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RRE ZonesLine Creation: Each FVG box now has a corresponding dashed line drawn through its center: Uses a dashed style for clear visibility Matches the FVG color (with 30% transparency) Extends to the right like the box Width of 1 pixel Synchronized Cleanup: When FVG boxes are removed (either by reaching max count or being filled by price), their corresponding center lines are also deleted automatically. The center lines help you: Quickly identify the 50% level of each FVG Use it as a potential target or entry level Better visualize the gap's midpoint for trading decisions
อินดิเคเตอร์ Pine Script®
โดย ramrajenterprises
2
Previous Day Week Month Highs & Lows [MHA Finverse]Previous Day Week Month Highs & Lows is a comprehensive multi-timeframe indicator that automatically plots previous period highs and lows across Daily, Weekly, Monthly, 4-Hour, and 8-Hour timeframes. Perfect for identifying key support and resistance levels that often act as magnets for price action. How It Works The indicator retrieves the highest high and lowest low from the previous completed period for each selected timeframe. Lines extend forward into current price action, allowing you to see when price approaches or breaks these critical levels in real-time. The indicator tracks the exact bar where each high and low occurred, ensuring accurate historical placement. --- Key Features Multi-Timeframe Levels: • Current Daily, Previous Daily, 4H, 8H, Weekly, and Monthly highs/lows • Fully customizable colors and line styles (Solid, Dashed, Dotted) • Adjustable line width and extension length Visual Enhancements: • Price labels showing exact level values • Range position percentage (distance from high/low) • Optional period boxes highlighting timeframe ranges • Day and date labels for reference Trading Tools: • Breakout markers when price crosses key levels • Touch count tracking (how many times price tested each level) • Time at level display (consolidation detection) • Customizable thresholds for touch and time analysis Alert System: • Individual alerts for each timeframe: Daily High/Low Break, 4H High/Low Break, 8H High/Low Break, Weekly High/Low Break, Monthly High/Low Break • Toggle switches to enable/disable alerts per timeframe • Clear messages showing which level was broken and at what price --- How to Use Setup: 1. Enable your preferred timeframes in "Highs & Lows MTF" settings 2. Customize colors and styles to match your chart 3. Turn on visual features like price labels and range percentages 4. Set up alerts by creating specific alert conditions or using toggle switches Trading Applications: Breakout Trading: Watch for strong momentum when price breaks above previous highs or below previous lows Support/Resistance: Use these levels as potential reversal points for entry/exit signals Range Trading: Trade between previous highs and lows using the range position indicator Stop Loss Placement: Place stops just beyond previous highs (shorts) or lows (longs) Multiple Timeframe Confirmation: Combine timeframes for stronger signals (e.g., Daily near Weekly support) --- Best Practices • Use Weekly/Monthly for swing trading, Daily/4H/8H for day trading • Combine with volume or momentum indicators for confirmation • Multiple timeframe levels clustering together create high-probability zones • The more touches a level has, the more significant it becomes --- Disclaimer This indicator is a technical analysis tool for identifying price levels based on historical data. It does not guarantee profits or predict future movements. Trading involves substantial risk. Always use proper risk management and never risk more than you can afford to lose.
อินดิเคเตอร์ Pine Script®
โดย humayunmha
4
Multi-MA + RSI Pullback Strategy (Jordan)1️⃣ Strategy logic I’ll code From your screenshots: Indicators • EMAs: 600 / 200 / 100 / 50 • RSI: length 6, levels 80 / 20 Rules (simplified so a script can handle them): • Use a higher-timeframe trend filter (15m or 1h) using the EMAs. • Take entries on the chart timeframe (you can use 1m or 5m). • Long: • Higher-TF trend is up. • Price is pulling back into a zone (between 50 EMA and 100 EMA on the entry timeframe – this approximates your 50–61% retrace). • RSI crosses below 20 (oversold). • Short: • Higher-TF trend is down. • Price pulls back between 50 & 100 EMAs. • RSI crosses above 80 (overbought). • Exits: ATR-based stop + take-profit with adjustable R:R (2:1 or 3:1). • Max 4 trades per day. News filter & “only trade gold” you handle manually (run it on XAUUSD and avoid news times yourself – TradingView can’t read the economic calendar from code).
กลยุทธ์ Pine Script®
โดย jordana4r79
Quality Detector (Buffett Style) + Beta [Solid]This indicator acts as an on-chart fundamental screener, designed to instantly evaluate the quality and financial health of a company directly on your price chart. The concept is inspired by "Buffettology" principles: looking for large, profitable companies with low debt. Additionally, it includes a Beta calculation to assess market volatility risk. The tool displays a panel in the bottom-right corner featuring four key metrics and a final verdict. How it Works & Metrics Used The script retrieves quarterly fundamental data ("FQ") and performs calculations to verify if the asset meets specific criteria. 1. Market Cap (Size) What it is: The total market value of the company's outstanding shares. Goal: To identify established, large-cap companies. Default Threshold: Must be greater than $10 Billion. 2. ROE - Return on Equity (Quality) What it is: A measure of financial performance calculated by dividing net income by shareholders' equity. Goal: To find companies that are efficient at generating profits from shareholders' capital. Default Threshold: Must be higher than 15%. 3. Total Debt to Equity (Health) What it is: A ratio indicating the relative proportion of shareholders' equity and debt used to finance a company's assets. Calculation: This script manually calculates this ratio by fetching TOTAL_DEBT and dividing it by TOTAL_EQUITY from fundamental data to ensure robustness across different symbols. Goal: To ensure the company is not overly leveraged. Default Threshold: Must be lower than 1.5. 4. Beta (Risk/Volatility) What it is: A measure of a stock's volatility in relation to the overall market (S&P 500). Calculation: It is calculated by comparing the asset's returns against SPY (S&P 500 ETF) returns over a 252-day period (approx. 1 trading year). Goal: To understand if the stock is more volatile (Beta > 1) or less volatile (Beta < 1) than the market. Note: Beta does not affect the final "Quality" score but serves as an extra risk indicator, highlighting in orange if Beta > 1. The Verdict (Scoring System) The indicator assigns a score from 0 to 3 based on the first three fundamental metrics (Size, ROE, and Debt/Equity). If a metric passes the threshold, it gets a green background and +1 point. If it fails, it gets a red background. Final Verdict: 💎 QUALITY GEM: The company passed all 3 fundamental checks (Score = 3/3). ⚠️ DISCARD: The company failed one or more fundamental checks. Settings You can customize the thresholds to fit your own investment strategy in the indicator settings: Minimum Market Cap (in Billions). Minimum ROE (%). Maximum Debt/Equity Ratio. Disclaimer: This tool is for informational and educational purposes only. It relies on third-party fundamental data which may sometimes be delayed or unavailable. Do not base investment decisions solely on this indicator.
