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Derivatives on the Chicago Board Options Exchange volatility index (VIX) have gained significant popularity over the last decade. The pricing of VIX derivatives involves evaluating the square root of the expected realised variance which…

Computational Finance · Quantitative Finance 2016-11-03 Ivan Guo , Gregoire Loeper

In this paper, we introduce a new time series model having a stochastic exponential tail. This model is constructed based on the Normal Tempered Stable distribution with a time-varying parameter. The model captures the stochastic…

Computational Finance · Quantitative Finance 2023-03-23 Young Shin Kim , Kum-Hwan Roh , Raphael Douady

The stochastic volatility model is a popular tool for modeling the volatility of assets. The model is a nonlinear and non-Gaussian state space model, and consequently is difficult to fit. Many approaches, both classical and Bayesian, have…

Methodology · Statistics 2019-07-22 Chen Gong , David S. Stoffer

We provide explicit conditions on the distribution of risk-neutral log-returns which yield sharp asymptotic estimates on the implied volatility smile. We allow for a variety of asymptotic regimes, including both small maturity (with…

Pricing of Securities · Quantitative Finance 2016-07-08 Francesco Caravenna , Jacopo Corbetta

We derive a small-time expansion for out-of-the-money call options under an exponential Levy model, using the small-time expansion for the distribution function given in Figueroa-Lopez & Houdre (2009), combined with a change of num\'eraire…

Pricing of Securities · Quantitative Finance 2011-12-15 Jose E. Figueroa-Lopez , Martin Forde

Rough volatility is a well-established statistical stylised fact of financial assets. This property has lead to the design and analysis of various new rough stochastic volatility models. However, most of these developments have been carried…

Mathematical Finance · Quantitative Finance 2019-10-31 Mehdi Tomas , Mathieu Rosenbaum

Using a large dataset on major FX rates, we test the robustness of the rough fractional volatility model over different time scales, by including smoothing and measurement errors into the analysis. Our findings lead to new stylized facts in…

Statistical Finance · Quantitative Finance 2021-11-09 Matthieu Garcin , Martino Grasselli

We apply path integration techniques to obtain option pricing with stochastic volatility using a generalized Black-Scholes equation known as the Merton and Garman equation. We numerically simulate the option prices using the technique of…

Condensed Matter · Physics 2007-05-23 Belal E. Baaquie , L. C. Kwek , M. Srikant

In this paper, we establish a probabilistic representation as well as some integration by parts formulae for the marginal law at a given time maturity of some stochastic volatility model with unbounded drift. Relying on a perturbation…

Probability · Mathematics 2020-11-23 Junchao Chen , Noufel Frikha , Houzhi Li

Rough volatility models are known to reproduce the behavior of historical volatility data while at the same time fitting the volatility surface remarkably well, with very few parameters. However, managing the risks of derivatives under…

Mathematical Finance · Quantitative Finance 2017-03-16 Omar El Euch , Mathieu Rosenbaum

We consider the hedging of European options when the price of the underlying asset follows a single-factor Markovian framework. By working in such a setting, Carr and Wu \cite{carr2014static} derived a spanning relation between a given…

Mathematical Finance · Quantitative Finance 2025-08-22 Purba Banerjee , Srikanth Iyer , Shashi Jain

Accurate prediction of financial market volatility is critical for risk management, derivatives pricing, and investment strategy. In this study, we propose a multitude of regime-switching methods to improve the prediction of S&P 500…

Statistical Finance · Quantitative Finance 2025-10-07 Ava C. Blake , Nivika A. Gandhi , Anurag R. Jakkula

Malliavin calculus is a powerful and general framework for the analysis of square-integrable random variables, but it often suffers from a lack of tractability and explicit representations. To address this limitation, we focus on a subclass…

Probability · Mathematics 2026-04-28 Eduardo Abi Jaber , Clément Rey , Dimitri Sotnikov

We compute a sharp small-time estimate for implied volatility under a general uncorrelated local-stochastic volatility model. For this we use the Bellaiche \cite{Bel81} heat kernel expansion combined with Laplace's method to integrate over…

Pricing of Securities · Quantitative Finance 2017-02-07 John Armstrong , Martin Forde , Matthew Lorig , Hongzhong Zhang

We consider an asset whose risk-neutral dynamics are described by a general class of local-stochastic volatility models and derive a family of asymptotic expansions for European-style option prices and implied volatilities. Our implied…

Computational Finance · Quantitative Finance 2014-12-01 Matthew Lorig , Stefano Pagliarani , Andrea Pascucci

We introduce a class of randomly time-changed fast mean-reverting stochastic volatility models and, using spectral theory and singular perturbation techniques, we derive an approximation for the prices of European options in this setting.…

Pricing of Securities · Quantitative Finance 2012-05-15 Matthew Lorig

This paper introduces novel volatility diffusion models to account for the stylized facts of high-frequency financial data such as volatility clustering, intra-day U-shape, and leverage effect. For example, the daily integrated volatility…

Methodology · Statistics 2022-06-01 Donggyu Kim , Minseok Shin

We suggest two classes of multivariate GARCH--models which are both easy to estimate and perform well in forecasting the covariance matrix of more than one hundred stocks. We apply methods from random matrix theory (RMT) to determine the…

Condensed Matter · Physics 2007-05-23 C. Reese , B. Rosenow

We present an explicit hedging strategy, which enables to prove arbitrageness of market incorporating at least two assets depending on the same random factor. The implied Black-Scholes volatility, computed taking into account the form of…

Pricing of Securities · Quantitative Finance 2011-03-01 Mikhail Martynov , Olga Rozanova

This study introduces computation of option sensitivities (Greeks) using the Malliavin calculus under the assumption that the underlying asset and interest rate both evolve from a stochastic volatility model and a stochastic interest rate…

Pricing of Securities · Quantitative Finance 2018-06-18 Bilgi Yilmaz