RSI Trend Authority [JOAT]RSI Trend Authority - VAR-RSI with OTT Trend Detection System
Introduction
RSI Trend Authority is an open-source overlay indicator that combines Variable Index Dynamic Average (VAR) smoothed RSI with the Optimized Trend Tracker (OTT) to create a complete trend detection and signal generation system. Unlike traditional RSI which oscillates in a separate pane, this indicator scales the RSI to price and overlays it directly on your chart, making trend analysis more intuitive.
The indicator generates clear BUY and SELL signals when the smoothed RSI crosses the OTT trailing stop line, providing actionable entry points with trend confirmation.
Originality and Purpose
This indicator is NOT a simple mashup of RSI and moving averages. It is an original implementation that transforms RSI into a trend-following overlay system:
Why VAR Smoothing? Traditional RSI is noisy and produces many false signals. The Variable Index Dynamic Average (VAR) is an adaptive smoothing algorithm based on the Chande Momentum Oscillator principle. It adjusts its smoothing factor based on market conditions - responding quickly during trends and smoothing out during choppy markets. This creates an RSI that filters noise while preserving genuine momentum shifts.
Why OTT Trailing Stop? The Optimized Trend Tracker (OTT) is a percentage-based trailing stop mechanism that only moves in the direction of the trend. When VAR-RSI crosses above OTT, a bullish trend is confirmed; when it crosses below, a bearish trend is confirmed. This provides clear, actionable signals rather than subjective interpretation.
Price Scaling Innovation: By scaling RSI (0-100) to price using the formula (RSI * close / 50), the indicator overlays directly on the price chart. This allows traders to see how momentum relates to actual price levels, making trend analysis more intuitive than a separate oscillator pane.
ATR Boundaries: Optional volatility-based boundaries show when price is extended relative to its normal range, helping identify potential reversal zones.
How the components work together:
VAR smoothing removes RSI noise while preserving trend information
OTT provides a dynamic trailing stop that generates clear crossover signals
Price scaling allows direct overlay on the chart for intuitive analysis
ATR boundaries add volatility context for profit target estimation
Core Components
1. VAR-RSI (Variable Index Dynamic Average RSI)
The foundation of this indicator is the VAR smoothing algorithm applied to RSI. VAR is an adaptive moving average that adjusts its smoothing factor based on the Chande Momentum Oscillator principle:
f_var_calc(float data, int length) =>
int a = 9
float b = data > nz(data ) ? data - nz(data ) : 0.0
float c = data < nz(data ) ? nz(data ) - data : 0.0
float d = math.sum(b, a)
float e = math.sum(c, a)
float f = nz((d - e) / (d + e))
float g = math.abs(f)
float h = 2.0 / (length + 1)
float x = ta.sma(data, length)
This creates an RSI that:
Responds quickly during trending conditions
Smooths out during choppy, sideways markets
Reduces false signals compared to raw RSI
2. OTT (Optimized Trend Tracker)
The OTT acts as a dynamic trailing stop that follows the VAR-RSI:
In uptrends, OTT trails below the VAR-RSI line
In downtrends, OTT trails above the VAR-RSI line
The OTT Percent parameter controls how closely it follows
When VAR-RSI crosses above OTT, a bullish trend is confirmed. When VAR-RSI crosses below OTT, a bearish trend is confirmed.
3. Price Scaling
The RSI (0-100 scale) is converted to price scale using:
float scaleFactor = close / 50.0
float varRSIScaled = varRSI * scaleFactor
This allows the indicator to overlay directly on price, showing how momentum relates to actual price levels.
