Strategy H4-H1-M15 Triple Screen + TableMaster of Multi-Timeframe Trading: "Triple Screen" Strategy
"▲▼ & BUY/SELL M15 Tags" — H1 Ready signals warn the trader in advance that a reversal is brewing on the medium timeframe.
Settings:
Stochastic Settings: Oscillator length and smoothing adjustment.
Overbought/Oversold: Overbought/oversold level settings (default 80/20).
SL Offset: Buffer in ticks/pips for setting stop-loss beyond extremes.
Usage Instructions:
Long: Background painted light green (H4 Trend UP + H1 Stoch Low), wait for green "BUY M15" tag.
Short: Background painted light red (H4 Trend DOWN + H1 Stoch High), wait for red "SELL M15" tag.
Entry → SL → TP = PROFIT
Short Description (for preview):
Comprehensive "Triple Screen" strategy based on MACD (H4) and Stochastic (H1, M15). Features trend monitoring panel and precise entry signals with automatic Stop Loss calculation.
Technical Notes (for developers):
Hardcoded Timeframes: "240" (H4) and "60" (H1) are hardcoded. For universal use on other timeframe combinations (D1-H4-H1), make these input.timeframe variables.
Repainting: request.security may cause repainting on historical bars (current bar is honest). Standard practice for multi-timeframe TradingView indicators.
Alerts: Built-in alert support for one-click trading convenience.
Indicatori e strategie
EMA Spread Exhaustion DetectorEMA Spread Exhaustion – Reversal Scalper's Tool
Identifies trend exhaustion for high-probability counter-trend entries. Triggers when EMA(4/9/20) stack is fully aligned and spread stretches beyond ±ATR threshold. Ideal confluence for TDI hooks + strong rejection candles on 15s charts. Visual markers, fills, and alerts for quick scalps.
TurboRSI Pro [JOAT]TurboRSI Pro - Multi-Length RSI Ensemble with Dynamic Momentum Analysis
Introduction
TurboRSI Pro is an open-source indicator that reimagines the classic RSI by calculating multiple RSI lengths simultaneously and combining them into a single, more reliable momentum reading. Instead of relying on a single RSI period that may lag or produce false signals, this indicator creates an ensemble of RSI values across a configurable range, providing a smoother and more robust momentum assessment.
The indicator is designed for traders who want deeper insight into momentum conditions without the noise that comes from single-period oscillators.
Originality and Purpose
This indicator is NOT a simple RSI with different settings. It is an original implementation that solves a fundamental problem with traditional RSI:
The Problem with Single-Period RSI: Traditional RSI uses a single lookback period (typically 14). The issue is that different market conditions favor different RSI lengths. A 14-period RSI might work well in one market phase but produce false signals in another. There's no "perfect" RSI length that works in all conditions.
The Multi-Length Solution: TurboRSI Pro calculates RSI across a range of lengths (default: 10 to 20) simultaneously, then averages all values to create a composite reading. This ensemble approach filters out period-specific noise while preserving genuine momentum shifts. When multiple RSI lengths agree, the signal is more reliable.
OB/OS Strength Percentage: The indicator tracks how many individual RSI lengths are in overbought or oversold territory. When 100% of lengths are overbought, it's a much stronger signal than when only 50% are. This percentage-based approach is original to this indicator and provides conviction assessment.
Candle Heatmap Innovation: An optional feature colors price bars based on deviation from a 200-bar linear regression line. This shows when price is statistically overextended (HOT/COLD) independent of RSI, providing another layer of analysis.
How the components work together:
Multi-length RSI ensemble provides a more robust momentum reading than single-period RSI
OB/OS Strength percentages quantify how many timeframes agree on the momentum condition
Dynamic channels expand/contract based on momentum strength across all calculated lengths
Candle heatmap adds statistical price deviation context independent of RSI
Core Concept: Multi-Length RSI Ensemble
Traditional RSI uses a single lookback period (typically 14). The problem is that different market conditions favor different RSI lengths. TurboRSI Pro solves this by:
Calculating RSI across a range of lengths (default: 10 to 20)
Averaging all RSI values to create a composite reading
Tracking how many individual RSI lengths are in overbought or oversold territory
Displaying this information as "OB Strength" and "OS Strength" percentages
This approach filters out noise while preserving genuine momentum shifts.
How the Multi-Length RSI Works
The calculation uses an efficient array-based approach:
int N = maxLength - minLength + 1
float diff = nz(srcInput - srcInput )
for i = 0 to N - 1
int len = minLength + i
float alpha = 1.0 / len
float numRma = alpha * diff + (1 - alpha) * array.get(numArr, i)
float denRma = alpha * math.abs(diff) + (1 - alpha) * array.get(denArr, i)
float rsiVal = denRma != 0 ? 50 * numRma / denRma + 50 : 50
avgRSI += rsiVal
Each RSI length is calculated using the RMA (Running Moving Average) formula, then all values are averaged. The result is a composite RSI that responds to momentum changes while filtering out period-specific noise.
Visual Components
1. Multi-Length RSI Line
The main oscillator line displays the averaged RSI value with a gradient color:
Green gradient when RSI is above 50 (bullish momentum)
Red gradient when RSI is below 50 (bearish momentum)
Color intensity increases as RSI approaches extreme levels
2. Dynamic Channels
Two adaptive channel lines track momentum extremes:
Upper Channel: Expands when multiple RSI lengths enter overbought territory
Lower Channel: Expands when multiple RSI lengths enter oversold territory
Channel width indicates momentum strength across all calculated lengths
3. Candle Heatmap
An optional feature that colors price bars based on deviation from a linear regression line:
Red/Orange bars: Price is significantly above the regression line (overextended to upside)
Blue bars: Price is significantly below the regression line (overextended to downside)
Yellow bars: Price is near the regression line (neutral)
The heatmap uses a 200-bar regression calculation to identify when price has deviated significantly from its statistical trend.
4. Reference Lines
Standard RSI reference levels are displayed:
80 and 20: Extreme overbought/oversold
70 and 30: Standard overbought/oversold thresholds
50: Neutral momentum line
5. Background Zones
Shaded areas indicate the percentage of RSI lengths in extreme territory:
Green shading from bottom: Percentage of lengths in overbought
Red shading from top: Percentage of lengths in oversold
Dashboard Panel
The dashboard displays real-time analysis in a 7-row table:
RSI Value: Current composite RSI reading (large text for visibility)
Momentum: Current state - OVERBOUGHT, OVERSOLD, BULLISH, BEARISH, or NEUTRAL
OB Strength: Percentage of RSI lengths currently above the overbought threshold
OS Strength: Percentage of RSI lengths currently below the oversold threshold
Heat Level: Current price deviation state - HOT, WARM, NEUTRAL, COOL, or COLD
Trend Bias: Overall trend assessment based on RSI level and channel direction
Optional Stochastic RSI
When enabled, an additional Stochastic RSI line is plotted. This applies the stochastic formula to the RSI itself, providing another layer of momentum analysis. The Stochastic RSI is more sensitive to short-term momentum shifts.
