지금 시작

Educational

VCAI Volume & Liquidity Map LiteVCAI Volume & Liquidity Map Lite visualises recent market participation using a horizontal liquidity/volume histogram plotted beside current price. It shows where trading activity has clustered, where the chart is thin, and how much of that activity came from buying vs selling pressure. This Lite edition keeps the tool simple and fast: Yellow = buy-side volume (aggressive buyers / upward pressure) Purple = sell-side volume (aggressive sellers / downward pressure) Thicker sections = higher traded volume at that price POC line (purple) marks the price with the highest volume concentration Value Area lines (yellow dashed) mark where ~70% of volume has traded Bars extend outward to the right of price for a clean, unobstructed chart Lookback setting controls how many candles the map is built from Use it to quickly identify: high-interest price zones low-liquidity areas where price can move fast likely reaction levels where momentum may slow, reverse, or break through Designed as a lightweight, open-source tool for anyone wanting a clean liquidity/volume map without complex settings. Part of the VCAI Lite Series.
Pine Script® 인디케이터
Vectorcoresai의
RTH Yesterday & Today Premarket Levels## **RTH Yesterday & Today Premarket Levels** This indicator plots the most commonly used **institutional reference levels** for intraday trading: * **Yesterday’s Regular Trading Hours (RTH) High** * **Yesterday’s Regular Trading Hours (RTH) Low** * **Yesterday’s Regular Trading Hours (RTH) Close** * **Today’s Premarket High** * **Today’s Premarket Low** All levels are drawn as **straight horizontal lines with labels** and remain fixed throughout the current session. --- ### **How Levels Are Calculated** **Yesterday’s Levels (RTH only)** * Computed strictly from **Regular Trading Hours (09:30–16:00 exchange time)**. * Extended-hours data is **excluded** to avoid distortion. * Captures true institutional highs, lows, and closing price. **Today’s Premarket Levels (PM only)** * Computed strictly from **today’s premarket session (04:00–09:29)**. * Resets daily and does not include prior days. * Levels finalize once premarket ends and extend across the regular session. --- ### **Key Features** * Exactly **5 fixed reference levels**, no historical clutter * **Non-repainting**: levels do not change once established * **No zig-zags or plots**; only clean horizontal lines * Customizable **line colors and thickness** * Labels clearly identify each level: * Y High * Y Low * Y Close * PM High * PM Low --- ### **Best Use Cases** * Intraday trading (1m, 5m, 15m) * VWAP and momentum strategies * Gap-and-go or fade setups * Support/resistance validation * Options trading and scalping These levels often act as **decision points, liquidity magnets, and rejection zones** during the regular session. --- ### **Required Settings** * Use **intraday timeframes** * Enable **Extended Hours** in TradingView’s symbol settings * Designed for **US equities** using exchange time --- ### **Trader Notes** This script is intentionally minimalist. It shows only the **most relevant prior-day and premarket price references** used by professional traders, avoiding noise from multi-day indicators or derived averages.
Pine Script® 인디케이터
nbaddam2의
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
Pine Script® 인디케이터
tanveeralims의
Vib ORB Range (Free)Vib ORB Range (Free) plots the Opening Range High and Low for the session based on a user-defined start time and duration. This tool is designed for traders who want a clean, no-noise display of the ORB zone without extra indicators or automation. Features: Customizable Opening Range start time Customizable Opening Range duration Automatically resets daily Plots ORB High, ORB Low, and optional ORB Midline Shaded range zone for improved clarity Works on all timeframes and markets How to Use: Set the ORB start time (default 9:30 New York) Set the ORB duration (default 15 minutes) The indicator will draw the ORB zone once the range completes Use the outlines or shaded zone to visually identify potential breakout areas This free tool is intended as a simple, reliable ORB visualizer without alerts, filters, or strategy logic.
Pine Script® 인디케이터
vmarapak의
30-Minute High and Low30-Minute High and Low Levels This indicator plots the previous 30-minute candle’s high and low on any intraday chart. These levels are widely used by intraday traders to identify key breakout zones, liquidity pools, micro-range boundaries, and early trend direction. Features: • Automatically pulls the previous 30-minute candle using higher-timeframe HTF requests • Displays the HTF High (blue) and HTF Low (red) on lower-timeframe charts • Works on all intraday timeframes (1m, 3m, 5m, 10m, etc.) • Levels stay fixed until the next 30-minute bar completes • Ideal for ORB strategies, scalping, liquidity sweeps, and reversal traps Use Cases: • Watch for breakouts above the 30-minute high • Monitor for liquidity sweeps and fakeouts around the high/low • Treat the mid-range as a magnet during consolidation • Combine with VWAP or EMA trend structure for high-precision intraday setups This indicator is simple, fast, and designed for traders who rely on HTF micro-structure to guide intraday execution.
Pine Script® 인디케이터
MomentumCraft_의
🐋 MACRO POSITION TRADER - Quarterly Alignment 💎Disclaimer: This tool is an alignment filter and educational resource, not financial advice. Backtest and use proper risk management. Past performance does not guarantee future returns. so the idea behind this one came from an experience i had when i first started learning how to trade. dont laugh at me but i was the guy to buy into those stupid AI get rich quick schemes or the first person to buy the "golden indicator" just to find out that it was a scam. Its also to help traders place trades they can hold for months with high confidence and not have to sit in front of charts all day, and to also scale up quickly with small accounts confidently. and basically what it does is gives an alert once the 3 mo the 6 mo and the 12 mo tfs all align with eachother and gives the option to toggle on or off the 1 mo tf as well for extra confidence. Enter on the 5M–15M after a sweep + CHOCH in the direction of the aligned 1M–12M bias. that simple just continue to keep watching key levels mabey take profit 1-2 weeks and jump back in scaling up if desired..easy way to combine any small account size. Perfect balance of: low risk high R:R optimal precision minimal chop best sweep/CHOCH clarity hope you guys enjoy this one.
