XAUUSD Lot Size Calculator + RSI (Yoothobbiz)This indicator is designed for Gold traders on the 5-minute timeframe (M5) who want a clear and editable lot size, stop loss, and take profit calculator directly on their chart.
✨ Features:
📌 Dynamic Lot Size Calculation – based on account capital, chosen risk %, and stop loss distance.
⚖️ Risk/Reward Management – automatically displays TP level using a customizable risk/reward ratio (e.g., 1:2, 1:3, etc.).
🛑 Stop Loss in Points & Price – calculates SL from recent M5 highs/lows, including spread.
🎯 Take Profit in Price & Points – automatically adjusted to your risk/reward ratio.
💵 Risk in USD – instantly shows how much capital is at risk per trade.
🕒 Custom Time Zone Support – displays the real trading time (default UTC-4 for New York), fully editable for any user.
⏱ Timeframe Label – clearly shows the working timeframe (M5 by default).
🎨 Fully Editable Display Panel:
Position (6 corners available).
Font family, size, style (bold/italic).
Text and background colors.
Adjustable spacing between lines.
🔑 How to Use:
Set your capital and risk % in the settings.
Adjust spread (in points) if needed.
Choose your risk/reward ratio.
The panel will display:
Recommended lot size for XAUUSD
Stop loss (price + points)
Take profit (price + ratio)
Risk in $
Timeframe & real-time clock
📍 Notes:
Optimized for XAUUSD (Gold) and the 5M timeframe.
Works on any asset/timeframe, but SL logic is based on M5 candle highs/lows.
Ideal for traders who want a fast and disciplined risk management tool right on their chart.
Portföy Yönetimi
Optimized Trend-Momentum SignalsThis indicator combines trend, momentum, and volume-strength factors into a single buy/sell signal system. It integrates:
SMA 200 → Identifies the long-term trend (price above = bullish bias, below = bearish bias).
MACD (12,26,9) → Confirms momentum direction with line crossovers.
RSI (7) → Filters strength (above 50 = bullish, below 50 = bearish).
ROC (45) → Validates positive or negative rate of change.
Signal Logic:
Buy Signal → Price above SMA 200, MACD bullish, RSI > 50, and ROC > 0.
Sell Signal → Price below SMA 200, MACD bearish, RSI < 50, and ROC < 0.
Features:
Clear arrows for BUY and SELL signals.
Long-term SMA plotted for trend visualization.
Alerts built-in for real-time notifications.
This tool helps traders filter out noise and act only when all major confirmation factors align, reducing false signals and improving decision-making.
Trend and Entry Marker with MA, Supports, Fib, and Trend LinesJust a little indicator I made when I was bored ...
Helps you find entries for trades!
10 EMA + ½ ATR Position SizingThis is a table that will show position sizing using both the 10 EMA and 1/2 ATR as stop losses. You can input account value and desired risk % and toggle between detailed and concise table styles.
Simple MADSimple MAD is a lightweight and customizable indicator that calculates the Median Absolute Deviation (MAD) over a configurable period to measure market volatility. It dynamically displays Stop-Loss (SL) and Take-Profit (TP) levels based on MAD multipliers, both in absolute price and percentage terms.
The indicator includes a clean, watermark-style table with full layout controls — allowing you to adjust position, text size, alignment, and colors. It supports both manual entry price and automatic use of the latest close, making it ideal for traders who want to manage risk with precision and clarity.
Perfect for swing traders, volatility-based strategies, and anyone looking to integrate MAD into their decision-making.
Staggered Exponential PullbacksIndicator Description: Staggered Exponential Pullbacks (Final)
Core Concept
This indicator is designed to dynamically track and visualize price pullbacks from a recent high. It serves as an intelligent alert system and a tool for visualizing potential support levels that follow a predefined, non-linear logic.
Instead of a fixed percentage interval, the indicator calculates the levels based on a fixed, exponentially increasing sequence of percentages. The distance between the levels increases as the price falls further. This models a strategy where larger price movements are tolerated as a pullback deepens before the next signal level is reached. The basis for this calculation is always the highest close of the last x candles.
Key Features
This indicator goes far beyond a simple calculation, offering a range of intelligent features for professional use:
Cascading, Fixed Levels: The levels are based on a fixed sequence of percentage distances (3.0%, 3.6%, 4.3%, etc.), where each new level is calculated from the previous level.
Persistent Support Levels ("Floors"): Once an alert level is breached, it transforms into a fixed support line ("floor"). This line will never move down, even if the market high subsequently drops.
Automatic Upward Adjustment: Established floors are automatically pulled upwards when the market shows new strength and makes higher highs. A once-reached -3% floor will therefore rise with the market.
Intelligent, Self-Cleaning Reset Logic: The indicator recognizes when a pullback sequence has ended and a new one has begun. "Ghost lines" from old, irrelevant price movements are automatically removed from the chart to ensure maximum clarity.
Cascade-Proof Alerts: Even during extremely fast sell-offs that break through multiple levels in a single candle, the indicator correctly captures every single level breach.
Customizable Visualization: All key parameters, such as the lookback period and the colors of the lines, can be easily adjusted in the settings.
Visual Elements on the Chart
The Orange Line (Highest Close): This is the reference line. It always shows the highest closing price within the defined lookback period and has a step-line shape.
The 'Floor' Lines (Default: Yellow): These are solid lines that indicate which percentage levels have already been breached in the current sequence. They function as established support levels.
