Adaptive VaR Control for Standardized Option Books under Marking Frictions

Paper: arXiv 2604.03499

Authors: Tenghan Zhong

Abstract

Short-horizon risk control matters for hedging and capital allocation. Yet existing Value-at-Risk studies rarely address standardized option books or the next-day valuation frictions that arise in derivatives data. This paper develops a framework for tail-risk control in standardized option books. The analysis focuses on the next-day realized loss and combines a base conditional quantile forecast with sequential conformal recalibration for adaptive Value-at-Risk control. This design addresses two central difficulties: unstable tail-risk forecasts under changing market conditions and the practical challenge of next-day valuation when exact same-contract quotes are unavailable. It also preserves economic interpretability through standardized construction and spot hedging when needed. Using SPX option data from 2018 to 2025, we show that the uncalibrated base model systematically underestimates downside risk across multiple standardized books. Sequential recalibration removes much of this shortfall, brings exceedance rates closer to target, and improves rolling-window tail stability, with the largest gains in the books where the raw forecast is most vulnerable. The paper also provides an approximate one-step exceedance-control result for the sequential recalibration rule and quantifies the error introduced by next-day marking.

Complexity vs Empirical Score

• Math Complexity: 6.5/10
• Empirical Rigor: 8.0/10
• Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper presents a mathematically sound approach combining conditional quantile forecasts with sequential conformal recalibration to tackle practical derivatives marking frictions. Its empirical evaluation on SPX options data from 2018–2025 provides robust validation for short-horizon tail-risk control.

Research Flowchart

  flowchart TD
    A["Research Goal:<br>Adaptive VaR Tail-Risk Control for Standardized Option Books under Marking Frictions"] --> B["Data Inputs:<br>SPX Option Data (2018–2025) & Next-Day Valuation Quotes"]
    
    B --> C["Standardized Book Construction:<br>Portfolio Formation & Spot Hedging"]
    
    C --> D["Base Forecasting:<br>Conditional Quantile Forecast for Next-Day Realized Loss"]
    
    D --> E["Adaptive Control:<br>Sequential Conformal Recalibration & Friction Error Quantification"]
    
    E --> F["Outcomes & Key Findings:<br>• Base model underestimates downside risk<br>• Recalibration restores target exceedance rates<br>• Enhanced rolling-window tail stability"]

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1 of 33 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.