Visual Components
VAR-RSI Line (Cyan/Magenta)
The main indicator line with gradient coloring:
Cyan gradient when RSI is above 50 (bullish)
Magenta gradient when RSI is below 50 (bearish)
Line thickness of 3 for clear visibility
OTT Line (Yellow Circles)
The trailing stop line displayed as circles:
Acts as dynamic support in uptrends
Acts as dynamic resistance in downtrends
Crossovers generate trading signals
Trend Fill
The area between VAR-RSI and OTT is filled:
Cyan fill during bullish trends
Magenta fill during bearish trends
Fill transparency allows price visibility
Buy position and LONG on Dashboard with a Uptrend:
ATR Boundaries (Optional)
Dotted lines showing volatility-based price boundaries:
Upper band: Close + (ATR x Multiplier)
Lower band: Close - (ATR x Multiplier)
Color matches current trend direction
Buy/Sell Signals
Clear labels appear at signal points:
BUY label below bar when VAR-RSI crosses above OTT
SELL label above bar when VAR-RSI crosses below OTT
Additional glow circles highlight signal bars
Bar Coloring
Optional feature that colors price bars:
Cyan bars during bullish trend
Magenta bars during bearish trend
Dashboard Panel
The 8-row dashboard provides comprehensive status information:
Signal: Current position - LONG or SHORT (large text)
VAR-RSI: Current smoothed RSI value (large text)
RSI State: OVERBOUGHT, OVERSOLD, BULLISH, or BEARISH
OTT Trend: UPTREND or DOWNTREND based on OTT direction
Bars Since: Number of bars since last signal
Price: Current close price (large text)
OTT Level: Current OTT trailing stop value
Input Parameters
RSI Settings:
RSI Length: Period for RSI calculation (default: 100)
Source: Price source (default: close)
VAR Settings:
VAR Length: Adaptive smoothing period (default: 50)
OTT Settings:
OTT Period: Trailing stop calculation period (default: 30)
OTT Percent: Distance percentage for trailing stop (default: 0.2)
ATR Trend Boundaries:
Show ATR Boundaries: Toggle visibility (default: enabled)
ATR Length: Period for ATR calculation (default: 14)
ATR Multiplier: Distance multiplier (default: 2.0)
Display Options:
Show Buy/Sell Signals: Toggle signal labels (default: enabled)
Show Status Table: Toggle dashboard (default: enabled)
Table Position: Choose corner placement
Color Bars by Trend: Toggle bar coloring (default: enabled)
Color Scheme:
Bullish Color: Main bullish color (default: cyan)
Bearish Color: Main bearish color (default: magenta)
OTT Line: Trailing stop color (default: yellow)
VAR-RSI Line: Main line color (default: teal)
ATR colors for boundaries
How to Use RSI Trend Authority
Signal-Based Trading:
Enter LONG when BUY signal appears (VAR-RSI crosses above OTT)
Enter SHORT when SELL signal appears (VAR-RSI crosses below OTT)
Use the OTT line as a trailing stop reference
Trend Confirmation:
Cyan fill indicates bullish trend - favor long positions
Magenta fill indicates bearish trend - favor short positions
Check RSI State in dashboard for momentum context
Using the Dashboard:
Monitor "Bars Since" to assess signal freshness
Check RSI State for overbought/oversold warnings
Use OTT Level as a reference for stop placement
ATR Boundaries:
Price near upper ATR band in uptrend suggests extension
Price near lower ATR band in downtrend suggests extension
Boundaries help identify potential reversal zones
Parameter Optimization
For Faster Signals:
Decrease RSI Length (try 50-80)
Decrease VAR Length (try 30-40)
Decrease OTT Period (try 15-25)
For Smoother Signals:
Increase RSI Length (try 120-150)
Increase VAR Length (try 60-80)
Increase OTT Period (try 40-50)
For Tighter Stops:
Decrease OTT Percent (try 0.1-0.15)
For Wider Stops:
Increase OTT Percent (try 0.3-0.5)
Alert Conditions
Three alert conditions are available:
Buy Signal: VAR-RSI crosses above OTT
Sell Signal: VAR-RSI crosses below OTT
Trend Change: OTT direction changes
Understanding the OTT Calculation
The OTT uses a percentage-based trailing mechanism:
float farkOTT = mavgOTT * ottPercent * 0.01
float longStopCalc = mavgOTT - farkOTT
float shortStopCalc = mavgOTT + farkOTT
longStop := mavgOTT > nz(longStop ) ? math.max(longStopCalc, nz(longStop )) : longStopCalc
shortStop := mavgOTT < nz(shortStop ) ? math.min(shortStopCalc, nz(shortStop )) : shortStopCalc
This ensures the trailing stop only moves in the direction of the trend, never against it.
