具有无界漂移的随机波动模型的部分积分公式的概率表示

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY Esaim-Probability and Statistics Pub Date : 2020-11-20 DOI:10.1051/ps/2022008
Junchao Chen, N. Frikha, Houzhi Li
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引用次数: 2

摘要

摘要本文建立了一类具有无界漂移的随机波动模型在给定时间成熟时的边际律的概率表示和部分积分公式。依靠马尔可夫半群的扰动技术,我们的公式是基于在随机时间网格上进化的简单马尔可夫链,为此我们开发了量身定制的马利亚文演算。在其他应用中,无偏蒙特卡罗路径模拟方法源于我们的公式,因此它可以用于以最优复杂性数值计算期权价格及其相对于金融中的初始值或希腊人的敏感性,即Delta和Vega,用于大型非平滑欧洲支付。数值结果表明了该方法的有效性。
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Probabilistic representation of integration by parts formulae for some stochastic volatility models with unbounded drift
Abstract. 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 technique for Markov semigroups, our formulae are based on a simple Markov chain evolving on a random time grid for which we develop a tailor-made Malliavin calculus. Among other applications, an unbiased Monte Carlo path simulation method stems from our formulas so that it can be used in order to numerically compute with optimal complexity option prices as well as their sensitivities with respect to the initial values or Greeks in finance, namely the Delta and Vega , for a large class of non-smooth European payoff. Numerical results are proposed to illustrate the efficiency of the method.
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来源期刊
Esaim-Probability and Statistics
Esaim-Probability and Statistics STATISTICS & PROBABILITY-
CiteScore
1.00
自引率
0.00%
发文量
14
审稿时长
>12 weeks
期刊介绍: The journal publishes original research and survey papers in the area of Probability and Statistics. It covers theoretical and practical aspects, in any field of these domains. Of particular interest are methodological developments with application in other scientific areas, for example Biology and Genetics, Information Theory, Finance, Bioinformatics, Random structures and Random graphs, Econometrics, Physics. Long papers are very welcome. Indeed, we intend to develop the journal in the direction of applications and to open it to various fields where random mathematical modelling is important. In particular we will call (survey) papers in these areas, in order to make the random community aware of important problems of both theoretical and practical interest. We all know that many recent fascinating developments in Probability and Statistics are coming from "the outside" and we think that ESAIM: P&S should be a good entry point for such exchanges. Of course this does not mean that the journal will be only devoted to practical aspects.
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