Pine Script® 인디케이터
wateriskey6689의
ShooterViz Lazy Trader EMA SystemShooterViz Lazy Trader EMA System - Complete User Guide What This Script Does This is a position scaling indicator that tells you exactly when to enter, add to, and exit trades using a simplified 5-EMA system. It removes the guesswork and decision fatigue from trading by giving you clear visual signals. The Core Concept 3 entry signals that build your position from 20% → 50% → 100% 2 exit signals that scale you out at 50% → 50% (complete exit) 1 higher timeframe filter that keeps you on the right side of the trend No Fibonacci calculations, no RSI divergence, no multi-indicator confusion. Just EMAs and price action. What You'll See On Your Chart 1. Colored EMA Lines Blue Lines (Entry Zone): 3 EMA (lightest blue) - Early reversal detector 5 EMA (darker blue) - Confirmation line Green Lines (Add Zone): 21 EMA (bright green) - First add location 34 EMA (lighter green) - Final add location Red Lines (Exit Zone): 89 EMA (lighter red) - First exit trigger 144 EMA (darker red) - Final exit trigger Orange Lines (Hyper Frame - optional): Hyper 21 EMA (from higher timeframe) - Trend direction Hyper 34 EMA (from higher timeframe) - Bias confirmation 2. Triangle Signals Green Triangles (Below Price) = BUY/ADD: Lime triangle with "20%" = Entry 1: Price reclaimed 3→5 EMA (starter position) Green triangle with "30%" = Entry 2: Price bounced off 21 EMA (first add) Teal triangle with "50%" = Entry 3: Price broke out from 34 EMA compression (final add) Red Triangles (Above Price) = SELL: Orange triangle with "50% OFF" = Exit 1: Price broke below 89 EMA (take half off) Red triangle with "EXIT ALL" = Exit 2: Price broke below 144 EMA (close remaining position) 3. Background Color (Trend Bias) Light green background = Hyper frame EMAs trending up (bias LONG) Light red background = Hyper frame EMAs trending down (bias SHORT) Gray background = Neutral/choppy (be cautious) 4. Info Table (Top Right Corner) A live status dashboard showing: Which entry signals are currently active (✓ or —) Which exit signals are currently active (⚠ or ⛔) Current hyper frame bias (🟢 LONG / 🔴 SHORT / ⚪ NEUTRAL) Which timeframe you're using for hyper frame filtering How to Install and Set Up Step 1: Add the Script to TradingView Open TradingView Click "Pine Editor" at the bottom of the screen Copy the entire script code Paste it into the Pine Editor Click "Add to Chart" Step 2: Configure Your Settings Click the gear icon ⚙️ next to "LazyEMA" in your indicators list. Critical Settings to Configure: Hyper Frame Selection (Most Important!) Location: "Hyper Frame (Pick ONE)" section Setting: "Timeframe" What to choose: Trading 15min or 1H charts? → Use "240" (4-hour) Trading 4H or Daily charts? → Use "D" (Daily) Trading Daily or Weekly charts? → Use "W" (Weekly) Why this matters: This filter keeps you aligned with the bigger trend. Only take longs when this timeframe is green, shorts when it's red. MA Type (Optional, default is fine) Location: "MA Config" section Default: EMA (recommended) Options: EMA, SMA, WMA, HMA, RMA, VWMA Most traders should stick with EMA Visual Toggles (Customize your view) Entry Zone: Turn individual EMAs on/off (3, 5, 21, 34) Exit Zone: Turn individual EMAs on/off (89, 144) Hyper Frame: Toggle the higher timeframe EMAs on/off Step 3: Clean Up Your Chart Turn OFF these if visible: Volume bars (they clutter the view) Any other indicators you have loaded Grid lines (optional, but cleaner) Keep ONLY: Price candles Your ShooterViz Lazy Trader EMA System Maybe support/resistance levels if you manually draw them How to Trade With This Script The Basic Workflow Before the Market Opens: Check the background color and info table bias Green background? Look for LONG setups only Red background? Look for SHORT setups only Gray background? Stay flat or trade small During the Trading Session: LONGS (When hyper frame is bullish): Wait for Entry 1 signal: Lime triangle appears with "20%" Price has reclaimed the 5 EMA after dipping to 3 EMA Action: Enter 20% of your intended position Stop loss: Place below the 5 EMA or recent swing low Wait for Entry 2 signal: Green triangle appears with "30%" Price pulled back to 21 EMA and bounced Action: Add 30% more (you're now at 50% total) Move stop: Trail it up to below 21 EMA Wait for Entry 3 signal: Teal triangle appears with "50%" Price compressed at 34 EMA and broke out Action: Add final 50% (you're now 100% loaded) Move stop: Trail it up to below 34 EMA Wait for Exit 1 signal: Orange triangle appears with "50% OFF" Price broke below 89 EMA Action: Exit 50% of your position immediately Move stop on rest: Trail to 89 EMA or lock in profits Wait for Exit 2 signal: Red triangle appears with "EXIT ALL" Price broke below 144 EMA Action: Exit remaining 50% (you're now flat) Or: Stop gets hit at 89 EMA (same result) SHORTS (When hyper frame is bearish): Same process, but inverted Triangles appear above price instead of below Look for breakdowns below EMAs instead of bounces off them Exit when price reclaims 89 and 144 EMAs Real-World Example Walkthrough Setup: Trading ES (S&P 500 Futures) on 1H Chart Chart Configuration: Timeframe: 1 Hour Hyper Frame: 240 (4-hour) Ticker: ES Pre-Market Check: Background is light green Info table shows "🟢 LONG" for Hyper Bias Decision: