Pure Price Zone Flow🔎 What this indicator is
It’s a price-action-based zone indicator. Unlike moving average systems, this one relies only on:
1. Swing Highs & Swing Lows → The highest and lowest points within a recent lookback period (like "mini support & resistance").
2. ATR (Average True Range) → A volatility measure that expands the zone, making it more adaptive to different market conditions.
3. Breakouts & Retests → When price breaks above a swing high (bullish) or below a swing low (bearish), the indicator marks it and highlights the new trend.
👉 The goal is to spot clean structure shifts and define clear trend zones where traders can position themselves.
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⚙️ How it is calculated
1. Swing High & Swing Low
o We look back len candles (default 20).
o Find the highest high (swingHigh) and the lowest low (swingLow) in that window.
o This forms the price range zone.
2. ATR Expansion
o We calculate ATR over the same len.
o Add/subtract it (multiplied by atrMult) to the zone edges to expand them.
o This ensures the zones breathe with volatility (tight in quiet markets, wide in choppy ones).
3. Mid-Zone
o Simply the average of swingHigh and swingLow.
o If price is above mid → bullish bias.
o If below mid → bearish bias.
o This gives us the trend color for candles.
4. Breakouts
o If the close crosses above swingHigh, we mark a bullish breakout with a label.
o If the close crosses below swingLow, we mark a bearish breakdown.
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📊 How it helps traders
This indicator helps by:
1. Identifying Structure Shifts
o Many traders watch swing highs/lows for breakouts or reversals.
o This automates the process and visually confirms when structure is broken.
2. Dynamic Zone Trading
o Instead of fixed support/resistance, the ATR expansion adapts to volatility.
o This avoids false signals in high-volatility conditions.
3. Trend Bias at a Glance
o Candle coloring instantly tells you whether price is in bullish or bearish territory relative to the mid-zone.
4. Breakout Confirmation
o The labels show when a breakout has occurred, so traders can react quickly (e.g., enter with trend, wait for retest, or avoid fading moves).
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🌍 Markets it works best in
• Crypto (Bitcoin, Ethereum, etc.): Very effective since crypto is breakout-driven and respects swing levels.
• Forex: Good for volatility-adaptive structure analysis, especially in trending pairs.
• Indices (SPX, NASDAQ, DAX, NIFTY): Useful for breakout trading during session opens or key news events.
• Commodities (Gold, Oil, Silver): Works well to define intraday ranges and breakout levels.
⚠️ Less useful in low-volatility, mean-reverting assets (like some penny stocks or sideways ranges), because breakouts may be rare or fake.
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💡 How it adds value
• Strips away unnecessary complexity (no lagging averages).
• Focuses directly on what price is doing structurally.
• Adaptive → works across different markets & timeframes.
• Easy visualization → zones, trend coloring, breakout markers.
• Helps traders trade with the flow of the market, instead of guessing tops/bottoms.
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👉 In short:
This indicator turns raw price action into clear, actionable zones.
It highlights when the market shifts from balance to breakout, so traders can align with momentum rather than fighting it.
Cerca negli script per "GOLD"
EMA Trend SuiteThe EMA Trend Suite is a trend-following tool built around a stack of four Exponential Moving Averages (EMAs): 9, 21, 51, and 200. It is designed to help traders quickly identify market bias, potential support/resistance zones, and directional momentum.
🔹 How it works:
EMA 200 – The Trend Boss
Price trading above EMA 200 → bullish bias is prioritized.
Price trading below EMA 200 → bearish bias is prioritized.
EMA 51 & EMA 21 – Dynamic Support & Resistance
These mid-range EMAs behave as adaptive support and resistance.
In bullish bias, pullbacks often respect EMA 21 or EMA 51.
In bearish bias, rallies often fail at EMA 21 or EMA 51.
EMA 9 – The Momentum Guide
The fastest EMA tracks short-term direction.
A clean break and hold beyond EMA 9 signals short-term momentum continuation.
EMA 9 crossing EMA 21 often signals the next move within the bias.
🔹 How to Trade It:
Identify the bias with EMA 200
Above EMA 200 = bullish bias.
Below EMA 200 = bearish bias.
Look for the trigger
In bullish bias: wait until EMA 9 crosses above EMA 21 → potential long signal.
In bearish bias: wait until EMA 9 crosses below EMA 21 → potential short signal.
Manage the trade with EMA 21 & 51
Price often bounces off EMA 21 and EMA 51.
In longs: if price starts closing below EMA 51, it’s often a warning to consider closing or reducing risk.
In shorts: if price starts closing above EMA 51, same idea — momentum might be weakening.
Ride momentum, don’t marry the trade
Sometimes price keeps trending strongly even after a close beyond EMA 51, but often it’s a sign of exhaustion. The suite is best used as a trend filter + timing tool, not a guaranteed entry/exit system.
🔹 Best Timeframes:
Gold, NAS100, US30, S&P500: Best results between 15M, 30M, and 1H.
Currency pairs (Forex): Best results on 1H, 4H, and Daily.
⚠️ Important Disclaimer:
This indicator is not a one-stop shop solution for trading.
It is not reliable in consolidations — EMA crossings can create false signals in sideways markets.
Always combine with other tools like candlestick patterns, market structure, or volume analysis.It should be seen as a guide to bias and momentum, not as a trading bot or automated strategy.
5EMA Touch/Break EMA Touch/Break Monitor (5 Lines) — Overview
Purpose: Track downside touches and breakdowns against key EMAs (default 20/60/100/200/300) to judge pullbacks and risk control.
Direction considered: From above to below only. Upside touches/breakouts are not counted.
Signals:
Downside Touch (T): Previous bar at/above EMA, current low ≤ EMA → draw an upward triangle below the bar in the EMA’s color.
Downside Break (B): Previous bar at/above EMA, current low ≤ EMA × (1 − threshold) (default 2%) → draw a gold downward triangle above the bar.
Priority: If both occur on the same bar, Break overrides Touch.
First-only: Within a continuous run, only the first bar is marked; condition must clear before re-marking.
Scope: Signals are produced only for EMAs with length ≥ 60 (adjustable).
Display: The status line shows EMA prices only; a top-right table shows EMA name / price / color.
Inputs: Adjustable EMA lengths; break threshold (default 2%); optional date filter (default 2024-02-14 → 2025-12-30).
Alerts: Global first-only alerts for downside touch/break, plus per-EMA alerts.
用途：跟踪价格对关键 EMA（默认 20/60/100/200/300）的下行触及与下破，便于回踩/风控判断。
仅计算方向：从上向下。向上的触及/突破不计。
信号含义：
下触及（T）：上一根在 EMA 上方，本根 低点 ≤ EMA → K线下方画与该 EMA 同色向上三角形。
下破位（B）：上一根在 EMA 上方，本根 低点 ≤ EMA × (1 − 阈值)（默认 2%） → K线上方画金色向下三角形。
优先级：同根同时满足时，破位优先于触及。
首次原则：连续区间内只标第一根；需先离开条件，才会再次标记。
范围限制：仅对 长度 ≥60 的 EMA 标记信号（阈值可改）。
显示：状态行只显示 5 条 EMA 的价格；右上角表格展示每条 EMA 的名称/价格/颜色。
参数：EMA 长度可改；破位阈值默认 2%；可启用日期过滤（默认 2024-02-14 → 2025-12-30）。
提醒：提供“向下触及/向下破位（首次）”总提醒与每条 EMA 独立提醒。
Timeless Command | QuantEdgeB🔍 Overview
Timeless Command is a multi-asset, multi-timeframe “sentiment dashboard” built around a custom Universal Strategy. It fuses two independent proprietary oscillators into one normalized signal, then snapshots that signal across six user-chosen assets and six user-chosen timeframes—right on your price chart. You instantly see whether Bitcoin, Ethereum, Gold, the U.S. Dollar Index, the S&P 500 or the Nasdaq are “Bullish” or “Bearish” from the 2-day down to the 15-minute horizon, plus an overall bias and bar-color overlays.
✨ Key Features
• 🧠 Universal Strategy
o Combines two independent strategic modules into a single oscillator.
o Applies upper/lower thresholds to generate Long/Short/Neutral signals.
• 🌐 Multi-Asset, Multi-TF Grid
o Up to six symbols (e.g. BTC, ETH, SPX, NDX, GOLD, DXY).
o Six configurable timeframes (days, hours, minutes).
o Automatic conversion of “4H” → “240” minutes for seamless request.security calls.
• 📊 Live Sentiment Table
o Arrow icons per asset/timeframe (“⬆️” vs “⬇️”).
o Per-asset average bias (“Bullish” / “Bearish” / “Neutral”), color-coded.
o Clean, right-aligned table overlay with asset labels and timeframe headers.
• 🎨 Chart Overlays
o Bar coloring driven by the first asset’s average TPI bias.
o Two EMAs (default 12/21) filled to show trend direction.
o Optional mini info table to explain bar-color logic.
⚙️ How It Works
1. Signal Calculation
o Applies thresholds (±0.1) to yield discrete signals from a Universal Strategy: +1 (long), –1 (short), 0 (neutral).
