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We price European options in a class of models in which the volatility of the underlying risky asset depends on the short rate of interest. Our study results in an explicit pricing formula that depends on knowledge of a characteristic…

Mathematical Finance · Quantitative Finance 2026-02-03 Tim Leung , Matthew Lorig

One-dimensional run-and-tumble processes may converge towards some localized non-equilibrium steady state when the two velocities and/or the two switching rates are space-dependent. A long dynamical trajectory can be then analyzed via the…

Statistical Mechanics · Physics 2021-08-23 Cecile Monthus

Based on the existing literature, this article presents the different ways of choosing the parameters of stochastic volatility models in general, in the context of pricing financial derivative contracts. This includes the use of stochastic…

Pricing of Securities · Quantitative Finance 2025-12-24 Fabien Le Floc'h

Adaptive time series forecasting is essential for prediction under regime changes. Several classical methods assume linear Gaussian state space model (LGSSM) with variances constant in time. However, there are many real-world processes that…

Machine Learning · Statistics 2024-02-23 Baptiste Abélès , Joseph de Vilmarest , Olivier Wintemberger

In equity and foreign exchange markets the risk-neutral dynamics of the underlying asset are commonly represented by stochastic volatility models with jumps. In this paper we consider a dense subclass of such models and develop analytically…

Pricing of Securities · Quantitative Finance 2010-10-11 Aleksandar Mijatović , Martijn Pistorius

Upper estimates of densities of convolution semigroups of probability measures are given under explicit assumptions on the corresponding L\'evy measure and the L\'evy--Khinchin exponent.

Probability · Mathematics 2010-06-30 Pawel Sztonyk

This paper proposes a hierarchical modeling approach to perform stochastic model specification in Markov switching vector error correction models. We assume that a common distribution gives rise to the regime-specific regression…

Econometrics · Economics 2019-09-06 Niko Hauzenberger , Florian Huber , Michael Pfarrhofer , Thomas O. Zörner

We develop at-the-money call-price and implied volatility asymptotic expansions in time to maturity for a class of asset-price models whose log returns follow a L\'evy process. Under mild assumptions placing the driving L\'evy process in…

Pricing of Securities · Quantitative Finance 2026-05-25 Allen Hoffmeyer , Christian Houdré

We propose a new generalisation of jump-telegraph process with variable velocities and jumps. Amplitude of the jumps and velocity values are random, and they depend on the time spent by the process in the previous state of the underlying…

Probability · Mathematics 2013-11-22 Nikita Ratanov

Credit Value Adjustment (CVA) is the difference between the value of the default-free and credit-risky derivative portfolio, which can be regarded as the cost of the credit hedge. Default probabilities are therefore needed, as input…

Mathematical Finance · Quantitative Finance 2018-06-21 Ola Hammarlid , Marta Leniec

These lectures notes aim at introducing L\'{e}vy processes in an informal and intuitive way, accessible to non-specialists in the field. In the first part, we focus on the theory of L\'{e}vy processes. We analyze a `toy' example of a…

Pricing of Securities · Quantitative Finance 2008-12-02 Antonis Papapantoleon

The usage of a spot volatility estimate based on a volatility decomposition in a time-changed price-model according to the trading times is investigated. In this model clock-time volatility splits up into the product of tick-time volatility…

Probability · Mathematics 2016-05-10 Rainer Dahlhaus , Sophon Tunyavetchakit

We consider the supOU stochastic volatility model which is able to exhibit long-range dependence. For this model we give conditions for the discounted stock price to be a martingale, calculate the characteristic function, give a strip where…

Pricing of Securities · Quantitative Finance 2014-04-08 Robert Stelzer , Jovana Zavišin

We build a sequence of empirical measures on the space D(R_+,R^d) of R^d-valued c\`adl\`ag functions on R_+ in order to approximate the law of a stationary R^d-valued Markov and Feller process (X_t). We obtain some general results of…

Probability · Mathematics 2011-05-31 Gilles Pagès , Fabien Panloup

This paper considers the case of pricing discretely-sampled variance swaps under the class of equity-interest rate hybridization. Our modeling framework consists of the equity which follows the dynamics of the Heston stochastic volatility…

Pricing of Securities · Quantitative Finance 2020-04-14 Teh Raihana Nazirah Roslan , Wenjun Zhang , Jiling Cao

We develop a method that relates the truncated cumulant-function of the fourth order with the L\'evian cumulant-function. This gives us explicit formulas for the L\'evy-parameters, which allow a real-time analysis of the state of a…

Statistical Mechanics · Physics 2019-12-04 Alexander Jurisch

We consider a stochastic volatility model with L\'evy jumps for a log-return process $Z=(Z_{t})_{t\geq 0}$ of the form $Z=U+X$, where $U=(U_{t})_{t\geq 0}$ is a classical stochastic volatility process and $X=(X_{t})_{t\geq 0}$ is an…

Pricing of Securities · Quantitative Finance 2012-02-23 J. E. Figueroa-López , R. Gong , C. Houdré

In this paper we study coupled fully non-local equations, where a linear non-local operator jointly acts on the time and space variables. We establish existence and uniqueness of the solution. A maximum principle is proved and used to…

Probability · Mathematics 2025-01-24 Giacomo Ascione , Enrico Scalas , Bruno Toaldo , Lorenzo Torricelli

We propose a new method for the estimation of a semiparametric tempered stable L\'{e}vy model. The estimation procedure combines iteratively an approximate semiparametric method of moment estimator, Truncated Realized Quadratic Variations…

Econometrics · Economics 2022-02-25 José E. Figueroa-López , Ruoting Gong , Yuchen Han

Inference, prediction and control of complex dynamical systems from time series is important in many areas, including financial markets, power grid management, climate and weather modeling, or molecular dynamics. The analysis of such highly…

Machine Learning · Statistics 2019-08-19 Hao Wu , Frank Noé
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