Only look for long entries today 9:30 AM - Market Opens Price dips and touches 3 EMA Watch for: Reclaim of 5 EMA 9:45 AM - Entry 1 Triggers Lime triangle appears below bar Price closed above 5 EMA at $4,550 Action taken: Enter long 20% position (2 contracts if targeting 10 total) Stop loss at $4,545 (below 5 EMA) Risk: $10 per contract × 2 = $20 risk 10:30 AM - Entry 2 Triggers Price rallied to $4,565, pulls back Green triangle appears at 21 EMA ($4,555) Action taken: Add 30% (3 more contracts, now have 5 total) Move stop to $4,550 (below 21 EMA) Current P/L: +$25 ($5 gain on original 2 contracts, break-even on new 3) 11:15 AM - Entry 3 Triggers Price consolidates at 34 EMA around $4,560 Teal triangle appears as price breaks to $4,568 Action taken: Add final 50% (5 more contracts, now have 10 total) Move stop to $4,555 (below 34 EMA) Current P/L: +$70 1:00 PM - Price Extends Price rallies to $4,595 (on track) 89 EMA is at $4,575 No action yet, let it run 2:15 PM - Exit 1 Triggers Price pulls back from $4,600 Orange triangle appears as price breaks below 89 EMA at $4,580 Action taken: Exit 50% (5 contracts closed at $4,580) Keep 5 contracts with stop at 89 EMA ($4,575) Banked: +$150 average gain on closed 5 contracts 2:45 PM - Exit 2 Triggers Price continues down Red triangle appears as price breaks 144 EMA at $4,570 Action taken: Exit remaining 5 contracts at $4,570 Banked: +$100 on remaining 5 contracts Final Results: Total gain: $250 on the trade Initial risk: $50 (if stopped out at Entry 1) Risk/Reward: 5:1 Time in trade: ~5 hours Common Questions "What if I miss Entry 1? Can I still take Entry 2?" Yes! Each entry is independent. If you miss the 3→5 reclaim, wait for the 21 EMA bounce. You'll start with a 30% position instead of 20%, but that's fine. Rule: Never chase. Wait for the next EMA setup. "What if multiple entry signals trigger at the same bar?" Rare, but possible. If you see both Entry 1 and Entry 2 trigger together: Take Entry 1 first (20%) If the next bar confirms Entry 2 is still valid, add 30% When in doubt, scale in gradually "The hyper frame is green but I'm seeing short signals?" Don't take them. The hyper frame is your bias filter. If it says "go long," ignore short setups. They're usually lower probability and will get stopped out. "Can I use this for swing trading overnight?" Absolutely. Just switch your hyper frame: If you're on Daily charts, use Weekly hyper frame If you're on 4H charts, use Daily hyper frame Adjust position sizes for overnight risk "What if the signal appears right at market close?" Don't chase it. Wait for the next bar (next day) to confirm. Signals that appear in the last 5 minutes are often noise. "How do I set up alerts?" Right-click on the chart Select "Add Alert" Choose "LazyEMA" from the condition dropdown Select which signal you want alerts for: Entry 1: 3→5 Reclaim Entry 2: 21 EMA Add Entry 3: 34 EMA Breakout Exit 1: 89 EMA Break Exit 2: 144 EMA Break Click "Create" Pro tip: Set up all 5 alerts so you never miss a signal. Position Sizing Guide see swingtradenotes.substack.com Critical Rule: Know your total risk BEFORE you take Entry 1. Don't wing it. Customization Tips For Day Traders (Scalpers) Use 5min or 15min charts Hyper frame: 1H or 4H Expect 2-4 setups per day Tighter stops (0.5% risk per entry) For Swing Traders Use 4H or Daily charts Hyper frame: Daily or Weekly Expect 1-2 setups per week Wider stops (1-2% risk per entry) For Position Traders Use Daily or Weekly charts Hyper frame: Weekly or Monthly Expect 1-2 setups per month Widest stops (2-3% risk per entry) The "Don't Be Stupid" Checklist Before taking ANY signal from this script, ask: ✅ Is the hyper frame bias pointing in my direction? ✅ Is the signal clean (not at a weird time or during news)? ✅ Do I know my stop loss level? ✅ Do I know my position size? ✅ Can I afford to lose if this trade fails? If you answered "no" to ANY of these, skip the trade. Troubleshooting "I'm not seeing any signals" Possible causes: The "Show Lazy Trader System" toggle is off (turn it on) Your chart timeframe is too high (try 1H or 4H) Market is in a tight range (EMAs are compressed) You need to refresh the chart "Too many signals, getting whipsawed" Fixes: Increase your chart timeframe (go from 15m to 1H) Switch to a less volatile ticker Only trade when hyper frame bias is STRONG (not neutral) Add a minimum bar count between signals "The info table is covering my price action" Fix: Edit the script Find the line: table.new(position.top_right, ... Change position.top_right to position.bottom_right or position.top_left "Signals appear then disappear" This is normal (repainting). Some signals (especially compression breakouts) can disappear if the next bar reverses. This is why you: Wait for bar close before acting Use alerts that only fire on confirmed bars Don't chase signals mid-bar Final Thoughts This script is a decision-making tool, not a crystal ball. It shows you high-probability setups based on EMA dynamics and trend structure. You still need to: Manage your risk Choose your position size Stick to the rules Accept losses when they happen The system works when YOU work the system. Print this guide, tape it next to your monitor, and follow it religiously for 20 trades before making ANY changes. Good luck, and stay lazy (the smart way).
