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An ergodic BSDE approach to forward entropic risk measures: representation and large-maturity behavior
Finance and Stochastics ( IF 1.7 ) Pub Date : 2018-12-12 , DOI: 10.1007/s00780-018-0377-3
Wing Fung Chong , Ying Hu , Gechun Liang , Thaleia Zariphopoulou

Using elements from the theory of ergodic backward stochastic differential equations (BSDEs), we study the behavior of forward entropic risk measures in stochastic factor models. We derive general representation results (via both BSDEs and convex duality) and examine their asymptotic behavior for risk positions of large maturities. We also compare them with their classical counterparts and provide a parity result.

中文翻译:

遍历BSDE的熵熵风险度量方法:代表性和成熟度行为

使用遍历后向随机随机微分方程(BSDE)理论中的元素,我们研究了随机因素模型中正向熵风险测度的行为。我们导出一般表示结果(通过BSDE和凸对偶),并检查它们的渐进行为对大到期风险位置的影响。我们还将它们与经典同类产品进行比较,并提供均等的结果。
更新日期:2018-12-12
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