Best Practices
Use on 1H timeframe or higher for more reliable signals
Wait for signal confirmation before entering trades
Consider RSI State when evaluating signal quality
Use ATR boundaries for profit target estimation
The longer RSI length (100) provides smoother trend detection
Combine with support/resistance analysis for better entries
Limitations
Signals may lag during rapid price movements due to smoothing
Works best in trending markets; may whipsaw in ranges
The overlay nature means RSI values are scaled, not absolute
Default parameters are optimized for crypto and forex; adjust for other markets
Technical Notes
This indicator is written in Pine Script v6 and uses:
VAR (Variable Index Dynamic Average) for adaptive smoothing
OTT (Optimized Trend Tracker) for trailing stop calculation
ATR for volatility-based boundaries
Gradient coloring for intuitive trend visualization
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
Indicatori e strategie
UT Bot Gereee88 (XAUUSD pip partial TP)This strategy is based on the UT Bot trading logic and is designed for swing trading with automated trade management.
It includes multiple configurable partial take profit levels, dynamic exits, and automatic position closure when an opposite signal appears.
All parameters such as sensitivity, profit targets, and behavior can be adjusted by the user to match different instruments, timeframes, and risk preferences.
This strategy is intended for educational and analytical purposes and does not provide financial advice or performance guarantees.
Delta/Volume Bubble Strategy [Quant Z-Score] Maxxed VersionDelta/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.
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.
Also available the matching indicator by yours truly.
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
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
Daily/Weekly FVG by KrisThis indicator is a Multi-Timeframe (MTF) tool designed to automatically identify and project Fair Value Gaps (Imbalances) from Daily and Weekly timeframes onto your current chart. It helps traders locate higher-timeframe Areas of Interest (POI) and liquidity voids without manually switching charts.
How it works:
The script utilizes `request.security` to fetch High and Low data from Daily and Weekly timeframes. It identifies a Fair Value Gap (FVG) based on the 3-candle formation logic where price moves inefficiently, leaving a gap between the wicks.
- Bullish FVG: Identified when the current Daily/Weekly Low is greater than the High of the candle from 2 periods ago.
- Bearish FVG: Identified when the current Daily/Weekly High is lower than the Low of the candle from 2 periods ago.
The indicator draws a box extending to the right to visualize the zone, along with a dotted midline which often acts as a sensitive support/resistance level.
Unique Feature: Smart Mitigation (Auto-Hide)
To keep your chart clean and focused on relevant data, the script includes a "Full Fill" logic. It continuously monitors price action relative to existing FVG boxes.
- If price completely crosses through a box (fully fills the gap), the indicator considers it "mitigated" and automatically hides the box and its midline (sets transparency to 100%).
- This ensures you only see "fresh" or unfilled gaps that are still relevant for trading.
Settings:
- TF Checkboxes (Daily/Weekly FVG): Toggle the visibility of Daily or Weekly gaps independently based on your analysis needs.
- Design Mode:
Colored: Uses classic Green (Bullish) and Red (Bearish) colors for easy trend identification.
Monochrome: Uses Gray tones for a minimalist look that reduces visual noise on the chart.
Usage:
Use these zones to identify potential reversal points or liquidity targets. Since these are higher-timeframe levels, they often carry more weight than intraday imbalances.
UT Bot final 15M XAUUSD High WinrateThis script is a 15-minute timeframe optimized swing trading strategy, designed for traders who prefer structured, rule-based entries and exits with a focus on trend quality and risk control.
The strategy is based on a modified UT Bot logic, enhanced with:
Sideways market filtering using ADX and ATR volatility conditions
Confirmed higher-quality entries by waiting for candle close on the signal timeframe
Retracement-based limit entries to improve average entry price
Multi-level partial take profits (TP1–TP5)
Configurable stop loss (fixed pips or percentage)
Automatic break-even after TP1
Full position close on opposite signal
The system is especially suitable for swing and semi-swing traders who want to:
Reduce trades during low-quality, ranging market conditions
Manage positions with partial exits and predefined risk
Use the strategy as a foundation for automation or alert-based trading bots
All key parameters (sensitivity, filters, take profits, stop loss, and entry behavior) are fully adjustable, allowing traders to adapt the strategy to different risk profiles and market conditions.