2. Multi-TF Signal Gathering
o For each asset, the script uses request.security to pull the TPI on each selected timeframe, locking values at bar close for consistency.
o Converts each reading into a binary direction (up/down).
3. Averaging & Labeling
o Averages the six directional values per asset to gauge overall bias.
o Renders a “Bullish” or “Bearish” label (or “Neutral” if exactly zero).
4. Visual Overlay
o Bar Color: The chart’s candles recolor based on the first asset’s average bias—blue for bullish, orange for bearish, gray for neutral.
o EMAs: Two exponential moving averages sweep the chart, filled to highlight trending regimes.
5. Dashboard Table
o Rows = assets, columns = timeframes + “Average” column.
o Each cell shows an arrow icon with background shading.
o Last column spells out the per-asset average bias in styled text and color.
🎯 Who Should Use It
• Macro Traders who want a quick cross-market heatmap.
• Multi-Asset Strategists balancing exposure across crypto, equities, FX and commodities.
• Systematic & Discretionary players looking for unified, threshold-based signals.
• Risk Managers needing a real-time sentinel on regime shifts across key markets.
⚙️ Default Settings
• Assets: BTCUSD, ETHUSD, SPX, NDX, GOLD, DXY
• Timeframes: 2D, 1D, 12H, 4H, 1H, 15m
• Thresholds: ±0.1 for long/short entries
📌 Conclusion
With Timeless Command, you gain an at-a-glance “command center” for cross-market sentiment. It turns complex, multi-TF oscillator data into a simple arrow-and-table view, coloring your price bars to reinforce the prevailing bias. Whether you’re hunting trend continuations, regime changes or mean-reversion setups, this overlay gives you the high-level context you need—without digging through six different charts.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Dual Custom Index with SpreadDual Custom Index with Spread
Create powerful custom indices from any instruments and analyze their relative strength dynamics
Overview
This advanced indicator allows you to build two completely customizable indices from your choice of instruments and analyze their spread relationship. Perfect for inter-market analysis, sector rotation strategies, currency strength comparisons, and sophisticated relative performance studies.
Key Features
🔧 Fully Customizable Index Construction
Build each index from up to 6 instruments with individual weightings
Enable/disable instruments on the fly without losing settings
Automatic weight validation ensures mathematically accurate calculations
Invert functionality for instruments that move opposite to index strength
📊 Advanced ADX-Based Methodology
Uses sophisticated ADX +DI/-DI directional bias calculations
Normalized bias calculation for consistent scaling across different instruments
Optimized default settings for intraday trading with full customization options
Professional-grade smoothing and filtering options
📈 Dual Analysis Modes
Difference Mode: Shows absolute strength difference (Index1 - Index2)
Ratio Mode: Shows relative performance ratio (Index1 / Index2)
Additional spread smoothing for cleaner signals
🎨 Professional Display Options
Custom labels with full color, size, and positioning control
Dynamic "Follow Line" labels that move with your data
Static corner positioning for reference displays
Clean error messaging and validation feedback
Use Cases
Gold Trading: Create gold strength vs USD strength indices for precise market timing
Sector Analysis: Compare technology vs financial sector strength for rotation strategies
Currency Strength: Build custom currency baskets for advanced forex analysis
Commodity Spreads: Analyze relative strength between different commodity groups
Regional Markets: Compare strength between different geographical market indices
Crypto Analysis: Track relative performance between different cryptocurrency sectors
Technical Specifications
Instruments per Index: Up to 6 with individual enable/disable
Weight Validation: Automatic 100% total weight enforcement
Calculation Method: ADX-based directional bias with trend strength weighting
Smoothing Options: Multiple levels of customizable smoothing
Error Handling: Professional validation with clear user feedback
Optimization Tips
Intraday Trading: Use DI Length 3-7 for faster response
Daily Analysis: Use DI Length 10-14 for smoother signals
Noisy Markets: Increase Final Smoothing for cleaner signals
Trending Markets: Lower smoothing values for faster reaction
Perfect for traders who need sophisticated inter-market analysis tools beyond standard indicators. Whether you're analyzing gold vs dollar dynamics, sector rotation opportunities, or custom currency strength relationships, this indicator provides institutional-grade analysis capabilities with complete customization flexibility.
Multi SMA by GreenDecodeThis indicator, created by GreenDecode, plots eight Simple Moving Averages (SMAs) with customizable lengths and resolutions. Each SMA can be toggled on or off, and the colors are distinctly set for easy identification: SMA1 (yellow), SMA2 (cyan), SMA3 (green), SMA4 (red), SMA5 (blue), SMA6 (lightblue), SMA7 (teal), and SMA8 (gold). The SMAs are calculated to avoid repainting by using the 'lookahead=barmerge.lookahead_off' parameter, ensuring historical accuracy. Ideal for technical analysis to identify trends and potential reversal points on various timeframes.
TrendLines with ATR and MA [KoTa]The "TrendLines with ATR and MA " indicator combines trend lines, breakout signals, ATR-based trend tracking, and moving averages (MA).
Input Settings and Customization:
After adding the indicator, click on its name at the top of the chart and open the "Settings" tab.
Main sections:
Trend Lines and Breakouts (Periods 1-5):
General Usage Tips:
Chart Timeframe: Works on any timeframe (from 1 minute to weekly). Shorter timeframes (e.g., 5-minute) generate more signals, while longer timeframes (e.g., daily) produce fewer but more reliable signals.
Compatibility: Overlay=true, meaning it is drawn directly on the candlestick chart. It can be combined with other indicators (e.g., RSI, MACD).
Advantages
This indicator outperforms standard trend line tools due to its automated, multi-period, and integrated features:
Automated Trend Line Drawing: Instead of manual drawing, it creates trend lines based on pivot highs/lows. Different periods (3-50) enable multi-timeframe analysis, allowing you to see short- and long-term trends on the same chart.
Breakout Detection and Labeling: Detects breakouts in real-time using dotted extensions. B (Buy) and S (Sell) labels (e.g., B1 for period1 up breakout) clarify signals. Historical breakouts are shown in gray for context.
ATR Integration: Volatility-based trend tracking (similar to SuperTrend). Calculates channel deviation to adapt to market volatility. Arrows highlight trend reversals quickly.
Moving Averages Integration: Flexible MA types (e.g., VWMA for volume-weighted analysis) for trend filtering. No Bollinger Bands option, but MAs can validate breakouts.
Performance and Visuals: Limits line count with max_lines_count for memory efficiency. Colors and line widths are customizable, and old elements are automatically managed (deleted or grayed out). Precision=0 ensures clean price formatting.
Flexibility: All components (trend lines, ATR, MA) can be toggled on/off, allowing for simple or complex usage.
Benefits Provided
This indicator speeds up trading decisions and reduces errors:
Trend and Support/Resistance Detection: Pivot-based lines provide automatic support (green, lows) and resistance (red, highs) levels. Benefit: Reduces manual analysis time, saving effort in scalping or swing trading.
Breakout Signals: Signals are triggered when the close price crosses over/under the extended line. Benefit: Catches potential trend starts early; ATR can filter false breakouts. B/S labels provide visual alerts, simplifying alert setup.
Volatility Adaptation (ATR): Adjusts trend lines based on market fluctuations. Benefit: Wider channels in high-volatility periods (e.g., crypto) and narrower in low volatility, reducing whipsaws (false signals). Arrows clearly show trend changes, ideal for position management.
MA Validation: MAs measure trend strength (e.g., EMA20 above indicates uptrend). Benefit: Filtering breakouts with MA crossovers improves accuracy. VWMA offers volume-based analysis to eliminate weak trends.
General Benefits:
Risk Management: Breakout levels can be used for stop-loss placement (e.g., below breakout).
Profit Potential: When tested on historical data (backtesting), it can be optimized by period—shorter periods for quick entries, longer for holding.
Educational Value: Visualizes fractal, pivot, and ATR concepts for new traders.
Time Savings: Automation eliminates hours of chart analysis; updates in real-time.
Multi-Asset Compatibility: Works for stocks, forex, and crypto; ATR shines in volatile assets.
Possible Strategies
This indicator supports various strategies, primarily focused on breakouts and trend following, enhanced by MA and ATR filtering.
Breakout Trading Strategy:
Rules: Enter long on B (Buy) label (crossover up line), short on S (Sell). For example, enter on B3 (period10), with stop-loss below the previous pivot low.
Filtering: Confirm with ATR arrow up (trend=0). Ensure price is above MA1 (20).
Exit: Profit target at ATR*2 or exit on reverse breakout (S).
Advantage: Ideal for scalping (p1-p2) or swing trading (p4-p5). Benefit: High win rate in volatile markets.
Trend Following Strategy:
Rules: Hold long if ATR trend line is green (up) and MA1 > MA2. Strengthen entry with breakout B.
Filtering: Use only larger period breakouts (p3-p5) with ATR in slow mode.
Exit: Exit on ATR arrow down (reversal) or MA crossover.
Advantage: Captures long-term trends with low drawdown. Benefit: Suitable for passive trading, especially on weekly charts.
Pullback Strategy:
Rules: In an uptrend (green ATR line), enter long when price pulls back to the downtrend line (green pivot low line).
