From Arbitrage Removal to Density Extraction: A Model-Free Framework for Short-Dated Options

Battle Count: 63

Highly relevant for quantitative trading in options markets, particularly for 0DTE and short-dated options which now dominate volume (58% of SPX volume is 0DTE). The pipeline provides a model-free, fast (seconds on standard laptop) method for extracting risk-neutral densities and constructing implied-volatility smiles that remain within bid-ask bounds. Directly applicable to: (1) intraday volatility monitoring, (2) event-risk trading around macro announcements, (3) nonparametric smile interpolation/extrapolation superior to SVI for ultra-short tenors, (4) tail-risk assessment, (5) options market-making via admissible price bounds. The ARIES component is also useful for data cleaning in any options pricing pipeline.

Moderate complexity. The pipeline uses standard optimization tools: LP solver (HiGHS) for ARIES and convex conic solver (Clarabel) for SEDEx. The mathematical framework involves linear programming, convex optimization, and Sobolev space theory. Key implementation challenges include: (1) constructing the compatible grid that includes all observed strikes, (2) calibrating regularization weights lambda1/lambda2 via the asymptotic scaling relation, (3) handling the iterative ARIES loop with proper vertex extraction from LP, (4) converting put quotes to synthetic calls via put-call parity, (5) estimating risk-free rate and dividend yield from option chains. The algorithms are clearly specified but require careful numerical implementation for stability.

The paper provides detailed algorithms (ARIES Algorithm 1, SEDEx Algorithm 2), specifies solver choices (HiGHS for LP, Clarabel for convex optimization), gives parameter selection guidelines (lambda ratio, mesh size), and includes full proofs. However, the empirical data (Cboe DataShop SPX/SPXW options) is proprietary and not publicly available. No code repository is mentioned. The synthetic Heston experiment is fully reproducible given stated parameters.