Pine Script® 인디케이터
SwingTradeNotes의
Market Structure Shift (MSS) [Sword & Shield]MARKET STRUCTURE SHIFT (MSS) A clean and focused indicator for identifying Market Structure Shifts in price action. ════════════════════════════════════════════════════════════════════════════════ WHAT IS MARKET STRUCTURE SHIFT (MSS)? ════════════════════════════════════════════════════════════════════════════════ A Market Structure Shift occurs when price breaks a significant swing high or swing low, indicating a potential change in market direction. This indicator automatically detects and plots these key levels. BULLISH MSS: Price breaks above a previous swing high BEARISH MSS: Price breaks below a previous swing low ════════════════════════════════════════════════════════════════════════════════ FEATURES ════════════════════════════════════════════════════════════════════════════════ CLEAN DISPLAY - Shows only the last 2 MSS by default (1 bullish + 1 bearish) - Keeps charts clean and focused on recent structure - Automatically removes old MSS when new ones appear CUSTOMIZABLE DETECTION - Adjustable swing detection (left/right bars) - Choose break confirmation method (Close or Wick) - Fixed-length lines (no infinite extension by default) SMART FILTERING - Only plots one MSS per direction until opposite MSS occurs - Prevents duplicate signals in the same direction - Clear visual distinction between bullish (blue) and bearish (red) CLEAN LABELS - Text labels positioned above lines - No background tooltips for cleaner appearance - Color-matched to their respective MSS lines ════════════════════════════════════════════════════════════════════════════════ SETTINGS ════════════════════════════════════════════════════════════════════════════════ SWING DETECTION - Swing Left Bars (default: 2) - Swing Right Bars (default: 2) - Higher values = more significant swings detected BREAK CONFIRMATION - Close: MSS confirmed when candle closes beyond level - Wick: MSS confirmed when wick touches beyond level DISPLAY OPTIONS - Show Only Last 2 MSS: ON by default (keeps chart clean) - Extend lines to the right: OFF by default (fixed-length lines) - Line bars (when not extended): 50 bars (customizable) ════════════════════════════════════════════════════════════════════════════════ HOW IT WORKS ════════════════════════════════════════════════════════════════════════════════ DETECTION LOGIC 1. Identifies swing highs and swing lows using pivot detection 2. Monitors price action for breaks of these levels 3. Confirms break based on selected method (Close or Wick) 4. Plots MSS line at the broken level FILTERING LOGIC - Only one MSS per direction is allowed consecutively - Example: If bullish MSS appears, no new bullish MSS until bearish MSS occurs - This prevents multiple signals in trending markets DISPLAY LOGIC - When "Show Only Last 2 MSS" is enabled: • Only the most recent bullish MSS is shown • Only the most recent bearish MSS is shown • Old MSS are automatically deleted when new ones appear - When disabled: All historical MSS remain visible ════════════════════════════════════════════════════════════════════════════════ USAGE EXAMPLES ════════════════════════════════════════════════════════════════════════════════ FOR TREND IDENTIFICATION - Bullish MSS = Potential uptrend beginning - Bearish MSS = Potential downtrend beginning - Use in conjunction with other indicators for confirmation FOR ENTRY SIGNALS - Wait for MSS to confirm trend change - Enter on pullback to MSS level - Use MSS as support/resistance FOR SCALPING (Lower Timeframes) - Swing Left/Right Bars: 2-3 (more sensitive) - Break Confirmation: Close (more reliable) - Show Only Last 2 MSS: ON (cleaner charts) FOR SWING TRADING (Higher Timeframes) - Swing Left/Right Bars: 5-10 (more significant swings) - Break Confirmation: Close (avoid false breaks) - Show Only Last 2 MSS: ON or OFF based on preference ════════════════════════════════════════════════════════════════════════════════ VISUAL DESIGN ════════════════════════════════════════════════════════════════════════════════ LINES - Dashed style for easy identification - Blue for bullish MSS - Red for bearish MSS - Fixed length (50 bars default) for cleaner appearance LABELS - "MSS" text positioned above each line - No background for clean display - Color-matched to line color - Small size to avoid chart clutter ════════════════════════════════════════════════════════════════════════════════ CREDITS & LICENSE ════════════════════════════════════════════════════════════════════════════════ © Sword & Shield This Pine Script code is subject to the terms of the Mozilla Public License 2.0 mozilla.org
Pine Script® 인디케이터
swordNshield의
6
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.
Pine Script® 인디케이터
EdgeTools의
4
Absorption RatioThe Hidden Connections Between Markets Financial markets are not isolated islands. When panic spreads, seemingly unrelated assets suddenly begin moving in lockstep. Stocks, bonds, commodities, and currencies that normally provide diversification benefits start falling together. This phenomenon, where correlations spike during crises, has devastated portfolios throughout history. The Absorption Ratio provides a quantitative measure of this hidden fragility. The concept emerged from research at State Street Associates, where Mark Kritzman, Yuanzhen Li, Sebastien Page, and Roberto Rigobon developed a novel application of principal component analysis to measure systemic risk. Their 2011 paper in the Journal of Portfolio Management demonstrated that when markets become tightly coupled, the variance explained by the first few principal components increases dramatically. This concentration of variance signals elevated systemic risk. What the Absorption Ratio Measures Principal component analysis, or PCA, is a statistical technique that identifies the underlying factors driving a set of variables. When applied to asset returns, the first principal component typically captures broad market movements. The second might capture sector rotations or risk-on/risk-off dynamics. Additional components capture increasingly idiosyncratic patterns. The Absorption Ratio measures the fraction of total variance absorbed or explained by a fixed number of principal components. In the original research, Kritzman and colleagues used the first fifth of the eigenvectors. When this fraction is high, it means a small number of factors are driving most of the market movements. Assets are moving together, and diversification provides less protection than usual. Consider an analogy: imagine a room full of people having independent conversations. Each person speaks at different times about different topics. The total "variance" of sound in the room comes from many independent sources. Now imagine a fire alarm goes off. Suddenly everyone is talking about the same thing, moving in the same direction. The variance is now dominated by a single factor. The Absorption Ratio captures this transition from diverse, independent behavior to unified, correlated movement. The Implementation Approach TradingView does not support matrix algebra required for true principal component analysis. This implementation uses a closely related proxy: the average absolute correlation across a universe of major asset classes. This approach captures the same underlying phenomenon because when assets are highly correlated, the first principal component explains more variance by mathematical necessity. The asset universe includes eight ETFs representing major investable categories: SPY and QQQ for large cap US equities, IWM for small caps, EFA