The 'Next Due' Line (Default: Purple): This is a step-line that displays the next expected alert level. It moves dynamically with the calculation. As soon as the price crosses this line, an alert is triggered, and it transforms into a yellow "Floor" line.
Settings (Inputs)
Number of Candles (Lookback): Defines how many past candles are used to determine the highest closing price.
Displayed Alert Levels (Max 10): Determines the maximum number of levels the indicator will calculate and display.
Color of Floors: Allows you to freely choose the color for the solid, established support lines.
Color of Next Due Line: Allows you to freely choose the color for the next, untriggered alert line.
Setting Up Alerts (Important!)
Since the indicator uses dynamic alert messages, the alert must be set up as follows:
Add the indicator to the chart.
Click the clock icon ("Alert") in the top toolbar.
In the "Condition" field, select the name of this indicator: Staggered Exponential Pullbacks.
In the second dropdown menu, you must select the option "Any alert() function call".
Message: The message box can be left empty. The indicator automatically generates a detailed message (e.g., "Price Alert: Level 2 (3.6%) reached!").
Click "Create".
You only need one single alert to cover all 10 levels.
Important Disclaimer: Not Financial Advice
This indicator is purely a technical analysis tool for visualizing price movements. The displayed lines and triggered alerts do not constitute buy or sell recommendations and are not a form of financial or investment advice. They serve for informational and analytical purposes only.
Trading decisions based on the information from this indicator are made solely at your own risk and responsibility. The author and developer of this script assume no liability for any trading losses. Always conduct your own comprehensive analysis and, if necessary, consult a qualified financial advisor before making any trading decisions.
Index Position Size Calculator for [US30 / US100 / SP500]What it does
This tool helps you size positions consistently for index trades on US30 (Dow Jones), NAS100 (Nasdaq-100), and SP500 (S&P 500). Enter your account balance, risk %, and your planned Entry / Stop-Loss / Target and the script calculates:
• Position Size (rounded to your lot/contract step)
• Risk-to-Reward (R/R)
• Potential P/L in USD based on your inputs
• Visual Entry / SL / TP lines with green/red zones and concise labels
Supported contract styles
Choose a preset for common products (e.g., CFD $1/pt, YM/NQ/ES futures, MYM/MNQ/MES micros) or override the economics yourself. You remain in control of the two key levers:
• $/point — how many dollars you gain/lose per 1 index point per contract/lot
• Point size — how many price units equal 1 index point on your chart (often 1.0, but some brokers use 0.1 or 0.5)
Inputs
• Account Balance ($) and Risk % per trade
• Index: US30 / NAS100 / SP500
• Contract: CFD / Futures (YM, NQ, ES) / Micros (MYM, MNQ, MES)
• $/point: auto from Contract or manual override
• Point size: auto from Index or manual override
• Position size step: rounding (e.g., 1 for futures, 0.01 for CFDs)
• Entry / SL / TP: typed values (snapped to tick), with on-chart zones and labels
• Display toggles for lines and labels
How the math works
• StopPoints = |Entry − SL| ÷ PointSize
• ProfitPoints = |TP − Entry| ÷ PointSize
• Position Size = (AccountBalance × Risk%) ÷ (StopPoints × $/point)
• R/R = ProfitPoints ÷ StopPoints
• Potential P/L = PositionSize × Points × $/point
How to use (quick start)
1. Select Index and Contract.
2. Confirm $/point and Point size match your broker’s specs.
3. Enter Entry / SL / TP for the trade idea.
4. Read the Position Size, R/R, and Potential P/L in the info box.
5. Adjust for fees, spreads, and slippage as needed.
Notes & limitations
• Broker symbols can vary. Always verify $/point and Point size for your instrument before risking capital.
• The script does not place orders and does not generate trade signals; it’s a sizing/visualization tool.
• Results can differ across brokers due to pricing, spreads, minimum lot sizes, and execution rules.
• Use on the intended indices; you’ll see a reminder if you load it elsewhere.
Changelog highlights
• Pine v6, constant-safe inputs, tick-snapping, global fills (no local-scope errors).
• Robust label handling and optional minimal chart markers.
Disclaimer
This script is provided for educational purposes only and does not constitute financial advice or a recommendation to buy or sell any security or derivative. Trading involves risk, including the possible loss of principal. Always do your own research, verify contract specifications with your broker, and consider testing in a demo environment before trading live.
LEAP Put Edge — Top Risk Oscillator (v6, divergences + HTF)Pinpoint market tops with precision — a composite oscillator built to spot exhaustion, bearish divergences, and high-probability LEAP Put entry zones.
The LEAP Put Edge — Top Risk Oscillator is designed specifically to help identify high-probability entry points for long-dated Put options (LEAPs) by highlighting exhaustion at market tops. Unlike generic overbought/oversold tools, it combines slower MACD and DMI/ADX for trend quality, RSI and Stochastic RSI for momentum extremes, volume spike and upper-wick exhaustion signals for capitulation risk, and optional bearish divergences in RSI and MACD to confirm weakening strength. The output is a smoothed composite score scaled from -100 to +100, where higher values indicate rising top-risk and bearish edge conditions. Clear thresholds, color-coded plots, and built-in alerts make it straightforward and practical for traders seeking simple, actionable signals to time Put entries with confidence.