Filtering: No breakout, supported by MA (price above MA). Set stop using ATR deviation.
Exit: New high breakout or ATR reversal.
Advantage: Low-risk entries, captures trend continuations. Benefit: Effective in range-bound markets.
Multi-Timeframe Combination:
Rules: Match short-period (p1) breakouts with long-period (p5) trends (e.g., p5 up + p1 B = long).
Filtering: ATR in medium mode, MAs in golden cross (20>50).
Advantage: Reduces false signals, validates H4 breakouts with D1 trends. Benefit: Suitable for professional traders, with backtesting showing 60%+ win rates.
Risk and Optimization Tips:
Position Sizing: Calculate using ATR (stop-loss distance / 1% risk).
Backtesting: Test in strategy mode; short periods may overtrade, while longer ones may miss opportunities.
Currency Strength v3.0Currency Strength v3.0
Summary
The Currency Strength indicator is a powerful tool designed to gauge the relative strength of major and emerging market currencies. By plotting the True Strength Index (TSI) of various currency indices, it provides a clear visual representation of which currencies are gaining momentum and which are losing it. This indicator automatically detects the currency pair on your chart and highlights the corresponding strength lines, simplifying analysis and helping you quickly identify potential trading opportunities based on currency dynamics.
Key Features
Comprehensive Currency Analysis: Tracks the strength of 19 currencies, including major pairs and several emerging market currencies.
Automatic Pair Detection: Intelligently identifies the base and quote currency of the active chart, automatically highlighting the relevant strength lines.
Dynamic Coloring: The base currency is consistently colored blue, and the quote currency is colored gold, making it easy to distinguish between the two at a glance.
Non-Repainting TSI Calculation: Uses the True Strength Index (TSI) for smooth and reliable momentum readings that do not repaint.
Customizable Settings: Allows for adjustment of the fast and slow periods for the TSI calculation to fit your specific trading style.
Clean Interface: Features a minimalist legend table that only displays the currencies relevant to your current chart, keeping your workspace uncluttered.
How It Works
The indicator pulls data from major currency indices (like DXY for the US Dollar and EXY for the Euro). For currencies that don't have a dedicated index, it uses their USD pair (e.g., USDCNY) and inverts the calculation to derive the currency's strength relative to the dollar. It then applies the True Strength Index (TSI) to this data. The TSI is a momentum oscillator that is less volatile than other oscillators, providing a more reliable measure of strength. The resulting values are plotted on the chart, allowing you to see how different currencies are performing against each other in real-time.
How to Use
Trend Confirmation: When the base currency's line is rising and above the zero line, and the quote currency's line is falling, it can confirm a bullish trend for the pair. The opposite would suggest a bearish trend.
Identifying Divergences: Look for divergences between the currency strength lines and the price action of the pair. For example, if the price is making higher highs but the base currency's strength is making lower highs, it could signal a potential reversal.
Crossovers: A crossover of the base and quote currency lines can signal a shift in momentum. A bullish signal occurs when the base currency line crosses above the quote currency line. A bearish signal occurs when it crosses below.
Overbought/Oversold Levels: The horizontal dashed lines at 0.5 and -0.5 can be used as general guides for overbought and oversold conditions, respectively. Strength moving beyond these levels may indicate an unsustainable move that is due for a correction.
Settings
Fast Period: The short-term period for the TSI calculation. Default is 7.
Slow Period: The long-term period for the TSI calculation. Default is 15.
Index Source: The price source used for the calculations (e.g., Close, Open). Default is Close.
Base Currency Color: The color for the base currency line. Default is Royal Blue.
Quote Currency Color: The color for the quote currency line. Default is Goldenrod.
Disclaimer
This indicator is intended for educational and analytical purposes only. It is not financial advice. Trading involves substantial risk, and past performance is not indicative of future results. Always conduct your own research and risk management before making any trading decisions.
EMA 9/21/50/200🔹 EMA 9 (Fastest EMA)
Short-term momentum tracker
Reacts quickly to price changes (follows candles closely).
Often used by scalpers and day traders for quick entries/exits.
Above price → short-term bullish push; below price → short-term bearish push.
🔹 EMA 21 (Short-Term Trend)
Short-to-medium-term trend indicator.
Commonly used on 15m, 1h, and 4h charts for swing entries.
Works as a dynamic support/resistance in trending markets.
EMA 9 crossing above/below EMA 21 = strong buy/sell signal.
🔹 EMA 50 (Medium-Term Trend)
Used to gauge the overall market trend for the past few weeks.
Many traders look at price relative to the EMA 50:
Above → bullish bias.
Below → bearish bias.
Acts as a stronger support/resistance than EMA 21.
🔹 EMA 200 (Long-Term Trend)
The big picture trend indicator (months of data).
Widely followed by institutions and big players.
If price is above EMA 200 → long-term bullish market.
If price is below EMA 200 → long-term bearish market.
Very powerful support/resistance line → many swing traders and investors use it as the ultimate trend filter.
🔀 How Traders Use Them Together
Trend Confirmation:
Bullish if EMA 9 > 21 > 50 > 200 (stacked in order).
Bearish if EMA 9 < 21 < 50 < 200.
Crossover Signals:
EMA 9 crossing EMA 21 = short-term entry/exit signal.
EMA 50 vs EMA 200 (the “Golden Cross” / “Death Cross”) shows major shifts.
Dynamic Support/Resistance:
Price often pulls back to EMAs before continuing trend → good entry zones.
✅ In simple terms:
EMA 9 & 21 → short-term trading signals.
EMA 50 → medium-term trend confirmation.
EMA 200 → long-term trend direction (the “line in the sand”).
Aethix Cipher DivergencesAethix Cipher Divergences v6
Core Hook: Custom indicator inspired by VuManChu B, Grok-enhanced for crypto intel—blends WaveTrend (WT) oscillator with multi-divergences for buy/sell circles (green/teal buys #00FFFF, red sells) and dots (divs, gold overbought alerts).
Key Features:
WaveTrend Waves: Dual waves (teal WT1, darker teal WT2) with VWAP (purple for neon vibe), overbought/oversold lines, crosses for signals.
Divergences: Regular/hidden for WT, RSI, Stoch—red bearish, green bullish dots; extra range for deeper insights.
RSI + MFI Area: Colored area (green positive, red negative) for sentiment/volume flow.
Stochastic RSI: K/D lines with fill for overbought/oversold trends.
Schaff Trend Cycle: Purple line for cycle smoothing.
Sommi Patterns: Flags (pink bearish, blue bullish) and diamonds for HTF patterns, purple higher VWAP.
MACD Colors on WT: Dynamic WT shading based on MACD for enhanced reads.
EMA/MA Unified with Pivot S/RIndicator Name:
EMA/MA Unified with Pivot S/R (Moving Average + Pivot Support/Resistance System)
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Indicator Purpose:
This indicator combines multi-period EMA/MA moving averages with the Pivot Support/Resistance (Pivot S/R) system to identify market trends, pullback zones, and key support and resistance levels, helping traders more clearly judge market structure and entry and exit points.
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Functional Description:
A. EMA/MA Trend System:
1. Secondary Retracement Lines (EMA60/MA60): Display short-term price fluctuations and pullback levels, helping to determine entry or expansion opportunities.
2. Primary Trend Moving Averages (EMA240/EMA720/EMA1440): Represent short-term, medium-term, and long-term trends, respectively, and are used to determine overall market direction. EMA240 serves as a short-term primary trend reference line, useful for trend confirmation and pullback trading.
B. EMA720 and EMA1440 Crossover Signals:
1. Golden Cross (EMA720 crosses above EMA1440): Confirms a bullish trend.
2. Death Cross (EMA720 crosses below EMA1440): Confirms a bearish trend.
C. Trend Band Fill:
Green bands indicate bullish trend bands, and red bands indicate bearish trend bands, visually displaying the direction and strength of the primary trend.
D. Pivot Point Support and Resistance System:
1. Pivot points are categorized as short-term swing support and resistance, medium-term pullback support and resistance, and long-term trend support and resistance, helping traders identify key support and resistance areas.
2. The system automatically generates corresponding multi-period pivot lines based on the current period and user settings, allowing trading in conjunction with moving average trends.
3. Pivot point display allows for flexible selection, displaying only short-term, medium-term, or long-term key points.
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Using Trend Lines:
A. Trend Trading:
1. Bullish Primary Trend: If the price breaks through the trend line and rises above the EMA240 or EMA/MA60, consider going long. The EMA240 can be used as a short-term trend filter to confirm that the bullish primary trend persists after a pullback.
2. Bearish Primary Trend: If the price breaks through the trend line and falls below the EMA240 or EMA/MA60, consider going short. The EMA240 can also filter out false breakouts and confirm the trend direction.
B. Pullback Trading:
1. Combining short-term pivot points (fluctuations) with trend lines can identify entry points after short-term price pullbacks.
2. Combining medium-term pivot points (retracements) with trend lines and the EMA240 can identify safe positions to add to positions after the trend continues.
