Statistical Approach to Implied Market Inefficiency Estimation

Fabrizio Di Sciorio (), Laura Molero González () and Juan E. Trinidad Segovia ()
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Fabrizio Di Sciorio: University of Almería, Department of Economics and Business
Laura Molero González: University of Almería, Department of Economics and Business
Juan E. Trinidad Segovia: University of Almería, Department of Economics and Business

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2024, pp 130-135 from Springer

Abstract: Abstract This study aims to estimate the information efficiency of financial markets based on the Hurst exponent, with a focus on the S&P 500 index. The approach involves using statistical models to estimate the implied Hurst exponent through the historical series of the VIX (a proxy for implied volatility) with a 30-day time lag. In this way, the traditional backward-type Hurst estimation is reconciled with that derived from the VIX, which represents a forward-looking measure (a proxy for 30-day volatility). The test sample also includes the COVID pandemic period. The results reveal a good fit from ensemble stacking models, with the random forest standing out as the most effective approach in estimating the implied Hurst index.

Keywords: Hurst Exponent; VIX; Inefficient Market; Ensemble Stacking; Regression (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-64273-9_22

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DOI: 10.1007/978-3-031-64273-9_22

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