อินดิเคเตอร์ Pine Script®
โดย MrOskama
Strategia S&P 500 vs US10Y YieldThis strategy explores the macroeconomic relationship between the equity market (S&P 500) and the debt market (10-Year Treasury Yield). Historically, rapid spikes in bond yields often exert downward pressure on equity valuations, leading to corrections or bear markets. The goal of this strategy is capital preservation. It attempts to switch to cash when yields are rising too aggressively and re-enter the stock market when the bond market stabilizes.
กลยุทธ์ Pine Script®
โดย adamniestoj
Elliott Wave Full Fractal System v2.0Elliott Wave Full Fractal System v2.0 – Q.C. FINAL (Guaranteed R/R) Elliott Wave Full Fractal System is a multi-timeframe wave engine that automatically labels Elliott impulses and ABC corrections, then builds a rule-based, ATR-driven risk/reward framework around the “W3–W4–W5” leg. “Guaranteed R/R” here means every order is placed with a predefined stop-loss and take-profit that respect a minimum Reward:Risk ratio – it does not mean guaranteed profits. Core Idea This strategy turns a full fractal Elliott Wave labelling engine into a systematic trading model. It scans fractal pivots on three wave degrees (Primary, Intermediate, Minor) to detect 5-wave impulses and ABC corrections. A separate “Trading Degree” pivot stream, filtered by a 200-EMA trend filter and ATR-based dynamic pivots, is then used to find W4 pullback entries with a minimum, user-defined Reward:Risk ratio. Default Properties & Risk Assumptions The backtest uses realistic but conservative defaults: // Default properties used for backtesting strategy( "Elliott Wave Full Fractal System - Q.C. FINAL (Guaranteed R/R)", overlay = true, initial_capital = 10000, // realistic account size default_qty_type = strategy.percent_of_equity, default_qty_value = 1, // 1% risk per trade commission_type = strategy.commission.cash_per_contract, commission_value = 0.005, // example stock commission slippage = 0 // see notes below ) Account size: 10,000 (can be changed to match your own account). Position sizing: 1% of equity per trade to keep risk per idea sustainable and aligned with TradingView’s recommendations. Commission: 0.005 cash per contract/share as a realistic example for stock trading. Slippage: set to 0 in code for clarity of “pure logic” backtesting. Real-life trading will experience slippage, so users should adjust this according to their market and broker. Always re-run the backtest after changing any of these values, and avoid using high risk fractions (5–10%+) as that is rarely sustainable. 1. Full Fractal Wave Engine The script builds and maintains four pivot streams using ATR-adaptive fractals: Primary Degree (Macro Trend): Captures the large swings that define the major trend. Labels ①–⑤ and ⒶⒷⒸ using blue “Circle” labels and thicker lines. Intermediate Degree (Trading Degree): Captures the medium swings (swing-trading horizon). Uses teal labels ( (1)…(5), (A)(B)(C) ). Minor Degree (Micro Structure): Tracks short-term swings inside the larger waves. Uses red roman numerals (i…v, a b c). ABC Corrections (Optional): When enabled, the engine tries to detect standard A–B–C corrective structures that follow a completed 5-wave impulse and plots them with dashed lines. Each degree uses a dynamic pivot lookback that expands when ATR is above its EMA, so the system naturally requires “stronger” pivots in volatile environments and reacts faster in quiet conditions. 2. Theory Rules & Strict Mode Normal Mode: More permissive detection. Designed to show more wave structures for educational / exploratory use. Strict Mode: Enforces key Elliott constraints: Wave 3 not shorter than waves 1 and 5. No invalid W4 overlap with W1 (for standard impulses). ABC Logic: After a confirmed bullish impulse, the script expects a down-up-down corrective pattern (A,B,C). After a bearish impulse, it looks for up-down-up. 3. Trend Filter & Pivots EMA Trend Filter: A configurable EMA (default 200) is used as a non-wave trend filter. Price above EMA → Only long setups are considered. Price below EMA → Only short setups are considered. ATR-Adaptive Pivots: The pivot engine scales its left/right bars based on current ATR vs ATR EMA, making waves and trading pivots more robust in volatile regimes. 4. Dynamic Risk Management (Guaranteed R/R Engine) The trading engine is designed around risk, not just pattern recognition: ATR-Based Stop: Stop-loss is placed at: Entry ± ATR × Multiplier (user-configurable, default 2.0). This anchors risk to current volatility. Minimum Reward:Risk Ratio: For each setup, the script: Computes the distance from entry to stop (risk). Projects a take-profit target at risk × min_rr_ratio away from entry. Only accepts the setup if risk is positive and the required R:R ratio is achievable. Result: Every order is created with both TP and SL at a predefined distance, so each trade starts with a known, minimum Reward:Risk profile by design. “Guaranteed R/R” refers exclusively to this order placement logic (TP/SL geometry), not to win-rate or profitability. 5. Trading Logic – W3–W4–W5 Pattern The Trading pivot stream (separate from visual wave degrees) looks for a simple but powerful pattern: Bullish structure: Sequence of pivots forms a higher-high / higher-low pattern. Price is above the EMA trend filter. A strong “W3” leg is confirmed with structure rules (optionally stricter in Strict mode). Entry (Long – W4 Pullback): The “height” of W3 is measured. Entry is placed at a configurable Fibonacci pullback (default 50%) inside that leg. ATR-based stop is placed below entry. Take-profit is projected to satisfy min Reward:Risk. Bearish structure: Mirrored logic (lower highs/lows, price below EMA, W3 down, W4 retrace up, W5 continuation down). Once a valid setup is found, the script draws a colored box around the entry zone and a label describing the type of signal (“LONG SETUP” or “SHORT SETUP”) with the suggested limit price. 6. Orders & Execution Entry Orders: The strategy uses limit orders at the computed W4 level (“Sniper Long” or “Sniper Short”). Exits: A single strategy.exit() is attached to each entry with: Take-profit at the projected minimum R:R target. Stop-loss at ATR-based level. One Trade at a Time: New setups are only used when there is no open position (strategy.opentrades == 0) to keep the logic clear and risk contained. 7. Visual Guide on the Chart Wave Labels: Primary: ①,②,③,④,⑤, ⒶⒷⒸ Intermediate: (1)…(5), (A)(B)(C) Minor: i…v, a b c Trend EMA: Single blue EMA showing the dominant trend. Setup Boxes: Green transparent box → long entry zone. Red transparent box → short entry zone. Labels: “LONG SETUP / SHORT SETUP” labels mark the proposed limit entry with price. 