C. Key Support and Resistance:
1. The intersection of pivot lines and trend lines represents potential support/resistance reversal points, suitable for use as take-profit or stop-loss references.
2. When a trend line breaks through a pivot line, it can be used as a trend confirmation or breakout trading signal.
3. The EMA 240 can be used as an additional filter to enhance the effectiveness of support and resistance levels.
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Suggestions for Use:
1. Suitable for use in conjunction with trend line and price pattern analysis. Prioritize trend following when the trend is clear, combining pivot points and the EMA 240 for trading.
2. Switch between different moving averages and pivot point systems to capture trends and pullbacks at different levels.
3. The EMA 240, as a short-term trend reference line, can filter out false breakouts and optimize entry and exit points.
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指标名称：
EMA/MA 融合枢轴支撑/阻力系统（移动平均线 + 枢轴支撑/阻力系统）
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指标用途：
该指标将多周期 EMA/MA 移动平均线与枢轴支撑/阻力系统（枢轴支撑/阻力系统）相结合，以识别市场趋势、回调区域以及关键支撑位和阻力位，帮助交易者更清晰地判断市场结构以及入场和出场点。
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功能描述：
A. EMA/MA 趋势系统：
1. 次要回撤线 (EMA60/MA60)：显示短期价格波动和回调水平，帮助确定入场或扩展机会。
2. 主要趋势移动平均线 (EMA240/EMA720/EMA1440)：分别代表短期、中期和长期趋势，用于判断整体市场方向。 EMA240 作为短期主要趋势参考线，可用于趋势确认和回调交易。
B. EMA720 和 EMA1440 交叉信号：
1. 黄金交叉（EMA720 上穿 EMA1440）：确认看涨趋势。
2. 死亡交叉（EMA720 下穿 EMA1440）：确认看跌趋势。
C. 趋势带填充：
绿色带表示看涨趋势带，红色带表示看跌趋势带，直观地显示主要趋势的方向和强度。
D. 枢轴点支撑位和阻力位系统：
1. 枢轴点分为短期波动支撑位和阻力位、中期回调支撑位和阻力位以及长期趋势支撑位和阻力位，帮助交易者识别关键支撑位和阻力位。
2. 系统会根据当前周期和用户设置自动生成相应的多周期枢轴线，以便结合移动平均线趋势进行交易。
3. 枢轴点显示允许灵活选择，仅显示短期、中期或长期关键点。
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使用趋势线：
A. 趋势交易：
1. 看涨主要趋势：如果价格突破趋势线并升至 EMA240 或 EMA/MA60 上方，则考虑做多。EMA240 可用作短期趋势过滤器，以确认看涨主要趋势在回调后是否持续。
2. 看跌主要趋势：如果价格突破趋势线并跌破 EMA240 或 EMA/MA60，则考虑做空。EMA240 还可以过滤掉假突破并确认趋势方向。
B. 回调交易：
1. 将短期枢轴点（波动）与趋势线相结合，可以识别短期价格回调后的入场点。
2. 将中期枢轴点（回撤点）与趋势线和 EMA240 指标相结合，可以识别趋势持续后可安全加仓的仓位。
C. 关键支撑位和阻力位：
1. 枢轴点和趋势线的交点代表潜在的支撑/阻力反转点，适合用作止盈或止损的参考。
2. 当趋势线突破枢轴点时，可以作为趋势确认或突破的交易信号。
3. EMA 240 指标可作为额外的过滤器，增强支撑位和阻力位的有效性。
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使用建议：
1. 适合与趋势线和价格形态分析结合使用。在趋势清晰时优先进行趋势跟踪，结合枢轴点和 EMA 240 指标进行交易。
2. 在不同的移动平均线和枢轴点系统之间切换，以捕捉不同水平的趋势和回调。
3、EMA 240作为短期趋势参考线，可以滤除假突破，优化进出点。
Ray Dalio's All Weather Strategy - Portfolio CalculatorTHE ALL WEATHER STRATEGY INDICATOR: A GUIDE TO RAY DALIO'S LEGENDARY PORTFOLIO APPROACH
Introduction: The Genesis of Financial Resilience
In the sprawling corridors of Bridgewater Associates, the world's largest hedge fund managing over 150 billion dollars in assets, Ray Dalio conceived what would become one of the most influential investment strategies of the modern era. The All Weather Strategy, born from decades of market observation and rigorous backtesting, represents a paradigm shift from traditional portfolio construction methods that have dominated Wall Street since Harry Markowitz's seminal work on Modern Portfolio Theory in 1952.
Unlike conventional approaches that chase returns through market timing or stock picking, the All Weather Strategy embraces a fundamental truth that has humbled countless investors throughout history: nobody can consistently predict the future direction of markets. Instead of fighting this uncertainty, Dalio's approach harnesses it, creating a portfolio designed to perform reasonably well across all economic environments, hence the evocative name "All Weather."
The strategy emerged from Bridgewater's extensive research into economic cycles and asset class behavior, culminating in what Dalio describes as "the Holy Grail of investing" in his bestselling book "Principles" (Dalio, 2017). This Holy Grail isn't about achieving spectacular returns, but rather about achieving consistent, risk-adjusted returns that compound steadily over time, much like the tortoise defeating the hare in Aesop's timeless fable.
HISTORICAL DEVELOPMENT AND EVOLUTION
The All Weather Strategy's origins trace back to the tumultuous economic periods of the 1970s and 1980s, when traditional portfolio construction methods proved inadequate for navigating simultaneous inflation and recession. Raymond Thomas Dalio, born in 1949 in Queens, New York, founded Bridgewater Associates from his Manhattan apartment in 1975, initially focusing on currency and fixed-income consulting for corporate clients.
Dalio's early experiences during the 1970s stagflation period profoundly shaped his investment philosophy. Unlike many of his contemporaries who viewed inflation and deflation as opposing forces, Dalio recognized that both conditions could coexist with either economic growth or contraction, creating four distinct economic environments rather than the traditional two-factor models that dominated academic finance.
The conceptual breakthrough came in the late 1980s when Dalio began systematically analyzing asset class performance across different economic regimes. Working with a small team of researchers, Bridgewater developed sophisticated models that decomposed economic conditions into growth and inflation components, then mapped historical asset class returns against these regimes. This research revealed that traditional portfolio construction, heavily weighted toward stocks and bonds, left investors vulnerable to specific economic scenarios.
The formal All Weather Strategy emerged in 1996 when Bridgewater was approached by a wealthy family seeking a portfolio that could protect their wealth across various economic conditions without requiring active management or market timing. Unlike Bridgewater's flagship Pure Alpha fund, which relied on active trading and leverage, the All Weather approach needed to be completely passive and unleveraged while still providing adequate diversification.
Dalio and his team spent months developing and testing various allocation schemes, ultimately settling on the 30/40/15/7.5/7.5 framework that balances risk contributions rather than dollar amounts. This approach was revolutionary because it focused on risk budgeting—ensuring that no single asset class dominated the portfolio's risk profile—rather than the traditional approach of equal dollar allocations or market-cap weighting.
The strategy's first institutional implementation began in 1996 with a family office client, followed by gradual expansion to other wealthy families and eventually institutional investors. By 2005, Bridgewater was managing over $15 billion in All Weather assets, making it one of the largest systematic strategy implementations in institutional investing.
The 2008 financial crisis provided the ultimate test of the All Weather methodology. While the S&P 500 declined by 37% and many hedge funds suffered double-digit losses, the All Weather strategy generated positive returns, validating Dalio's risk-balancing approach. This performance during extreme market stress attracted significant institutional attention, leading to rapid asset growth in subsequent years.
The strategy's theoretical foundations evolved throughout the 2000s as Bridgewater's research team, led by co-chief investment officers Greg Jensen and Bob Prince, refined the economic framework and incorporated insights from behavioral economics and complexity theory. Their research, published in numerous institutional white papers, demonstrated that traditional portfolio optimization methods consistently underperformed simpler risk-balanced approaches across various time periods and market conditions.
Academic validation came through partnerships with leading business schools and collaboration with prominent economists. The strategy's risk parity principles influenced an entire generation of institutional investors, leading to the creation of numerous risk parity funds managing hundreds of billions in aggregate assets.
In recent years, the democratization of sophisticated financial tools has made All Weather-style investing accessible to individual investors through ETFs and systematic platforms. The availability of high-quality, low-cost ETFs covering each required asset class has eliminated many of the barriers that previously limited sophisticated portfolio construction to institutional investors.
The development of advanced portfolio management software and platforms like TradingView has further democratized access to institutional-quality analytics and implementation tools. The All Weather Strategy Indicator represents the culmination of this trend, providing individual investors with capabilities that previously required teams of portfolio managers and risk analysts.
Understanding the Four Economic Seasons
The All Weather Strategy's theoretical foundation rests on Dalio's observation that all economic environments can be characterized by two primary variables: economic growth and inflation. These variables create four distinct "economic seasons," each favoring different asset classes. Rising growth benefits stocks and commodities, while falling growth favors bonds. Rising inflation helps commodities and inflation-protected securities, while falling inflation benefits nominal bonds and stocks.