Trade Calculator {Phanchai}Trade Calculator 🧮 {Phanchai} — Documentation
A lightweight sizing helper for TradingView that turns your risk per trade into an estimated maximum nominal position size — using the most recent chart low as your stop reference. Built for speed and clarity right on the chart.
Key Features
Clean on-chart info table with configurable font size and position.
Row toggles: show/hide each line (Price, Last Low, Risk per Trade, Entry − Low, SL to Low %, Max. Nominal Value in USDT).
Configurable low reference: Last N bars or Running since load .
Low label placed exactly at the wick of the lowest bar (no horizontal line).
Custom padding: add extra rows above/below and blank columns left/right (with custom whitespace/text fillers) to fine-tune layout.
Integer display for Risk per Trade (USDT) and Max. Nominal Value (USDT); decimals configurable elsewhere.
Open source script — easy to read and extend.
How to Use
Add the indicator: open TradingView → Indicators → paste the source code → Add to chart.
Pick your low reference in settings:
Last N bars — uses the lowest low within your chosen lookback.
Running since load — tracks the lowest low since the script loaded.
Set your capital and risk:
Total Capital — your account size in USDT.
Max. invest Capital per Trade (%) — your risk per trade as a percent of Total Capital.
Tidy the table:
Use Table Position and Table Size to place it.
Add Extra rows/columns and set left/right fillers (spaces allowed) for padding.
Toggle individual rows (on/off) to show only what you need.
Read the numbers:
Act. Price in USDT — current close.
Last Low in USDT — stop reference price.
Risk per Trade — whole-USDT value of your risk budget for this trade.
Entry − Low — absolute risk per unit.
SL to Low (%) — percentage distance from price to low.
Max. Nominal Value in USDT — estimated max nominal position size given your risk budget and stop at the low.
Scope
This calculator is designed for long trades only (stop below price at the chart low).
Notes & Assumptions
Does not factor fees, funding, slippage, tick size, or broker/venue position limits.
“Running since load” updates as new lows appear; “Last N bars” uses only the selected lookback window.
If price equals the low (zero distance), sizing will be undefined (division by zero guarded as “—”).
Risk Warning
Trading involves substantial risk. Always double-check every value the calculator shows, confirm your stop distance, and verify position sizing with your broker/platform before entering any order. Never risk money you cannot afford to lose.
Open Source & Feedback
The source code is open. If you spot a bug or have an idea to improve the tool, feel free to share suggestions — I’m happy to iterate and make it better.
Weekly pecentage tracker by PRIVATE
Settings Picture below this link: 👇
i.ibb.co
What it is
A lightweight “Weekly % Tracker” overlay that lets you manually enter weekly performance (in percent) for XAUUSD + up to 10 FX pairs, then shows:
a small table panel with each enabled symbol and its % result
one TOTAL row (Sum / Average / Compounded across all enabled symbols)
an optional mini badge showing the % for a single selected symbol
Nothing is auto-calculated from price—you type the % yourself.
Key settings
Panel: show/hide, position, number of decimals, colors (background, text, green/red).
Total mode:
Sum – adds percentages
Average – mean of enabled rows
Compounded –
(
∏
(
1
+
𝑝
/
100
)
−
1
)
×
100
(∏(1+p/100)−1)×100
Symbols:
XAUUSD (toggle + label + % input)
10 FX pairs (each has On/Off, label text, % input). You can rename labels to any symbol text you want.
Mini badge: show/hide, position, and symbol to display.
How it works
Overlay indicator: overlay=true; just draws UI on the chart (no plots).
Arrays (syms, vals, ons) collect the row data in order: XAU first, then FX1…FX10.
Helpers:
posFrom() converts a position string (e.g., “Top Right”) into a position.* constant.
wp_col() picks green/red/neutral based on the sign of the %.
wp_round() rounds values to the selected decimals.
calc_total() computes the TOTAL with the chosen mode over enabled rows only.
Table creation logic:
Counts how many rows are enabled.
If none enabled or panel is off: the panel table is deleted, so no box/background is visible.
If enabled and on: the panel is (re)created at the chosen position.
On each last bar (barstate.islast), it clears the table to transparent (bgcolor=na) and then fills one row per enabled symbol, followed by a single TOTAL row.
Mini badge:
Always (re)created on position change.
Shows selected symbol’s % (or “-” if that symbol isn’t enabled or has no value).
Colors text green/red by sign.
Notes & limits
It’s manual input—the script doesn’t read trades or P/L from price.
You can rename each row’s label to match any symbol name you want.
When no rows are enabled, the panel disappears entirely (no empty background).
Designed to be light: only draws tables; no heavy plotting.
If you want the TOTAL row to be optional, or different color thresholds, or CSV-style export/import of the values, say the word and I’ll add it.
India Nifty Index Performances DashboardSelf explanatory tabular view of Nifty sector performance ranked top & bottom across calendar year vs. financial year — a clear view of market leaders and laggards.
Options available: Day, Week, Month, Quarter, Calendar Year, (India) Financial Year p
performances. Included Gold (from Mcx), Sme (from Bse), 10Y Gsec for comparison.
Economic Profit (Fixed & Labeled) — Rated + PeersFRAC (Fundamental-Rated-Asset-Calculate)
FRAC is a fundamentals-driven tool designed to measure whether a company is creating or destroying shareholder value. Unlike surface ratios, FRAC uses Economic Profit (ROIC – WACC) as its engine, showing whether a business truly outperforms its cost of capital.