8. How to Use This Strategy Attach the strategy to your chart Choose your market (stocks, indices, FX, crypto, futures, etc.) and timeframe (for example 1h, 4h, or Daily). Then add the strategy to the chart from your Scripts list. Start with the default settings Leave all inputs on their defaults first. This lets you see the “intended” behaviour and the exact properties used for the published backtest (account size, 1% risk, commission, etc.). Study the wave map Zoom in and out and look at the three wave degrees: Blue circles → Primary degree (big picture trend). Teal (1)…(5) → Intermediate degree (swing structure). Red i…v → Minor degree (micro waves). Use this to understand how the engine is interpreting the Elliott structure on your symbol. Watch for valid setups Look for the coloured boxes and labels: Green box + “LONG SETUP” label → potential W4 pullback long in an uptrend. Red box + “SHORT SETUP” label → potential W4 pullback short in a downtrend. Only trades in the direction of the EMA trend filter are allowed by the strategy. Check the Reward:Risk of each idea For each setup, inspect: Limit entry price. ATR-based stop level. Projected take-profit level. Make sure the minimum Reward:Risk ratio matches your own rules before you consider trading it. Backtest and evaluate Open the Strategy Tester: Verify you have a decent sample size (ideally 100+ trades). Check drawdowns, average trade, win-rate and R:R distribution. Change markets and timeframes to see where the logic behaves best. Adapt to your own risk profile If you plan to use it live: Set Initial Capital to your real account size. Adjust default_qty_value to a risk level you are comfortable with (often 0.5–2% per trade). Set commission and slippage to realistic broker values. Re-run the backtest after every major change. Use as a framework, not a signal machine Treat this as a structured Elliott/R:R framework: Filter signals by higher-timeframe trend, major S/R, volume, or fundamentals. Optionally hide some wave degrees or ABC labels if you want a cleaner chart. Combine the system’s structure with your own trade management and discretion. Best Practices & Limitations This is an approximate Elliott Wave engine based on fractal pivots. It does not replace a full discretionary Elliott analysis. All wave counts are algorithmic and can differ from a manual analyst’s interpretation. Like any backtest, results depend heavily on: Symbol and timeframe. Sample size (more trades are better). Realistic commission/slippage settings. The 0-slippage default is chosen only to show the “raw logic”. In real markets, slippage can significantly impact performance. No strategy wins all the time. Losing streaks and drawdowns will still occur even with a strict R:R framework. Disclaimer This script is for educational and research purposes only and does not constitute financial advice or a recommendation to buy or sell any security. Past performance, whether real or simulated, is not indicative of future results. Always test on multiple symbols/timeframes, use conservative risk, and consult your financial advisor before trading live capital.
กลยุทธ์ Pine Script®
โดย mbedaiwi2
MTF Switch Level (Single TF)Multi-timeframe Switch Level (Single TF) This indicator marks the most recent “switch level” created by breakout / breakdown behaviour on the current timeframe. How it works – After a bullish breakout (close above the previous bar’s high), the script sets a bearish switch level at that previous high. – After a bearish breakdown (close below the previous bar’s low), it sets a bullish switch level at that previous low. – A single horizontal line extends from the latest switch level. – The line and “S” label turn bullish when price is above the level and bearish when price is below it. – Optional alerts fire when price crosses the active switch level. Use-cases – Visualise where breakout traders are likely trapped. – Define a simple “above = bullish / below = bearish” bias line. – Combine with higher-timeframe analysis or other tools for context. Inputs – Enable/disable bullish and bearish switch conditions. – Line length, colour, style, thickness. – Label position and offsets. – Alert conditions for crosses. Disclaimer This tool is for charting and educational purposes only and is not financial advice or a signal service. Always do your own research and risk management.
อินดิเคเตอร์ Pine Script®
โดย TRADE_the_ORB
Continuation Model by XausThis report summarizes the historical performance of the Institutional Daily Bias Probability Model on EURUSD daily data for the 2025 calendar year. The model combines three components: 1. Continuation bias around the previous day's high/low (PDH/PDL). 2. Reversal bias based on failed continuation, failed breakouts, and exhaustion. 3. Neutral bias to identify liquidity-building days when no directional trades should be taken. A fixed 25-pip stop loss (0.0025) is assumed for R-multiple calculations. Trades are only taken when Neutral score < 50 and either Continuation or Reversal score is at least 70, with Neutral overriding, then Reversal, then Continuation.
อินดิเคเตอร์ Pine Script®
โดย CCRafael46
FOMC Federal Fund Rate Tracker [MHA Finverse]The FOMC Rate Tracker is a comprehensive indicator that visualizes Federal Reserve interest rate decisions and tracks market behavior during FOMC meeting periods. This tool helps traders analyze historical rate changes and anticipate market movements around Federal Open Market Committee announcements. Key Features: • Visual FOMC Periods - Automatically highlights each FOMC meeting period with colored boxes spanning from announcement to the next meeting • Complete Rate Data - Displays actual rates, forecasts, previous rates, and rate differences for every meeting from 2021-2026 • Multiple Color Modes - Choose between cycle colors for visual distinction or rate difference colors (green for hikes, red for cuts, gray for holds) • Smart Filtering - Filter periods by rate hikes only, cuts only, no change, or surprise moves to focus on specific market conditions • Performance Metrics - Track average returns during rate hikes, cuts, and holds to identify historical patterns • Volatility Analysis - Measure and compare price volatility across different FOMC periods • Statistical Dashboard - View total hikes, cuts, holds, surprises, and longest hold streaks at a glance • Built-in Alerts - Get notified 1 day before FOMC meetings, on meeting day, or when rates change How It Works: The indicator divides your chart into distinct periods between FOMC meetings, with each period showing a labeled box containing the meeting date, actual rate, forecast, previous rate, and rate difference. Future meetings are marked as "UPCOMING" to help you prepare for scheduled announcements. Use Cases: - Analyze how markets typically react to rate hikes vs. cuts - Identify volatility patterns around FOMC announcements - Backtest strategies based on monetary policy cycles - Plan trades around upcoming Federal Reserve meetings - Study the impact of surprise rate decisions on price action Customization Options: - Adjustable box transparency and outlines - Customizable label sizes and colors - Toggle individual dashboards on/off - Filter specific types of rate decisions - Configure alert preferences This indicator is ideal for traders who incorporate fundamental analysis and monetary policy into their trading decisions. The historical data provides context for understanding market reactions to Federal Reserve actions.
