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.
週期
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.
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.
Prev Day ±1% BoundaryThis indicator plots dynamic intraday price bands based on the previous day’s close. It calculates a reference price using yesterday’s daily close and draws:
An upper boundary at +1% above the previous close
A lower boundary at –1% below the previous close
These levels are shown as horizontal lines across all intraday bars, with an optional shaded zone between them.
How to use:
Use the boundaries as intraday reference levels for potential support, resistance, or mean-reversion zones.
When price trades near the upper band, it may indicate short-term extension to the upside relative to the prior close.
When price trades near the lower band, it may indicate short-term extension to the downside.
The shaded region between the lines highlights a ±1% normal fluctuation zone around the previous day’s closing price.
This tool is especially useful for intraday traders on indices like SPX, providing quick visual context for how far price has moved relative to the prior session’s close.
UNDETECTED FX - Psychologic LevelsThis indicator automatically plots major 250-pip psychological levels on XAUUSD and highlights the price zones around them. These levels act as strong reaction points where liquidity, reversals, and institutional activity commonly occur.
What the Indicator Does
✔ Plots every 250-pip level starting from a user-defined base (e.g., 4050 → 4075 → 4100 → 4125 → …)
✔ Each level is represented by a thick black horizontal line for maximum visual clarity
✔ Around every 250-pip level, the indicator draws a liquidity zone
Top of zone: +200 pips
Bottom of zone: –200 pips
(configured as ± zoneHalf in settings)
✔ Uses extend: both, so levels stretch across the entire chart and stay fixed, no matter how far you scroll
✔ Zones are filled with a customizable color for clear premium/discount visualization
✔ The indicator never repaints and requires no updates after drawing — all levels are fixed on their price coordinates
Why It’s Useful
🔹 Helps quickly identify institutional levels where gold often reacts
🔹 Acts as a framework for scalping, intraday trading, and swing bias
🔹 Makes it easy to spot liquidity sweeps, rejections, and premium/discount areas
🔹 Clearly shows market structure breaks around key psychological levels
🔹 Forces discipline by creating predefined, fixed levels for trading decisions
Best Use Case
XAUUSD scalpers
Intraday traders who rely on precision entries
Traders who use psychological levels, liquidity grabs, or smart-money concepts
Anyone wanting a clean, non-cluttered chart with high-impact levels only
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.
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
TrendStrike: The Pullback EngineTrendStrike: The Pullback Engine - The Ultimate Pullback entry System
ApexFlow: Sniper Pro is a complete day-trading system designed to filter out market noise and identify high-probability entries. It combines institutional trend filters, structural support & resistance, and volatility checks to ensure you only trade when the odds are stacked in your favor.
🎯 How It Works:
The "King" Filter (EMA 200):
White Line: The script forces you to trade with the major trend.
Rule: If price is Above the White Line, it only looks for LONGS. If Below, it only looks for SHORTS.
The Trend Cloud (SMA 50 vs SMA 100):
🔵 Blue Cloud: Bullish Trend. Look for buys on dips.
🟠 Orange Cloud: Bearish Trend. Look for sells on rallies.
⛔ The "Chop" Safety (ADX Filter):
The system includes an ADX volatility filter. If the market is chopping sideways (ADX < 20), the dashboard will go gray and ALL signals are blocked to save you from fake-outs.
🌊 Structural Support & Resistance:
Purple Lines: Major Resistance zones.
Blue Lines: Major Support zones.
Use these to take profits.
🚀 The Signals (Entry Guide):
The script waits for a Pullback to the trend line (SMA 50) and only fires if the price bounces with strong momentum and volume.
🚀 LONG SIGNAL (Green Rocket):
Trend is UP, Price dipped to the 50 SMA, then bounced with a Green Candle + High Volume.
Exit: A red Stop Loss line is drawn automatically below the candle.
🩸 SHORT SIGNAL (Red Drop):
Trend is DOWN, Price rallied to the 50 SMA, then rejected with a Red Candle + High Volume.
Exit: A green Stop Loss line is drawn automatically above the candle.
📊 The Dashboard:
Located on the left, it gives you a live readout of the market health:
MAJOR TREND: Tells you if you are in an UPTREND or DOWNTREND.
VOLUME: Shows the current candle's volume. It lights up Green for buying pressure and Red for selling pressure.
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.
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
Zero Lag EMA_BhavatThis is a test script for zelma. This is intended to cut down the lag from traditional ema indicators.
window//@version=5
indicator("Smart Money Time Windows (GMT+3:30)", overlay=true)
// ✅ Window 1 — 08:30 to 09:05 Tehran Time
w1 = time(timeframe.period, "0830-0905", "Asia/Tehran")
// ✅ Window 2 — 13:50 to 14:40 Tehran Time
w2 = time(timeframe.period, "1350-1440", "Asia/Tehran")
// ✅ Window 3 — 17:15 to 18:00 Tehran Time
w3 = time(timeframe.period, "1715-1800", "Asia/Tehran")
bgcolor(not na(w1) ? color.new(color.blue, 85) : na)
bgcolor(not na(w2) ? color.new(color.orange, 85) : na)
bgcolor(not na(w3) ? color.new(color.purple, 85) : na)
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.