This framework, detailed extensively in Bridgewater's research papers from the 1990s, suggests that by holding assets that perform well in each economic season, an investor can create a portfolio that remains resilient regardless of which season unfolds. The elegance lies not in predicting which season will occur, but in being prepared for all of them simultaneously.
Academic research supports this multi-environment approach. Ang and Bekaert (2002) demonstrated that regime changes in economic conditions significantly impact asset returns, while Fama and French (2004) showed that different asset classes exhibit varying sensitivities to economic factors. The All Weather Strategy essentially operationalizes these academic insights into a practical investment framework.
The Original All Weather Allocation: Simplicity Masquerading as Sophistication
The core All Weather portfolio, as implemented by Bridgewater for institutional clients and later adapted for retail investors, maintains a deceptively simple static allocation: 30% stocks, 40% long-term bonds, 15% intermediate-term bonds, 7.5% commodities, and 7.5% Treasury Inflation-Protected Securities (TIPS). This allocation may appear arbitrary to the uninitiated, but each percentage reflects careful consideration of historical volatilities, correlations, and economic sensitivities.
The 30% stock allocation provides growth exposure while limiting the portfolio's overall volatility. Stocks historically deliver superior long-term returns but with significant volatility, as evidenced by the Standard & Poor's 500 Index's average annual return of approximately 10% since 1926, accompanied by standard deviation exceeding 15% (Ibbotson Associates, 2023). By limiting stock exposure to 30%, the portfolio captures much of the equity risk premium while avoiding excessive volatility.
The combined 55% allocation to bonds (40% long-term plus 15% intermediate-term) serves as the portfolio's stabilizing force. Long-term bonds provide substantial interest rate sensitivity, performing well during economic slowdowns when central banks reduce rates. Intermediate-term bonds offer a balance between interest rate sensitivity and reduced duration risk. This bond-heavy allocation reflects Dalio's insight that bonds typically exhibit lower volatility than stocks while providing essential diversification benefits.
The 7.5% commodities allocation addresses inflation protection, as commodity prices typically rise during inflationary periods. Historical analysis by Bodie and Rosansky (1980) demonstrated that commodities provide meaningful diversification benefits and inflation hedging capabilities, though with considerable volatility. The relatively small allocation reflects commodities' high volatility and mixed long-term returns.
Finally, the 7.5% TIPS allocation provides explicit inflation protection through government-backed securities whose principal and interest payments adjust with inflation. Introduced by the U.S. Treasury in 1997, TIPS have proven effective inflation hedges, though they underperform nominal bonds during deflationary periods (Campbell & Viceira, 2001).
Historical Performance: The Evidence Speaks
Analyzing the All Weather Strategy's historical performance reveals both its strengths and limitations. Using monthly return data from 1970 to 2023, spanning over five decades of varying economic conditions, the strategy has delivered compelling risk-adjusted returns while experiencing lower volatility than traditional stock-heavy portfolios.
During this period, the All Weather allocation generated an average annual return of approximately 8.2%, compared to 10.5% for the S&P 500 Index. However, the strategy's annual volatility measured just 9.1%, substantially lower than the S&P 500's 15.8% volatility. This translated to a Sharpe ratio of 0.67 for the All Weather Strategy versus 0.54 for the S&P 500, indicating superior risk-adjusted performance.
More impressively, the strategy's maximum drawdown over this period was 12.3%, occurring during the 2008 financial crisis, compared to the S&P 500's maximum drawdown of 50.9% during the same period. This drawdown mitigation proves crucial for long-term wealth building, as Stein and DeMuth (2003) demonstrated that avoiding large losses significantly impacts compound returns over time.
The strategy performed particularly well during periods of economic stress. During the 1970s stagflation, when stocks and bonds both struggled, the All Weather portfolio's commodity and TIPS allocations provided essential protection. Similarly, during the 2000-2002 dot-com crash and the 2008 financial crisis, the portfolio's bond-heavy allocation cushioned losses while maintaining positive returns in several years when stocks declined significantly.
However, the strategy underperformed during sustained bull markets, particularly the 1990s technology boom and the 2010s post-financial crisis recovery. This underperformance reflects the strategy's conservative nature and diversified approach, which sacrifices potential upside for downside protection. As Dalio frequently emphasizes, the All Weather Strategy prioritizes "not losing money" over "making a lot of money."
Implementing the All Weather Strategy: A Practical Guide
The All Weather Strategy Indicator transforms Dalio's institutional-grade approach into an accessible tool for individual investors. The indicator provides real-time portfolio tracking, rebalancing signals, and performance analytics, eliminating much of the complexity traditionally associated with implementing sophisticated allocation strategies.
To begin implementation, investors must first determine their investable capital. As detailed analysis reveals, the All Weather Strategy requires meaningful capital to implement effectively due to transaction costs, minimum investment requirements, and the need for precise allocations across five different asset classes.
For portfolios below $50,000, the strategy becomes challenging to implement efficiently. Transaction costs consume a disproportionate share of returns, while the inability to purchase fractional shares creates allocation drift. Consider an investor with $25,000 attempting to allocate 7.5% to commodities through the iPath Bloomberg Commodity Index ETF (DJP), currently trading around $25 per share. This allocation targets $1,875, enough for only 75 shares, creating immediate tracking error.
At $50,000, implementation becomes feasible but not optimal. The 30% stock allocation ($15,000) purchases approximately 37 shares of the SPDR S&P 500 ETF (SPY) at current prices around $400 per share. The 40% long-term bond allocation ($20,000) buys 200 shares of the iShares 20+ Year Treasury Bond ETF (TLT) at approximately $100 per share. While workable, these allocations leave significant cash drag and rebalancing challenges.
The optimal minimum for individual implementation appears to be $100,000. At this level, each allocation becomes substantial enough for precise implementation while keeping transaction costs below 0.4% annually. The $30,000 stock allocation, $40,000 long-term bond allocation, $15,000 intermediate-term bond allocation, $7,500 commodity allocation, and $7,500 TIPS allocation each provide sufficient size for effective management.
For investors with $250,000 or more, the strategy implementation approaches institutional quality. Allocation precision improves, transaction costs decline as a percentage of assets, and rebalancing becomes highly efficient. These larger portfolios can also consider adding complexity through international diversification or alternative implementations.
The indicator recommends quarterly rebalancing to balance transaction costs with allocation discipline. Monthly rebalancing increases costs without substantial benefits for most investors, while annual rebalancing allows excessive drift that can meaningfully impact performance. Quarterly rebalancing, typically on the first trading day of each quarter, provides an optimal balance.
Understanding the Indicator's Functionality
The All Weather Strategy Indicator operates as a comprehensive portfolio management system, providing multiple analytical layers that professional money managers typically reserve for institutional clients. This sophisticated tool transforms Ray Dalio's institutional-grade strategy into an accessible platform for individual investors, offering features that rival professional portfolio management software.
The indicator's core architecture consists of several interconnected modules that work seamlessly together to provide complete portfolio oversight. At its foundation lies a real-time portfolio simulation engine that tracks the exact value of each ETF position based on current market prices, eliminating the need for manual calculations or external spreadsheets.
DETAILED INDICATOR COMPONENTS AND FUNCTIONS
Portfolio Configuration Module
The portfolio setup begins with the Portfolio Configuration section, which establishes the fundamental parameters for strategy implementation. The Portfolio Capital input accepts values from $1,000 to $10,000,000, accommodating everyone from beginning investors to institutional clients. This input directly drives all subsequent calculations, determining exact share quantities and portfolio values throughout the implementation period.
The Portfolio Start Date function allows users to specify when they began implementing the All Weather Strategy, creating a clear demarcation point for performance tracking. This feature proves essential for investors who want to track their actual implementation against theoretical performance, providing realistic assessment of strategy effectiveness including timing differences and implementation costs.
Rebalancing Frequency settings offer two options: Monthly and Quarterly. While monthly rebalancing provides more precise allocation control, quarterly rebalancing typically proves more cost-effective for most investors due to reduced transaction costs. The indicator automatically detects the first trading day of each period, ensuring rebalancing occurs at optimal times regardless of weekends, holidays, or market closures.
The Rebalancing Threshold parameter, adjustable from 0.5% to 10%, determines when allocation drift triggers rebalancing recommendations. Conservative settings like 1-2% maintain tight allocation control but increase trading frequency, while wider thresholds like 3-5% reduce trading costs but allow greater allocation drift. This flexibility accommodates different risk tolerances and cost structures.
Visual Display System
The Show All Weather Calculator toggle controls the main dashboard visibility, allowing users to focus on chart visualization when detailed metrics aren't needed. When enabled, this comprehensive dashboard displays current portfolio value, individual ETF allocations, target versus actual weights, rebalancing status, and performance metrics in a professionally formatted table.
Economic Environment Display provides context about current market conditions based on growth and inflation indicators. While simplified compared to Bridgewater's sophisticated regime detection, this feature helps users understand which economic "season" currently prevails and which asset classes should theoretically benefit.
Rebalancing Signals illuminate when portfolio drift exceeds user-defined thresholds, highlighting specific ETFs that require adjustment. These signals use color coding to indicate urgency: green for balanced allocations, yellow for moderate drift, and red for significant deviations requiring immediate attention.
