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Aggiornato RS High Beta Exposure | QuantLapse
RS High Beta Exposure | QuantLapse
Conceptual Foundation and Innovation
The RS High Beta Exposure indicator from QuantLapse is a comprehensive multi-asset allocation and momentum-ranking system that integrates beta and trend analysis, pairwise relative strength comparison, and volatility-adjusted filtering.
Its objective is to identify dominant crypto assets while dynamically reallocating High Beta exposure based on a calculated relative strength. The objective is to integrate trend analysis along with volatility filtering to these pairs to determine its relative strength.
At its core, RS High Beta Exposure indicator measures the systematic (β) performance of each asset relative to other assets provided combining these measures with inter-asset ratio trends to determine which assets exhibit superior strength and momentum relative to the other assets.
This integration of relative strength comparison, and trend and filtering analysis represents a quantitative evolution of traditional relative strength analysis, designed for adaptive asset rotation across major cryptocurrencies.
Technical Composition and Calculation
The indicator is structured around three major analytical layers:
1. Beta and Alpha Analysis
-Each asset’s return is decomposed into systematic components relative to the other assets by using a trend based, volatility filtering model.
-Assets with the highest point on a relative strength basis above the median are considered outperformers and eligible for allocation.
2. Pairwise Ratio Momentum
-Every asset is compared against all others through a ratio-trend, where momentum based trend scores quantify the directional momentum between each pair.
-In addition, we filter any false signals with volatility adjusted trends in which ensure high quality signals.
3. High Confidence Ranking
-Using the Pairwise Momentum signals, the RS High Beta Exposure scores them. If the asset comparison is given a signal, the RS High Beta Exposure scores points for each asset.
-If the total points of an asset is 5, its given the rank the dominant asset and is most likely to outperform.
By combining these layers, RS High Beta Exposure determines not only which assets is the strongest but also which assets to be invested.
User Inputs and Feature Adaptability
The indicator includes set of customizable parameters to support portfolio and risk management preferences:
Start Date Filter – Defines the beginning of live strategy evaluation.
Display Options – Able to change the location of the RS Table, Background and equity color.
Asset Selection – Modify or replace up to six crypto assets in the ranking matrix
Pine Script®
Each module operates cohesively to maintain analytical transparency while allowing user-level control over system sensitivity and behavior.
Real World, Practical Applications
The RS High Beta Exposure indicator is designed for systematic traders and quantitative portfolio managers who seek a disciplined framework for dynamic crypto asset rotation.
Key applications include:
High-Beta Asset Identification: Systematically identify crypto assets exhibiting relative dominance and stronger momentum characteristics versus peers within the comparison set.
Rule-Based Portfolio Rotation: Reallocate exposure toward leading assets using objective pairwise signals, reducing emotional decision-making and FOMO-driven trades.
Trend-Aligned Risk Participation: Employ the pairwise relative strength model to maintain exposure only during favorable momentum conditions, helping avoid prolonged participation in weak or deteriorating trends.
By combining relative strength comparisons with trend-aware filtering, this framework bridges quantitative finance and market regime analysis, providing a structured, data-driven approach to crypto asset allocation.
Advantages and Strategic Value
RS High Beta Exposure goes beyond conventional relative strength tools by integrating multi-asset comparison, ratio-based dominance scoring, and volatility-aware regime filtering into a single coherent framework.
By employing a three-layer confluence model — combining trend integrity, relative performance attribution, and volatility-state confirmation — the system improves the reliability of rotation and trend-following decisions.
The model is particularly valuable for traders seeking to:
The inclusion of visual allocation tables and a dynamic alert system makes RS High Beta Exposure both transparent and actionable, supporting discretionary analysis as well as systematic or automated trading workflows.
Alerts and Visualization
The script delivers clear, intuitive visual cues and alert-based feedback to support real-time decision-making:
An integrated alert system automatically notifies users whenever allocation states change (e.g., “100% XRP” or “100% CASH”).