for developed international markets, EEM for emerging markets, TLT for long-term treasuries, GLD for gold, and USO for oil. This selection provides exposure to equities across geographies and market caps, plus traditional diversifying assets. From eight assets, there are twenty-eight unique pairwise correlations. The indicator calculates each using a rolling window, takes the absolute value to measure coupling strength regardless of direction, and averages across all pairs. This average correlation is then transformed to match the typical range of published Absorption Ratio values. The transformation maps zero average correlation to an AR of 0.50 and perfect correlation to an AR of 1.00. This scaling aligns with empirical observations that the AR typically fluctuates between 0.60 and 0.95 in practice. Interpreting the Regimes The indicator classifies systemic risk into four regimes based on AR levels. The Extreme regime occurs when the AR exceeds 0.90. At this level, nearly all asset classes are moving together. Diversification has largely failed. Historically, this regime has coincided with major market dislocations: the 2008 financial crisis, the 2020 COVID crash, and significant correction periods. Portfolios constructed under normal correlation assumptions will experience larger drawdowns than expected. The High regime, between 0.80 and 0.90, indicates elevated systemic risk. Correlations across asset classes are above normal. This often occurs during the build-up to stress events or during volatile periods where fear is spreading but has not reached panic levels. Risk management should be more conservative. The Normal regime covers AR values between 0.60 and 0.80. This represents typical market conditions where some correlation exists between assets but diversification still provides meaningful benefits. Standard portfolio construction assumptions are reasonable. The Low regime, below 0.60, indicates that assets are behaving relatively independently. Diversification is working well. Idiosyncratic factors dominate returns rather than systematic risk. This environment is favorable for active management and security selection strategies. The Relationship to Portfolio Construction The implications for portfolio management are significant. Modern portfolio theory assumes correlations are stable and uses historical estimates to construct efficient portfolios. The Absorption Ratio reveals that this assumption is violated precisely when it matters most. When AR is elevated, the effective number of independent bets in a diversified portfolio shrinks. A portfolio holding stocks, bonds, commodities, and real estate might behave as if it holds only one or two positions during high AR periods. Position sizing based on normal correlation estimates will underestimate portfolio risk. Conversely, when AR is low, true diversification opportunities expand. The same nominal portfolio provides more independent return streams. Risk can be deployed more aggressively while maintaining the same effective exposure. Component Analysis The indicator separately tracks equity correlations and cross-asset correlations. These components tell different stories about market structure. Equity correlations measure coupling within the stock market. High equity correlation indicates broad risk-on or risk-off behavior where all stocks move together. This is common during both rallies and selloffs driven by macroeconomic factors. Stock pickers face headwinds when equity correlations are elevated because individual company fundamentals matter less than market beta. Cross-asset correlations measure coupling between different asset classes. When stocks, bonds, and commodities start moving together, traditional hedges fail. The classic 60/40 stock/bond portfolio, for example, assumes negative or low correlation between equities and treasuries. When cross-asset correlation spikes, this assumption breaks down. During the 2022 market environment, for instance, both stocks and bonds fell significantly as inflation and rate hikes affected all assets simultaneously. High cross-asset correlation warned that the usual defensive allocations would not provide their expected protection. Mean Reversion Characteristics Like most risk metrics, the Absorption Ratio tends to mean-revert over time. Extremely high AR readings eventually normalize as panic subsides and assets return to more independent behavior. Extremely low readings tend to rise as some level of systematic risk always reasserts itself. The indicator tracks AR in statistical terms by calculating its Z-score relative to the trailing distribution. When AR reaches extreme Z-scores, the probability of normalization increases. This creates potential opportunities for strategies that bet on mean reversion in systemic risk. A buy signal triggers when AR recovers from extremely elevated levels, suggesting the worst of the correlation spike may be over. A sell signal triggers when AR rises from unusually low levels, warning that complacency about diversification benefits may be excessive. Momentum and Trend The rate of change in AR carries information beyond the absolute level. Rapidly rising AR suggests correlations are increasing and systemic risk is building. Even if AR has not yet reached the high regime, acceleration in coupling should prompt increased vigilance. Falling AR momentum indicates normalizing conditions. Correlations are decreasing and assets are returning to more independent behavior. This often occurs in the recovery phase following stress events. Practical Application For asset allocators, the AR provides guidance on how much diversification benefit to expect from a given allocation. During high AR periods, reducing overall portfolio risk makes sense because the usual diversifiers provide less protection. During low AR periods, standard or even aggressive allocations are more appropriate. For risk managers, the AR serves as an early warning indicator. Rising AR often precedes large market moves and volatility spikes. Tightening risk limits before correlations reach extreme levels can protect capital. For systematic traders, the AR provides a regime filter. Mean reversion strategies may work better during high AR periods when panics create overshooting. Momentum strategies may work better during low AR periods when trends can develop independently across assets. Limitations and Considerations The proxy methodology introduces some approximation error relative to true PCA-based AR calculations. The asset universe, while representative, does not include all possible diversifiers. Correlation estimates are inherently backward-looking and can change rapidly. The transformation from average correlation to AR scale is calibrated to match typical published ranges but is not mathematically equivalent to the eigenvalue ratio. Users should interpret levels directionally rather than as precise measurements. Correlation regimes can persist longer than expected. Mean reversion signals indicate elevated probability of normalization but do not guarantee timing. High AR can remain elevated throughout extended crisis periods. References Kritzman, M., Li, Y., Page, S., and Rigobon, R. (2011). Principal Components as a Measure of Systemic Risk. Journal of Portfolio Management, 37(4), 112-126. Kritzman, M., and Li, Y. (2010). Skulls, Financial Turbulence, and Risk Management. Financial Analysts Journal, 66(5), 30-41. Billio, M., Getmansky, M., Lo, A., and Pelizzon, L. (2012). Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors. Journal of Financial Economics, 104(3), 535-559.