Input Parameters
RSI Settings:
Min RSI Length: Starting length for the RSI range (default: 10)
Max RSI Length: Ending length for the RSI range (default: 20)
Source: Price source for calculation (default: ohlc4)
Overbought: Upper threshold (default: 70)
Oversold: Lower threshold (default: 30)
Candle Heatmap:
Enable Heatmap: Toggle bar coloring on/off (default: enabled)
Regression Length: Lookback for linear regression calculation (default: 200)
Display:
Show Dashboard: Toggle the information panel (default: enabled)
Show Dynamic Channels: Toggle channel lines (default: enabled)
Show Stochastic RSI: Toggle additional Stoch RSI line (default: disabled)
Colors:
Bullish: Color for bullish conditions (default: teal)
Bearish: Color for bearish conditions (default: red)
Neutral: Color for neutral conditions (default: gray)
How to Use TurboRSI Pro
Identifying Momentum Shifts:
Watch for RSI crossing above 50 for bullish momentum confirmation
Watch for RSI crossing below 50 for bearish momentum confirmation
Use the gradient color to quickly assess momentum direction
Using OB/OS Strength:
When OB Strength reaches 100%, all RSI lengths are overbought - strong reversal potential
When OS Strength reaches 100%, all RSI lengths are oversold - strong bounce potential
Partial readings (e.g., 50%) indicate mixed conditions across timeframes
Heatmap Analysis:
HOT readings combined with high RSI suggest overextension - caution for longs
COLD readings combined with low RSI suggest oversold conditions - watch for reversal
Use heatmap divergence from RSI for additional confirmation
Channel Interpretation:
Expanding upper channel with rising RSI confirms strong bullish momentum
Expanding lower channel with falling RSI confirms strong bearish momentum
Channel contraction suggests momentum is weakening
Alert Conditions
Six alert conditions are available:
RSI Overbought: RSI crosses above overbought threshold
RSI Oversold: RSI crosses below oversold threshold
RSI Bullish Cross: RSI crosses above 50
RSI Bearish Cross: RSI crosses below 50
All RSI Overbought: Every RSI length is in overbought territory
All RSI Oversold: Every RSI length is in oversold territory
Best Practices
Use on higher timeframes (1H, 4H, Daily) for more reliable signals
Combine with price action analysis - RSI confirms, it does not predict
Pay attention to OB/OS Strength percentages for conviction assessment
The heatmap works best on assets with clear trending behavior
Adjust min/max RSI lengths based on your trading style - wider range for smoother signals
Limitations
Like all oscillators, can remain in overbought/oversold territory during strong trends
The heatmap regression may lag during rapid price movements
Multi-length calculation requires more processing than single RSI
Best suited for swing trading and position trading timeframes
Technical Notes
This indicator is written in Pine Script v6 and uses:
Array-based calculations for efficient multi-length RSI computation
Linear regression for heatmap deviation analysis
Gradient coloring for intuitive visual feedback
State management for dynamic channel calculations
The source code is open and available for review and modification.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management.
-Made with passion by officialjackofalltrades
Engulfing Reversal PatternThe Engulfing Reversal Pattern indicator seeks out both bullish and bearish reversal patterns. This indicator offers the user numerous options to modify the indicator to their needs.
Key features:
Ability to adjust the size of the Engulfing candle in comparison to the prior candle
Ability to adjust the number of breakout candles
Indicator adapts to the Time Frame it is being used in
You can choose between identifying only Bearish patterns, only Bullish patterns or both.
Indicator Arrow size can be adjusted in size.
Advanced Concept V4 Change your trading time zone to New York . To maximize readiness for institutional trading setups based on the prescribed models, traders should set alarms for specific times in the New York Time Zone (EST/EDT), which is generally 10.5 hours behind IST.
Asian Stop Hunt Model
The Stop Hunt Model is a liquidity-based strategy designed to exploit market stop-loss sweeps by aligning with the IPDA daily bias. The core idea is to wait for price to sweep the engineered liquidity of the Asian Session High or Low (after 10:30 AM IST). Once the sweep occurs, the trader confirms the market's true direction via a Change of Character (CHoCH) on the lower timeframe. The entry is then taken only on a retest of the resulting price inefficiency, specifically a Balanced Price Range (BPR) or imbalance, which represents the institutional entry point. By targeting the next major liquidity pool with a minimum 1:3 risk-to-reward ratio, the model prioritizes discipline and quality over frequent trading.
The New York Open Model
The New York Open Model is an index-focused strategy (SPX500, NAS100, US30) that trades solely during the New York Session (9:30 AM – 12:30 PM NYT). It establishes a Range Zone high and low from midnight until the open, treating these boundaries as institutional liquidity targets. Execution is triggered by a mandatory liquidity sweep of one side of this range, followed by a confirming Change of Character (CHoCH) on the 1-minute chart. Entry is taken precisely on the retest of a resulting price inefficiency (like an FVG), aiming for the opposite side of the session range, prioritizing simplicity, timing, and controlled risk over external biases like IPDA.
The ATM Strategy
The ATM Strategy is a high-precision, New York-session trading model designed to capture institutional liquidity moves using the IPDA directional bias. The strategy operates by first defining a Range Zone (00:00 to 8:30 AM NY time) where high and low boundaries act as liquidity targets. Execution is restricted to the Trading Zone (8:30AM to 12:30 PM NY time) and is only triggered when price executes a mandatory liquidity sweep of one range boundary that aligns with the IPDA bias. This sweep must then be confirmed on the 1-minute chart by a Change of Character (CHoCH). Final entry is taken on the retest of a resulting price inefficiency (like an FVG or BPR), with targets set at session highs or lows, ensuring institutional-style execution with high clarity and discipline.
The Central Bank Dealer Range (CBDR)
The Central Bank Dealer Range (CBDR) model is a disciplined, institutional trading strategy used on the 15-minute chart, primarily focusing on London Session liquidity for major currency pairs. The core idea is to align with Interbank Price Delivery Algorithm (IPDA) bias, which dictates a mandatory liquidity sweep (a false breakout of the previous day's high or low) must occur first. Following this sweep, a visible price imbalance (Fair Value Gap) must form within the London Session. Entry is strictly taken only on the retest of this imbalance zone, confirming institutional order flow, with a fixed target at the opposite boundary of the previous day's range.
Asset Volatility Heatmap [SeerQuant]Asset Volatility Heatmap (AVH)
AVH is a cross-sectional volatility dashboard that ranks up to 30 assets and visualizes regime shifts as a time-series heatmap.
It computes annualized historical volatility (%) on a fixed 1D basis, then maps each asset’s volatility into a configurable color spectrum for fast, intuitive scanning of risk conditions across cryptocurrencies.
⚙️ How It Works
1. Daily, Annualized Historical Volatility
Each asset is measured on a fixed 1D timeframe (independent of your chart timeframe). Volatility is annualized and expressed in percentage terms. The user can choose between 1 of 4 volatility estimators: Close-Close (log returns stdev), Parkinson (H/L), Garman-Klass or Rogers-Satchell.
2. Heatmap
A heatmap is plotted on the lower window (sorting is turned on by default). Each row represents a rank position. (Rank #1 highest vol ... Rank #30 lowest vol). This means that tokens will move between rows over time as their volatility changes. The asset labels show the current token sitting in each rank bucket. This setting can be turned off for more of a "random" look.
3. Color Scaling
The user can select how the color range is normalized for visualization.
n = (v - scaleMin) / (scaleMax - scaleMin)
Cross-Section: Scales colors using the current bar’s cross-sectional min/max across the asset list.
Rolling: Scales colors using a lookback window of cross-sectional ranges, so today’s values are judged relative to recent volatility history.
Fixed: Uses your chosen Fixed Scale Min / Max for consistent benchmarking across time.
4. Contrast Control
The Color Contrast control option changes how aggressively the palette emphasizes extremes (useful for making “risk spikes” pop vs keeping gradients smooth).
5. Summary Table + Composite Read
The table highlights the highest vol / lowest vol token, along with average / median volatility, and a simple regime read (low / medium / high cross-sectional volatility).
✨ How to Use (Practical Reads)
Spot risk-on / risk-off transitions: When the heatmap “heats up” broadly (more hot colors across ranks), cross-sectional volatility is expanding (higher dispersion / risk).
Identify which names are driving the narrative: With sorting ON, the top ranks show which assets are currently the volatility leaders — often where attention, liquidity, and positioning stress is concentrated.
Use it as a regime overlay: Low/steady colors across most ranks tends to align with calmer conditions; sharp bright bursts signal volatility events.
