
doi: 10.1111/mafi.12024
The aim of this work is to advocate the use of multifractional Brownian motion (mBm) as a relevant model in financial mathematics. mBm is an extension of fractional Brownian motion where the Hurst parameter is allowed to vary in time. This enables the possibility to accommodate for varying local regularity, and to decouple it from long‐range dependence properties. While we believe that mBm is potentially useful in a variety of applications in finance, we focus here on a multifractional stochastic volatility Hull & White model that is an extension of the model studied in Comte and Renault. Using the stochastic calculus with respect to mBm developed in Lebovits and Lévy Véhel, we solve the corresponding stochastic differential equations. Since the solutions are of course not explicit, we take advantage of recently developed numerical techniques, namely functional quantization‐based cubature methods, to get accurate approximations. This allows us to test the behavior of our model (as well as the one in Comte and Renault) with respect to its parameters, and in particular its ability to explain some features of the implied volatility surface. An advantage of our model is that it is able both to fit smiles at different maturities, and to take volatility persistence into account in a more precise way than Comte and Renault.
[MATH.MATH-PR] Mathematics [math]/Probability [math.PR], Numerical methods (including Monte Carlo methods), Stochastic models in economics, Stochastic integrals, fractional Brownian motion, Gaussian processes, Fractional processes, including fractional Brownian motion, white noise theory, S-transform, White noise theory, stochastic differential equations, Derivative securities (option pricing, hedging, etc.), vector quantization, Hull-White model, Wick-Itō integral, Gaussian process, functional quantization, multifractional Brownian motion, Karhunen-Loève
[MATH.MATH-PR] Mathematics [math]/Probability [math.PR], Numerical methods (including Monte Carlo methods), Stochastic models in economics, Stochastic integrals, fractional Brownian motion, Gaussian processes, Fractional processes, including fractional Brownian motion, white noise theory, S-transform, White noise theory, stochastic differential equations, Derivative securities (option pricing, hedging, etc.), vector quantization, Hull-White model, Wick-Itō integral, Gaussian process, functional quantization, multifractional Brownian motion, Karhunen-Loève
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