🔹 What FRAC Does
Calculates ROIC (Return on Invested Capital) vs. WACC (Weighted Average Cost of Capital).
Shows whether a company is creating or destroying shareholder value.
Uses tiered color coding for clarity:
🔵 Superior (Aqua Blue) → Top tier; best of the best.
🟣 Elite (Purple) → Strong value creation.
🟢 Positive (Green) → Solid, creating shareholder value.
🟡 Marginal (Yellow) → Barely covering cost of capital.
🔴 Negative (Red) → Value destruction.
🔹 Composite Ranking System (1–4)
FRAC also assigns each company a Composite Rank so you can compare multiple names side by side. The rank works like this:
Rank 1 → Superior (🔵 Aqua Blue)
Best possible rating; wide gap between ROIC and WACC.
Rank 2 → Elite (🟣 Purple)
Strongly positive; above-average capital efficiency.
Rank 3 → Positive (🟢 Green)
Creating value but only moderately; not a top compounder.
Rank 4 → Marginal/Negative (🟡/🔴)
Weak or destructive; either barely covering WACC or losing money on capital.
✅ How to Use the Ranks
When comparing a set of peers (e.g., NVDA, AMD, INTC):
FRAC will display each company’s color rating + composite rank (1–4).
You can instantly see who is strongest vs. weakest in the group.
Best decisions = overweight Rank 1 & 2 companies, avoid Rank 4 names.
🔹 Key Inputs Explained
Risk-Free Asset → Typically the 10-Year US Treasury yield (US10Y).
Corporate Tax Rate → Effective tax rate for the company’s country (e.g., USCTR).
Expected Market Return → Historical average ~8–10%, adjustable.
Beta Lookback Period → Controls how far back Beta is calculated (longer = more stable, shorter = more reactive).
👉 These must be set correctly for FRAC to calculate WACC accurately.
🔹 Example Comparison
NVDA: ROIC 25% – WACC 7% = +18% → 🔵 Superior → Rank 1
AMD: ROIC 17% – WACC 8% = +9% → 🟣 Elite → Rank 2
INTC: ROIC 11% – WACC 9% = +2% → 🟢 Positive → Rank 3
FSLY: ROIC 5% – WACC 10% = –5% → 🔴 Negative → Rank 4
🔹 Why It Matters
Buffett said: “The best businesses are those that can consistently generate returns on capital above their cost of capital.”
FRAC turns that into a visual + numeric rating system (1–4), making comparisons across peers simple and actionable.
🔹 Credit
FRAC was created by Hunter Hammond (Elite x FineFir), inspired by corporate finance models of Economic Profit and Economic Value Added (EVA).
⚠️ Disclaimer: FRAC is a research framework, not financial advice. Always pair with full due diligence.
Fear & Greed Oscillator — LEAPs (v6, manual DMI/ADX)Fear & Greed Oscillator for LEAPs — a composite sentiment/trend tool that highlights long-term fear/greed extremes and trend quality for better LEAP entries and exits.
This custom Fear & Greed Oscillator (FGO-LEAP) is designed for swing trades and long-term LEAP option entries. It blends multiple signals — MACD (trend), ADX/DMI (trend quality), OBV (accumulation/distribution), RSI & Stoch RSI (momentum), and volume spikes — into a single score that ranges from –100 (extreme fear) to +100 (extreme greed). The weights are tuned for LEAPs, emphasizing slower trend and accumulation signals rather than short-term noise.
Use Weekly charts for the main signal and Daily only for entry timing. Entries are strongest when the score is above zero and rising, with both MACD and DMI positive. Extreme Fear (< –60) can mark long-term bottoms when followed by a recovery, while Extreme Greed (> +60) often signals overheated conditions. A cross below zero is an early warning to reduce or roll positions.
Parabolic CCI Pro — Long & Short + ATR Risk — [AlphaFinansData]English Description (Enhanced)
🔹 CCI + Parabolic SAR Strategy (Long & Short, Smart Risk Management)
This indicator combines the power of CCI (Commodity Channel Index) and Parabolic SAR, creating a highly reliable trading system that adapts to market conditions.
🚀 How It Works:
Trend Hunting: CCI detects weakening momentum and potential reversal zones.
Confirmation: Parabolic SAR confirms the trend direction, reducing false signals.
Smart Risk Management: Offers both fixed-percentage and ATR-based dynamic Stop Loss & Take Profit, adjusting to volatility automatically.
Performance Dashboard: Tracks win rate, average profit/loss, max drawdown, and winning/losing streaks for deeper strategy insights.
⚡ Who Is It For?
Day traders looking for quick entries and exits,
Swing traders seeking to capture trend reversals,
Risk-conscious investors who want disciplined SL/TP management.
💡 More than just a signal generator, this indicator provides traders with a structured trading framework that helps maintain consistency and discipline.
Position Size Calculator (Sidebar)Position Size Calculator to make sure you size up on trades correctly. Risk Management is important!
Crypto Position Size CalculatorPosition Size Calculator for Crypto.
This indicator uses the current price and a selected stop loss to calculate your position size without having to work it out elsewhere!
Simply set your account size, desired risk percentage and stop loss level and it will work out how many lots and the dollar value of your desired position.
Hope you enjoy!