✨ Customizable Settings
1. Assets
30 symbol inputs (defaults to crypto, but works across markets)
2. Calculation Settings
Length (lookback)
Volatility Estimator (Close-Close / Parkinson / GK / RS)
3. Style Settings
Color Scheme (SeerQuant / Viridis / Plasma / Magma / Turbo / Red-Blue)
Color Scaling (Cross-Section / Rolling / Fixed)
Scaling Lookback (for Rolling)
Fixed Scale Min / Max (for Fixed)
Color Contrast (emphasize extremes vs smooth gradients)
Sort Heatmap (High → Low)
Gradient Legend toggle
Focus Mode (highlights the chart symbol if included)
Ticker Label Right Padding
🚀 Features & Benefits
Cross-sectional volatility at a glance (dispersion/risk conditions)
Sortable rank heatmap for tracking “who’s hot” in volatility
Multiple estimators for different volatility philosophies
Flexible normalization (current cross-section, rolling context, or fixed benchmarks)
Clean legend + summary stats for quick context
📌 Notes
Sorting changes which token appears in each row over time (rows are rank buckets).
Volatility is computed on 1D even if your chart is lower/higher timeframe.
📜 Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Always consult a licensed financial advisor before making trading decisions. Use at your own risk.
Global Sovereign Spread MonitorIn the summer of 2011, the yield on Italian government bonds rose dramatically while German Bund yields fell to historic lows. This divergence, measured as the BTP-Bund spread, reached nearly 550 basis points in November of that year, signaling what would become the most severe test of the European monetary union since its inception. Portfolio managers who monitored this spread had days, sometimes weeks, of advance warning before equity markets crashed. Those who ignored it suffered significant losses.
The Global Sovereign Spread Monitor is built on a simple but powerful observation that has been validated repeatedly in academic literature: sovereign bond spreads contain forward-looking information about systemic risk that is not fully reflected in equity prices (Longstaff et al., 2011). When investors demand higher yields to hold peripheral government debt relative to safe-haven bonds, they are expressing a view about credit risk, liquidity conditions, and the probability of systemic stress. This information, when properly analyzed, provides actionable signals for traders across all asset classes.
The Science of Sovereign Spreads
The academic study of government bond yield differentials began in earnest following the creation of the European Monetary Union. Codogno, Favero and Missale (2003) published what remains one of the foundational papers in this field, examining why yields on government bonds within a currency union should differ at all. Their analysis, published in Economic Policy, identified two primary drivers: credit risk and liquidity. Countries with higher debt-to-GDP ratios and weaker fiscal positions commanded higher yields, but importantly, these spreads widened dramatically during periods of market stress even when fundamentals had not changed significantly.
This observation led to a crucial insight that Favero, Pagano and von Thadden (2010) explored in depth in the Journal of Financial and Quantitative Analysis. They found that liquidity effects can amplify credit risk during stress periods, creating a feedback loop where rising spreads reduce liquidity, which in turn pushes spreads even higher. This dynamic explains why sovereign spreads often move in non-linear fashion, remaining stable for extended periods before suddenly widening rapidly.
Longstaff, Pan, Pedersen and Singleton (2011) extended this research in their American Economic Review paper by examining the relationship between sovereign credit default swap spreads and bond spreads across multiple countries. Their key finding was that a significant portion of sovereign credit risk is driven by global factors rather than country-specific fundamentals. This means that when spreads widen in Italy, it often reflects broader risk aversion that will eventually affect other asset classes including equities and corporate bonds.
The practical implication of this research is clear: sovereign spreads function as a leading indicator for systemic risk. Aizenman, Hutchison and Jinjarak (2013) confirmed this in their analysis of European sovereign debt default probabilities, finding that spread movements preceded rating downgrades and provided earlier warning signals than traditional fundamental analysis.
How the Indicator Works
The Global Sovereign Spread Monitor translates these academic findings into a systematic framework for monitoring credit conditions. The indicator calculates yield differentials between peripheral government bonds and German Bunds, which serve as the benchmark safe-haven asset in European markets. Italian ten-year yields minus German ten-year yields produce the BTP-Bund spread, the single most important metric for Eurozone stress. Spanish yields minus German yields produce the Bonos-Bund spread, providing a secondary confirmation signal. The transatlantic US-Bund spread captures divergence between the two major safe-haven markets.
Raw spreads are converted to Z-scores, which measure how many standard deviations the current spread is from its historical average over the lookback period. This normalization is essential because absolute spread levels vary over time with interest rate cycles and structural changes in sovereign debt markets. A spread of 150 basis points might have been concerning in 2007 but entirely normal in 2023 following the European debt crisis and subsequent ECB interventions.
The composite index combines these individual Z-scores using weights that reflect the relative importance of each spread for global risk assessment. Italy receives the highest weight because it represents the third-largest sovereign bond market globally and any Italian debt crisis would have systemic implications for the entire Eurozone. Spain provides confirmation of peripheral stress, while the US-Bund spread captures flight-to-quality dynamics between the two primary safe-haven markets.
Regime classification transforms the continuous Z-score into discrete states that correspond to different market environments. The Stress regime indicates that spreads have widened to levels historically associated with crisis periods. The Elevated regime signals rising risk aversion that warrants increased attention. Normal conditions represent typical spread behavior, while the Calm regime may actually signal complacency and potential mean-reversion opportunities.
Retail Trader Applications
For individual traders without access to institutional research teams, the Global Sovereign Spread Monitor provides a window into the macro environment that typically remains opaque. The most immediate application is risk management for equity positions.
Consider a trader holding a diversified portfolio of European stocks. When the composite Z-score rises above 1.0 and enters the Elevated regime, historical data suggests an increased probability of equity market drawdowns in the coming days to weeks. This does not mean the trader must immediately liquidate all positions, but it does suggest reducing position sizes, tightening stop-losses, or adding hedges such as put options or inverse ETFs.
The BTP-Bund spread specifically provides actionable information for anyone trading EUR/USD or European equity indices. Research by De Grauwe and Ji (2013) demonstrated that sovereign spreads and currency movements are closely linked during stress periods. When the BTP-Bund spread widens sharply, the Euro typically weakens against the Dollar as investors question the sustainability of the monetary union. A retail forex trader can use the indicator to time entries into EUR/USD short positions or to exit long positions before spread-driven selloffs occur.
The regime classification system simplifies decision-making for traders who cannot constantly monitor multiple data feeds. When the dashboard displays Stress, it is time to adopt a defensive posture regardless of what individual stock charts might suggest. When it displays Calm, the trader knows that risk appetite is elevated across institutional markets, which typically supports equity prices but also means that any negative catalyst could trigger a sharp reversal.
Mean-reversion signals provide opportunities for more active traders. When spreads reach extreme levels in either direction, they tend to revert toward their historical average. A Z-score above 2.0 that begins declining suggests professional investors are starting to buy peripheral debt again, which historically precedes broader risk-on behavior. A Z-score below minus 1.0 that starts rising may indicate that complacency is ending and risk-off positioning is beginning.
The key for retail traders is to use the indicator as a filter rather than a primary signal generator. If technical analysis suggests a long entry in European stocks, check the sovereign spread regime first. If spreads are elevated or rising, the technical setup becomes higher risk. If spreads are stable or compressing, the technical signal has a higher probability of success.
Professional Applications
Institutional investors use sovereign spread analysis in more sophisticated ways that go beyond simple risk filtering. Systematic macro funds incorporate spread data into quantitative models that generate trading signals across multiple asset classes simultaneously.
Portfolio managers at large asset allocators use sovereign spreads to make strategic allocation decisions. When the composite Z-score trends higher over several weeks, they reduce exposure to peripheral European equities and bonds while increasing allocations to German Bunds, US Treasuries, and other safe-haven assets. This rotation often happens before explicit risk-off signals appear in equity markets, giving these investors a performance advantage.