Elliott Wave Pattern AnalyzerElliott Wave Pattern Analyzer
Overview
This indicator automatically detects Elliott Wave impulse patterns and diagonal formations on your chart. It analyzes price structure based on classic Elliott Wave rules and displays wave counts with confidence scores, Fibonacci projections, and invalidation levels.
Why I Built This
After reading Glenn Neely's book on Elliott Wave theory, I wanted to put my learning into practice by building something tangible. There's no better way to understand a concept than trying to code it!
I'll be honest – corrective wave patterns (zigzags, flats, triangles, combinations) were simply too complex for me to implement reliably. So instead, I focused on what I could manage: impulse waves and diagonal patterns. Maybe someday I'll tackle the corrections, but for now, this is my humble contribution.
The retracement visualization style was inspired by LuxAlgo's elegant approach – credit where credit is due!
How It Works
1. Wave Detection
The indicator uses pivot points to identify potential 5-wave structures:
WaveRuleWave 2Cannot retrace more than 100% of Wave 1Wave 3Cannot be the shortest among Waves 1, 3, 5Wave 4Should not overlap Wave 1 territory (impulse)Wave 5Completes the motive structure
2. Pattern Types
Impulse Waves
Classic 5-wave motive structure
Wave 3 typically extends (≥1.618 of Wave 1)
Strict mode enforces all Elliott rules
Diagonal Patterns
Ending diagonal (wedge-shaped)
Waves progressively contract
Lines 1-3 and 2-4 converge to an apex
Often signals trend exhaustion
3. Confidence Scoring
Each pattern receives a confidence score (0-100%) based on:
Fibonacci ratio adherence
Wave proportion relationships
Rule compliance
Structural clarity
Only patterns exceeding your threshold (default: 60%) are displayed.
4. Fibonacci Projections
After Wave 5 completion, the indicator projects potential retracement levels:
0.382, 0.500, 0.618, 0.786 of the entire impulse
5. Extension Channel
Connects Wave 0 origin to the retracement low, projecting:
0.618, 1.000, 1.272, 1.618 extensions
Optional extended levels: 2.000, 2.618, 4.236
6. Invalidation Levels
Shows the price level where the wave count becomes invalid – helping you know when your analysis is wrong.
Settings Explained
Impulse Wave Settings
Pivot Length: Sensitivity of wave detection (recommended: 5, 7, 14)
Strict Mode: Enforce all classic Elliott rules
Min Wave 3 Extension: Minimum ratio for Wave 3 (default: 1.618)
Diagonal Wave Settings
Allow Wave 4-1 Overlap: Required for valid diagonals
Extend Trendline: Project diagonal boundaries forward
Projection Settings
Fibonacci Levels: Customize retracement targets
Extension Bars: How far projections extend on chart
Pattern Management
Max Patterns: Limit displayed patterns to reduce clutter
Pattern Lifetime: Auto-remove old patterns after X bars
Use Cases
Trend Trading: Enter on Wave 3 or Wave 5 breakouts
Reversal Spotting: Diagonal completion often signals reversals
Target Setting: Use Fibonacci extensions for take-profit levels
Risk Management: Invalidation levels provide clear stop-loss references
Notes
This indicator uses pivot detection and may repaint – signals are confirmed after the specified pivot length
Designed for educational and analytical purposes, not as a signal generator
Elliott Wave analysis is subjective – this is my algorithmic interpretation
Works best on liquid markets with clear trend structure
Not financial advice – always do your own research
Re-publishing Notice
This indicator was previously blocked due to some house rule violations on my part. I've recently had time to review and fix those issues, and I'm now re-publishing a compliant version. Thanks for your patience!
Feedback Welcome
I'm still learning Elliott Wave theory myself, so if you spot any issues or have suggestions for improvement, please leave a comment. Let's learn together!
Happy trading! 📈
COMBO: LuxAlgo SFP + EXTREMOS + VWAP 3rd Band + LG (15m)This is the best indicator 1h chart
High and low points daily
Simple RSI Strategy - Rule Based Higher Timeframe Trading
HOW IT WORKS
With the default settings, the strategy buys when RSI reaches 30 and closes when RSI reaches 40 .
That’s it.
A simple, rule-based mean reversion strategy designed for higher timeframes , where market noise is lower and trading becomes easier to manage.