Together, these visualization and alert features make RS High Beta Exposure both analytically rigorous and easy to interpret, even in fast-moving live market conditions.
Summary and Usage Tips
RS High Beta Exposure is an advanced interpretation of relative strength analysis, blending pairwise momentum comparisons, multi-asset dominance scoring, and adaptive volatility filters into a disciplined framework for crypto asset rotation.
By combining cross-asset selection with systematic allocation logic, the indicator helps traders determine when to be exposed, which asset demonstrates leadership, and when to step aside during unfavorable conditions. The model is best applied on the 1D timeframe, where its structure is optimized for identifying sustained leadership rather than short-term price noise. For broader context and confirmation, it can be used alongside other QuantLapse systematic models at the portfolio level.
Note: Past performance does not guarantee future results. This indicator is intended for research and educational use within TradingView.
Conceptual Foundation and Innovation
The RS High Beta Exposure indicator from QuantLapse is a comprehensive multi-asset allocation and momentum-ranking system that integrates beta and trend analysis, pairwise relative strength comparison, and volatility-adjusted filtering.
Its objective is to identify dominant crypto assets while dynamically reallocating High Beta exposure based on a calculated relative strength. The objective is to integrate trend analysis along with volatility filtering to these pairs to determine its relative strength.
At its core, RS High Beta Exposure indicator measures the systematic (β) performance of each asset relative to other assets provided combining these measures with inter-asset ratio trends to determine which assets exhibit superior strength and momentum relative to the other assets.
This integration of relative strength comparison, and trend and filtering analysis represents a quantitative evolution of traditional relative strength analysis, designed for adaptive asset rotation across major cryptocurrencies.
Technical Composition and Calculation
The indicator is structured around three major analytical layers:
1. Beta and Alpha Analysis
-Each asset’s return is decomposed into systematic components relative to the other assets by using a trend based, volatility filtering model.
-Assets with the highest point on a relative strength basis above the median are considered outperformers and eligible for allocation.
2. Pairwise Ratio Momentum
-Every asset is compared against all others through a ratio-trend, where momentum based trend scores quantify the directional momentum between each pair.
-In addition, we filter any false signals with volatility adjusted trends in which ensure high quality signals.
3. High Confidence Ranking
-Using the Pairwise Momentum signals, the RS High Beta Exposure scores them. If the asset comparison is given a signal, the RS High Beta Exposure scores points for each asset.
-If the total points of an asset is 5, its given the rank the dominant asset and is most likely to outperform.
By combining these layers, RS High Beta Exposure determines not only which assets is the strongest but also which assets to be invested.
User Inputs and Feature Adaptability
The indicator includes set of customizable parameters to support portfolio and risk management preferences:
Start Date Filter – Defines the beginning of live strategy evaluation.
Display Options – Able to change the location of the RS Table, Background and equity color.
Asset Selection – Modify or replace up to six crypto assets in the ranking matrix
asset1 = input.symbol("CRYPTO:XRPUSD", title ="Asset 1")
asset2 = input.symbol("CRYPTO:BNBUSD", title ="Asset 2")
asset3 = input.symbol("CRYPTO:ADAUSD", title ="Asset 3")
asset4 = input.symbol("CRYPTO:DOGEUSD", title ="Asset 4")
asset5 = input.symbol("CRYPTO:XLMUSD", title ="Asset 5")
asset6 = input.symbol("CRYPTO:LINKUSD", title ="Asset 6")
Each module operates cohesively to maintain analytical transparency while allowing user-level control over system sensitivity and behavior.
Real World, Practical Applications
The RS High Beta Exposure indicator is designed for systematic traders and quantitative portfolio managers who seek a disciplined framework for dynamic crypto asset rotation.
Key applications include:
High-Beta Asset Identification: Systematically identify crypto assets exhibiting relative dominance and stronger momentum characteristics versus peers within the comparison set.