Fixed income specialists at banks and hedge funds use sovereign spreads for relative value trades. When the BTP-Bund spread widens to historically elevated levels but fundamentals have not deteriorated proportionally, they may go long Italian government bonds and short German Bunds, betting on mean reversion. These trades require careful risk management because spreads can widen further before reversing, but when properly sized they offer attractive risk-adjusted returns.
Risk managers at financial institutions use sovereign spread monitoring as an input to Value-at-Risk models and stress testing frameworks. Elevated spreads indicate higher correlation among risk assets, which means diversification benefits are reduced precisely when they are needed most. This information feeds into position sizing decisions across the entire trading book.
Currency traders at proprietary trading firms incorporate sovereign spreads into their EUR/USD and EUR/CHF models. The relationship between the BTP-Bund spread and EUR weakness is well-documented in academic literature and provides a systematic edge when combined with other factors such as interest rate differentials and positioning data.
Central bank watchers use sovereign spreads to anticipate policy responses. The European Central Bank has demonstrated repeatedly that it will intervene when spreads reach levels that threaten financial stability, most notably through the Outright Monetary Transactions program announced in 2012 and the Transmission Protection Instrument introduced in 2022. Understanding spread dynamics helps investors anticipate these interventions and position accordingly.
Interpreting the Dashboard
The statistics panel provides real-time information that supports both quick assessments and deeper analysis. The composite Z-score is the primary metric, representing the weighted average of all spread Z-scores. Values above zero indicate spreads are wider than their historical average, while values below zero indicate compression. The magnitude matters: a reading of 0.5 suggests modestly elevated stress, while 2.0 or higher indicates conditions similar to historical crisis periods.
The regime classification translates the Z-score into actionable categories. Stress should trigger immediate review of risk exposure and consideration of hedges. Elevated warrants increased vigilance and potentially reduced position sizes. Normal indicates no immediate concerns from sovereign markets. Calm suggests risk appetite may be elevated, which supports risk assets but also creates potential for sharp reversals if sentiment changes.
The percentile ranking provides historical context by showing where the current Z-score falls within its distribution over the lookback period. A reading of 90 percent means spreads are wider than they have been 90 percent of the time over the past year, which is significant even if the absolute Z-score is not extreme. This metric helps identify when spreads are creeping higher before they reach official stress thresholds.
Momentum indicates whether spreads are widening or compressing. Rising momentum during elevated spread conditions is particularly concerning because it suggests stress is accelerating. Falling momentum during stress suggests the worst may be past and mean reversion could be beginning.
Individual spread readings allow traders to identify which component is driving the composite signal. If the BTP-Bund spread is elevated but Bonos-Bund remains normal, the stress may be Italy-specific rather than systemic. If all spreads are widening together, the signal reflects broader flight-to-quality that affects all risk assets.
The bias indicator provides a simple summary for traders who need quick guidance. Risk-Off means spreads indicate defensive positioning is appropriate. Risk-On means spread conditions support risk-taking. Neutral means spreads provide no clear directional signal.
Limitations and Risk Factors
No indicator provides perfect signals, and sovereign spread analysis has specific limitations that users must understand. The European Central Bank has demonstrated its willingness to intervene in sovereign bond markets when spreads threaten financial stability. The Transmission Protection Instrument announced in 2022 specifically targets situations where spreads widen beyond levels justified by fundamentals. This creates a floor under peripheral bond prices and means that extremely elevated spreads may not persist as long as historical patterns would suggest.
Political events can cause sudden spread movements that are impossible to anticipate. Elections, government formation crises, and policy announcements can move spreads by 50 basis points or more in a single session. The indicator will reflect these moves but cannot predict them.
Liquidity conditions in sovereign bond markets can temporarily distort spread readings, particularly around quarter-end and year-end when banks adjust their balance sheets. These technical factors can cause spread widening or compression that does not reflect fundamental credit risk.
The relationship between sovereign spreads and other asset classes is not constant over time. During some periods, spread movements lead equity moves by several days. During others, both markets move simultaneously. The indicator provides valuable information about credit conditions, but users should not expect mechanical relationships between spread signals and subsequent price moves in other markets.
Conclusion
The Global Sovereign Spread Monitor represents a systematic application of academic research on sovereign credit risk to practical trading decisions. The indicator monitors yield differentials between peripheral and safe-haven government bonds, normalizes these spreads using statistical methods, and classifies market conditions into regimes that correspond to different risk environments.
For retail traders, the indicator provides risk management information that was previously available only to institutional investors with access to Bloomberg terminals and dedicated research teams. By checking the sovereign spread regime before executing trades, individual investors can avoid taking excessive risk during periods of elevated credit stress.
For professional investors, the indicator offers a standardized framework for monitoring sovereign credit conditions that can be integrated into broader macro models and risk management systems. The real-time calculation of Z-scores, regime classifications, and component spreads provides the inputs needed for systematic trading strategies.
The academic foundation is robust, built on peer-reviewed research published in top finance and economics journals over the past two decades. The practical applications have been validated through multiple market cycles including the European debt crisis of 2011-2012, the COVID-19 shock of 2020, and the rate normalization stress of 2022.
Sovereign spreads will continue to provide valuable forward-looking information about systemic risk for as long as credit conditions vary across countries and investors respond rationally to changes in default probabilities. The Global Sovereign Spread Monitor makes this information accessible and actionable for traders at all levels of sophistication.
References
Aizenman, J., Hutchison, M. and Jinjarak, Y. (2013) What is the Risk of European Sovereign Debt Defaults? Fiscal Space, CDS Spreads and Market Pricing of Risk. Journal of International Money and Finance, 34, pp. 37-59.
Codogno, L., Favero, C. and Missale, A. (2003) Yield Spreads on EMU Government Bonds. Economic Policy, 18(37), pp. 503-532.
De Grauwe, P. and Ji, Y. (2013) Self-Fulfilling Crises in the Eurozone: An Empirical Test. Journal of International Money and Finance, 34, pp. 15-36.
Favero, C., Pagano, M. and von Thadden, E.L. (2010) How Does Liquidity Affect Government Bond Yields? Journal of Financial and Quantitative Analysis, 45(1), pp. 107-134.
Longstaff, F.A., Pan, J., Pedersen, L.H. and Singleton, K.J. (2011) How Sovereign Is Sovereign Credit Risk? American Economic Review, 101(6), pp. 2191-2212.
Manganelli, S. and Wolswijk, G. (2009) What Drives Spreads in the Euro Area Government Bond Market? Economic Policy, 24(58), pp. 191-240.
Arghyrou, M.G. and Kontonikas, A. (2012) The EMU Sovereign-Debt Crisis: Fundamentals, Expectations and Contagion. Journal of International Financial Markets, Institutions and Money, 22(4), pp. 658-677.
Super Regression Trend█ OVERVIEW
Super Regression Trend is an advanced trend-following indicator that combines classic linear regression with a SuperTrend mechanism based on RMSE (Root Mean Square Error). Instead of traditional ATR, it uses price deviations from the regression line, allowing for highly precise adaptation to current market volatility. The indicator is clean, dynamic, and equipped with optional risk management tools — automatic Take Profit and Stop Loss levels displayed after each trend reversal signal. Perfect for traders seeking solid trend confirmation with built-in position management support.
█ CONCEPT
The indicator was created to combine the advantages of linear regression (smooth trend tracking) with the reliability of the SuperTrend mechanism (trailing stop).
The key element is calculating RMSE based on deviations of the source price from the regression line over a specified period. The band around the regression (RMSE × multiplier) creates dynamic, trailing upper and lower levels. The trend changes only after price closes beyond this band — this allows the indicator to react quickly to new impulses while effectively filtering noise and false breakouts in consolidation.