Core logic:
Long when RSI moves into oversold territory
Exit when RSI mean-reverts upward
Optional short trades from overbought levels
One position at a time (no pyramiding)
No filters.
No discretion.
Just clear, testable rules.
MARKETS & TIMEFRAMES
This strategy is intended for:
Indices (Nasdaq, S&P 500, DAX, etc.)
Liquid futures and CFDs
Higher timeframes: 2H, 4H and Daily
The published example is Nasdaq (NDX) on the 2-hour timeframe .
Higher timeframes are strongly recommended.
HOW TO USE IT
Apply the strategy on a higher timeframe
Adjust RSI levels per market if needed
Use TradingView alerts to avoid constant screen-watching
Focus on execution, risk control, and consistency
This strategy is meant to be a building block , not a complete trading business on its own.
For long-term consistency, it works best when combined with other uncorrelated, rule-based systems.
IMPORTANT
This is not financial advice
All results are historical and not indicative of future performance
Always forward-test and apply proper risk management
For additional notes, setups and related systems, visit my TradingView profile page .
Liquidation Heatmap Zones CamnextlevelFind Liquidation zones where the high leverage trades are being liquidated
Argentina Bonds TIR - Sovereign Bond Yield Curves Indicator# Argentina Bonds TIR
A comprehensive indicator that calculates the Internal Rate of Return (IRR/TIR) for Argentine sovereign bonds and projects future price curves at fixed yield levels.
## Features
**Real-time TIR Calculation**
- Calculates current yield based on market price and expected cashflows
- Uses Newton-Raphson iterative method for precise IRR calculation
- Day count convention: Actual/365 with T+1 settlement
**Automatic Currency Conversion**
- Works with any trading currency: ARS, USD MEP (D suffix), USD Cable (C suffix)
- Automatically converts prices using AL30/AL30D/AL30C ratios
- Bonares use MEP conversion, Globales use Cable conversion
**Yield Curve Projections**
- Projects price curves 150 bars into the future (configurable)
- Fixed TIR lines at 7%, 8%, 9%, 10%, 11%, 12% (each toggleable)
- Current TIR line showing price trajectory at current yield
- Custom TIR line with user-defined yield value
**Clear Labeling**
- Labels positioned near current date for easy reading (configurable offset)
- Color-coded lines for quick identification
- Info panel showing bond details, prices, TIR, and exchange rates
## Supported Bonds
**Bonares** (Argentina legislation, USD MEP): AE38, AL29, AL30, AL35, AL41, AN29
**Globales** (Foreign legislation, USD Cable): GD29, GD30, GD35, GD38, GD41, GD46
## How to Use
1. Apply indicator to any supported bond symbol (e.g., BCBA:AL30D, BCBA:GD35C)
2. The indicator auto-detects bond type and currency
3. View current TIR in the info panel
4. Use projected lines to visualize price targets at different yield levels
5. Toggle individual TIR lines on/off as needed
6. Add a custom TIR line for specific yield analysis
## Settings
**Display**: Show/hide current TIR line, projection bars (30-300), label offset in days
**Fixed TIR Lines**: Individual toggles for 7%, 8%, 9%, 10%, 11%, 12%
**Custom TIR**: Enable custom TIR line, set value (%), choose color
**Colors**: Customize colors for all lines
## Info Panel
Shows bond ticker, type (Bonar/Global), trading currency, current price, native price, current TIR percentage, MEP and CCL exchange rates.
---
## Español
Indicador que calcula la Tasa Interna de Retorno (TIR) para bonos soberanos argentinos y proyecta curvas de precios futuros a niveles fijos de rendimiento.
### Características
- Cálculo de TIR en tiempo real usando método Newton-Raphson
- Conversión automática de moneda (ARS, USD MEP, USD Cable)
- Líneas de TIR fijas al 7%, 8%, 9%, 10%, 11%, 12%
- Línea de TIR personalizada configurable
- Panel informativo con detalles del bono y tipos de cambio
### Bonos Soportados
- **Bonares** (USD MEP): AE38, AL29, AL30, AL35, AL41, AN29
- **Globales** (USD Cable): GD29, GD30, GD35, GD38, GD41, GD46
---
**DISCLAIMER**: This indicator is for informational and educational purposes only. Eco Valores S.A. does NOT provide investment advice or recommendations. Consult a qualified financial advisor before making investment decisions.
