Continuous-time limits of multi-period cost-of-capital margins

IF 1.3 Q2 STATISTICS & PROBABILITY Statistics & Risk Modeling Pub Date : 2020-04-17 DOI:10.1515/strm-2019-0008
Hampus Engsner, F. Lindskog
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引用次数: 1

Abstract

Abstract We consider multi-period cost-of-capital valuation of a liability cash flow subject to repeated capital requirements that are partly financed by capital injections from capital providers with limited liability. Limited liability means that, in any given period, the capital provider is not liable for further payment in the event that the capital provided at the beginning of the period turns out to be insufficient to cover both the current-period payments and the updated value of the remaining cash flow. The liability cash flow is modeled as a continuous-time stochastic process on [ 0 , T ] {[0,T]} . The multi-period structure is given by a partition of [ 0 , T ] {[0,T]} into subintervals, and on the corresponding finite set of times, a discrete-time cost-of-capital-margin process is defined. Our main objective is the analysis of existence and properties of continuous-time limits of discrete-time cost-of-capital-margin processes corresponding to a sequence of partitions whose meshes tend to zero. Moreover, we provide explicit expressions for the limit processes when cash flows are given by Itô diffusions and processes with independent increments.
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多期资本成本边际的连续时间限制
我们考虑负债现金流的多期资本成本评估,这些现金流受到重复资本要求的影响,部分资金来自有限责任资本提供者的资本注入。有限责任是指,在任何给定期间,如果在期初提供的资本不足以支付当期付款和剩余现金流量的更新价值,则资本提供者不承担进一步付款的责任。将负债现金流建模为[0,T] {[0,T]}上的连续时间随机过程。通过将[0,T] {[0,T]}划分为子区间给出了多周期结构,并在相应的有限时间集合上定义了一个离散时间资本边际成本过程。我们的主要目标是分析离散时间资本边际成本过程的连续时间极限的存在性和性质,这些过程对应于网格趋向于零的分区序列。此外,我们提供了当现金流由Itô扩散和具有独立增量的过程给出时的极限过程的显式表达式。
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来源期刊
Statistics & Risk Modeling
Statistics & Risk Modeling STATISTICS & PROBABILITY-
CiteScore
1.80
自引率
6.70%
发文量
6
期刊介绍: Statistics & Risk Modeling (STRM) aims at covering modern methods of statistics and probabilistic modeling, and their applications to risk management in finance, insurance and related areas. The journal also welcomes articles related to nonparametric statistical methods and stochastic processes. Papers on innovative applications of statistical modeling and inference in risk management are also encouraged. Topics Statistical analysis for models in finance and insurance Credit-, market- and operational risk models Models for systemic risk Risk management Nonparametric statistical inference Statistical analysis of stochastic processes Stochastics in finance and insurance Decision making under uncertainty.
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