█ FEATURES
Data source:
- Source price (default: close)
- Regression Length
Calculations:
- Linear regression line (ta.linreg)
- RMSE of deviations within the length window
- Upper and lower bands: regression ± (RMSE × Multiplier)
Trailing mechanism:
Levels are “pulled” in the direction opposite to the trend (minimized/maximized)
Trend change logic:
- Down → Up: close > upper band
- Up → Down: close < lower band
Visualization:
- SuperTrend line with breaks at reversal points
- Optional gradient fill between SuperTrend line and regression
- Optional bar coloring based on current trend
- “Buy” labels (green upward arrow) and “Sell” labels (red downward arrow) only on confirmed trend changes
Risk management:
- Optional automatic TP1/TP2/TP3 and SL levels after each signal
Two calculation modes:
- Candle Multiplier – multiplier of average candle body size (SMA(|open–close|))
- Percentage – percentage of the signal close price
Levels drawn as short horizontal lines
Persistent table in the top-right corner with current TP/SL values
Alerts:
- Buy Signal – triggers only on confirmed uptrend change
- Sell Signal – triggers only on confirmed downtrend change
█ HOW TO USE
Add to chart → paste the code in Pine Editor or search for “Super Regression Trend”.
Main settings:
- Regression Length → default 20 (regression window length)
- RMSE Multiplier → default 2 (key sensitivity parameter)
- Show SuperTrend Line / Fill to Regression / Color Bars → visual options
- Show TP/SL Levels → enable/disable risk management tools
- TP/SL Calculation Mode → “Candle Multiplier” or “Percentage”
- Multipliers/percentages for TP1–TP3 and SL → fully customizable
Interpretation:
- Green line and shading = uptrend
- Red line and shading = downtrend
- Higher RMSE Multiplier = fewer signals, higher quality
- Lower Multiplier = faster reaction, more signals (aggressive mode)
█ APPLICATIONS
Excellent for:
- Classic trend-following (enter with trend, exit on reversal)
- Momentum and breakout strategies
- Automated position management with optional TP/SL levels
Best combined with:
- Support/resistance levels, Pivot Points, psychological round numbers
- Confirmation from oscillators (RSI, Stochastic, MACD)
- Volume or volume profile analysis
Style adaptation:
- Scalping / daytrading → shorter regression length (10–20) and lower Multiplier (1.5–2.0)
- Swing / longer-term positions → longer regression (30–50) and higher Multiplier (2.0–3.0)
█ NOTES
- Works on all markets and timeframes
- Effectiveness depends on matching the RMSE Multiplier to the instrument’s volatility
- Higher Multiplier and Length values = fewer, but significantly more reliable signals
Step Channel█ OVERVIEW
"Step Channel" is a technical analysis indicator that builds a dynamic price channel based on market volatility (ATR) and a step-like logic for updating levels. It is ideal for traders using market structure analysis, price action, as well as trend-following, range-bound, and breakout strategies.
Thanks to the adjustable channel width, the indicator can be easily adapted to various instruments, timeframes, and trading styles – from scalping to swing trading.
█ CONCEPTS
The indicator is a universal trading tool that supports trend detection, trading in consolidation, and breakout-based strategies.
The key feature is the step-like update of the baseline (MID). Unlike classic moving averages:
- the MID line does not react to every candle
- it updates only after breaking a volatility-based level
- each breakout creates a new "step" in the market structure
This keeps the market structure clear, with regime changes being distinct and objective.
█ FEATURES
ATR-based dynamic channel
The channel width automatically adjusts to current volatility – widening during high-activity periods and narrowing in consolidations, ensuring constant adaptation to market conditions.
Structural MID line
Central, adaptive trend line updated in steps after a breakout.
Inner levels (IN)
The zone of typical price movement within the structure. These levels change only after a sustained breakout confirmed by candle close – this exact breakout generates the structural signals (Step UP/DOWN).
Outer levels (OUT)
An orientational zone indicating the potential reach of a strong, single price move beyond the current structure. Price never stays in this zone (levels shift immediately after breaking IN). Primarily used as:
- main take-profit levels
- dynamic SL in aggressive strategies
Structural signals
Generated exclusively at the moment of a real structure change:
- Step UP – upside breakout
- Step DOWN – downside breakout
Signals appear only on the breakout candle.
Built-in alerts
Instant notifications for:
- Step UP
- Step DOWN
█ HOW TO USE
Adding to the chart
Search in the TradingView indicators library: "Step Channel" or paste the code in Pine Editor.
Key parameter configuration:
- ATR Length – longer value = more stable structure (fewer signals)
- Inner Multiplier – sensitivity of inner levels (lower = narrower operational channel)
- Outer Multiplier – reach of outer extremes (higher = further TP)
- Price position interpretation:
- near MID → market equilibrium, potential consolidation
- in IN zone → healthy, controlled trend move
- in OUT zone → only an orientational target for extreme move (price does not stay in this zone)
█ APPLICATIONS
- Trend strategies – entries after Step UP/DOWN signal in the direction of the new trend, re-entry at MID, trailing stop along MID; generally positions only in line with the current structure direction
- Range trading – buying at lower IN/OUT and selling at upper IN/OUT in the absence of structure change
- Breakout strategies – entries on breakout candle close with volume or HTF confirmation
- Position management – SL behind MID or opposite IN, TP at OUT (full) or IN (partial)
- Scalping on low timeframes – quick trades inside the IN channel with tight SL
- Swing trading – trend filtering on HTF and precise entries on LTF after structural signal
█ NOTES
- works on all markets and timeframes
- requires individual adjustment of multipliers to the instrument and trading style
- recommended to use with additional indicators, e.g. RSI, Fibonacci, pivots
Liquidation Heatmap Zones CamnextlevelFind Liquidation zones where the high leverage trades are being liquidated
Supply & Demand (MTF) [Bearly Invested]Overview
This multi-timeframe supply and demand zone indicator identifies institutional price areas using a unique "Last 2 Opposite Candles" methodology. Unlike traditional support/resistance indicators, this script detects zones by analyzing momentum-based impulse moves and marking the base formed by the last two opposite-colored candles before the displacement.
How It Works
Zone Detection Logic
The indicator identifies supply and demand zones through a four-step process:
Momentum Detection: Monitors for consecutive candles with body sizes exceeding the 20-period average body size by a configurable multiplier (default 0.5x)
Impulse Confirmation: When the required number of momentum candles (default: 4 candles within 4-bar span) is detected, the script identifies a potential impulse move
Base Identification: Looks back through all consecutive momentum bars, then scans up to 50 bars to find the last two opposite-colored candles that formed before the impulse
Zone Creation: Creates a supply/demand zone using the combined high and low of those two opposite candles
Multi-Timeframe Analysis
The indicator supports up to three simultaneous timeframes, allowing you to identify higher timeframe zones while trading on lower timeframes. Each timeframe independently calculates zones using its own momentum criteria, providing confluence when multiple timeframe zones align.
Zone Combination Feature
When "Combine Zones" is enabled, overlapping zones from different timeframes or detection instances are automatically merged into single zones. Combined zones display all contributing timeframes in the label (e.g., "15 Min & 30 Min").
Zone Management
Invalidation Methods
Choose between two zone invalidation approaches:
Wick: Zone remains valid until price wicks through the boundary
Close: Zone remains valid until a candle closes through the boundary
Zone Filtering
The script includes built-in filters to reduce noise:
Minimum zone size requirement (10 bars on detection timeframe)
Maximum zone size limit (1.5x ATR)
Minimum 5-bar cooldown between new zone detections
Distance-based filtering (zones beyond max lookback are hidden)
Key Features
Retest & Break Detection
Retests: Automatically marks when price retests an active zone with "R" labels
Breaks: Optionally displays "B" labels when zones are invalidated
Built-in cooldown system prevents label spam (5-bar minimum between retests)
Alert Conditions
Four alert types are included:
Supply Zone Retest
Demand Zone Retest
Supply Zone Break
Demand Zone Break
Configuration Guide
General Settings
Zone Count: High (30 zones), Medium (5), Low (3), or One (single most recent zone per type)
Momentum Count: Number of consecutive momentum candles required (default: 4)
Momentum Span: Maximum bars to scan for momentum confirmation (default: 4)
Max Lookback For Opposite Candles: How far back to search for base candles (default: 50)
Max Distance To Last Bar: Controls historical zone visibility (High: 1250 bars, Normal: 500, Low: 150)
Timeframe Configuration
Enable up to three timeframes simultaneously. When multiple timeframes show the same value (e.g., chart timeframe), duplicate detection automatically disables redundant calculations.