Adaptive MVRV & RSI Strategy V6 (Dynamic Thresholds)Strategy Explanation
This is an advanced Dollar-Cost Averaging (DCA) strategy for Bitcoin that aims to adapt to long-term market cycles and changing volatility. Instead of relying on fixed buy/sell signals, it uses a dynamic, weighted approach based on a combination of on-chain data and classic momentum.
Core Components:
Dual-Indicator Signal: The strategy combines two powerful indicators for a more robust signal:
MVRV Ratio: An on-chain metric to identify when Bitcoin is fundamentally over or undervalued relative to its historical cost basis.
Weekly RSI: A classic momentum indicator to gauge long-term market strength and identify overbought/oversold conditions.
Dynamic, Self-Adjusting Thresholds: The core innovation of this strategy is that it avoids fixed thresholds (e.g., "sell when RSI is 70"). Instead, the buy and sell zones are dynamically calculated based on a long-term (2-year) moving average and standard deviation of each indicator. This allows the strategy to automatically adapt to Bitcoin's decreasing volatility and changing market structure over time.
Weighted DCA (Scaling In & Out): The strategy doesn't just buy or sell a fixed amount. The size of its trades is scaled based on conviction:
Buying: As the MVRV and RSI fall deeper into their "undervalued" zones, the percentage of available cash used for each purchase increases.
Selling: As the indicators rise further into "overvalued" territory, the percentage of the current position sold also increases.
This creates an adaptive system that systematically accumulates during periods of fear and distributes during periods of euphoria, with the intensity of its actions directly tied to the extremity of market conditions.
Sector Rotation & Money Flow Dashboard📊 Overview
The Sector Rotation & Money Flow Dashboard is a comprehensive market analysis tool that tracks 39 major sector ETFs in real-time, providing institutional-grade insights into sector rotation, momentum shifts, and money flow patterns. This indicator helps traders identify which sectors are attracting capital, which are losing favor, and where the next opportunities might emerge.
Perfect for swing traders, position traders, and investors who want to stay ahead of sector rotation and ride the strongest trends while avoiding weak sectors.
🎯 What This Indicator Does
Tracks 39 Major Sectors: From technology to utilities, cryptocurrencies to commodities
Calculates Multiple Timeframes: 1-week, 1-month, 3-month, and 6-month performance
Advanced Momentum Metrics: Proprietary momentum score and acceleration calculations
Relative Strength Analysis: Compare sector performance against any benchmark index
Money Flow Signals: Visual indicators showing where institutional money is moving
Smart Filtering: Pre-built strategy filters for different trading styles
Trend Detection: Emoji-based visual system for quick trend identification
💡 Key Features
1. Performance Metrics
Multiple timeframe analysis (1W, 1M, 3M, 6M)
Month-over-month change tracking
Relative strength vs benchmark index
2. Advanced Analytics
Momentum Score: Weighted composite of recent performance
Acceleration: Rate of change in momentum (second derivative)
Money Flow Signals: IN/OUT/TURN/WATCH indicators
3. Strategy Preset Filters
🎯 Swing Trade: High momentum opportunities
📈 Trend Follow: Established uptrends
🔄 Mean Reversion: Oversold bounce candidates
💎 Value Hunt: Deep value opportunities
🚀 Breakout: Emerging strength
⚠️ Risk Off: Sectors to avoid
4. Customization
All 39 sector ETFs can be customized
Adjustable benchmark index
Flexible display options
Multiple sorting methods
📋 Settings Documentation
Display Settings
Show Table (Default: On)
Toggles the entire dashboard display
Table Position (Default: Middle Center)
Choose from 9 positions on your chart
Options: Top/Middle/Bottom × Left/Center/Right
Rows to Show (Default: 15)
Number of sectors displayed (5-40)
Useful for focusing on top/bottom performers
Sort By (Default: Momentum)
1M/3M/6M: Sort by specific timeframe performance
Momentum: Weighted recent performance score
Acceleration: Rate of momentum change
1M Change: Month-over-month improvement
RS: Relative strength vs benchmark
Flow: IN First: Prioritize sectors with inflows
Flow: TURN First: Focus on reversal candidates
Recovery Plays: Oversold sectors recovering
Oversold Bounce: Deepest declines with positive signs
Top Gainers/Losers 3M: Best/worst quarterly performers
Best Acc + Mom: Combined strength score
Worst Acc (Topping): Sectors losing momentum
Filter Settings
Strategy Preset Filter (Default: All)
All: No filtering
🎯 Swing Trade: Mom >5, Acc >2, Money flowing in
📈 Trend Follow: Positive 1M & 3M, RS >0
🔄 Mean Reversion: Oversold but improving
💎 Value Hunt: Down >10% with recovery signs
🚀 Breakout: Rapid momentum surge
⚠️ Risk Off: Declining or topping sectors
Custom Flow Filter: Use manual flow filter
Custom Flow Signal Filter (Default: All)
Only active when Strategy Preset = "Custom Flow Filter"
IN Only: Strong inflows
TURN Only: Reversal signals
WATCH Only: Recovery candidates
OUT Only: Outflow sectors
Active Flows Only: Any non-neutral signal
Hide Low Volume ETFs (Default: Off)
Filters out illiquid sectors (future enhancement)
Visual Settings
Show Trend Emojis (Default: On)
🚀 Breakout (Strong 1M + High Acceleration)
🔥 Hot Recovery (From -10% to positive)
💪 Steady Uptrend (All timeframes positive)
➡️ Sideways/Ranging
⚠️ Warning/Topping (Up >15%, now slowing)
📉 Falling (Negative + declining)
🔄 Bottoming (Improving from lows)
Compact Mode (Default: Off)
Removes decimals for cleaner display
Useful when showing many rows
Min Data Points Required (Default: 3)
Minimum data points needed to display a sector
Prevents showing sectors with insufficient data
Relative Strength Settings
RS Benchmark Index (Default: AMEX:SPY)
Index to compare all sectors against
Can use SPY, QQQ, IWM, or any other index
RS Period (Days) (Default: 21)
Lookback period for RS calculation
21 days = 1 month, 63 days = 3 months, etc.