อินดิเคเตอร์ Pine Script®
โดย humayunmha
1
15 min Trailstop15m High/Low Liquidity Lines (1m) — Indicator Description 15m High/Low Liquidity Lines (1m) is a precision liquidity-mapping tool designed for intraday traders who understand the importance of higher-timeframe liquidity levels while executing on the 1-minute chart. This indicator automatically detects confirmed 15-minute swing highs and swing lows using pivot logic. When a new 15m high or low forms: ✔ Liquidity Line Generation A horizontal line is drawn exactly at the price level of the pivot. The line is anchored to the exact 1-minute candle that produced the 15m high/low, ensuring perfect visual alignment. The line extends only up to the current bar — not across the whole chart. Optional text labels (“15m High”, “15m Low”) can be shown at the start of each line. ✔ Auto-Cleanup (Smart Liquidity Sweep Detection) If price trades through the level, the corresponding line and label are: Instantly deleted Marking the level as taken/swept Allowing the chart to stay clean and focused on active liquidity only This mimics institutional liquidity logic: once the high or low is violated, the target is considered filled and removed. ✔ Alerts The indicator includes built-in alerts that fire when: A new 15m high is confirmed A new 15m low is confirmed This allows the trader to react immediately when fresh liquidity levels appear. ✔ Customization Options You can fully tailor the visual representation: Turn highs and/or lows on or off Choose line style (solid, dashed, dotted) Customize line color and thickness Customize the label style, size, and transparency Who Is This For? This indicator is ideal for: ICT-style traders Liquidity-based scalpers 1-minute ES/NQ traders Anyone who uses HTF liquidity levels to frame trades on the LTF It provides a clean, automated method to track active 15-minute liquidity levels directly on the 1-minute chart with zero clutter and perfect alignment.
อินดิเคเตอร์ Pine Script®
โดย alexnyabeze
1
Stage 2 Pullback Swing indicatorThis scanner is built for swing traders who want high-probability pullbacks inside strong, established uptrends. It targets names in a confirmed Stage 2 bull phase (Weinstein model) that have pulled back 10–30% from a recent swing high on light selling volume, while still respecting fast EMAs. Goal: find powerful uptrending stocks during controlled dips before the next leg higher. What it looks for Strong prior uptrend: price above the 50 and 200 SMAs, momentum positive over multiple timeframes Confirmed Stage 2: price above a rising 30-week MA on the weekly chart Pullback depth: 10–30% off recent swing highs—not too shallow, not broken Pullback quality: range contained, no panic selling, trend structure intact EMA behavior: price near EMA10 or EMA20 at signal time Volume contraction: sellers fading throughout the pullback Bullish shift: green candle back in trend direction Why this matters This setup hints at institutions defending positions during a temporary dip. Strong stocks pull back cleanly with declining volume, then resume the primary trend. This script alerts you when those conditions align. Best way to use Filter a strong universe before applying—quality tickers only Pair with clear trade plans: risk defined by prior swing low or ATR Trigger alerts instead of hunting charts manually Intended for Swing traders who want momentum continuation setups Traders who prefer entering on controlled retracements Anyone tired of chasing extended breakouts
อินดิเคเตอร์ Pine Script®
โดย tanveeralims
ALT Risk Metric StrategyHere's a professional write-up for your ALT Risk Strategy script: ALT/BTC Risk Strategy - Multi-Crypto DCA with Bitcoin Correlation Analysis Overview This strategy uses Bitcoin correlation as a risk indicator to time entries and exits for altcoins. By analyzing how your chosen altcoin performs relative to Bitcoin, the strategy identifies optimal accumulation periods (when alt/BTC is oversold) and profit-taking opportunities (when alt/BTC is overbought). Perfect for traders who want to outperform Bitcoin by strategically timing altcoin positions. Key Innovation: Why Alt/BTC Matters Most traders focus solely on USD price, but Alt/BTC ratios reveal true altcoin strength: When Alt/BTC is low → Altcoin is undervalued relative to Bitcoin (buy opportunity) When Alt/BTC is high → Altcoin has outperformed Bitcoin (take profits) This approach captures the rotation between BTC and alts that drives crypto cycles Key Features 📊 Advanced Technical Analysis RSI (60% weight): Primary momentum indicator on weekly timeframe Long-term MA Deviation (35% weight): Measures distance from 150-period baseline MACD (5% weight): Minor confirmation signal EMA Smoothing: Filters noise while maintaining responsiveness All calculations performed on Alt/BTC pairs for superior market timing 💰 3-Tier DCA System Level 1 (Risk ≤ 70): Conservative entry, base allocation Level 2 (Risk ≤ 50): Increased allocation, strong opportunity Level 3 (Risk ≤ 30): Maximum allocation, extreme undervaluation Continuous buying: Executes every bar while below threshold for true DCA behavior Cumulative sizing: L3 triggers = L1 + L2 + L3 amounts combined 📈 Smart Profit Management Sequential selling: Must complete L1 before L2, L2 before L3 Percentage-based exits: Sell portions of position, not fixed amounts Auto-reset on re-entry: New buy signals reset sell progression Prevents premature full exits during volatile conditions 🤖 3Commas Automation Pre-configured JSON webhooks for Custom Signal Bots Multi-exchange support: Binance, Coinbase, Kraken, Bitfinex, Bybit Flexible quote currency: USD, USDT, or BUSD Dynamic order sizing: Automatically adjusts to your tier thresholds Full webhook documentation compliance 🎨 Multi-Asset Support Pre-configured for popular altcoins: ETH (Ethereum) SOL (Solana) ADA (Cardano) LINK (Chainlink) UNI (Uniswap) XRP (Ripple) DOGE RENDER Custom option for any other crypto How It Works Risk Metric Calculation (0-100 scale): Fetches weekly Alt/BTC price data for stability Calculates RSI, MACD, and deviation from 150-period MA Normalizes MACD to 0-100 range using 500-bar lookback Combines weighted components: (MACD × 0.05) + (RSI × 0.60) + (Deviation × 0.35) Applies 5-period EMA smoothing for cleaner signals Color-Coded Risk Zones: Green (0-30): Extreme buying opportunity - Alt heavily oversold vs BTC Lime/Yellow (30-70): Accumulation range - favorable risk/reward Orange (70-85): Caution zone - consider taking initial profits Red/Maroon (85-100+): Euphoria zone - aggressive profit-taking Entry Logic: Buys execute every candle when risk is below threshold As risk decreases, position sizing automatically scales up Example: If risk drops from 60→25, you'll be buying at L1 rate until it hits 50, then L2 rate, then L3 rate Exit Logic: Sells only trigger when in profit AND risk exceeds thresholds Sequential execution ensures partial profit-taking If new buy signal occurs before all sells complete, sell levels reset to L1 Configuration Guide Choosing Your Altcoin: Select crypto from dropdown (or use CUSTOM for unlisted coins) Pick your exchange Choose quote currency (USD, USDT, BUSD) Risk Metric Tuning: Long Term MA (default 150): Higher = more extreme signals, Lower = more frequent RSI Length (default 10): Lower = more volatile, Higher = smoother Smoothing (default 5): Increase for less noise, decrease for faster reaction Buy Settings (Aggressive DCA Example): L1 Threshold: 70 | Amount: $5 L2 Threshold: 50 | Amount: $6 L3 Threshold: 30 | Amount: $7 Total L3 buy = $18 per candle when deeply oversold Sell Settings (Balanced Exit Example): L1: 70 threshold, 25% position L2: 85 threshold, 35% position L3: 100 threshold, 40% position (final exit) 3Commas Setup Bot Configuration: Create Custom Signal Bot in 3Commas Set trading pair to your altcoin/USD (e.g., ETH/USD, SOL/USDT) Order size: Select "Send in webhook, quote" to use strategy's dollar amounts Copy Bot UUID and Secret Token Script Configuration: Paste credentials into 3Commas section inputs Check "Enable 3Commas Alerts" Save and apply to chart TradingView Alert: Create Alert → Condition: "alert() function calls only" Webhook URL: api.3commas.io Enable "Webhook URL" checkbox Expiration: Open-ended Strategy Advantages ✅ Outperform Bitcoin: Designed specifically to beat BTC by timing alt rotations ✅ Capture Alt Seasons: Automatically accumulates when alts lag, sells when they pump ✅ Risk-Adjusted Sizing: Buys more when cheaper (better risk/reward) ✅ Emotional Discipline: Systematic approach removes fear and FOMO ✅ Multi-Asset: Run same strategy across multiple altcoins simultaneously ✅ Proven Indicators: Combines RSI, MACD, and MA deviation - battle-tested tools Backtesting Insights Optimal Timeframes: Daily chart: Best for backtesting and signal generation Weekly data is fetched internally regardless of display timeframe Historical Performance Characteristics: Accumulates heavily during bear markets and BTC dominance periods Captures explosive altcoin rallies when BTC stagnates Sequential selling preserves capital during extended downtrends Works best on established altcoins with multi-year history Risk Considerations: Requires capital reserves for extended accumulation periods Some altcoins may never recover if fundamentals deteriorate Past correlation patterns may not predict future performance Always size positions according to personal risk tolerance Visual Interface Indicator Panel Displays: Dynamic color line: Green→Lime→Yellow→Orange→Red as risk increases Horizontal threshold lines: Dashed lines mark your buy/sell levels Entry/Exit labels: Green labels for buys, Orange/Red/Maroon for sells Real-time risk value: Numerical display on price scale Customization: All threshold lines are adjustable via inputs Color scheme clearly differentiates buy zones (green spectrum) from sell zones (red spectrum) Line weights emphasize most extreme thresholds (L3 buy and L3 sell) Strategy Philosophy This strategy is built on the principle that altcoins move in cycles relative to Bitcoin. During Bitcoin rallies, alts often bleed against BTC (high sell, accumulate). When Bitcoin consolidates, alts pump (take profits). By measuring risk on the Alt/BTC chart instead of USD price, we time these rotations with precision. The 3-tier system ensures you're always averaging in at better prices and scaling out at better prices, maximizing your Bitcoin-denominated returns. Advanced Tips Multi-Bot Strategy: Run this on 5-10 different altcoins simultaneously to: Diversify correlation risk Capture whichever alt is pumping Smooth equity curve through rotation Pairing with BTC Strategy: Use alongside the BTC DCA Risk Strategy for complete portfolio coverage: BTC strategy for core holdings ALT strategies for alpha generation Rebalance between them based on BTC dominance Threshold Calibration: Check 2-3 years of historical data for your chosen alt Note where risk metric sat during major bottoms (set buy thresholds) Note where it peaked during euphoria (set sell thresholds) Adjust for your risk tolerance and holding period Credits Strategy Development & 3Commas Integration: Claude AI (Anthropic) Technical Analysis Framework: RSI, MACD, Moving Average theory Implementation: pommesUNDwurst Disclaimer This strategy is for educational purposes only. Cryptocurrency trading involves substantial risk of loss. Altcoins are especially volatile and many fail completely. The strategy assumes liquid markets and reliable Alt/BTC price data. Always do your own research, understand the fundamentals of any asset you trade, and never risk more than you can afford to lose. Past performance does not guarantee future results. The authors are not financial advisors and assume no liability for trading decisions. Additional Warning: Using leverage or trading illiquid altcoins amplifies risk significantly. This strategy is designed for spot trading of established cryptocurrencies with deep liquidity. Tags: Altcoin, Alt/BTC, DCA, Risk Metric, Dollar Cost Averaging, 3Commas, ETH, SOL, Crypto Rotation, Bitcoin Correlation, Automated Trading, Alt Season Feel free to modify any sections to better match your style or add specific backtesting results you've observed! 🚀Claude is AI and can make mistakes. Please double-check responses. Sonnet 4.5