Visual Options
Customizable supply/demand colors with transparency
"Show Historic Zones" toggles visibility of broken/invalidated zones
Text color and label positioning controls
Combined zones display with increased opacity for emphasis
Best Practices
Timeframe Selection: Use higher timeframes (15m, 30m, 1H) for swing trades; lower timeframes work for scalping when combined with HTF confluence
Zone Invalidation: "Close" method reduces false breaks from wicks; "Wick" method is more conservative
Zone Count: Start with "Medium" or "Low" settings to avoid chart clutter, especially on lower timeframes
Momentum Parameters: Lower values (3-4) detect more zones; higher values (5-6) create stricter, higher-quality zones
Combine Zones: Enable this feature to merge overlapping multi-timeframe zones for cleaner charts and stronger confluence areas
Important Notes
Zones are calculated in real-time on the detection timeframe and displayed on your chart timeframe
The indicator looks back a maximum of 2000 bars for calculations
Maximum of 500 boxes/labels can be displayed simultaneously due to Pine Script limitations
Zones older than the "Max Distance" setting are automatically hidden but still tracked for break/retest detection
The "Last 2 Opposite Candles" method may produce zones of varying sizes depending on the range of those base candles
Stochastic RSI with DivergencesStochastic RSI with Divergences - Enhanced Edition
DESCRIPTION
- This is an enhanced version of the classic Stochastic RSI indicator with divergence detection, originally created by @fskrypt (Log RSI), @RicardoSantos (Divergences), @JustUncleL (edits), and @NeoButane (2018 modifications). Full credit to these talented developers for the foundational work.
ENHANCEMENTS & MODIFICATIONS
- This version adds several user-requested features for improved customization and clarity:
- Divergence Signal Labels: Regular divergence signals now display "Buy" (green) and "Sell" (red) instead of generic "R" markers. Hidden divergences show "H-Buy" and "H-Sell" for clearer identification.
- Customizable Colors: User-adjustable colors for both K line (default: blue) and D line (default: orange) allow traders to match their chart themes.
- Adjustable Transparency: Separate opacity controls for the K/D fill shading (default: 70%) and background zones (default: 98%) provide precise visual customization without overwhelming the chart.
- Optional Divergence Lines: Toggle the green and red divergence connecting lines on/off while keeping the Buy/Sell labels visible, reducing visual clutter when desired.
- Organized Settings: All inputs are logically grouped (StochRSI Settings, Divergence Settings, Colors, Opacity) for easier navigation and configuration.
HOW IT WORKS
- The indicator identifies regular and hidden divergences between price action and the Stochastic RSI oscillator:
- Regular Bullish Divergence (Buy): Price makes lower lows while StochRSI makes higher lows - potential reversal signal
- Regular Bearish Divergence (Sell): Price makes higher highs while StochRSI makes lower highs - potential reversal signal
- Hidden Bullish Divergence (H-Buy): Price makes higher lows while StochRSI makes lower lows - trend continuation signal
- Hidden Bearish Divergence (H-Sell): Price makes lower highs while StochRSI makes higher highs - trend continuation signal
- The Stochastic RSI oscillates between 0-100, with readings above 80 indicating overbought conditions and below 20 indicating oversold conditions.
SETTINGS
StochRSI Settings
RSI Length: 14 (default)
Stoch Length: 14 (default)
K Smoothing: 3 (default)
D Smoothing: 3 (default)
Log Scale: Optional logarithmic transformation
Average K & D: Optional blending of both lines
Divergence Settings
Show Divergences: Toggle all divergence signals
Show Hidden Divergences: Toggle H-Buy/H-Sell signals
Show Divergence Lines: Toggle connecting lines between divergence points
Show Divergences Channel: Display fractal channels
Colors
K Line Color: Customize the fast line
D Line Color: Customize the slow line
Opacity
- Background Opacity: Control 20-80 zone shading (0-100)
K/D Fill Opacity: Control area between K and D lines (0-100)
USE CASES
- Momentum trading: Identify overbought/oversold conditions
Divergence trading: Spot potential reversals and trend continuations
Multi-timeframe analysis: Confirm signals across different timeframes
Trend confirmation: Use with other indicators for confluence
CREDITS
- Original concept and code: @fskrypt (Log RSI), @RicardoSantos (Divergence detection), @JustUncleL (modifications), @NeoButane (2018 updates)
Enhanced by: NPR21 (User interface improvements, label modifications, transparency controls)
HOHO Oscillator Squeeze With AGAIG TurnsHOHO OSCILLATOR SQUEEZE WITH AGAIG TURN DETECTION
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OVERVIEW
This powerful indicator combines three proven trading concepts into one visually stunning, highly accurate momentum and trend analysis tool:
• HOHO (Hump Oscillator) - Multi-timeframe momentum oscillator
• Squeeze Indicator - Bollinger Bands/Keltner Channel volatility compression detector
• AGAIG (As Good As It Gets) Turn Detection - Intelligent price reversal identification
The result is a comprehensive trading system that identifies high-probability entry and exit points with exceptional visual clarity.
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KEY FEATURES
HOHO OSCILLATOR
The foundation of this indicator is the Hump Oscillator, which creates distinctive wave patterns ("humps") above and below the zero line. These colorful columns provide instant visual feedback on momentum direction and strength:
• Fast oscillator (thin columns) - Responsive to immediate price action
• Slow oscillator (wide columns) - Confirms underlying trend momentum
• Color-coded bars shift from bright (strong momentum) to dark (weakening momentum)
• Fully customizable MA types (EMA/SMA) and lengths
SQUEEZE DETECTION
Integrated Bollinger Band and Keltner Channel analysis identifies volatility compression:
• Yellow zero-line dots signal active squeeze conditions
• Optional yellow background highlights compression zones
• Anticipates explosive breakout moves
• Adjustable BB and KC parameters for different markets and timeframes
AGAIG TURN DETECTION
Intelligent price reversal identification based on the "As Good As It Gets" methodology:
• Automatically identifies significant market turning points
• Adjustable sensitivity via "Turn Detection Length" (lower = more signals, higher = fewer signals)
• Strength filter ensures only quality setups are marked (1-10 scale)
• Eliminates noise and false signals common in traditional pivot indicators
VISUAL SIGNALS
• BUY arrows (green triangles) mark bullish reversal opportunities
• SELL arrows (red triangles) mark bearish reversal opportunities
• Text labels positioned for optimal readability
• All arrows appear at actual turning points with configurable lookback offset
FLEXIBLE CUSTOMIZATION
• Choose between EMA or SMA for all moving average calculations
• Adjustable oscillator lengths for different trading styles
• Configurable turn detection sensitivity
• Optional bar coloring based on Fast or Slow momentum
• Clean, professional visual design
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HOW TO USE
ENTRY SIGNALS
Look for BUY/SELL arrows combined with:
1. Squeeze conditions (yellow markers) for highest-probability setups
2. Oscillator color confirmation (green for longs, red for shorts)
3. Turn strength that meets your minimum requirements
TREND CONFIRMATION
• Strong green humps = bullish momentum building
• Strong red humps = bearish momentum building
• Oscillator crossing zero = momentum shift
• Color transitions = momentum strengthening or weakening
VOLATILITY ANALYSIS
• Yellow zero-line dots = consolidation/squeeze active
• Expansion after squeeze = high-probability breakout opportunity
• Combine with turn arrows for precise entry timing
PARAMETER TUNING
For scalping/day trading (5m-15m charts):
• Turn Detection Length: 3-5
• Turn Strength: 2-4
For swing trading (1H-4H charts):
• Turn Detection Length: 5-8
• Turn Strength: 3-5
For position trading (Daily charts):
• Turn Detection Length: 8-15
• Turn Strength: 5-7
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CREDITS & ATTRIBUTION
This indicator builds upon the excellent work of:
• HOHO (Hump Oscillator) - Original concept from ThinkorSwim community
• Squeeze Indicator - Based on TTM Squeeze by John Carter
• AGAIG (As Good As It Gets) - Turn detection methodology by NPR21
Converted and enhanced for TradingView with permission from the trading community.