Sector ETF Settings (Groups 1-39)
Each sector has two inputs:
Symbol: The ticker (e.g., "AMEX:XLF")
Name: Display name (e.g., "Financials")
All 39 sectors can be customized to track different ETFs or markets.
📈 Column Explanations
Sector: ETF name/description
1M%: 1-month (21-day) performance
3M%: 3-month (63-day) performance
6M%: 6-month (126-day) performance
Mom: Momentum score (weighted average, recent-biased)
Acc: Acceleration (momentum rate of change)
Δ1M: Month-over-month change
RS: Relative strength vs benchmark
Flow: Money flow signal
↗️ IN: Strong inflows
🔄 TURN: Potential reversal
👀 WATCH: Recovery candidate
↘️ OUT: Outflows
—: Neutral
🎮 Usage Tips
For Swing Traders (3-14 days)
Use "🎯 Swing Trade" filter
Sort by "Acceleration" or "Momentum"
Look for Flow = "IN" and Mom >10
Confirm with positive RS
For Position Traders (2-8 weeks)
Use "📈 Trend Follow" filter
Sort by "RS" or "Best Acc + Mom"
Focus on consistent green across timeframes
Ensure RS >3 for market leaders
For Value Investors
Use "💎 Value Hunt" filter
Sort by "Recovery Plays" or "Top Losers 3M"
Look for improving Δ1M
Check for "WATCH" or "TURN" signals
For Risk Management
Regularly check "⚠️ Risk Off" filter
Sort by "Worst Acc (Topping)"
Review holdings for ⚠️ warning emojis
Exit sectors showing "OUT" flow
Market Regime Recognition
Bull Market: Many sectors showing "IN" flow, positive RS
Bear Market: Widespread "OUT" flows, negative RS
Rotation: Mixed flows, some "IN" while others "OUT"
Recovery: Multiple "TURN" and "WATCH" signals
🔧 Pro Tips
Combine Filters + Sorting: Filter first to narrow candidates, then sort to prioritize
Multi-Timeframe Confirmation: Best setups show alignment across 1M, 3M, and momentum
RS is Key: Sectors outperforming SPY (RS >0) tend to continue outperforming
Acceleration Matters: Positive acceleration often precedes price breakouts
Flow Transitions: "WATCH" → "TURN" → "IN" progression identifies new trends early
Regular Scans:
Daily: Check "Acceleration" sort
Weekly: Review "1M Change"
Monthly: Analyze "RS" shifts
Divergence Signals:
Price up but Acceleration down = Potential top
Price down but Acceleration up = Potential bottom
Sector Pairs Trading: Long sectors with "IN" flow, short sectors with "OUT" flow
⚠️ Important Notes
This indicator makes 40 security requests (maximum allowed)
Best used on Daily timeframe
Data updates in real-time during market hours
Some ETFs may show "—" if data is unavailable
🎯 Common Strategies
"Follow the Flow"
Only trade sectors showing "IN" flow with positive RS
"Rotation Catcher"
Focus on "TURN" signals in sectors down >15% from highs
"Momentum Rider"
Trade top 3 sectors by Momentum score, exit when Acceleration turns negative
"Mean Reversion"
Buy sectors in bottom 20% by 3M performance when Δ1M improves
"Relative Strength Leader"
Maintain positions only in sectors with RS >5
Not financial advice - always do additional research
Stock Profit Calculator — Live Mode
## Overview
This Pine Script indicator calculates, in real time, the financial impact of a stock trade, including purchase/sale commissions, capital gains tax (CGT), and return on investment (ROI). It displays a compact table with key values and also calculates the breakeven price to see at what level the net P/L returns to zero.
---
## Inputs and customization
- **Number of shares:** `shares` defines the purchased quantity.
- **Purchase price:** `buyPrice` is the unit cost; the total purchase is calculated from this.
- **Live selling price:** `sellPrice = close` uses the last bar’s price for live valuation.
- **Fixed or percentage commissions:** `useFixedComm` selects the model.
- **Fixed:** `buyCommFixed`, `sellCommFixed`.
- **Percentage:** `buyCommPct`, `sellCommPct` (applied to notional value).
- **CGT rate:** `cgtRate` is the percentage rate, applied only in case of profit.
- **Table position:** `tablePosition` with predefined options.
- **Visual style:** `colTxt`, `colPos`, `colNeg`, `colBg`, `colHdr`, `colFrame` for text color, positive/negative P/L, background, header, and borders.
> Tip: if your broker uses minimum fees or composite fees, turn on “Use fixed commissions?” and enter the two fixed fees; otherwise, use the percentage model.
