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We consider a stochastic process driven by a diffusion and jumps. We devise a technique, which is based on a discrete record of observations, for identifying the times when jumps larger than a suitably defined threshold occurred. The…

Statistics Theory · Mathematics 2007-06-13 Cecilia Mancini

In this paper, we develop a 4/2 stochastic volatility plus jumps model, namely, a new stochastic volatility model including the Heston model and 3/2 model as special cases. Our model is highly tractable by applying the Lie symmetries theory…

Computational Finance · Quantitative Finance 2015-11-05 Wei Lin , Shenghong Li , Xingguo Luo , Shane Chern

Some expansion methods have been proposed for approximately pricing options which has no exact closed formula. Benhamou et al. (2010) presents the smart expansion method that directly expands the expectation value of payoff function with…

Computational Finance · Quantitative Finance 2019-08-27 Kenji Nagami

We investigate the extension of the multilevel Monte Carlo path simulation method to jump-diffusion SDEs. We consider models with finite rate activity, using a jump-adapted discretisation in which the jump times are computed and added to…

Computational Finance · Quantitative Finance 2011-06-24 Yuan Xia

We analyze the valuation partial differential equation for European contingent claims in a general framework of stochastic volatility models where the diffusion coefficients may grow faster than linearly and degenerate on the boundaries of…

Probability · Mathematics 2011-12-13 Erhan Bayraktar , Constantinos Kardaras , Hao Xing

This work examines a stochastic volatility model with double-exponential jumps in the context of option pricing. The model has been considered in previous research articles, but no thorough analysis has been conducted to study its quality…

Pricing of Securities · Quantitative Finance 2025-09-17 Gaetano Agazzotti , Claudio Aglieri Rinella , Jean-Philippe Aguilar , Justin Lars Kirkby

We derive a forward equation for arbitrage-free barrier option prices, in terms of Markovian projections of the stochastic volatility process, in continuous semi-martingale models. This provides a Dupire-type formula for the coefficient…

Mathematical Finance · Quantitative Finance 2016-09-19 Ben Hambly , Matthieu Mariapragassam , Christoph Reisinger

Standard jump-diffusion models assume independence between jumps and diffusion components. We develop a multi-type jump-diffusion model where jump occurrence and magnitude depend on contemporaneous diffusion movements. Unlike previous…

Mathematical Finance · Quantitative Finance 2025-12-18 Hamza Virk , Yihren Wu , Majnu John

This research addresses accurate option pricing by employing models beyond the traditional Black-Scholes framework. While Black-Scholes provides a closed-form solution, it is limited by assumptions of constant volatility, no dividends, and…

Computational Finance · Quantitative Finance 2026-04-08 Karmanpartap Singh Sidhu , Pranshi Saxena

Fast pricing of American-style options has been a difficult problem since it was first introduced to financial markets in 1970s, especially when the underlying stocks' prices follow some jump-diffusion processes. In this paper, we propose a…

Computational Finance · Quantitative Finance 2013-05-21 Helin Zhu , Fan Ye , Enlu Zhou

Local volatility is a versatile option pricing model due to its state dependent diffusion coefficient. Calibration is, however, non-trivial as it involves both proposing a hypothesis model of the latent function and a method for fitting it…

Mathematical Finance · Quantitative Finance 2021-12-08 Martin Tegner , Stephen Roberts

Recent empirical evidence has highlighted the crucial role of jumps in both price and volatility within the cryptocurrency market. In this paper, we integrate price--volatility co-jumps and volatility short-term dependency into a coherent…

Pricing of Securities · Quantitative Finance 2025-06-17 Boyi Li , Weixuan Xia

Volatility measures the amplitude of price fluctuations. Despite it is one of the most important quantities in finance, volatility is not directly observable. Here we apply a maximum likelihood method which assumes that price and volatility…

Computational Finance · Quantitative Finance 2012-09-03 Jordi Camprodon , Josep Perelló

In the paper we consider the problem of valuation and hedging of American options written on dividend-paying assets whose price dynamics follow the multidimensional diffusion model. We derive a stochastic balance equation for the American…

Pricing of Securities · Quantitative Finance 2021-02-26 Malkhaz Shashiashvili

Given discrete time observations over a fixed time interval, we study a nonparametric Bayesian approach to estimation of the volatility coefficient of a stochastic differential equation. We postulate a histogram-type prior on the volatility…

Methodology · Statistics 2019-04-01 Shota Gugushvili , Frank van der Meulen , Moritz Schauer , Peter Spreij

We study the estimation of leverage effect and volatility of volatility by using high-frequency data with the presence of jumps. We first construct spot volatility estimator by using the empirical characteristic function of the…

Methodology · Statistics 2026-03-03 Qiang Liu , Zhi Liu , Wang Zhou

We consider the pricing of derivatives written on the discretely sampled realized variance of an underlying security. In the literature, the realized variance is usually approximated by its continuous-time limit, the quadratic variation of…

Pricing of Securities · Quantitative Finance 2010-11-24 Martin Keller-Ressel , Johannes Muhle-Karbe

The problem of integrated volatility estimation for the solution X of a stochastic differential equation with L{\'e}vy-type jumps is considered under discrete high-frequency observations in both short and long time horizon. We provide an…

Statistics Theory · Mathematics 2020-05-01 Chiara Amorino , Arnaud Gloter

Following the foundational work of the Black--Scholes model, extensive research has been developed to price the option by addressing its underlying assumptions and associated pricing biases. This study introduces a novel framework for…

Mathematical Finance · Quantitative Finance 2025-08-21 Tapan Kar , Suprio Bhar , Barun Sarkar , Sesha Meka

In this paper, we obtain sharp asymptotic formulas with error estimates for the Mellin convolution of functions, and use these formulas to characterize the asymptotic behavior of marginal distribution densities of stock price processes in…

Pricing of Securities · Quantitative Finance 2014-03-24 Archil Gulisashvili , Josep Vives
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