Paper: arXiv 2512.20190

Authors: Anastasiia Zbandut

Abstract

This paper measures price differences between Hegic option quotes on Arbitrum and a model-based benchmark built on Black–Scholes model with regime-sensitive volatility estimated via a two-regime MS-AR-(GJR)-GARCH model. Using option-level feasible GLS, we find benchmark prices exceed Hegic quotes on average, especially for call options. The price spread rises with order size, strike, maturity, and estimated volatility, and falls with trading volume. By underlying, wrapped Bitcoin options show larger and more persistent spreads, while Ethereum options are closer to the benchmark. The framework offers a data-driven analysis for monitoring and calibrating on-chain option pricing logic.

Complexity vs Empirical Score

  • Math Complexity: 6.5/10
  • Empirical Rigor: 7.5/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper presents a solid empirical analysis of on-chain option pricing using a robust MS-AR-(GJR)-GARCH volatility framework and Feasible GLS. It bridges theoretical options pricing with practical Decentralized Finance (DeFi) market microstructure dynamics, offering novel insights into AMM pricing deviations.

Research Flowchart

  flowchart TD
    A[Research Goal: Assess Hegic On-Chain Option Pricing vs Model Benchmark] --> B[Data Inputs: WBTC & WETH Hegic Quotes + Spot Returns]
    B --> C[Estimate Volatility via Two-Regime MS-AR-GJR-GARCH Model]
    C --> D[Calculate Black-Scholes Model Benchmark Prices]
    D --> E[Analyze Spreads via Feasible Generalized Least Squares - FGLS]
    E --> F[Findings: Benchmark Exceeds Hegic Quotes, Especially Calls & WBTC]
    E --> G[Findings: Spreads Scale with Size, Strike, Maturity & Volatility]

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0 of 58 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.