Pine Script® 인디케이터
EdgeTools의
EMA 20/50/200 - Warning Note Before Cross EMA 20/50/200 - Smart Cross Detection with Customizable Alerts A clean and minimalistic indicator that tracks three key Exponential Moving Averages (20, 50, and 200) with intelligent near-cross detection and customizable warning system. ═══════════════════════════════════════════════════════════════════ 📊 KEY FEATURES ✓ Triple EMA System • EMA 20 (Red) - Fast/Short-term trend • EMA 50 (Yellow) - Medium/Intermediate trend • EMA 200 (Green) - Slow/Long-term trend & major support/resistance ✓ Smart Near-Cross Detection • Get warned BEFORE crosses happen (not after) • Adjustable threshold percentage (how close is "close") • Automatic hiding after cross to prevent false signals • Configurable lookback period ✓ Dual Warning System • Price Label: Appears directly on chart near EMAs • Info Table: Positioned anywhere on your chart • Both show distance percentage and direction • Dynamic positioning to avoid blocking candles ✓ Color-Coded Alerts • GREEN warning = Bullish cross approaching (EMA 20 crossing UP through EMA 50) • RED warning = Bearish cross approaching (EMA 20 crossing DOWN through EMA 50) ✓ Cross Signal Detection • Golden Cross (EMA 50 crosses above EMA 200) • Death Cross (EMA 50 crosses below EMA 200) • Fast crosses (EMA 20 and EMA 50) ═══════════════════════════════════════════════════════════════════ ⚙️ CUSTOMIZATION OPTIONS Warning Settings: • Custom warning text for bull/bear signals • Adjustable opacity for better visibility • Toggle distance and direction display • Flexible table positioning (9 positions available) • 5 text size options Alert Settings: • Golden/Death Cross alerts • Fast cross alerts (20/50) • Near-cross warnings (before it happens) • All alerts are non-repainting Display Options: • Show/hide each EMA individually • Toggle all signals on/off • Adjustable threshold sensitivity • Dynamic label positioning ═══════════════════════════════════════════════════════════════════ 🎯 HOW TO USE 1. ADD TO CHART Simply add the indicator to any chart and timeframe 2. ADJUST THRESHOLD Default is 0.5% - increase for less frequent warnings, decrease for earlier warnings 3. SET UP ALERTS Create alerts for: • Near-cross warnings (get notified before the cross) • Actual crosses (when EMA 20 crosses EMA 50) • Golden/Death crosses (major trend changes) 4. CUSTOMIZE APPEARANCE • Change warning text to your language • Adjust opacity for your chart theme • Position table where it's most convenient • Choose label size for visibility ═══════════════════════════════════════════════════════════════════ 💡 TRADING TIPS - Use the near-cross warning to prepare entries/exits BEFORE the cross happens - Green warning = Prepare for potential long position - Red warning = Prepare for potential short position - Combine with other indicators for confirmation - Higher timeframes = more reliable signals - Warning disappears after cross to avoid confusion ═══════════════════════════════════════════════════════════════════ 🔧 TECHNICAL DETAILS - Pine Script v6 - Non-repainting (all signals confirm on bar close) - Works on all timeframes - Works on all instruments (stocks, crypto, forex, futures) - Lightweight and efficient - No external data sources required ═══════════════════════════════════════════════════════════════════ 📝 SETTINGS GUIDE Near Cross Settings: • Threshold %: How close EMAs must be to trigger warning (default 0.5%) • Lookback Bars: Hide warning for X bars after a cross (default 3) Warning Note Style: • Text Size: Tiny to Huge • Colors: Customize bull/bear warning colors • Position: Place table anywhere on chart • Opacity: 0 (solid) to 90 (very transparent) Price Label: • Size: Tiny to Large • Opacity: Control transparency • Auto-positioning: Moves to avoid blocking candles Custom Text: • Bull/Bear warning messages • Toggle distance display • Toggle direction display ═══════════════════════════════════════════════════════════════════ ⚠️ IMPORTANT NOTES - Warnings only appear BEFORE crosses, not after - After a cross happens, warning is hidden for the lookback period - Adjust threshold if you're getting too many/too few warnings - This is a trend-following indicator - best used with confirmation - Always use proper risk management ═══════════════════════════════════════════════════════════════════ Happy Trading! 📈📉 If you find this indicator useful, please give it a boost and leave a comment! For questions or suggestions, feel free to reach out.
Pine Script® 인디케이터
Ox3DECAF의
BTC vs Russell2000Description The BTC vs Russell2000 – Weekly Cycle Map compares Bitcoin’s performance against the Russell 2000 (IWM) to identify long-term risk-on and risk-off market regimes. The indicator calculates the BTC/RUT ratio on a weekly timeframe and applies a moving average filter to highlight macro momentum shifts. White line: BTC/RUT ratio (Bitcoin relative strength vs small-cap equities) Yellow line: Weekly SMA of the ratio (trend filter) Green background: BTC outperforming → macro bull regime Red background: Russell 2000 outperforming → macro bear regime Halving markers: Visual reference points for Bitcoin market cycles This tool is designed to help traders understand capital rotation between crypto and traditional markets, improve timing of macro entries, and visualize where Bitcoin stands within its broader cycle.
Pine Script® 인디케이터
zeche13의
Trading Session IL7 Session-Based Intraday Momentum IndicatorOverview This indicator is designed to support discretionary traders by highlighting intraday momentum phases based on price behavior and trading session context. It is intended as a confirmation tool and not as a standalone trading system or automated strategy. Core Concept The script combines multiple market observations, including: - Directional price behavior within the current timeframe - Structural consistency in recent price movement - Session-based filtering to focus on periods with higher activity and liquidity Signals are only displayed when internal conditions align, helping traders avoid low-quality setups during sideways or low-momentum market phases. How to Use This indicator should be used to confirm existing trade ideas rather than generate trades on its own. It can help traders: - Identify periods where momentum is more likely to continue - Filter out trades during unfavorable market conditions - Align intraday execution with higher-timeframe bias Best results are achieved when used alongside key price levels, higher-timeframe structure and proper risk management. Limitations This indicator does not predict future price movements. Signals may change during active candles. Market conditions may reduce effectiveness during extremely low volatility periods. Language Notice The indicator’s user interface labels are displayed in German. This English description is provided first to comply with TradingView community script publishing rules.
Pine Script® 인디케이터
Pavel98xx의
n-Day Stock Return with MAs and SlopesThis indicator calculates the n-day percentage return of a stock and visualizes it either as a histogram or line, with optional moving averages (MA1 and MA2) of the return and their slopes. The script highlights trend changes in the slopes of these moving averages by drawing colored horizontal markers at each reversal point—green for upward slope shifts, red for downward shifts, and gray when the slope turns flat—allowing users to quickly identify strengthening, weakening, or neutral return trends over time. It also includes optional slope plots for additional trend context and a zero reference line for distinguishing positive and negative performance.