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.
5-Bar BreakoutThis indicator shows if the price is breaking out above the high or the low of the previous 5 bars
Renko Scalp ScannerThis scanner is optimized for short term bursts for Renko.
DESCRIPTION: This indicator scans the 7 major forex pairs (EURUSD, GBPUSD, USDJPY, USDCHF, AUDUSD, USDCAD, NZDUSD) on 1-pip Renko charts. It ranks them from BEST (#1, top row) to WORST (#7, bottom row) based on a predictive score (0-100) that combines LIVE momentum (current run length, whipsaws, brick timing) + 24-HOUR HISTORICAL consistency (clean long runs, stability).
Higher score = longer, cleaner, more predictable runs ahead (backtested 74% hit rate for 5+ brick continuations).
HOW TO USE THE TABLE:
1. Add to a 1-second Renko chart (Traditional, Box Size: 0.0001 for non-JPY; 0.01 for JPY pairs).
2. RANK: Position 1–7 (green highlight on #1 = switch to this pair NOW).
3. PAIR: Symbol + direction arrow (↑=buy bias, ↓=sell bias).
4. SCORE: 0–100 total (≥85=monster run; ≥75=strong; ≥60=decent; <60=avoid).
5. RUN │ HIST% │ SEC: Current live run length │ % of 24h runs that were clean 8+ bricks │ Live avg seconds per brick (ideal 5–12s).
6. Trade the #1 pair in the arrow direction until whipsaw or score drops <75. Set alerts for score ≥83.
Backtested on 1-year data: Catches 84% of 10+ brick runners. Refreshes every second.
猛の掟・初動スクリーナー_完成版//@version=5
indicator("猛の掟・初動スクリーナー_完成版", overlay=true)
// =============================
// 入力パラメータ
// =============================
emaLenShort = input.int(5, "短期EMA", minval=1)
emaLenMid = input.int(13, "中期EMA", minval=1)
emaLenLong = input.int(26, "長期EMA", minval=1)
macdFastLen = input.int(12, "MACD Fast", minval=1)
macdSlowLen = input.int(26, "MACD Slow", minval=1)
macdSignalLen = input.int(9, "MACD Signal", minval=1)
macdZeroTh = input.float(0.2, "MACDゼロライン近辺とみなす許容値", step=0.05)
volMaLen = input.int(5, "出来高平均日数", minval=1)
volMinRatio = input.float(1.3, "出来高倍率(初動判定しきい値)", step=0.1)
volStrongRatio = input.float(1.5, "出来高倍率(本物/三点シグナル用)", step=0.1)
highLookback = input.int(60, "直近高値の参照本数", minval=10)
pullbackMin = input.float(5.0, "押し目最小 ", step=0.5)
pullbackMax = input.float(15.0, "押し目最大 ", step=0.5)
breakLookback = input.int(15, "レジブレ後とみなす本数", minval=1)
wickBodyMult = input.float(2.0, "ピンバー:下ヒゲが実体の何倍以上か", step=0.5)
// ★ シグナル表示 ON/OFF
showMou = input.bool(true, "猛シグナルを表示")
showKaku = input.bool(true, "確シグナルを表示")
// =============================
// 基本指標計算
// =============================
emaShort = ta.ema(close, emaLenShort)
emaMid = ta.ema(close, emaLenMid)
emaLong = ta.ema(close, emaLenLong)
= ta.macd(close, macdFastLen, macdSlowLen, macdSignalLen)
volMa = ta.sma(volume, volMaLen)
volRatio = volMa > 0 ? volume / volMa : 0.0
recentHigh = ta.highest(high, highLookback)
prevHigh = ta.highest(high , highLookback)
pullbackPct = recentHigh > 0 ? (recentHigh - close) / recentHigh * 100.0 : 0.0
// ローソク足
body = math.abs(close - open)
upperWick = high - math.max(open, close)
lowerWick = math.min(open, close) - low
// =============================
// A：トレンド条件
// =============================
emaUp = emaShort > emaShort and emaMid > emaMid and emaLong > emaLong
goldenOrder = emaShort > emaMid and emaMid > emaLong
aboveEma2 = close > emaLong and close > emaLong
trendOK = emaUp and goldenOrder and aboveEma2
// =============================
// B：MACD条件
// =============================
macdGC = ta.crossover(macdLine, macdSignal)
macdNearZero = math.abs(macdLine) <= macdZeroTh
macdUp = macdLine > macdLine
macdOK = macdGC and macdNearZero and macdUp
// =============================
// C：出来高条件
// =============================
volInitOK = volRatio >= volMinRatio // 8条件用
volStrongOK = volRatio >= volStrongRatio // 三点シグナル用
volumeOK = volInitOK
// =============================
// D：ローソク足パターン
// =============================
isBullPinbar = lowerWick > wickBodyMult * body and lowerWick > upperWick and close >= open
isBullEngulf = close > open and open < close and close > open
isBigBullCross = close > emaShort and close > emaMid and open < emaShort and open < emaMid and close > open
candleOK = isBullPinbar or isBullEngulf or isBigBullCross
// =============================
// E：価格帯（押し目＆レジブレ）
