Fair Volatility in the Fractional Stochastic Regularity Model
Sergio Bianchi (),
Daniele Angelini,
Massimiliano Frezza,
Anna Maria Palazzo and
Augusto Pianese
Additional contact information
Sergio Bianchi: Sapienza University
Daniele Angelini: Sapienza University
Massimiliano Frezza: Sapienza University
Anna Maria Palazzo: University of Cassino and Southern Lazio
Augusto Pianese: University of Cassino and Southern Lazio
A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2024, pp 61-66 from Springer
Abstract:
Abstract Within the efficient markets framework, discounted stock prices are typically represented through Brownian martingales. The primary measure for evaluating risk is the volatility of log-returns, under the assumption that higher variability indicates greater associated risk. The theoretical foundation of this claim stems from the characterization of the path regularity of price process through the Lévy characterization theorem of Brownian motion. Since this explanation lacks a financial interpretation when considering more realistic models, such as stochastic volatility models, it is necessary to disentangle volatility and regularity. Replacing volatility by the Hölder regularity provides insights into market deviations from the equilibrium of the martingale model, and - within the Fractional Stochastic Regularity Model - contributes to identify the “fair” volatility aimed by the market.
Keywords: Hölder exponent; Volatility; Fractional Stochastic Regularity Model (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_11
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DOI: 10.1007/978-3-031-64273-9_11
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