**AVISO LEGAL**: Este indicador es solo para fines informativos y educativos. Eco Valores S.A. NO brinda asesoramiento ni recomendaciones de inversión. Consulte con un asesor financiero calificado antes de invertir.
Professional Grid & Reversal Bot v10 (Binance Style)Professional Grid & Reversal Bot v10 (Binance Style) – Open Source & Educational
About this Script:
This script is an advanced Grid Trading & Smart Reversal strategy, inspired by professional Binance-style execution. It is designed as an educational, open-source tool for traders who want to understand market dynamics, grid logic, and risk management.
How it Works:
1️⃣ Grid Execution:
• Divides the price range between the high and low into multiple levels (Grids).
• Opens Buy orders in the lower half and Sell orders in the upper half.
• Levels are calculated dynamically based on the highest and lowest prices over a selected lookback period.
2️⃣ Smart Reversal System:
• Detects price touches on the high or low range boundaries to identify potential reversal points.
• Opens Buy orders at the lows and Sell orders at the highs using a configurable confirmation percentage (revPct).
• Helps traders capture short-term price swings effectively.
3️⃣ Risk & Size Management:
• Position sizing based on USD amount and leverage.
• Automatic Take Profit (TP) and Stop Loss (SL) for every trade.
• Controls overtrading via the "pyramiding" parameter (max open trades).
4️⃣ Advanced Visualization:
• Plots the grid range with high/low levels and fills the background for clear context.
• Highlights potential Supply and Demand Zones.
• Displays a dynamic "Binance-style" Order Book table showing Side, Price, Quantity, and PnL.
5️⃣ Key Counters & Indicators:
• levelsArr → Stores all grid levels for execution and plotting.
• touchedHigh / touchedLow → Monitors range touches to trigger reversals.
• strategy.openprofit → Displays live open trade PnL directly on the chart.
Additional Features:
• Supports both English and Arabic languages.
• Dark Theme optimized for readability.
• Dynamic control panel updates on every bar.
• Flexible settings for Auto or Manual grid range updates.
User Guidance:
• This script is for educational purposes only; it does not guarantee profits.
• We recommend adjusting Grid Levels, Reversal Percentage, and Trade Size to experiment with different strategies.
Community Engagement:
• Suggestions and improvements are welcome! 💡
• If you have ideas for new features, let's develop them together to enhance learning.
• Please support the script with a Like & Boost if you find it useful.
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HMA Trend Scalper V1[wjdtks255]
Overview
This indicator is a high-performance trend-following system optimized for crypto futures trading. It provides clear entry signals and dynamic, real-time risk management tools to help traders stay on the right side of the market.
Key Features
Dynamic Trend Tracking: Uses a specialized HMA (Hull Moving Average) to filter market noise and identify the core trend.
Real-time TP/SL Extension: Unlike static indicators, the Take Profit (TP) and Stop Loss (SL) lines extend candle-by-candle along with the price action.
Clean Chart UI: Lines only exist from the entry point to the current candle, preventing chart clutter.
Automatic Completion: Once the price hits a target, the line stops extending and marks the result (Target Hit or Stop Out).
Trading Strategy (How to Trade)
1. Long Entry (🚀 LONG)
Condition: The price must be above the trend line, and a breakout of the recent 5-candle high must occur with significant volume.
Action: Enter a Long position when the "🚀 LONG" label appears.
Exit: Hold until the price reaches the Cyan (Aqua) TP line or hits the Yellow SL line.
2. Short Entry (💀 SHORT)
Condition: The price must be below the trend line, and a breakdown of the recent 5-candle low must occur with significant volume.
Action: Enter a Short position when the "💀 SHORT" label appears.
Exit: Hold until the price reaches the Cyan (Aqua) TP line or hits the Yellow SL line.
3. Risk Management
Stop Loss: The indicator automatically calculates the optimal SL based on recent volatility (ATR) and swing points.
Take Profit: The TP is set at a calculated ratio to ensure a positive risk-to-reward setup.
Settings
Trend Sensitivity: Adjust the HMA length to match your preferred timeframe (Scalping vs. Swing).