---
## Calculation logic
#### Purchase costs
- **Total purchase:**
\
- **Purchase commission:**
\
- **Net entry cost:**
\
#### Sale revenues
- **Total sale (with live price):**
\
- **Sale commission:**
\
- **Net exit revenue:**
\
#### P/L and taxes
- **Gross P/L:**
\
- **CGT (only on positive P/L):**
\
- **Net P/L:**
\
#### ROI
- **Percentage ROI on invested capital:**
\
#### Breakeven
- **Gross breakeven** shown in the table: the unit price that makes the net P/L exactly zero, including purchase cost and an estimate of the sale commission.
\
In the script, if commissions are fixed it adds the fixed sale fee; if percentage-based, the sale component is not included in this row (conservative approximation).
- **Breakeven with tax** (calculated but not shown):
\
Useful when you want the post-CGT result to be exactly zero. Not displayed in the table but ready for use.
> Note: CGT applies only on positive profits; near breakeven, the tax effect is null or only kicks in beyond a threshold. That’s why the script distinguishes between the “gross” and “with tax” versions.
---
## On-screen table
- **Displayed rows:**
- **Purchase:** total net entry cost (with commissions).
- **Sale:** total net exit revenue (with commissions).
- **Gross P/L:** difference between netSell and netBuy.
- **CGT:** estimated tax only if there’s a gain.
- **Net P/L:** P/L after taxes.
- **ROI (%):** percentage return on netBuy.
- **Breakeven:** gross unit breakeven price.
- **Conditional colors:**
- **P/L and ROI:** green for ≥ 0, red for < 0.
- **Headers and cells:** customizable via the color inputs.
- **Efficient refresh:** the table updates only on the last bar via `barstate.islast` to avoid unnecessary redraws.
---
## Behavior and performance
- **Overlay:** displayed on the price chart.
- **Persistent variable:** table is created once with `var table`.
- **Live price:** `sellPrice` follows the current `close`, making P/L, ROI, and breakeven dynamic.
---
## Limitations and suggestions
- **Commission model:** when using percentage commissions, the breakeven in the table doesn’t add the sale percentage fee in the “breakevenPrice” formula. For more precision, you could solve the equation including the percentage fee on exit.
- **Breakeven with tax:** `breakevenWithTax` is a linear estimate; near zero profit, tax may be null. You might choose to display it instead of, or alongside, the gross breakeven.
- **Precision and formatting:** values are shown with `format.mintick`. If the symbol has very small ticks, consider a custom format for better readability.
- **Edge cases:** ROI is undefined if `netBuy = 0` (unlikely in practice but good to note).
> Pro tip: if you want to show the breakeven with tax, add a “Breakeven (post-CGT)” row printing `breakevenWithTax`. If you prefer a single row, replace the shown value with the post-CGT one.
---
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.
Awesome Indicator# Moving Average Ribbon with ADR% - Complete Trading Indicator
## Overview
The **Moving Average Ribbon with ADR%** is a comprehensive technical analysis indicator that combines multiple analytical tools to provide traders with a complete picture of price trends, volatility, relative performance, and position sizing guidance. This multi-faceted indicator is designed for both swing and positional traders looking for data-driven entry and exit signals.
## Key Components
### 1. Moving Average Ribbon System
- **4 Customizable Moving Averages** with default periods: 13, 21, 55, and 189
- **Multiple MA Types**: SMA, EMA, SMMA (RMA), WMA, VWMA
- **Color-coded visualization** for easy trend identification
- **Flexible configuration** allowing users to modify periods, types, and colors
### 2. Average Daily Range Percentage (ADR%)
- Calculates the average daily volatility as a percentage
- Uses a 20-period simple moving average of (High/Low - 1) * 100
- Helps traders understand the stock's typical daily movement range
- Essential for position sizing and stop-loss placement
### 3. Volume Analysis (Up/Down Ratio)
- Analyzes volume distribution over the last 55 periods
- Calculates the ratio of volume on up days vs down days
- Provides insight into buying vs selling pressure
- Values > 1 indicate more buying volume, < 1 indicate more selling volume
### 4. Absolute Relative Strength (ARS)
- **Dual timeframe analysis** with customizable reference points
- **High ARS**: Performance relative to benchmark from a high reference point (default: Sep 27, 2024)
- **Low ARS**: Performance relative to benchmark from a low reference point (default: Apr 7, 2025)
- Uses NSE:NIFTY as default comparison symbol
- Color-coded display: Green for outperformance, Red for underperformance
### 5. Relative Performance Table
- **5 timeframes**: 1 Week, 1 Month, 3 Months, 6 Months, 1 Year
- Shows stock performance **relative to benchmark index**
- Formula: (Stock Return - Index Return) for each period
- **Color coding**:
- Lime: >5% outperformance
- Yellow: -5% to +5% relative performance
- Red: <-5% underperformance
### 6. Dynamic Position Allocation System
- **6-factor scoring system** based on price vs EMAs (21, 55, 189)
- Evaluates:
- Price above/below each EMA
- EMA alignment (21>55, 55>189, 21>189)
- **Allocation recommendations**:
- 100% allocation: Score = 6 (all bullish signals)
- 75% allocation: Score = 4
- 50% allocation: Score = 2
- 25% allocation: Score = 0
- 0% allocation: Score = -2, -4, -6 (bearish signals)
## Display Tables
### Performance Table (Top Right)
Shows relative performance vs benchmark across multiple timeframes with intuitive color coding for quick assessment.