Advanced Label System
The rebalancing label system represents one of the indicator's most innovative features, providing three distinct detail levels to accommodate different user needs and experience levels. The "None" setting displays simple symbols marking portfolio start and rebalancing events without cluttering the chart with text. This minimal approach suits experienced investors who understand the implications of each symbol.
"Basic" label mode shows essential information including portfolio values at each rebalancing point, enabling quick assessment of strategy performance over time. These labels display "START $X" for portfolio initiation and "RBL $Y" for rebalancing events, providing clear performance tracking without overwhelming detail.
"Detailed" labels provide comprehensive trading instructions including exact buy and sell quantities for each ETF. These labels might display "RBL $125,000 BUY 15 SPY SELL 25 TLT BUY 8 IEF NO TRADES DJP SELL 12 SCHP" providing complete implementation guidance. This feature essentially transforms the indicator into a personal portfolio manager, eliminating guesswork about exact trades required.
Professional Color Themes
Eight professionally designed color themes adapt the indicator's appearance to different aesthetic preferences and market analysis styles. The "Gold" theme reflects traditional wealth management aesthetics, while "EdgeTools" provides modern professional appearance. "Behavioral" uses psychologically informed colors that reinforce disciplined decision-making, while "Quant" employs high-contrast combinations favored by quantitative analysts.
"Ocean," "Fire," "Matrix," and "Arctic" themes provide distinctive visual identities for traders who prefer unique chart aesthetics. Each theme automatically adjusts for dark or light mode optimization, ensuring optimal readability across different TradingView configurations.
Real-Time Portfolio Tracking
The portfolio simulation engine continuously tracks five separate ETF positions: SPY for stocks, TLT for long-term bonds, IEF for intermediate-term bonds, DJP for commodities, and SCHP for TIPS. Each position's value updates in real-time based on current market prices, providing instant feedback about portfolio performance and allocation drift.
Current share calculations determine exact holdings based on the most recent rebalancing, while target shares reflect optimal allocation based on current portfolio value. Trade calculations show precisely how many shares to buy or sell during rebalancing, eliminating manual calculations and potential errors.
Performance Analytics Suite
The indicator's performance measurement capabilities rival professional portfolio analysis software. Sharpe ratio calculations incorporate current risk-free rates obtained from Treasury yield data, providing accurate risk-adjusted performance assessment. Volatility measurements use rolling periods to capture changing market conditions while maintaining statistical significance.
Portfolio return calculations track both absolute and relative performance, comparing the All Weather implementation against individual asset classes and benchmark indices. These metrics update continuously, providing real-time assessment of strategy effectiveness and implementation quality.
Data Quality Monitoring
Sophisticated data quality checks ensure reliable indicator operation across different market conditions and potential data interruptions. The system monitors all five ETF price feeds plus economic data sources, providing quality scores that alert users to potential data issues that might affect calculations.
When data quality degrades, the indicator automatically switches to fallback values or alternative data sources, maintaining functionality during temporary market data interruptions. This robust design ensures consistent operation even during volatile market conditions when data feeds occasionally experience disruptions.
Risk Management and Behavioral Considerations
Despite its sophisticated design, the All Weather Strategy faces behavioral challenges that have derailed countless well-intentioned investment plans. The strategy's conservative nature means it will underperform growth stocks during bull markets, potentially by substantial margins. Maintaining discipline during these periods requires understanding that the strategy optimizes for risk-adjusted returns over absolute returns.
Behavioral finance research by Kahneman and Tversky (1979) demonstrates that investors feel losses approximately twice as intensely as equivalent gains. This loss aversion creates powerful psychological pressure to abandon defensive strategies during bull markets when aggressive portfolios appear more attractive. The All Weather Strategy's bond-heavy allocation will seem overly conservative when technology stocks double in value, as occurred repeatedly during the 2010s.
Conversely, the strategy's defensive characteristics provide psychological comfort during market stress. When stocks crash 30-50%, as they periodically do, the All Weather portfolio's modest losses feel manageable rather than catastrophic. This emotional stability enables investors to maintain their investment discipline when others capitulate, often at the worst possible times.
Rebalancing discipline presents another behavioral challenge. Selling winners to buy losers contradicts natural human tendencies but remains essential for the strategy's success. When stocks have outperformed bonds for several quarters, rebalancing requires selling high-performing stock positions to purchase seemingly stagnant bond positions. This action feels counterintuitive but captures the strategy's systematic approach to risk management.
Tax considerations add complexity for taxable accounts. Frequent rebalancing generates taxable events that can erode after-tax returns, particularly for high-income investors facing elevated capital gains rates. Tax-advantaged accounts like 401(k)s and IRAs provide ideal vehicles for All Weather implementation, eliminating tax friction from rebalancing activities.
Capital Requirements and Cost Analysis
Comprehensive cost analysis reveals the capital requirements for effective All Weather implementation. Annual expenses include management fees for each ETF, transaction costs from rebalancing, and bid-ask spreads from trading less liquid securities.
ETF expense ratios vary significantly across asset classes. The SPDR S&P 500 ETF charges 0.09% annually, while the iShares 20+ Year Treasury Bond ETF charges 0.20%. The iShares 7-10 Year Treasury Bond ETF charges 0.15%, the Schwab US TIPS ETF charges 0.05%, and the iPath Bloomberg Commodity Index ETF charges 0.75%. Weighted by the All Weather allocations, total expense ratios average approximately 0.19% annually.
Transaction costs depend heavily on broker selection and account size. Premium brokers like Interactive Brokers charge $1-2 per trade, resulting in $20-40 annually for quarterly rebalancing. Discount brokers may charge higher per-trade fees but offer commission-free ETF trading for selected funds. Zero-commission brokers eliminate explicit trading costs but often impose wider bid-ask spreads that function as hidden fees.
Bid-ask spreads represent the difference between buying and selling prices for each security. Highly liquid ETFs like SPY maintain spreads of 1-2 basis points, while less liquid commodity ETFs may exhibit spreads of 5-10 basis points. These costs accumulate through rebalancing activities, typically totaling 10-15 basis points annually.
For a $100,000 portfolio, total annual costs including expense ratios, transaction fees, and spreads typically range from 0.35% to 0.45%, or $350-450 annually. These costs decline as a percentage of assets as portfolio size increases, reaching approximately 0.25% for portfolios exceeding $250,000.
Comparing costs to potential benefits reveals the strategy's value proposition. Historical analysis suggests the All Weather approach reduces portfolio volatility by 35-40% compared to stock-heavy allocations while maintaining competitive returns. This volatility reduction provides substantial value during market stress, potentially preventing behavioral mistakes that destroy long-term wealth.
Alternative Implementations and Customizations
While the original All Weather allocation provides an excellent starting point, investors may consider modifications based on personal circumstances, market conditions, or geographic considerations. International diversification represents one potential enhancement, adding exposure to developed and emerging market bonds and equities.
Geographic customization becomes important for non-US investors. European investors might replace US Treasury bonds with German Bunds or broader European government bond indices. Currency hedging decisions add complexity but may reduce volatility for investors whose spending occurs in non-dollar currencies.
Tax-location strategies optimize after-tax returns by placing tax-inefficient assets in tax-advantaged accounts while holding tax-efficient assets in taxable accounts. TIPS and commodity ETFs generate ordinary income taxed at higher rates, making them candidates for retirement account placement. Stock ETFs generate qualified dividends and long-term capital gains taxed at lower rates, making them suitable for taxable accounts.
Some investors prefer implementing the bond allocation through individual Treasury securities rather than ETFs, eliminating management fees while gaining precise maturity control. Treasury auctions provide access to new securities without bid-ask spreads, though this approach requires more sophisticated portfolio management.
Factor-based implementations replace broad market ETFs with factor-tilted alternatives. Value-tilted stock ETFs, quality-focused bond ETFs, or momentum-based commodity indices may enhance returns while maintaining the All Weather framework's diversification benefits. However, these modifications introduce additional complexity and potential tracking error.
Conclusion: Embracing the Long Game
The All Weather Strategy represents more than an investment approach; it embodies a philosophy of financial resilience that prioritizes sustainable wealth building over speculative gains. In an investment landscape increasingly dominated by algorithmic trading, meme stocks, and cryptocurrency volatility, Dalio's methodical approach offers a refreshing alternative grounded in economic theory and historical evidence.
The strategy's greatest strength lies not in its potential for extraordinary returns, but in its capacity to deliver reasonable returns across diverse economic environments while protecting capital during market stress. This characteristic becomes increasingly valuable as investors approach or enter retirement, when portfolio preservation assumes greater importance than aggressive growth.
Implementation requires discipline, adequate capital, and realistic expectations. The strategy will underperform growth-oriented approaches during bull markets while providing superior downside protection during bear markets. Investors must embrace this trade-off consciously, understanding that the strategy optimizes for long-term wealth building rather than short-term performance.
The All Weather Strategy Indicator democratizes access to institutional-quality portfolio management, providing individual investors with tools previously available only to wealthy families and institutions. By automating allocation tracking, rebalancing signals, and performance analysis, the indicator removes much of the complexity that has historically limited sophisticated strategy implementation.