Volume Multiplier: Filter out weak moves by increasing the volume breakout requirement.
Custom Styles: Fully customize line colors, widths, and styles (Solid, Dashed, Dotted) in the settings menu.
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.
BULL Whale Finder + BTC 1hBULL Whale Finder + BTC 1h is a long-only strategy designed to capture strong impulsive moves in Bitcoin.
It trades expansion (Whale) bars that appear in the direction of the trend, confirmed by the 200-period moving average on both 1H and 4H, with price holding above the 20-period moving average.
Entries focus on impulsive moves that originate from structural zones, not late breakouts.
Risk management is fully automated:
ATR-based initial stop
Automatic profit protection (Pay-Self)
Adds and partial exits based on the expansion-bar sequence
A protected runner managed with a trailing stop
The user only sets the risk per trade (MLPT).
All other parameters are hardcoded and locked to prevent over-optimization.
👉 Ready for backtesting, discretionary execution, or full automation.
OI Grid for Gold/Oil-Auto plot OI level
-For Gold and Crude Oil
-Price diff function between future/spot price
EDUVEST QQE Signal v3.0 - Multi-Timeframe Scoring SystemEDUVEST QQE Signal v3.0 - Multi-Timeframe Scoring System
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█ ORIGINALITY
This indicator combines QQE (Quantitative Qualitative Estimation) with HMA (Hull Moving Average) and introduces a unique AI-based scoring system that rates signal quality from 0-100. Unlike traditional QQE indicators that show simple buy/sell signals, this version categorizes signals into four strength levels: BIG CHANCE, SUPER, POWER, and STRONG.
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█ WHAT IT DOES
- Generates scored BUY/SELL signals with quality ratings (60-100 points)
- Categorizes signals into 4 strength levels for easy decision making
- Supports Multi-Timeframe (MTF) analysis
- Auto-detects asset type and applies optimized QQE factors
- Provides customizable alerts based on score thresholds
Signal Hierarchy:
- 💰 BIG CHANCE (90-100): Highest probability setups
- ⚡ SUPER (80-89): Very strong signals
- 🚀 POWER (70-79): Strong signals with HMA confluence
- 💪 STRONG (60-69): Standard quality signals
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
█ HOW IT WORKS
【QQE Calculation】
QQE is based on a smoothed RSI with dynamic bands:
1. Calculate RSI with specified period (default: 14)
2. Apply EMA smoothing to RSI (Smoothing Factor, default: 5)
3. Calculate ATR of the smoothed RSI
4. Create dynamic bands: RSI ± (ATR × QQE Factor)
The QQE Factor is automatically adjusted per asset:
- Forex (USDJPY, EURUSD): 3.8 - 4.238
- Gold (XAUUSD): 8.0
- Crypto (BTC): 12.0, (ETH): 10.0
- Indices (NASDAQ): 4.238
【HMA Calculation】
Hull Moving Average for trend confirmation:
HMA = WMA(2 × WMA(price, n/2) - WMA(price, n), √n)
【Signal Generation】
- BUY: QQE crosses above its band (QQExlong == 1)
- SELL: QQE crosses below its band (QQExshort == 1)
【AI Scoring System】
The score is calculated from multiple factors:
Signal Base (0-35 points):
- QQE + HMA confluence: +35
- QQE or HMA alone: +25
QQE Strength (10-25 points):
- RSI distance from 50 (momentum strength)
- >30 distance: +25, >20: +20, >10: +15, else: +10
Volatility Score (-10 to +15 points):
- ATR ratio 1.1-2.0: +15 (optimal volatility)
- ATR ratio <0.8: -10 (low volatility warning)
Volume Confirmation (-5 to +15 points):
- Volume > 120% of average: +15
- Volume < 80% of average: -5
Base Points: +15
Final Score = Clamped(0, 100, sum of all factors)
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█ HOW TO USE
【Recommended Settings】
- Timeframe: 5M, 15M, 1H, 4H
- Best on: Forex, Gold, NASDAQ, BTC/ETH
- Minimum Score: 60 (adjustable)
【Reading Signals】
- BIG CHANCE (Gold label, 90+): Highest conviction - consider larger position
- SUPER (Yellow label, 80-89): Very strong - standard position
- POWER (Cyan/Magenta label, 70-79): Strong with trend confirmation
- STRONG (Green/Red label, 60-69): Valid but use additional confirmation
【MTF Feature】
Enable MTF to analyze signals from a higher timeframe while viewing lower timeframe charts. The indicator auto-selects 5-minute as the analysis timeframe, or you can set it manually.
