Large and moderate deviations for stochastic Volterra systems
Large and moderate deviations for stochastic Volterra systems
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DOI：
10.1016/j.spa.2022.03.017
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发表时间：
2020-04
影响因子：
1.4
通讯作者：
A. Jacquier;A. Pannier
中科院分区：
文献类型：
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作者：
A. Jacquier;A. Pannier
对于一类一般的具有奇异核的多维随机Volterra方程，我们给出了大偏差原理和中偏差原理的统一处理。我们的方法是基于Budhiraja和Dupuis(2019)；Dupuis和Ellis(1997)的弱收敛方法。我们特别展示了这个框架如何包含数学金融中使用的大多数粗略的波动率模型，首次产生Path中等偏差，并概括了文献中的许多最近结果。
We provide a unified treatment of pathwise large and moderate deviations principles for a general class of multidimensional stochastic Volterra equations with singular kernels, not necessarily of convolution form. Our methodology is based on the weak convergence approach by Budhiraja and Dupuis (2019); Dupuis and Ellis (1997). We show in particular how this framework encompasses most rough volatility models used in mathematical finance, yields pathwise moderate deviations for the first time and generalises many recent results in the literature.