กลยุทธ์ Pine Script®
โดย nakphanan
BTC DCA Risk Metric StrategyBTC DCA Risk Strategy - Automated Dollar Cost Averaging with 3Commas Integration Overview This strategy combines the proven Oakley Wood Risk Metric with an intelligent tiered Dollar Cost Averaging (DCA) system, designed to help traders systematically accumulate Bitcoin during periods of low risk and take profits during high-risk conditions. Key Features 📊 Multi-Component Risk Assessment 4-Year SMA Deviation: Measures Bitcoin's distance from its long-term mean 20-Week MA Analysis: Tracks medium-term momentum shifts 50-Day/50-Week MA Ratio: Captures short-to-medium term trend strength All metrics are normalized by time to account for Bitcoin's maturing market dynamics 💰 3-Tier DCA Buy System Level 1 (Low Risk): Conservative entry with base allocation Level 2 (Lower Risk): Increased allocation as opportunity improves Level 3 (Extreme Low Risk): Maximum allocation during rare buying opportunities Buys execute every bar while risk remains below thresholds, enabling true DCA accumulation 📈 Progressive Profit Taking Sell Level 1: Take initial profits as risk increases Sell Level 2: Scale out further positions during elevated risk Sell Level 3: Final exit during extreme market conditions Sell levels automatically reset when new buy signals occur, allowing flexible re-entry 🤖 3Commas Integration Fully automated webhook alerts for Custom Signal Bots JSON payloads formatted per 3Commas API specifications Supports multiple exchanges (Binance, Coinbase, Kraken, Gemini, Bybit) Configurable quote currency (USD, USDT, BUSD) How It Works The strategy calculates a composite risk metric (0-1 scale): 0.0-0.2: Extreme buying opportunity (green zone) 0.2-0.5: Favorable accumulation range (yellow zone) 0.5-0.8: Neutral to cautious territory (orange zone) 0.8-1.0+: High risk, profit-taking zone (red zone) Buy Logic: As risk decreases, position sizes increase automatically. If risk drops from L1 to L3 threshold, the strategy combines all three tier allocations for maximum exposure. Sell Logic: Sequential profit-taking ensures you capture gains progressively. The system won't advance to Sell L2 until L1 completes, preventing premature full exits. Configuration Risk Metric Parameters: All calculations use Bitcoin price data (any BTC chart works) Time-normalized formulas adapt to market maturity No manual parameter tuning required Buy Settings: Set risk thresholds for each tier (default: 0.20, 0.10, 0.00) Define dollar amounts per tier (default: $10, $15, $20) Fully customizable to your risk tolerance and capital Sell Settings: Configure risk thresholds for profit-taking (default: 1.00, 1.50, 2.00) Set percentage of position to sell at each level (default: 25%, 35%, 40%) 3Commas Setup: Create a Custom Signal Bot in 3Commas Copy Bot UUID and Secret Token into strategy inputs Enable 3Commas Alerts checkbox Create TradingView alert: Condition → "alert() function calls only", Webhook → api.3commas.io Backtesting Results Strengths: Systematically buys dips without emotion Averages down during extended bear markets Captures explosive bull run profits through tiered exits Pyramiding (1000 max orders) allows true DCA behavior Considerations: Requires sufficient capital for multiple buys during prolonged downtrends Backtest on Daily timeframe for most reliable signals Past performance does not guarantee future results Visual Design The indicator pane displays: Color-coded risk metric line: Changes from white→red→orange→yellow→green as risk decreases Background zones: Green (buy), yellow (hold), red (sell) areas Dashed threshold lines: Clear visual markers for each buy/sell level Entry/Exit labels: Green buy labels and orange/red sell labels mark all trades Credits Original Risk Metric: Oakley Wood Strategy Development & 3Commas Integration: Claude AI (Anthropic) Modifications: pommesUNDwurst Disclaimer This strategy is for educational and informational purposes only. Cryptocurrency trading carries substantial risk of loss. Always conduct your own research and never invest more than you can afford to lose. The authors are not financial advisors and assume no responsibility for trading decisions made using this tool.
กลยุทธ์ Pine Script®
โดย nakphanan
Macro Timing Window Signal ⏱️ Macro Timing Window Signal – Check/X Indicator This indicator displays a green check mark ✔️ or red X ✖️ in the top-right corner of the chart based on a repeating macro time cycle that divides every hour into active and inactive windows. How it works: • ✔️ Green Check (Active Macro Window): Appears from xx:45 → xx:15 of the next hour (30-minute macro window). • ✖️ Red X (Inactive Macro Window): Appears from xx:16 → xx:44 (mid-hour cooldown window). • Optional flash signal at the exact macro flip points (xx:45, xx:00, xx:15) to highlight transitions. • Supports sound alerts so you never miss the start or end of a macro window. This tool is designed for traders who incorporate macro-driven time cycles, liquidity sessions, or algorithmic delivery windows into their strategy. The display is fixed on-screen, clean, and unobtrusive, ensuring instant recognition of the current macro state without cluttering the chart.