【Alert Setup】
1. Enable alerts in settings
2. Set minimum score threshold (default: 60)
3. Create alert with "Any alert() function call"
【Important Notes】
- Signals are confirmed at bar close (no repainting)
- Higher scores = higher probability, not guaranteed profits
- Always use proper risk management
- Consider market context and support/resistance levels
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█ SETTINGS
⏱️ MTF Settings
- MTF Use: Enable multi-timeframe analysis
- Manual Timeframe: Override auto-detection
- Show Panel: Display info panel (default: OFF)
🎨 Design
- Neon Colors: Vibrant color scheme
- Show HMA Line: Display HMA on chart
- Minimum Score: Filter weak signals
- Label Transparency: Adjust label opacity
- Large Labels: Mobile-friendly sizing
🔧 QQE Settings
- RSI Period: RSI calculation period
- Smoothing: EMA smoothing factor
- AI Score: Enable scoring system
🔔 Alerts
- Enable Alerts: Turn on/off notifications
- Minimum Score: Alert threshold
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█ CREDITS
QQE concept originally developed by John Ehlers.
HMA (Hull Moving Average) by Alan Hull.
Enhanced with scoring system and MTF support by EduVest.
License: Mozilla Public License 2.0
CISD Projections [LuxAlgo]The CISD Projections tool automatically plots mechanical price projection targets based on fractal market structure and swing manipulation legs. These projections offer dynamic, statistically informed targets that align with how prices tend to expand after a reversal point is confirmed.
🔶 USAGE
Projections are mechanical target levels derived from the manipulation leg following a confirmed change in state of delivery (CISD). They estimate where price is most likely to travel next by applying extended Fibonacci projection levels off the swing that initiated the move.
The tool works in the following way:
1. Detect the reversal bar that signals a shift in delivery.
2. Identify the manipulation leg: the swing that caused the reversal.
3. Anchor projections from this leg using customized Fibonacci levels such as 1, 2, 2.5, 4, 4.5 — each representing a potential target based on leg size and market expansion expectation.
For a correct target interpretation:
Average-sized legs often target between 2 and 2.5 levels.
Expanding legs may reach 4 to 4.5.
Large manipulation legs may warrant conservative expectations, focusing on 1 target.
As we can see in the image, traders must be aware of current market conditions and manipulation leg size in order to decide which levels to target and ask the right questions: Is volatility contracting or expanding? Is this manipulation leg smaller or larger than the previous ones?
Ultimately, projections provide objective, mechanical targets rather than subjective guesswork. They can be used on their own or in conjunction with liquidity zones, CISDs, and structural levels. They also help identify realistic price targets based on measured swing magnitude.
🔹 Filtering Setups
The chart shows how the output is affected by different filtering options:
Bars Threshold: show setups with a minimum number of bars in the manipulation leg.
CISD Filter: show setups only at the top or bottom of the range for the last X bars.
Invalidate CISDs on CHoCH: setups stop expanding after the first close beyond the manipulation leg.
We can obtain more meaningful setups with larger filter values by filtering the setups, or we can zoom in on details at the trader's discretion by disabling all filters.
🔶 SETTINGS
Bars Threshold: Minimum number of bars of each setup.
CISD Filter: Enable or disable the filter and select the length. This filter identifies setups at the top or bottom of the range over the last X bars.
Invalidate CISDs on CHoCH: Stop the level extension on ChoCH against CISD. This occurs when there is a close below the bottom on bullish setups and a close above the top on bearish setups.
🔹 Projections
Enable or disable each projection, select the projection level, and choose a style.
🔹 Style
CISD Level: Enable or disable CISD price level and select style.
Labels size: Select the size of the labels.
Bullish Color: Select a color for bullish setups.
Bearish Color: Select a color for bearish setups.
Background Fill: Enable or disable the background fill between the price and the extreme projection.
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.
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 😴
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.