// =============================
pullbackOK = pullbackPct >= pullbackMin and pullbackPct <= pullbackMax
isBreakout = close > prevHigh and close <= prevHigh
barsSinceBreak = ta.barssince(isBreakout)
afterBreakZone = barsSinceBreak >= 0 and barsSinceBreak <= breakLookback
afterBreakPullbackOK = afterBreakZone and pullbackOK and close > emaShort
priceOK = pullbackOK and afterBreakPullbackOK
// =============================
// 8条件の統合
// =============================
allRulesOK = trendOK and macdOK and volumeOK and candleOK and priceOK
// =============================
// 最終三点シグナル
// =============================
longLowerWick = lowerWick > wickBodyMult * body and lowerWick > upperWick
macdGCAboveZero = ta.crossover(macdLine, macdSignal) and macdLine > 0
volumeSpike = volStrongOK
finalThreeSignal = longLowerWick and macdGCAboveZero and volumeSpike
buyConfirmed = allRulesOK and finalThreeSignal
// =============================
// 描画
// =============================
plot(emaShort, color=color.new(color.yellow, 0), title="EMA 短期(5)")
plot(emaMid, color=color.new(color.orange, 0), title="EMA 中期(13)")
plot(emaLong, color=color.new(color.blue, 0), title="EMA 長期(26)")
// シグナル表示（ON/OFF付き）
plotshape(showMou and allRulesOK, title="猛の掟 8条件クリア候補", location=location.belowbar, color=color.new(color.lime, 0), text="猛")
plotshape(showKaku and buyConfirmed, title="猛の掟 最終三点シグナル確定", location=location.belowbar, color=color.new(color.yellow, 0), text="確")
// =============================
// アラート条件
// =============================
alertcondition(allRulesOK, title="猛の掟 8条件クリア候補", message="猛の掟 8条件クリア候補シグナル発生")
alertcondition(buyConfirmed, title="猛の掟 最終三点シグナル確定", message="猛の掟 最終三点シグナル＝買い確定")
VIX/VXV Ratio (TitsNany)This script plots the VXV/VIX ratio, which compares medium-term volatility (90-day fear) to short-term volatility (30-day fear). When the ratio rises above key levels like 1.16 or 1.24, it signals that traders expect future stress, often preceding market pullbacks. When the ratio falls toward or below 1.0, short-term fear is spiking, which typically occurs during active selloffs or volatility events. In short, elevated readings warn of potential market drops ahead, while sharp declines in the ratio reflect panic already hitting the market.
CRR - Reloj Sesiones & DominioIt uses simple rules:
00:00 – 07:00 → Tokyo / ASIA
07:00 – 12:00 → London / EUROPE
12:00 – 21:00 → New York / AMERICA
21:00 – 24:00 → Outside main sessions
Each session is assigned a color:
Tokyo → Blue
London → Yellow
New York → Green
Outside → Gray
2. Displays the current time in GMT format
Example: 14:32 GMT
3. Minimalist on-screen display (HUD)
The top center of the screen shows:
Continent (ASIA / EUROPE / AMERICA)
Which session is currently dominant (TOKYO / LONDON / NEW YORK)
The GMT time
All in a sleek table with dynamic colors based on the session.
🧠 In short:
A smart clock that tells you which session is dominant, which continent you're in, and what time it is in GMT, with a nice on-screen HUD.
NoProcess PivotsNoProcess Pivots
Visualize the structural framework of price action with NoProcess Pivots, a precision tool for multi-timeframe confluence trading.
Pivots are mathematically derived levels where price statistically finds support, resistance, or equilibrium. Institutional order flow respects these levels as key decision points where liquidity pools form and inefficiencies seek rebalancing.
NoProcess Pivots displays historical pivot ranges as period-bounded zones across Daily, Weekly, and Quarterly timeframes—allowing you to observe how price has respected or violated these levels over time. By projecting ±33% extensions beyond R1/S1, traders can identify targets, retracement levels, and key reversal points.
Cross-reference pivots across multiple timeframes to find confluence zones where Daily, Weekly, and Quarterly levels stack. These high-conviction areas offer the clearest setups for entries and exits.
Features:
Multi-timeframe pivots: Daily, Weekly, Quarterly
Historical levels with adjustable depth
Period-bounded zones
±33% extensions
Adaptive light/dark mode table
Real-time Δ PP percentage
Pivot cross alerts
Built for traders who respect the math behind the markets.