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BEST PRACTICES
✓ Use on liquid markets (major indices, forex pairs, crypto)
✓ Combine with support/resistance levels for confluence
✓ Wait for oscillator color confirmation before entry
✓ Higher turn strength settings = fewer but higher-quality signals
✓ Squeeze breakouts offer exceptional risk/reward opportunities
✓ Practice proper risk management and position sizing
✗ Don't trade every arrow - wait for confluence
✗ Don't ignore the oscillator colors - they show momentum health
✗ Don't use overly sensitive settings in choppy markets
✗ Don't trade counter to the oscillator trend without strong confirmation
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WHAT MAKES THIS INDICATOR UNIQUE
Unlike standalone momentum oscillators or simple pivot indicators, this tool synthesizes three proven methodologies into a single, coherent visual system. The combination of momentum analysis (HOHO), volatility detection (Squeeze), and intelligent turn identification (AGAIG) provides traders with a comprehensive view of market conditions and high-probability trading opportunities.
The indicator's visual design uses color psychology and positioning to make complex market analysis instantly understandable at a glance - critical for fast-moving markets and quick decision-making.
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SUITABLE FOR
• Day traders on 5m-30m timeframes
• Swing traders on 1H-Daily timeframes
• Scalpers seeking momentum confirmation
• Options traders identifying reversal points
• Futures traders (especially /ES, /NQ, /YM)
• Forex traders on major pairs
• Cryptocurrency traders
TBSTurtle Soup Body Pattern
The Turtle Soup Body is a price action pattern derived from the classic Turtle Soup setup, designed to identify false breakouts beyond recent highs or lows, with a strong emphasis on the candle body close.
This pattern occurs when price briefly breaks above a recent swing high (or below a recent swing low), triggering breakout traders, but then fails to sustain the move. Instead of focusing only on wicks, the Turtle Soup Body setup requires the candle body to close back inside the previous range, signaling rejection and loss of breakout momentum.
Key characteristics of the Turtle Soup Body pattern include:
A clearly defined recent high or low (typically a 20-period high/low)
Price breaks the level intraday, creating a false breakout
The candle body closes back below the high (for short setups) or above the low (for long setups)
Confirmation that market participants are trapped on the wrong side of the move
The Turtle Soup Body pattern is commonly used as a mean-reversion or reversal setup, offering tight stop-loss placement and favorable risk–reward ratios. It is especially effective in ranging or overextended market conditions and can be applied across multiple timeframes in the Forex market.
Discipline Sleeping TimeThe Sleeping Time indicator highlights a predefined time window on the chart that represents your sleeping hours. This will help doing backtest easily by filtering out unrealistic result of trades while we are still sleeping.
During the selected period:
- The chart background is softly shaded to visually mark your sleep window
- The first candle of the range is labeled “Sleep”
- The last candle of the range is labeled “Wake Up”
You can also use it for other purpose.
This makes it easy to:
- Visually avoid trading during sleep hours
- Identify when a trading session should be inactive
- Maintain discipline and consistency across different markets and timezones
Key Features:
- Custom Time Range
Define your sleeping hours using a start and end time.
- UTC Offset Selector
Adjust the time window using a UTC offset dropdown (−10 to +13), so the indicator aligns correctly with your local time.
- Clear Visual Markers
Background shading during sleep hours
- Start label: Sleep
- End label: Wake Up
- Customizable Labels
Change label text, size, and style to suit your chart layout.
Best Use Case
Use this indicator to lock in rest time, avoid emotional trades, and respect personal trading boundaries. Because good trades start with good sleep 😴
Sesion Operativa - Codigo InstitucionalThis indicator is designed for institutional and precision traders who need to visualize market liquidity and key session operating ranges without visual clutter.
Unlike standard session indicators, this tool focuses on clarity and the projection of key levels (Highs and Lows) to identify potential future reaction zones.
Key Features:
4 Customizable Sessions: Pre-configured with key institutional times (Pre-NY, NY Open, London, and Asia). Each session is fully adjustable in time, color, and style.
Minimalist Labeling: Displays the session name and operating range (in pips/points) in a clean, direct format (e.g., NY - 45), removing decimals and unnecessary text to keep the chart clean.
Range Projections: Option to project the Highs and Lows of each session forward (N candles) to use them as dynamic support or resistance levels.
Opening Highlight (NYSE): Special feature to highlight candle colors during specific high-volatility times (default 09:30 - 09:35 UTC-5), perfect for identifying manipulation or liquidity injections at the stock market open.
Adjustable Time Zone: Default setting is UTC-5 (New York), but fully adaptable to any user time zone.
The Cantillon Liquidity Trap [SFP] - PRORetail traders chase breakouts. Institutions engineer traps."
The Problem: How often do you see price break a key High/Low, trigger your stop loss, and then immediately reverse in the other direction? This is not bad luck. This is a Liquidity Grab (Swing Failure Pattern). Institutions need your stop orders to fill their large positions. Once they are filled, the market reverses.
How This Tool Helps: The Cantillon Liquidity Trap automatically detects these manipulation points in real-time. It does not just look for "wicks"—it uses a strict institutional algorithm to identify:
Major Pivot Points: (Where the stops are hiding).
The Sweep: (The stop run).
The Failure: (Price closing back inside the range).
Volume Confirmation: (Smart money absorption).
The Signals:
🟥 TRAP (Bearish): A Swing High was swept, but buyers failed to hold. Look for Shorts.
🟩 GRAB (Bullish): A Swing Low was swept, but sellers were absorbed. Look for Longs.
🚀 How to Trade This (The Strategy): This tool provides the "WHEN" (The Trigger). To get the highest win rate, you must combine it with the "WHERE" (The Level).
Optimum Setup: Wait for a "TRAP" signal that aligns perfectly with a Volume Shelf or AVWAP. When "Time" (SFP) meets "Location" (Cantillon Level), you have an A+ Institutional Setup.
This is optimized for 4H, but feel free to play with it.
👇 Works best together with my "the cantillon overlay" signature below.
Delta/Volume Bubble Signals [Quant Z-Score] Maxxed Version Delta/Volume Bubble Signals Maxxed Verison
This indicator combines advanced volume delta analysis with smart filtering to generate high-conviction intraday signals on futures like YM, ES, and NQ (5-minute charts perform particularly well in testing).
Special thanks to L&L Capital for the LNL Trend System, which provides the excellent dynamic chop detection and cloud visuals used here.
A very BIG thanks to tncylyv for the original volume delta bubble script — its Z-score normalization on extreme volume/delta is the foundation of the core detection logic.This entire system is now possible thanks to TradingView's addition of Volume Delta data in the Footprint chart, allowing accurate lower-timeframe delta aggregation without external feeds. Core Concept the indicator identifies extreme volume/delta spikes — moments when significant buying or selling pressure appears — and only signals when multiple confluence filters align. This results in lower-frequency, higher-quality trades that aim to capture institutional momentum while avoiding noise.
How It Works — Key Components Volume Delta Detection (The Heart of the System) Uses TradingView's built-in footprint delta (aggregated from lower TF, default 1-second bars).
Calculates absolute delta and applies a rolling Z-score (default lookback 60 bars) to normalize extremes across different volatility regimes and instruments.