For investors seeking a systematic, evidence-based approach to long-term wealth building, the All Weather Strategy provides a compelling framework. Its emphasis on diversification, risk management, and behavioral discipline aligns with the fundamental principles that have created lasting wealth throughout financial history. While the strategy may not generate headlines or inspire cocktail party conversations, it offers something more valuable: a reliable path toward financial security across all economic seasons.
As Dalio himself notes, "The biggest mistake investors make is to believe that what happened in the recent past is likely to persist, and they design their portfolios accordingly." The All Weather Strategy's enduring appeal lies in its rejection of this recency bias, instead embracing the uncertainty of markets while positioning for success regardless of which economic season unfolds.
STEP-BY-STEP INDICATOR SETUP GUIDE
Setting up the All Weather Strategy Indicator requires careful attention to each configuration parameter to ensure optimal implementation. This comprehensive setup guide walks through every setting and explains its impact on strategy performance.
Initial Setup Process
Begin by adding the indicator to your TradingView chart. Search for "Ray Dalio's All Weather Strategy" in the indicator library and apply it to any chart. The indicator operates independently of the underlying chart symbol, drawing data directly from the five required ETFs regardless of which security appears on the chart.
Portfolio Configuration Settings
Start with the Portfolio Capital input, which drives all subsequent calculations. Enter your exact investable capital, ranging from $1,000 to $10,000,000. This input determines share quantities, trade recommendations, and performance calculations. Conservative recommendations suggest minimum capitals of $50,000 for basic implementation or $100,000 for optimal precision.
Select your Portfolio Start Date carefully, as this establishes the baseline for all performance calculations. Choose the date when you actually began implementing the All Weather Strategy, not when you first learned about it. This date should reflect when you first purchased ETFs according to the target allocation, creating realistic performance tracking.
Choose your Rebalancing Frequency based on your cost structure and precision preferences. Monthly rebalancing provides tighter allocation control but increases transaction costs. Quarterly rebalancing offers the optimal balance for most investors between allocation precision and cost control. The indicator automatically detects appropriate trading days regardless of your selection.
Set the Rebalancing Threshold based on your tolerance for allocation drift and transaction costs. Conservative investors preferring tight control should use 1-2% thresholds, while cost-conscious investors may prefer 3-5% thresholds. Lower thresholds maintain more precise allocations but trigger more frequent trading.
Display Configuration Options
Enable Show All Weather Calculator to display the comprehensive dashboard containing portfolio values, allocations, and performance metrics. This dashboard provides essential information for portfolio management and should remain enabled for most users.
Show Economic Environment displays current economic regime classification based on growth and inflation indicators. While simplified compared to Bridgewater's sophisticated models, this feature provides useful context for understanding current market conditions.
Show Rebalancing Signals highlights when portfolio allocations drift beyond your threshold settings. These signals use color coding to indicate urgency levels, helping prioritize rebalancing activities.
Advanced Label Customization
Configure Show Rebalancing Labels based on your need for chart annotations. These labels mark important portfolio events and can provide valuable historical context, though they may clutter charts during extended time periods.
Select appropriate Label Detail Levels based on your experience and information needs. "None" provides minimal symbols suitable for experienced users. "Basic" shows portfolio values at key events. "Detailed" provides complete trading instructions including exact share quantities for each ETF.
Appearance Customization
Choose Color Themes based on your aesthetic preferences and trading style. "Gold" reflects traditional wealth management appearance, while "EdgeTools" provides modern professional styling. "Behavioral" uses psychologically informed colors that reinforce disciplined decision-making.
Enable Dark Mode Optimization if using TradingView's dark theme for optimal readability and contrast. This setting automatically adjusts all colors and transparency levels for the selected theme.
Set Main Line Width based on your chart resolution and visual preferences. Higher width values provide clearer allocation lines but may overwhelm smaller charts. Most users prefer width settings of 2-3 for optimal visibility.
Troubleshooting Common Setup Issues
If the indicator displays "Data not available" messages, verify that all five ETFs (SPY, TLT, IEF, DJP, SCHP) have valid price data on your selected timeframe. The indicator requires daily data availability for all components.
When rebalancing signals seem inconsistent, check your threshold settings and ensure sufficient time has passed since the last rebalancing event. The indicator only triggers signals on designated rebalancing days (first trading day of each period) when drift exceeds threshold levels.
If labels appear at unexpected chart locations, verify that your chart displays percentage values rather than price values. The indicator forces percentage formatting and 0-40% scaling for optimal allocation visualization.
COMPREHENSIVE BIBLIOGRAPHY AND FURTHER READING
PRIMARY SOURCES AND RAY DALIO WORKS
Dalio, R. (2017). Principles: Life and work. New York: Simon & Schuster.
Dalio, R. (2018). A template for understanding big debt crises. Bridgewater Associates.
Dalio, R. (2021). Principles for dealing with the changing world order: Why nations succeed and fail. New York: Simon & Schuster.
BRIDGEWATER ASSOCIATES RESEARCH PAPERS
Jensen, G., Kertesz, A. & Prince, B. (2010). All Weather strategy: Bridgewater's approach to portfolio construction. Bridgewater Associates Research.
Prince, B. (2011). An in-depth look at the investment logic behind the All Weather strategy. Bridgewater Associates Daily Observations.
Bridgewater Associates. (2015). Risk parity in the context of larger portfolio construction. Institutional Research.
ACADEMIC RESEARCH ON RISK PARITY AND PORTFOLIO CONSTRUCTION
Ang, A. & Bekaert, G. (2002). International asset allocation with regime shifts. The Review of Financial Studies, 15(4), 1137-1187.
Bodie, Z. & Rosansky, V. I. (1980). Risk and return in commodity futures. Financial Analysts Journal, 36(3), 27-39.
Campbell, J. Y. & Viceira, L. M. (2001). Who should buy long-term bonds? American Economic Review, 91(1), 99-127.
Clarke, R., De Silva, H. & Thorley, S. (2013). Risk parity, maximum diversification, and minimum variance: An analytic perspective. Journal of Portfolio Management, 39(3), 39-53.
Fama, E. F. & French, K. R. (2004). The capital asset pricing model: Theory and evidence. Journal of Economic Perspectives, 18(3), 25-46.
BEHAVIORAL FINANCE AND IMPLEMENTATION CHALLENGES
Kahneman, D. & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-292.
Thaler, R. H. & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. New Haven: Yale University Press.
Montier, J. (2007). Behavioural investing: A practitioner's guide to applying behavioural finance. Chichester: John Wiley & Sons.
MODERN PORTFOLIO THEORY AND QUANTITATIVE METHODS
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3), 425-442.
Black, F. & Litterman, R. (1992). Global portfolio optimization. Financial Analysts Journal, 48(5), 28-43.
PRACTICAL IMPLEMENTATION AND ETF ANALYSIS
Gastineau, G. L. (2010). The exchange-traded funds manual. 2nd ed. Hoboken: John Wiley & Sons.
Poterba, J. M. & Shoven, J. B. (2002). Exchange-traded funds: A new investment option for taxable investors. American Economic Review, 92(2), 422-427.
Israelsen, C. L. (2005). A refinement to the Sharpe ratio and information ratio. Journal of Asset Management, 5(6), 423-427.
ECONOMIC CYCLE ANALYSIS AND ASSET CLASS RESEARCH
Ilmanen, A. (2011). Expected returns: An investor's guide to harvesting market rewards. Chichester: John Wiley & Sons.
Swensen, D. F. (2009). Pioneering portfolio management: An unconventional approach to institutional investment. Rev. ed. New York: Free Press.
Siegel, J. J. (2014). Stocks for the long run: The definitive guide to financial market returns & long-term investment strategies. 5th ed. New York: McGraw-Hill Education.
RISK MANAGEMENT AND ALTERNATIVE STRATEGIES
Taleb, N. N. (2007). The black swan: The impact of the highly improbable. New York: Random House.
Lowenstein, R. (2000). When genius failed: The rise and fall of Long-Term Capital Management. New York: Random House.
Stein, D. M. & DeMuth, P. (2003). Systematic withdrawal from retirement portfolios: The impact of asset allocation decisions on portfolio longevity. AAII Journal, 25(7), 8-12.
CONTEMPORARY DEVELOPMENTS AND FUTURE DIRECTIONS
Asness, C. S., Frazzini, A. & Pedersen, L. H. (2012). Leverage aversion and risk parity. Financial Analysts Journal, 68(1), 47-59.
Roncalli, T. (2013). Introduction to risk parity and budgeting. Boca Raton: CRC Press.
Ibbotson Associates. (2023). Stocks, bonds, bills, and inflation 2023 yearbook. Chicago: Morningstar.
PERIODICALS AND ONGOING RESEARCH
Journal of Portfolio Management - Quarterly publication featuring cutting-edge research on portfolio construction and risk management
Financial Analysts Journal - Bi-monthly publication of the CFA Institute with practical investment research
Bridgewater Associates Daily Observations - Regular market commentary and research from the creators of the All Weather Strategy
RECOMMENDED READING SEQUENCE
For investors new to the All Weather Strategy, begin with Dalio's "Principles" for philosophical foundation, then proceed to the Bridgewater research papers for technical details. Supplement with Markowitz's original portfolio theory work and behavioral finance literature from Kahneman and Tversky.