Rule-Based Portfolio Rotation: Reallocate exposure toward leading assets using objective pairwise signals, reducing emotional decision-making and FOMO-driven trades.
Trend-Aligned Risk Participation: Employ the pairwise relative strength model to maintain exposure only during favorable momentum conditions, helping avoid prolonged participation in weak or deteriorating trends.
By combining relative strength comparisons with trend-aware filtering, this framework bridges quantitative finance and market regime analysis, providing a structured, data-driven approach to crypto asset allocation.
Advantages and Strategic Value
RS High Beta Exposure goes beyond conventional relative strength tools by integrating multi-asset comparison, ratio-based dominance scoring, and volatility-aware regime filtering into a single coherent framework.
By employing a three-layer confluence model — combining trend integrity, relative performance attribution, and volatility-state confirmation — the system improves the reliability of rotation and trend-following decisions.
The model is particularly valuable for traders seeking to:
- Mitigate drawdowns while participating in higher-beta assets through regime-aware exposure control.
- Identify persistent outperformers early in emerging market trends.
- Maintain capital exposure only when statistical and momentum conditions signal elevated confidence.
The inclusion of visual allocation tables and a dynamic alert system makes RS High Beta Exposure both transparent and actionable, supporting discretionary analysis as well as systematic or automated trading workflows.
Alerts and Visualization
The script delivers clear, intuitive visual cues and alert-based feedback to support real-time decision-making:
- Color-coded background states visually indicate the current allocation regime.
- Allocation labels and summary tables display the dominant asset and its relative strength in real time.
An integrated alert system automatically notifies users whenever allocation states change (e.g., “100% XRP” or “100% CASH”).
Together, these visualization and alert features make RS High Beta Exposure both analytically rigorous and easy to interpret, even in fast-moving live market conditions.
Summary and Usage Tips
RS High Beta Exposure is an advanced interpretation of relative strength analysis, blending pairwise momentum comparisons, multi-asset dominance scoring, and adaptive volatility filters into a disciplined framework for crypto asset rotation.
By combining cross-asset selection with systematic allocation logic, the indicator helps traders determine when to be exposed, which asset demonstrates leadership, and when to step aside during unfavorable conditions. The model is best applied on the 1D timeframe, where its structure is optimized for identifying sustained leadership rather than short-term price noise. For broader context and confirmation, it can be used alongside other QuantLapse systematic models at the portfolio level.
Note: Past performance does not guarantee future results. This indicator is intended for research and educational use within TradingView.
Note di rilascio
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Fixed Back testing Date Feature Script su invito
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⌛️ Get Invite-Only Access To Our World Class Systems ⬇️
https://whop.com/quantlapse-systems/
⌛️ Get Invite-Only Access To Our World Class Systems ⬇️
whop.com/quantlapse-systems/
whop.com/quantlapse-systems/
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Script su invito
Solo gli utenti approvati dall'autore possono accedere a questo script. È necessario richiedere e ottenere l'autorizzazione per utilizzarlo. Tale autorizzazione viene solitamente concessa dopo il pagamento. Per ulteriori dettagli, seguire le istruzioni dell'autore riportate di seguito o contattare direttamente QuantLapse.
TradingView NON consiglia di acquistare o utilizzare uno script a meno che non si abbia piena fiducia nel suo autore e se ne comprenda il funzionamento. È inoltre possibile trovare alternative gratuite e open source nei nostri script della community.
Istruzioni dell'autore
⌛️ Get Invite-Only Access To Our World Class Systems ⬇️
https://whop.com/quantlapse-systems/
⌛️ Get Invite-Only Access To Our World Class Systems ⬇️
whop.com/quantlapse-systems/
whop.com/quantlapse-systems/
Declinazione di responsabilità
Le informazioni e le pubblicazioni non sono intese come, e non costituiscono, consulenza o raccomandazioni finanziarie, di investimento, di trading o di altro tipo fornite o approvate da TradingView. Per ulteriori informazioni, consultare i Termini di utilizzo.