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Titlebook: Continuous Time Processes for Finance; Switching, Self-exci Donatien Hainaut Book 2022 The Editor(s) (if applicable) and The Author(s), und

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2039-1471 xhaustive presentation of sub-diffusionsThis book explores recent topics in quantitative finance with an emphasis on applications and calibration to time-series. This last aspect is often neglected in the existing mathematical finance literature while it is crucial for risk management. The first par
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https://doi.org/10.1007/978-3-322-88949-2f a shock, increases as soon as a jump in price occurs. The influence of this jump on the intensity then decays exponentially over time. This chapter reviews the features of self-exciting jump-diffusions and provides the theoretical background to read Chap. . about non-Markov extensions of such processes.
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https://doi.org/10.1007/978-3-322-88949-2ith the Metropolis–Hastings procedure of Chap. . to estimate parameters. This approach, called the Particle Markov Chain Monte Carlo (PMCMC) algorithm, will be used in Chap. . to quantify illiquidity and in Chap. . to fit Volterra processes. The particle filter serves in Chap. . to estimate the sample path of jump intensity.
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Test, Testbarkeit, Testautomat und Testboard the analytical tractability offered by stochastic calculus. This chapter fills a gap in the literature by providing a closed form expression of the moment generating function (mgf) of non-Markov self-exciting jump processes.
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Particle Filtering and Estimation,ith the Metropolis–Hastings procedure of Chap. . to estimate parameters. This approach, called the Particle Markov Chain Monte Carlo (PMCMC) algorithm, will be used in Chap. . to quantify illiquidity and in Chap. . to fit Volterra processes. The particle filter serves in Chap. . to estimate the sample path of jump intensity.
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Non-Markov Models for Contagion and Spillover, the analytical tractability offered by stochastic calculus. This chapter fills a gap in the literature by providing a closed form expression of the moment generating function (mgf) of non-Markov self-exciting jump processes.
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Book 2022glected in the existing mathematical finance literature while it is crucial for risk management. The first part of this book focuses on switching regime processes that allow to model economic cycles in financial markets. After a presentation of their mathematical features and applications to stocks
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