อินดิเคเตอร์ Pine Script®
โดย chadp9
BTC - FRIC: Friction & Realized Intensity CompositeTitle: BTC - FRIC: Friction & Realized Intensity Composite Data: IntoTheBlock Overview & Philosophy FRIC (Friction & Realized Intensity Composite) is a specialized on-chain oscillator designed to visualize the "psychological battlegrounds" of the Bitcoin network. Most indicators focus on Price or Momentum. FRIC focuses on Cost Basis. It operates on the thesis that the market experiences maximum "Friction" when the price revisits the cost basis of a large number of holders. These are the zones where investors are emotionally triggered to react—either to exit "at breakeven" after a loss (creating resistance) or to defend their entry (creating support). This indicator answers two questions simultaneously: Intensity: Is the market hitting a Wall (High Friction) or a Vacuum (Low Friction)? Valuation: Is this happening at a market bottom or a top? The "Alpha" (Wall vs. Vacuum) Why we visualize both extremes: This indicator filters out the "Noise" (the middle range) to show you only the statistically significant anomalies. 1. The "Wall" (Positive Z-Score Bars) What it is : A statistically high number of addresses are at breakeven. The Implication : Expect a grind. Price action often slows down or reverses here because "Bag Holders" are selling into strength to get out flat, or new buyers are establishing a floor. 2. The "Vacuum" (Negative Z-Score Bars) What it is : A statistically low number of addresses are at breakeven. The Implication : Expect acceleration. The price is moving through a zone where very few people have a cost basis. With no natural "breakeven supply" to block the path, price often enters Price Discovery or Free Fall. Methodology The indicator constructs a composite view using two premium metrics from IntoTheBlock: 1. The "Activity" (Friction Z-Score): We utilize the Breakeven Addresses Percentage. This measures the % of all addresses where the current price equals the average cost basis. - Normalization: We apply a rolling Z-Score (Standard Deviation) to this data. - The Filter: We hide the "Noise" (e.g., Z-Scores between -2.0 and +2.0) to isolate only the events where market structure is truly stretched. 2. The "Context" (Valuation Heatmap): We utilize the MVRV Ratio to color-code the friction. Deep Value (< 1.0): Price is below the average "Fair Value" of the network. Overheated (> 3.0): Price is significantly extended above the "Fair Value." Credit: The MVRV Ratio was originally conceptualized by Murad Mahmudov and David Puell. It remains one of the gold standards for detecting Bitcoin's fair value deviations. How to Read the Indicator The chart is visualized as a Noise-Filtered Heatmap. 1. The Bars (Intensity) Bars Above Zero: High Friction (Congestion). The market is fighting through a supply wall. Bars Below Zero: Low Friction (Vacuum). The market is accelerating through thin air. Gray/Ghosted: Noise. Routine market activity; no significant signal. 2. The Colors (Valuation Context) The color tells you why the friction is happening: 🟦 Deep Blue (The "Capitulation Buy"): Signal: High Friction + Low MVRV. Meaning : Investors are panic-selling at breakeven/loss, but the asset is fundamentally undervalued. Historically, these are high-conviction cycle bottoms. 🟥 Dark Red (The "FOMO Sell"): Signal: High Friction + High MVRV. Meaning : Investors are churning at high valuations. Smart money is often distributing to late retail arrivers. Historically marks cycle tops. 🟨 Yellow/Orange (The "Trend Battle"): Signal: High Friction + Neutral MVRV. Meaning : The market is contesting a level within a trend (e.g., a mid-cycle correction). Visual Guide & Features 10-Zone Heatmap: A granular color gradient that shifts from Dark Blue (Deep Value) → Sky Blue → Grey (Neutral) → Orange → Dark Red (Top). Noise Filter A unique feature that "ghosts out" insignificant data, leaving only the statistically relevant signals visible. Data Check Monitor A diagnostic table in the bottom-right corner that confirms the live connection to IntoTheBlock data streams and displays the current regime in real-time. Settings Lookback Period (Default: 90): The rolling window used for the Z-Score calculation. Shortening this (e.g., to 30) makes the indicator more sensitive to local volatility; lengthening it (e.g., to 365) aligns it with macro cycles. Noise Threshold (Default: 2.0): The strictness of the filter. Only friction events exceeding this Z-Score will be highlighted in full color. Show Status Table : Toggles the on-screen dashboard. Disclaimer This script is for research and educational purposes only. It relies on third-party on-chain data which may be subject to latency or revision. Past performance of on-chain metrics does not guarantee future price action. Tags bitcoin, btc, on-chain, mvrv, intotheblock, friction, z-score, fundamental, valuation, cycle
อินดิเคเตอร์ Pine Script®
โดย Rob_Maths
FlowTrinity - Crypto Dominance Rotation IndexFlowTrinity — Crypto Dominance Rotation Index (Tracks BTC / Stablecoin / Altcoin dominance flows with standardized oscillators) ⚪ Overview FlowTrinity decomposes total crypto market structure into three capital-flow regimes — BTC dominance, Stablecoin dominance, and Altcoin dominance — each normalized into oscillator form. Additionally, a fourth histogram tracks Total Market Cap expansion/contraction relative to BTC+Stable capital, revealing underlying rotation pressure not visible in raw dominance charts. Each component is standardized through SMA/STD normalization, producing smoothed 0–100 style oscillations that highlight overbought/oversold rotation extremes, risk-on/risk-off transitions, and capital cycle inflection zones. ⚪ Flow Components Stablecoin Dominance Oscillator —White line Measures the combined USDT + USDC share of market dominance. High values indicate increased hedging behavior or sidelined capital. Low values coincide with renewed risk appetite and capital deployment into crypto assets. Altcoin Dominance Oscillator — Orange Line Tracks the share of liquidity rotating into altcoins (Total – BTC – Stable). Rising values indicate broad market expansion and speculative activity. Falling values reflect flight-to-safety or concentration back into majors. BTC Dominance Oscillator — Purple line(off by default Normalized BTC dominance revealing transitions between Bitcoin-led markets and altcoin-led cycles. Useful for identifying BTC absorption phases vs. altcoins dispersion regimes. Total–BTC–Stable MarketCap Difference Histogram — histogram A normalized histogram of total market cap change minus BTC+Stable market cap change. • Positive → altcoin segment expanding • Negative → capital retreating into BTC or stables Acts as a structural layer confirming or contradicting dominance-based signals. Normalization Logic All flows use SMA + standard deviation scaling (lookback 7 / smoothing 7), enabling consistent comparison across unrelated dominance and market-cap metrics. ⚪ Use Cases • Identify shifts between BTC-led and alt-led markets • Detect early signs of liquidity rotation • If Stablecoin OSC is oversold, liquidity may soon rotate to BTC or Altcoins, signaling potential price moves. • If Stablecoin OSC is overbought and Altcoin OSC is oversold, it can indicate an early buying opportunity in Altcoins. • Watching these oscillator positions helps spot early market rotations and plan entries or exits. snapshot Disclaimer This indicator is for educational and informational purposes only and does not constitute financial advice or investment guidance. Cryptocurrency trading involves significant risk; you are solely responsible for your trading decisions, based on your financial objectives and risk tolerance. The author assumes no liability for any losses arising from the use of this tool.
