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In this paper we propose an efficient pricing-hedging framework for volatility derivatives which simultaneously takes into account path roughness and jumps. Instead of dealing with log-volatility, we directly model the instantaneous variance of a risky asset in terms of a fractional Ornstein-Uhlenbeck process driven by an infinite-activity L{e}vy subordinator, which is shown to exhibit roughness under suitable conditions and also eludes the need for an independent Brownian component. This structure renders the characteristic function of forward variance obtainable at least in semi-closed form, subject to a generic integrable kernel. To analyze financial derivatives, primarily swaps and European-style options, on average forward volatility, we introduce a general class of power-type derivatives on the average forward variance, which also provide a way of adjusting the option investors risk exposure. Pricing formulae are based on numerical inverse Fourier transform and, as illustrated by an empirical study on VIX options, permit stable and efficient model calibration once specified.
In this paper, a pricing formula for volatility swaps is delivered when the underlying asset follows the stochastic volatility model with jumps and stochastic intensity. By using Feynman-Kac theorem, a partial integral differential equation is obtain
A new paradigm recently emerged in financial modelling: rough (stochastic) volatility, first observed by Gatheral et al. in high-frequency data, subsequently derived within market microstructure models, also turned out to capture parsimoniously key s
The research presented in this article provides an alternative option pricing approach for a class of rough fractional stochastic volatility models. These models are increasingly popular between academics and practitioners due to their surprising con
Sparked by Al`os, Leon, and Vives (2007); Fukasawa (2011, 2017); Gatheral, Jaisson, and Rosenbaum (2018), so-called rough stochastic volatility models such as the rough Bergomi model by Bayer, Friz, and Gatheral (2016) constitute the latest evolution
This paper studies pricing derivatives in an age-dependent semi-Markov modulated market. We consider a financial market where the asset price dynamics follow a regime switching geometric Brownian motion model in which the coefficients depend on finit