average. A basic division problem yielding a number that measures a very basic human desire: How well did this investment do compared to the downside risk it experienced.
In the world of financial analysis and investment management, ratios are abundant. There are many ratios that are truly important to a particular analysis. However, the sheer abundance of ratios that are available often overwhelms the casual investor, leading them to disregard ratios altogether. I would argue for those investors that desire a way to rank an investment by its ability to satisfy this very fundamental human desire, the Sortino Ratio is the number they need to consider.
Disappointing in the marketplace for research, the Sortino Ratio is not featured prominently. It is much easier to find the inflows a particular ETF has experienced than the Sortino Ratio. Inflows are important. They measure how much people are investing into an ETF. However, they are mostly only important to the fund manager, not the investor. What investors care about is the Risk-Adjusted Return. This is the Sortino Ratio.
FACTOR MONITORThe Factor Monitor is a comprehensive designed to track relative strength and standard deviation movements across multiple market segments and investment factors. The indicator calculates and displays normalized percentage moves and their statistical significance (measured in standard deviations) across daily, 5-day, and 20-day periods, providing a multi-timeframe view of market dynamics.
Key Features:
Real-time tracking of relative performance between various ETF pairs (e.g., QQQ vs SPY, IWM vs SPY)
Standard deviation scoring system that identifies statistically significant moves
Color-coded visualization (green/red) for quick interpretation of relative strength
Multiple timeframe analysis (1-day, 5-day, and 20-day moves)
Monitoring of key market segments:
Style factors (Value, Growth, Momentum)
Market cap segments (Large, Mid, Small)
Sector relative strength
Risk factors (High Beta vs Low Volatility)
Credit conditions (High Yield vs Investment Grade)
The tool is particularly valuable for:
Identifying significant factor rotations in the market
Assessing market breadth through relative strength comparisons
Spotting potential trend changes through statistical deviation analysis
Monitoring sector leadership and market regime shifts
Quantifying the magnitude of market moves relative to historical norms
Composer Strategy 1 (Haggis Levered)This strategy dynamically selects an asset to trade each day based on a set of predefined market conditions and technical indicators. It uses relative strength index (RSI) and moving averages to evaluate momentum and trends across multiple tickers, aiming to identify the most advantageous asset for the current market environment. By switching between leveraged ETFs, inverse funds, and defensive assets, the strategy seeks to capitalize on both bullish and bearish scenarios while mitigating risk during uncertain periods.
The approach emphasizes adaptability by monitoring key metrics like overbought or oversold signals and comparing cumulative returns and relative performance across asset classes. This flexibility allows the strategy to respond to changing market dynamics daily, aligning with short-term trends while maintaining a systematic and disciplined methodology for asset allocation.
TearRepresentative's Rule-Based Dip Buying Strategy Rule-Based Dip Buying Strategy Indicator
This TradingView indicator, inspired by TearRepresentative [ , is a refined tool designed to assist traders in implementing a rule-based dip buying strategy. The indicator automates the identification of optimal buy and sell points, helping traders stay disciplined and minimize emotional biases. It is tailored to index trading, specifically leveraged ETFs like SPXL, to capture opportunities in market pullbacks and recoveries.
Key Features
Dynamic Buy Levels:
Tracks the local high over a customizable lookback period and calculates three buy levels based on percentage drops from the high:
Buy Level 1: First entry point (e.g., 15% drop).
Buy Level 2: Second entry point (e.g., additional 10% drop).
Buy Level 3: Third entry point (e.g., additional 7% drop).
Average Price Tracking:
Dynamically calculates the average price for entered positions when multiple buy levels are triggered.
Sell Level:
Computes a take-profit level (e.g., 20% above the average price) to automate profit-taking when the market rebounds.
Signal Visualization:
Buy Signals: Displayed as green triangles at each buy level.
Sell Signals: Displayed as red triangles at the sell level.
Alerts:
Configurable alerts notify traders when buy or sell signals are triggered, ensuring no opportunity is missed.
Visual Aids:
Semi-transparent and dynamic lines represent buy and sell levels for clear visualization.
Labels provide additional clarity for active levels, helping traders quickly identify actionable signals.
How It Works
The indicator analyzes market movements to identify dips based on predefined thresholds.
Buy signals are triggered when the market price reaches specified levels below the local high.
Once a position is taken, the indicator dynamically adjusts the average entry price and calculates the corresponding sell level.
A sell signal is generated when the market price rises above the calculated take-profit level.
Why Use This Indicator?
Discipline: Automates decision-making, removing emotional factors from trading.
Clarity: Provides clear entry and exit points to simplify complex market dynamics.
Versatility: Suitable for all market conditions, especially during pullbacks and rebounds.
Customization: Allows traders to tailor parameters to their preferred trading style and risk tolerance.
Acknowledgment
This indicator is based on the strategy and insights provided by TearRepresentative, whose expertise in rule-based trading has inspired countless traders. TearRepresentative's approach emphasizes simplicity, reliability, and consistency, offering a robust framework for long-term success.