อินดิเคเตอร์ Pine Script®
โดย sanbangaje
1
Credit Spread RegimeThe Credit Market as Economic Barometer Credit spreads are among the most reliable leading indicators of economic stress. When corporations borrow money by issuing bonds, investors demand a premium above the risk-free Treasury rate to compensate for the possibility of default. This premium, known as the credit spread, fluctuates based on perceptions of economic health, corporate profitability, and systemic risk. The relationship between credit spreads and economic activity has been studied extensively. Two papers form the foundation of this indicator. Pierre Collin-Dufresne, Robert Goldstein, and Spencer Martin published their influential 2001 paper in the Journal of Finance, documenting that credit spread changes are driven by factors beyond firm-specific credit quality. They found that a substantial portion of spread variation is explained by market-wide factors, suggesting credit spreads contain information about aggregate economic conditions. Simon Gilchrist and Egon Zakrajsek extended this research in their 2012 American Economic Review paper, introducing the concept of the Excess Bond Premium. They demonstrated that the component of credit spreads not explained by default risk alone is a powerful predictor of future economic activity. Elevated excess spreads precede recessions with remarkable consistency. What Credit Spreads Reveal Credit spreads measure the difference in yield between corporate bonds and Treasury securities of similar maturity. High yield bonds, also called junk bonds, carry ratings below investment grade and offer higher yields to compensate for greater default risk. Investment grade bonds have lower yields because the probability of default is smaller. The spread between high yield and investment grade bonds is particularly informative. When this spread widens, investors are demanding significantly more compensation for taking on credit risk. This typically indicates deteriorating economic expectations, tighter financial conditions, or increasing risk aversion. When the spread narrows, investors are comfortable accepting lower premiums, signaling confidence in corporate health. The Gilchrist-Zakrajsek research showed that credit spreads contain two distinct components. The first is the expected default component, which reflects the probability-weighted cost of potential defaults based on corporate fundamentals. The second is the excess bond premium, which captures additional compensation demanded beyond expected defaults. This excess premium rises when investor risk appetite declines and financial conditions tighten. The Implementation Approach This indicator uses actual option-adjusted spread data from the Federal Reserve Economic Database (FRED), available directly in TradingView. The ICE BofA indices represent the industry standard for measuring corporate bond spreads. The primary data sources are FRED:BAMLH0A0HYM2, the ICE BofA US High Yield Index Option-Adjusted Spread, and FRED:BAMLC0A0CM, the ICE BofA US Corporate Index Option-Adjusted Spread for investment grade bonds. These indices measure the spread of corporate bonds over Treasury securities of similar duration, expressed in basis points. Option-adjusted spreads account for embedded options in corporate bonds, providing a cleaner measure of credit risk than simple yield spreads. The methodology developed by ICE BofA is widely used by institutional investors and central banks for monitoring credit conditions. The indicator offers two modes. The HY-IG excess spread mode calculates the difference between high yield and investment grade spreads, isolating the pure compensation for below-investment-grade credit risk. This measure is less affected by broad interest rate movements. The HY-only mode tracks the absolute high yield spread, capturing both credit risk and the overall level of risk premiums in the market. Interpreting the Regimes Credit conditions are classified into four regimes based on Z-scores calculated from the spread proxy. The Stress regime occurs when spreads reach extreme levels, typically above a Z-score of 2.0. At this point, credit markets are pricing in significant default risk and economic deterioration. Historically, stress regimes have coincided with recessions, financial crises, and major market dislocations. The 2008 financial crisis, the 2011 European debt crisis, the 2016 commodity collapse, and the 2020 pandemic all triggered credit stress regimes. The Elevated regime, between Z-scores of 1.0 and 2.0, indicates above-normal risk premiums. Credit conditions are tightening. This often occurs in the build-up to stress events or during periods of uncertainty. Risk management should be heightened, and exposure to credit-sensitive assets may be reduced. The Normal regime covers Z-scores between -1.0 and 1.0. This represents typical credit conditions where spreads fluctuate around historical averages. Standard investment approaches are appropriate. The Low regime occurs when spreads are compressed below a Z-score of -1.0. Investors are accepting below-average compensation for credit risk. This can indicate complacency, strong economic confidence, or excessive risk-taking. While often associated with favorable conditions, extremely tight spreads sometimes precede sudden reversals. Credit Cycle Dynamics Beyond static regime classification, the indicator tracks the direction and acceleration of spread movements. This reveals where credit markets stand in the credit cycle. The Deteriorating phase occurs when spreads are elevated and continuing to widen. Credit conditions are actively worsening. This phase often precedes or coincides with economic downturns. The Recovering phase occurs when spreads are elevated but beginning to narrow. The worst may be over. Credit conditions are improving from stressed levels. This phase often accompanies the early stages of economic recovery. The Tightening phase occurs when spreads are low and continuing to compress. Credit conditions are very favorable and improving further. This typically occurs during strong economic expansions but may signal building complacency. The Loosening phase occurs when spreads are low but beginning to widen from compressed levels. The extremely favorable conditions may be normalizing. This can be an early warning of changing sentiment. Relationship to Economic Activity The predictive power of credit spreads for economic activity is well-documented. Gilchrist and Zakrajsek found that the excess bond premium predicts GDP growth, industrial production, and unemployment rates over horizons of one to four quarters. When credit spreads spike, the cost of corporate borrowing increases. Companies may delay or cancel investment projects. Reduced investment leads to slower growth and eventually higher unemployment. The transmission mechanism runs from financial conditions to real economic activity. Conversely, tight credit spreads lower borrowing costs and encourage investment. Easy credit conditions support economic expansion. However, excessively tight spreads may encourage over-leveraging, planting seeds for future stress. Practical Application For equity investors, credit spreads provide context for market risk. Equities and credit often move together because both reflect corporate health. Rising credit spreads typically accompany falling stock prices. Extremely wide spreads historically have coincided with equity market bottoms, though timing the reversal remains challenging. For fixed income investors, spread regimes guide sector allocation decisions. During stress regimes, flight to quality favors Treasuries over corporates. During low regimes, spread compression may offer limited additional return for credit risk, suggesting caution on high yield. For macro traders, credit spreads complement other indicators of financial conditions. Credit stress often leads equity volatility, providing an early warning signal. Cross-asset strategies may use credit regime as a filter for position sizing. Limitations and Considerations FRED data updates with a lag, typically one business day for the ICE BofA indices. For intraday trading decisions, more current proxies may be necessary. The data is most reliable on daily timeframes. Credit spreads can remain at extreme levels for extended periods. Mean reversion signals indicate elevated probability of normalization but do not guarantee timing. The 2008 crisis saw spreads remain elevated for many months before normalizing. The indicator is calibrated for US credit markets. Application to other regions would require different data sources such as European or Asian credit indices. The relationship between spreads and subsequent economic activity may vary across market cycles and structural regimes. References Collin-Dufresne, P., Goldstein, R.S., and Martin, J.S. (2001). The Determinants of Credit Spread Changes. Journal of Finance, 56(6), 2177-2207. Gilchrist, S., and Zakrajsek, E. (2012). Credit Spreads and Business Cycle Fluctuations. American Economic Review, 102(4), 1692-1720. Krishnamurthy, A., and Muir, T. (2017). How Credit Cycles across a Financial Crisis. Working Paper, Stanford University.
อินดิเคเตอร์ Pine Script®
โดย EdgeTools
4