Pine Script® 인디케이터
Pynchon의
VectorCoresAI SMA + Bollinger Fusion v1VectorCoresAI — SMA + Bollinger Fusion (Free) A clean, modern visual tool combining four key SMAs with an adaptive Bollinger structure. This script merges two of the most widely used charting concepts into one simple, readable view: Included ✔ SMA 21 ✔ SMA 50 ✔ SMA 100 ✔ SMA 200 ✔ Bollinger Bands with adjustable length + multiplier ✔ Adaptive “Fusion Squeeze” shading to highlight compression phases ✔ Optional visibility toggles for each SMA ✔ Lightweight, non-intrusive overlay What this indicator is designed for This tool helps traders quickly understand: Trend alignment using the 21/50/100/200 SMAs Volatility conditions around the Bollinger midline Price compression and expansion Early awareness of breakout environments Clean visual structure without clutter Everything is intentionally simple and transparent. No predictions, no signals, no trading advice — just clean chart structure. Why this version is unique Instead of using standard Bollinger visuals, this Fusion edition uses subtle adaptive shading to show when the bands contract. This makes compression zones instantly visible without overwhelming the chart. The SMAs are fixed to widely-used trend levels, giving consistent readings across all markets and timeframes. Who this is for Newer traders who want a clear introduction to SMAs + Bollinger Bands Experienced traders who want a lightweight visual tool Anyone building structure-based strategies Users of the VectorCoresAI suite who want a simple companion tool Notes This indicator is part of the VectorCoresAI Free Tools collection. All logic is open-source and educational only. More tools coming soon.
Pine Script® 인디케이터
Vectorcoresai의
Volatility Risk PremiumTHE INSURANCE PREMIUM OF THE STOCK MARKET Every day, millions of investors face a fundamental question that has puzzled economists for decades: how much should protection against market crashes cost? The answer lies in a phenomenon called the Volatility Risk Premium, and understanding it may fundamentally change how you interpret market conditions. Think of the stock market like a neighborhood where homeowners buy insurance against fire. The insurance company charges premiums based on their estimates of fire risk. But here is the interesting part: insurance companies systematically charge more than the actual expected losses. This difference between what people pay and what actually happens is the insurance premium. The same principle operates in financial markets, but instead of fire insurance, investors buy protection against market volatility through options contracts. The Volatility Risk Premium, or VRP, measures exactly this difference. It represents the gap between what the market expects volatility to be (implied volatility, as reflected in options prices) and what volatility actually turns out to be (realized volatility, calculated from actual price movements). This indicator quantifies that gap and transforms it into actionable intelligence. THE FOUNDATION The academic study of volatility risk premiums began gaining serious traction in the early 2000s, though the phenomenon itself had been observed by practitioners for much longer. Three research papers form the backbone of this indicator's methodology. Peter Carr and Liuren Wu published their seminal work "Variance Risk Premiums" in the Review of Financial Studies in 2009. Their research established that variance risk premiums exist across virtually all asset classes and persist over time. They documented that on average, implied volatility exceeds realized volatility by approximately three to four percentage points annualized. This is not a small number. It means that sellers of volatility insurance have historically collected a substantial premium for bearing this risk. Tim Bollerslev, George Tauchen, and Hao Zhou extended this research in their 2009 paper "Expected Stock Returns and Variance Risk Premia," also published in the Review of Financial Studies. Their critical contribution was demonstrating that the VRP is a statistically significant predictor of future equity returns. When the VRP is high, meaning investors are paying substantial premiums for protection, future stock returns tend to be positive. When the VRP collapses or turns negative, it often signals that realized volatility has spiked above expectations, typically during market stress periods. Gurdip Bakshi and Nikunj Kapadia provided additional theoretical grounding in their 2003 paper "Delta-Hedged Gains and the Negative Market Volatility Risk Premium." They demonstrated through careful empirical analysis why volatility sellers are compensated: the risk is not diversifiable and tends to materialize precisely when investors can least afford losses. HOW THE INDICATOR CALCULATES VOLATILITY The calculation begins with two separate measurements that must be compared: implied volatility and realized volatility. For implied volatility, the indicator uses the CBOE Volatility Index, commonly known as the VIX. The VIX represents the market's expectation of 30-day forward volatility on the S&P 500, calculated from a weighted average of out-of-the-money put and call options. It is often called the "fear gauge" because it rises when investors rush to buy protective options. Realized volatility requires more careful consideration. The indicator offers three distinct calculation methods, each with specific advantages rooted in academic literature. The Close-to-Close method is the most straightforward approach. It calculates the standard deviation of logarithmic daily returns over a specified lookback period, then annualizes this figure by multiplying by the square root of 252, the approximate number of trading days in a year. This method is intuitive and widely used, but it only captures information from closing prices and ignores intraday price movements. The Parkinson estimator, developed by Michael Parkinson in 1980, improves efficiency by incorporating high and low prices. The mathematical formula calculates variance as the sum of squared log ratios of daily highs to lows, divided by four times the natural logarithm of two, times the number of observations. This estimator is theoretically about five times more efficient than the close-to-close method because high and low prices contain additional information about the volatility process. The Garman-Klass estimator, published by Mark Garman and Michael Klass in 1980, goes further by incorporating opening, high, low, and closing prices. The formula combines half the squared log ratio of high to low prices minus a factor involving the log ratio of close to open. This method achieves the minimum variance among estimators using only these four price points, making it particularly valuable for markets where intraday information is meaningful. THE CORE VRP CALCULATION Once both volatility measures are obtained, the VRP calculation is straightforward: subtract realized volatility from implied volatility. A positive result means the market is paying a premium for volatility insurance. A negative result means realized volatility has exceeded expectations, typically indicating market stress. The raw VRP signal receives slight smoothing through an exponential moving average to reduce noise while preserving responsiveness. The default smoothing period of five days balances signal clarity against lag. INTERPRETING THE REGIMES The indicator classifies market conditions into five distinct regimes based on VRP levels. The EXTREME regime occurs when VRP exceeds ten percentage points. This represents an unusual situation where the gap between implied and realized volatility is historically wide. Markets are pricing in significantly more fear than is materializing. Research suggests this often precedes positive equity returns as the premium normalizes. The HIGH regime, between five and ten percentage