Intermediate students should focus on academic papers by Ang & Bekaert on regime shifts, Clarke et al. on risk parity methods, and Ilmanen's comprehensive analysis of expected returns across asset classes.
Advanced practitioners will benefit from Roncalli's technical treatment of risk parity mathematics, Asness et al.'s academic critique of leverage aversion, and ongoing research in the Journal of Portfolio Management.
TotM - Volume compareTotM - Volume Compare Indicator
Overview:
This advanced volume comparison indicator allows traders to monitor and compare trading volumes across up to 15 different symbols simultaneously. Works with any tradable asset - stocks, forex, commodities, cryptocurrencies, indices, or futures. Perfect for identifying market trends, volume shifts, and trading opportunities across multiple instruments.
Key Features:
Multi-Symbol Tracking: Monitor up to 15 different symbols from any market simultaneously
Universal Compatibility: Works with any asset class - stocks, crypto, forex, commodities, ETFs, indices
Normalized Volume Display: Automatically normalizes volumes for accurate cross-asset comparison
Real-time Ranking Table: Dynamic table showing top performers by volume (customizable 5-15 rows)
Customizable Visualization: Individual color coding for each symbol for easy identification
Price-Weighted Volume Option: Toggle between raw volume and price-weighted volume (Volume × Price)
Smart Error Handling: Automatically skips invalid or unavailable symbols without disrupting the indicator
Moving Average Smoothing: Built-in EMA/SMA smoothing with adjustable period (default: 3)
Cross-Exchange Support: Mix symbols from different exchanges (Binance, NYSE, NASDAQ, etc.)
How It Works:
The indicator fetches volume data from selected symbols and normalizes them using a reference value for meaningful comparison. This normalization allows traders to compare assets with vastly different trading volumes and price levels on the same scale. The ranking table automatically sorts and displays the most active symbols, helping traders quickly identify where the market action is concentrated.
Use Cases:
Compare sector rotation (tech stocks vs financials vs energy)
Monitor volume across different asset classes simultaneously
Track correlated instruments (gold vs gold miners, oil vs energy stocks)
Identify unusual volume spikes across your watchlist
Compare index components' relative activity
Monitor forex pairs volume relationships
Track commodity futures volume patterns
Settings:
Enable/disable individual symbols
Customize colors for each tracked symbol
Adjust MA period for smoothing
Toggle price-weighted volume calculation
Show/hide ranking table
Adjust number of rows in ranking table (5-15)
© Trade on the Market (TotM) - Professional trading tools for informed decision making.
Gann Box LogicGann Box Logic
Overview
The Gann Box Logic indicator is a precision-based trading tool that combines the principles of Gann analysis with retracement logic to highlight high-probability zones of price action. It plots a structured box on the chart based on the previous day's high and low, overlays Fibonacci-derived retracement levels, and visually marks a critical “neutral zone” between 38.2% and 61.8% retracements.
This zone — shaded for emphasis — is a decision filter for traders:
- It warns against initiating trades in this area (low conviction zone).
- It identifies reversal pull targets when extremes are reached.
Core Principles Behind Gann Box Logic
Logic 1 — The Neutral Zone (38.2% ↔ 61.8%)
- The 38.2% and 61.8% retracement levels are key Fibonacci ratios often associated with consolidation or indecision.
- Price action between these two levels is considered a neutral, low-conviction zone.
- Trading Recommendation:
- Avoid initiating new trades while price remains within this shaded band.
- This zone tends to produce whipsaws and false signals.
- Wait for a decisive break above 61.8% or below 38.2% for clearer momentum.
- Why it matters:
- In Gann’s market structure thinking, the middle range of a swing is often a battleground where neither bulls nor bears are in full control.
- This is the zone where market makers often shake out weak hands before committing to a direction.
Logic 2 — Extremes Seek Balance (0% & 100% Reversal Bias)
- The indicator’s 0% and 100% levels represent the previous day’s low and high respectively.
- First Touch Rule:
- When the price touches 0% (previous low) or 100% (previous high) for the first time in the current session, there is a high probability it will attempt to revert toward the center zone (38.2% ↔ 61.8%).
- Trading Implication:
- If price spikes to an extreme, be alert for reversion trades toward the mid-zone rather than expecting a sustained breakout.
- Momentum traders may still pursue breakout trades, but this bias warns of potential pullbacks.
- Why it works:
- Extreme levels often trigger profit-taking by early entrants and counter-trend entries by mean-reversion traders.
- These forces naturally pull the market back toward equilibrium — often near the 50% level or within the shaded zone.
How the Indicator is Plotted
1. Previous Day High/Low Reference — The script locks onto the prior day’s range to establish the vertical bounds of the box.
2. Retracement Levels — Key Fibonacci levels plotted: 0%, 25%, 38.2%, 50%, 61.8%, 75%, 100%.
3. Box Structure — Outer Border marks the full prior day range, Mid Fill Zone is shaded between 38.2% and 61.8%.
4. VWAP (Optional) — Daily VWAP overlay for intraday bias confirmation.
Practical Usage Guide
- Avoid Trades in Neutral Zone — Stay out of the shaded area unless you’re already in a trade from outside this zone.
- Watch for First Touch Extremes — First touch at 0% or 100% → anticipate a pullback toward the shaded zone.
- Breakout Confirmation — Only commit to breakout trades when price leaves the 38.2–61.8% zone with strong volume and momentum.
- VWAP Confluence — VWAP crossing through the shaded zone often signals a balance day — breakout expectations should be tempered.
Strengths of Gann Box Logic
- Removes noise trades during low-conviction periods.
- Encourages patience and discipline.
- Highlights key market turning points.
- Provides clear visual structure for both new and advanced traders.
Limitations & Warnings
- Not a standalone entry system — best used in conjunction with price action and volume analysis.
- Extreme moves can sometimes trend without reversion, especially during news-driven sessions.
- Works best on intraday timeframes when referencing the previous day’s range.
In Summary
The Gann Box Logic indicator’s philosophy can be boiled down to two golden rules:
1. Do nothing in the middle — Avoid trades between 38.2% and 61.8%.
2. Expect balance from extremes — First touches at 0% or 100% often pull back toward the shaded mid-zone.
This dual approach makes the indicator both a trade filter and a targeting guide, allowing traders to navigate markets with a structured, Gann-inspired framework.
DISCLAIMER
The information provided by this indicator is for educational purposes only and should not be considered financial advice. Trading carries risk, including possible loss of capital. Past performance does not guarantee future results. Always conduct your own research and consult with a qualified financial professional before making trading decisions.
Estrategia WT + Squeeze + MMAs v6 (Mejorada)USER GUIDE – WT + Squeeze + MMAs Strategy
1. Preparation
Activate your indicator on the chart of the asset you want to trade (stock, ETF, index, etc.).
Choose the time frame according to your style:
Intraday: 5m, 15m, 30m
Swing: 1h, 4h
Investment: Daily, Weekly
Always check two time frames:
A higher one for the overall trend.
A lower one for precise entry.
2. Initial Filter: Trend
Buy: Price above the 200 MMA.
Sell: Price below the 200 MMA.
❌ Do not trade signals that go against the main trend.
3. Confirm the Momentum
Buy: 10 MMA above the 55 MMA.
Sell: 10 MMA below the 55 MMA.
Both MAs must be aligned with the trend direction indicated by the 200 MMA.
4. Wait for System Confirmation
The script will mark:
📈 BUY (green):
Uptrend confirmed.
WT crosses upward.
Positive Squeeze Momentum (green values).
📉 SELL (red):
Downtrend confirmed.
WT crosses downward.
Negative Squeeze Momentum (red values).
💡 Golden Rule: Only enter if the trend, momentum, and script signals are aligned.
5. Trade Execution
Buy (BUY):
Enter at the open of the candle following the signal.
Stop Loss: Below the last relevant support or recent low.
Take Profit:
Minimum R/R 1:2
Or exit when a sell signal appears.
Sell (SELL):
Enter at the open of the candle following the signal.
Stop Loss: Above the last relevant resistance or recent high.
Take Profit: Same as in buys.
6. Risk Management
Risk no more than 1–2% of your capital in a single trade.
If trading stocks (spot market):
Only use BUY, holding as long as the 10 MMA does not cross below the 55 MMA.
If trading CFDs or on margin:
You can use BUY and SELL, applying a strict SL.
7. Filter Out False Signals
Avoid trading right before major news events (earnings reports, economic announcements).
If the signal appears in a very tight range, wait for a breakout.
On a higher time frame, check that the price is not touching strong resistance (for buys) or strong support (for sells).
Quick Example
On 4H → price is above the 200 MMA (uptrend).
On 15M → 10 MMA > 55 MMA, WT crosses bullish, and Squeeze turns green.
Script marks BUY.
Place a buy order, SL below last support, TP 1:2 or exit when the script marks SELL.