Bubbles visualize spikes above threshold (default 1.7σ).
BUY/SELL signals require the same threshold plus additional filters.
Absorption Filter (Enabled by Default) Detects high volume/delta with minimal price movement ("effort vs result" failure = trapped traders).
Purple glow on bubbles + optional alert.
Signals are suppressed on absorption bars to avoid counter-trend traps.
Trend Filter (Nadaraya-Watson from jdehorty as default) Non-repainting kernel regression line for smooth, adaptive trend following.
Signals only fire when price is on the correct side of the trend line (above for longs, below for shorts). Can be disabled or switched to EMA/WMA/KAMA.
LNL Chop Filter (Tight Mode by Default) Dynamic ATR-based stop zones from L&L's system.
When stop levels appear on both sides of price = sideways/chop (no-go zone).
Signals completely suppressed during chop.
Signals & Visuals
BUY: Small blue "BUY" label below bar.
SELL: Small red "SELL" label above bar.
CLOSE LONG: Tiny dark grey "CLOSE" label above bar (on opposite SELL signal or stop hit).
CLOSE SHORT: Tiny dark grey "CLOSE" label below bar (on opposite BUY signal or stop hit).
No overlap — closes only appear on actual exit/reversal bars.
Alerts (Fully Separate)Individual toggles for:
BUY Signal
SELL Signal
CLOSE LONG (opposite SELL)
CLOSE SHORT (opposite BUY)
Absorption Detected
Unusual Volume/Delta
Usage Tips Best on intraday futures (YM 5-min has shown strong results in testing).
Defaults are tuned for balance: 1.7σ threshold, Tight LNL mode, absorption on.
Strategy version (separate script) adds LNL trailing stops for actual backtesting/exits.
Customize freely — try different LNL modes (Net for wider range), trend types, or Z-thresholds.
To backtest and optimize using the matching strategy which I created as well.
Important: Forward Test Thoroughly This indicator was refined on historical data, so there's always risk of over-fitting.
Always forward test on live or paper accounts for weeks/months before real capital: Validate across different market regimes (trending, ranging, high/low volatility).
Compare out-of-sample periods.
Adjust one parameter at a time and re-validate forward.
Markets change — what worked yesterday may need tweaking tomorrow.
Feel free to use, modify, and share. Good luck, and trade well! — Max
ORB | Feng FuturesThe ORB | Feng Futures indicator automatically detects the Opening Range Breakout (ORB) for each trading session, plotting the High, Low, and Midline in real time. This tool is built for futures traders who rely on ORB structure to confirm trends, identify breakout zones, and recognize reversal areas early in the session.
Features:
• Auto-calculated ORB High, Low, and Midline
• Multi-timezone session support (NY, Chicago, London, Tokyo, etc.)
• Customize ORB time range and time window for display
• Real-time updating lines that freeze at session close
• Optional labels with customizable size, color, and offset
• Save and view multiple previous ORB sessions
• Full color customization for all levels
• Automatically hides on higher timeframes (Daily+) to reduce clutter
• Works on ES, NQ, and all intraday futures charts
• Works on stocks, crypto, forex, and other tradeable assets where ORB is applicable
Disclaimer: This indicator is for educational purposes only and does not constitute financial advice. Trading futures involves significant risk and may not be suitable for all investors. Always do your own research and use proper risk management.
NQ Volume Flip + Heiken Ashi Wick BreakThe HA Wick Break (second indicator) will ONLY alert and plot arrows if the bar is ALSO a true volume color flip bar
Dynamic ATR-based Renko Overlay - Non repaintingDaily ATR-Based Renko Overlay
Overview
This Pine Script v5 indicator creates a dynamic Renko overlay on your time-based charts (optimized for 1-minute timeframes), using the previous period's ATR from a user-specified higher timeframe (default: 1-hour) to determine brick sizes. Unlike traditional Renko charts, this is an overlay that draws Renko bricks directly on top of your existing candles, allowing you to combine the noise-filtering power of Renko with the full features of time-based charts.
It's designed for traders who want Renko's trend-clarity benefits without switching chart types, especially useful for intraday trading in volatile markets like forex, stocks, or crypto.
Key Features
- Adaptive Brick Sizing: Brick size is calculated as a percentage (default 40%) of the previous period's ATR (Average True Range, default length 14) from the selected higher timeframe (default: 1-hour). This makes bricks volatility-adjusted—larger in high-vol periods to reduce noise, smaller in low-vol for more detail.
- Periodic Recalculation: Resets brick size at the start of each new period based on the user-specified reset timeframe (default: daily), using the prior period's ATR from the chosen timeframe. This ensures relevance without unwanted disruptions.
- Traditional Renko Logic: Uses 1-box reversal (a full brick against the trend to reverse). Bricks form based on closing prices, ignoring time and minor fluctuations.
- Visual Style: Stepped lines with green (up) and red (down) fills for a box-like appearance. Semi-transparent for easy overlay on candles.
- Customizable Inputs:
- ATR Length: Adjust the ATR period (default: 14).
- Percentage of ATR: Fine-tune brick sensitivity (default: 0.4 or 40%; range 0-1).
- ATR Timeframe: Specify the timeframe for ATR calculation (default: "60" for 1-hour; enter as a string like "240" for 4-hour, "D" for daily, etc.).
- Reset Timeframe: Specify the period for recalculating the brick size (default: "D" for daily; enter as a string like "W" for weekly, "M" for monthly, etc.).
How It Works
1. Fetches ATR from the user-specified timeframe via `request.security` for higher-timeframe volatility data.
2. On new periods based on the reset timeframe (or first load), sets brick size to `percent * ATR_HTF`.
3. Tracks Renko "close" and "previous close" to calculate bricks:
- Upward moves add green bricks in multiples of the size.
- Downward moves add red bricks.
- Reversals require a full brick against the direction.
4. Plots and fills create the overlay, updating on each 1-min bar close.
Add it to a 1-minute chart for best results—bricks will adapt periodically while you retain full candle visibility.
Why This Indicator is Helpful
TradingView's native Renko charts are powerful but come with limitations that can frustrate serious traders:
- No Bar Replay: Native Renko doesn't support TradingView's bar replay feature, making it hard to simulate historical trading sessions.
- Inaccurate/Repainting Strategy Testing: Strategies on native Renko can repaint or lack precision due to the non-time-based nature, leading to unreliable backtests.
- Limited Data History: Fast Renko timeframes (e.g., small bricks) often load very little historical data, restricting long-term analysis.
This overlay solves these by building Renko on a time-based chart:
- Full Bar Replay Support: Replay sessions as usual on your 1-min chart—the Renko follows along.
- Accurate, Non-Repainting Testing: Test strategies on the underlying time chart without repainting issues, as Renko is derived from closes.
- Unlimited Data Depth: Access TradingView's full historical data for 1-min charts (up to years of bars), not limited by Renko's data constraints.
- Hybrid Analysis: Overlay Renko on candles to spot trends while using volume, indicators (e.g., RSI, MAs), or drawing tools that don't work well on native Renko.
It's a game-changer for trend-following, breakout strategies, or filtering noise in short-term trades. No more switching charts—get the best of both worlds!
Usage Tips
- Best on 1-min charts for intraday precision, but experiment with others.
- Tune the percentage lower (e.g., 0.3) for more bricks/sensitivity, higher (e.g., 0.5) for fewer/false-signal reduction.
- Adjust the ATR timeframe to match your strategy—e.g., "240" for longer-term volatility or "15" for shorter.
- Customize the reset timeframe for different recalculation frequencies—e.g., "W" for weekly resets to capture broader market shifts, or "240" for every 4 hours.
- Combine with alerts: right now I am experimenting with 90 period EMA and the Renko brick pullbacks to find some EDGE
If you find this useful, give it a thumbs up or share your tweaks in the comments. Feedback welcome—happy trading! 🚀