### Metrics Table (Bottom Right)
Displays key statistics:
- **ADR%**: Average Daily Range percentage
- **U/D**: Up/Down volume ratio
- **Allocation%**: Recommended position size
- **High ARS%**: Relative strength from high reference
- **Low ARS%**: Relative strength from low reference
## How to Use This Indicator
### For Trend Analysis
1. **Moving Average Ribbon**: Look for price above ascending MAs for bullish trends
2. **MA Alignment**: Bullish when shorter MAs are above longer MAs
3. **Color coordination**: Use consistent color scheme for quick visual analysis
### For Entry/Exit Timing
1. **Performance Table**: Enter when showing consistent outperformance across timeframes
2. **Volume Analysis**: Confirm entries with U/D ratio > 1.5 for strong buying
3. **ARS Values**: Look for positive ARS readings for relative strength confirmation
### For Position Sizing
1. **Allocation System**: Use the recommended allocation percentage
2. **ADR% Consideration**: Adjust position size based on volatility
3. **Risk Management**: Lower allocation in high ADR% stocks
### For Risk Management
1. **ADR% for Stop Loss**: Set stops at 1-2x ADR% below entry
2. **Relative Performance**: Reduce positions when consistently underperforming
3. **Volume Confirmation**: Be cautious when U/D ratio deteriorates
## Best Practices
### Timeframe Recommendations
- **Intraday**: Use lower MA periods (5, 13, 21, 55)
- **Swing Trading**: Default settings work well (13, 21, 55, 189)
- **Position Trading**: Consider higher periods (21, 50, 100, 200)
### Market Conditions
- **Trending Markets**: Focus on MA alignment and relative performance
- **Sideways Markets**: Rely more on ADR% for range trading
- **Volatile Markets**: Reduce allocation percentage regardless of signals
### Customization Tips
1. Adjust reference dates for ARS calculation based on significant market events
2. Change comparison symbol to sector-specific indices for better relative analysis
3. Modify MA periods based on your trading style and market characteristics
## Technical Specifications
- **Version**: Pine Script v6
- **Overlay**: Yes (plots on price chart)
- **Real-time Updates**: Yes
- **Data Requirements**: Minimum 252 bars for complete calculations
- **Compatible Timeframes**: All standard timeframes
## Limitations
- Performance calculations require sufficient historical data
- ARS calculations depend on selected reference dates
- Volume analysis may be less reliable in low-volume stocks
- Relative performance is only as good as the chosen benchmark
This indicator is designed to provide a comprehensive analysis framework rather than simple buy/sell signals. It's recommended to use this in conjunction with your overall trading strategy and risk management rules.
MNQ Contract Size CalculatorSimple drag and drop contract size calculator for MNQ. Uses variables for half risk ($100) and full risk ($200) to adjust your contract size. Perfect for 50k funded accounts.
LANZ Strategy 6.0🔷 LANZ Strategy 6.0 — NY Session Entry Tool & Multi-Account Risk Manager
LANZ Strategy 6.0 - Is a trading tool designed to help traders plan, execute, and manage operations with a focus on risk management, multi-account handling, and visual clarity.
It works exclusively on the 1-hour timeframe ⏳ and is optimized for the New York market opening dynamics.
🧠 Core Concept
The strategy identifies bullish trading opportunities based on the 09:00 NY candle. Once detected, it automatically calculates and draws:
EP (Entry Price) — The exact level where the trade setup triggers.
SL (Stop Loss) — Based on a customizable percentage of the candle's high–low range or wick extremes.
TP (Take Profit) — Calculated using your chosen Risk–Reward Ratio (e.g., 1:5, 1:3, etc.).
⚙️ Main Features
⏳ Time-Specific Execution
Operates only when the 09:00 NY candle closes bullish.
Ideal for traders who align with the New York Session market structure.
💰 Multi-Account Lot Size Management
Up to 5 independent accounts can be configured with their own capital and risk %, showing the exact lot size to use for each.
📏 Adaptive Risk Control
Supports both Forex and non-Forex assets (indices, gold, oil).
For non-Forex, you can manually define the pip value according to your broker’s specs.
🎨 Visual Trade Map
Automatically plots clean and easy-to-read EP, SL, and TP lines with customizable colors, styles, and thickness.
A floating information panel displays levels, pip distances, and lot sizes.
🔔 Real-Time Alerts
Alerts for:
Entry signal detection.
Stop Loss hit.
Take Profit hit.
Manual close at the defined session end.
📊 Example
If you trade GBPUSD with Account #1 set to $10,000 and 2% risk,
and the 09:00 NY candle closes bullish with SL = 30 pips and RR = 5:1:
EP, SL, and TP levels are drawn instantly.
Risk = $200 (2% of $10,000).
Lot size is calculated automatically.
All details are shown in the on-chart panel.
🛠️ How to Use
Load the indicator on a 1-hour chart.
Configure risk settings and account data.
Wait for the 09:00 NY candle to close bullish.
Use the displayed lot size and levels to execute your trade.
Let the tool alert you for SL, TP, or manual close.
⚠️ Disclaimer:
This script is for educational purposes only. It does not guarantee profits and past performance does not represent future results. Always manage your risk responsibly.
👨💻 Credits:
💡 Developed by: LANZ
🧠 Execution Model & Logic Design: LANZ
📅 Designed for: 1H timeframe and NY-based entries
