Paper: arXiv 2508.16598

Authors: Maciej Wysocki

Abstract

This paper examines systematic put-writing strategies applied to S&P 500 Index options, with a focus on position sizing as a key determinant of long-term performance. Despite the well-documented volatility risk premium, where implied volatility exceeds realized volatility, the practical implementation of short-dated volatility-selling strategies remains underdeveloped in the literature. This study evaluates three position sizing approaches: the Kelly criterion, VIX-based volatility regime scaling, and a novel hybrid method combining both. Using SPXW options with expirations from 0 to 5 days, the analysis explores a broad design space, including moneyness levels, volatility estimators, and memory horizons. Results show that ultra-short-dated, far out-of-the-money options deliver superior risk-adjusted returns. The hybrid sizing method consistently balances return generation with robust drawdown control, particularly under low-volatility conditions such as those seen in 2024. The study offers new insights into volatility harvesting, introducing a dynamic sizing framework that adapts to shifting market regimes. It also contributes practical guidance for constructing short-dated option strategies that are robust across market environments. These findings have direct applications for institutional investors seeking to enhance portfolio efficiency through systematic exposure to volatility premia.

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 employs advanced mathematical frameworks including the Kelly criterion, Monte Carlo simulations, and sophisticated volatility regime analysis, demonstrating moderate-to-high mathematical density. It achieves high empirical rigor through comprehensive backtesting using real S&P 500 options data, extensive parameter sweeps, and focus on implementation details like transaction costs and margin requirements.

Research Flowchart

  flowchart TD
  A["Research Goal<br>Optimize systematic put-writing<br>position sizing for SPX options"] --> B["Key Methodology<br>Evaluate 3 Sizing Approaches"]
  
  B --> B1["Kelly Criterion<br>Fractional Kelly versions"]
  B --> B2["VIX-Based Scaling<br>Regime-dependent sizing"]
  B --> B3["Hybrid Method<br>Combined Kelly & VIX scaling"]
  
  C["Data & Inputs<br>SPXW Options 0-5 DTE<br>2010-2024, multiple moneynesses"] --> D["Computational Process<br>Exhaustive Grid Search<br>over design space"]
  
  B1 & B2 & B3 --> D
  
  D --> E{"Key Findings & Outcomes"}
  
  E --> F1["FAR OTM + Ultra-Short DTE<br>Best risk-adjusted returns"]
  E --> F2["Hybrid Method Dominates<br>Superior drawdown control<br>Optimal in 2024 low-vol"]
  E --> F3["Dynamic Sizing Framework<br>Adapts to market regimes<br>Enhances portfolio efficiency"]
  
  F1 & F2 & F3 --> G["Practical Application<br>Institutional volatility<br>premium harvesting"]