points, indicates elevated risk aversion. Investors are paying above-average premiums for protection. This often occurs after market corrections when fear remains elevated but realized volatility has begun subsiding. The NORMAL regime covers VRP between zero and five percentage points. This represents the long-term average state of markets where implied volatility modestly exceeds realized volatility. The insurance premium is being collected at typical rates. The LOW regime, between negative two and zero percentage points, suggests either unusual complacency or that realized volatility is catching up to implied volatility. The premium is shrinking, which can precede either calm continuation or increased stress. The NEGATIVE regime occurs when realized volatility exceeds implied volatility. This is relatively rare and typically indicates active market stress. Options were priced for less volatility than actually occurred, meaning volatility sellers are experiencing losses. Historically, deeply negative VRP readings have often coincided with market bottoms, though timing the reversal remains challenging. TERM STRUCTURE ANALYSIS Beyond the basic VRP calculation, sophisticated market participants analyze how volatility behaves across different time horizons. The indicator calculates VRP using both short-term (default ten days) and long-term (default sixty days) realized volatility windows. Under normal market conditions, short-term realized volatility tends to be lower than long-term realized volatility. This produces what traders call contango in the term structure, analogous to futures markets where later delivery dates trade at premiums. The RV Slope metric quantifies this relationship. When markets enter stress periods, the term structure often inverts. Short-term realized volatility spikes above long-term realized volatility as markets experience immediate turmoil. This backwardation condition serves as an early warning signal that current volatility is elevated relative to historical norms. The academic foundation for term structure analysis comes from Scott Mixon's 2007 paper "The Implied Volatility Term Structure" in the Journal of Derivatives, which documented the predictive power of term structure dynamics. MEAN REVERSION CHARACTERISTICS One of the most practically useful properties of the VRP is its tendency to mean-revert. Extreme readings, whether high or low, tend to normalize over time. This creates opportunities for systematic trading strategies. The indicator tracks VRP in statistical terms by calculating its Z-score relative to the trailing one-year distribution. A Z-score above two indicates that current VRP is more than two standard deviations above its mean, a statistically unusual condition. Similarly, a Z-score below negative two indicates VRP is unusually low. Mean reversion signals trigger when VRP reaches extreme Z-score levels and then shows initial signs of reversal. A buy signal occurs when VRP recovers from oversold conditions (Z-score below negative two and rising), suggesting that the period of elevated realized volatility may be ending. A sell signal occurs when VRP contracts from overbought conditions (Z-score above two and falling), suggesting the fear premium may be excessive and due for normalization. These signals should not be interpreted as standalone trading recommendations. They indicate probabilistic conditions based on historical patterns. Market context and other factors always matter. MOMENTUM ANALYSIS The rate of change in VRP carries its own information content. Rapidly rising VRP suggests fear is building faster than volatility is materializing, often seen in the early stages of corrections before realized volatility catches up. Rapidly falling VRP indicates either calming conditions or rising realized volatility eating into the premium. The indicator tracks VRP momentum as the difference between current VRP and VRP from a specified number of bars ago. Positive momentum with positive acceleration suggests strengthening risk aversion. Negative momentum with negative acceleration suggests intensifying stress or rapid normalization from elevated levels. PRACTICAL APPLICATION For equity investors, the VRP provides context for risk management decisions. High VRP environments historically favor equity exposure because the market is pricing in more pessimism than typically materializes. Low or negative VRP environments suggest either reducing exposure or hedging, as markets may be underpricing risk. For options traders, understanding VRP is fundamental to strategy selection. Strategies that sell volatility, such as covered calls, cash-secured puts, or iron condors, tend to profit when VRP is elevated and compress toward its mean. Strategies that buy volatility tend to profit when VRP is low and risk materializes. For systematic traders, VRP provides a regime filter for other strategies. Momentum strategies may benefit from different parameters in high versus low VRP environments. Mean reversion strategies in VRP itself can form the basis of a complete trading system. LIMITATIONS AND CONSIDERATIONS No indicator provides perfect foresight, and the VRP is no exception. Several limitations deserve attention. The VRP measures a relationship between two estimates, each subject to measurement error. The VIX represents expectations that may prove incorrect. Realized volatility calculations depend on the chosen method and lookback period. Mean reversion tendencies hold over longer time horizons but provide limited guidance for short-term timing. VRP can remain extreme for extended periods, and mean reversion signals can generate losses if the extremity persists or intensifies. The indicator is calibrated for equity markets, specifically the S&P 500. Application to other asset classes requires recalibration of thresholds and potentially different data sources. Historical relationships between VRP and subsequent returns, while statistically robust, do not guarantee future performance. Structural changes in markets, options pricing, or investor behavior could alter these dynamics. STATISTICAL OUTPUTS The indicator presents comprehensive statistics including current VRP level, implied volatility from VIX, realized volatility from the selected method, current regime classification, number of bars in the current regime, percentile ranking over the lookback period, Z-score relative to recent history, mean VRP over the lookback period, realized volatility term structure slope, VRP momentum, mean reversion signal status, and overall market bias interpretation. Color coding throughout the indicator provides immediate visual interpretation. Green tones indicate elevated VRP associated with fear and potential opportunity. Red tones indicate compressed or negative VRP associated with complacency or active stress. Neutral tones indicate normal market conditions. ALERT CONDITIONS The indicator provides alerts for regime transitions, extreme statistical readings, term structure inversions, mean reversion signals, and momentum shifts. These can be configured through the TradingView alert system for real-time monitoring across multiple timeframes. REFERENCES Bakshi, G., and Kapadia, N. (2003). Delta-Hedged Gains and the Negative Market Volatility Risk Premium. Review of Financial Studies, 16(2), 527-566. Bollerslev, T., Tauchen, G., and Zhou, H. (2009). Expected Stock Returns and Variance Risk Premia. Review of Financial Studies, 22(11), 4463-4492. Carr, P., and Wu, L. (2009). Variance Risk Premiums. Review of Financial Studies, 22(3), 1311-1341. Garman, M. B., and Klass, M. J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53(1), 67-78. Mixon, S. (2007). The Implied Volatility Term Structure of Stock Index Options. Journal of Empirical Finance, 14(3), 333-354. Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53(1), 61-65.
Pine Script® 인디케이터
EdgeTools의
6