利用随机算法估算系统性亏空风险度量

IF 1.4 4区 经济学 Q3 BUSINESS, FINANCE SIAM Journal on Financial Mathematics Pub Date : 2024-08-08 DOI:10.1137/22m1539344
Sarah Kaakaï, Anis Matoussi, Achraf Tamtalini
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引用次数: 0

摘要

SIAM 金融数学期刊》,第 15 卷第 3 期,第 700-733 页,2024 年 9 月。 摘要:引入系统风险度量是为了捕捉全球风险以及由相互关联的金融机构系统产生的相应传染效应。为此,提出了两种方法。在第一种方法中,系统风险度量可解释为在汇总单个风险后确保系统安全所需的最低现金量。在第二种方法中,系统性风险度量可解释为在汇总单个风险之前,通过向每个单一机构分配资本来确保系统安全的最小现金量。尽管多位学者对这些风险度量背后的理论进行了深入研究,但迄今为止,数值部分一直被忽视。在本文中,我们使用随机算法方案来估算多元缺口风险度量,并证明所得到的估算结果是一致的,且渐近正态的。我们还在几个例子中对这些算法的性能进行了数值测试。
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Estimation of Systemic Shortfall Risk Measure Using Stochastic Algorithms
SIAM Journal on Financial Mathematics, Volume 15, Issue 3, Page 700-733, September 2024.
Abstract.Systemic risk measures were introduced to capture the global risk and the corresponding contagion effects that are generated by an interconnected system of financial institutions. To this purpose, two approaches were suggested. In the first one, systemic risk measures can be interpreted as the minimal amount of cash needed to secure a system after aggregating individual risks. In the second approach, systemic risk measures can be interpreted as the minimal amount of cash that secures a system by allocating capital to each single institution before aggregating individual risks. Although the theory behind these risk measures has been well investigated by several authors, the numerical part has been neglected so far. In this paper, we use stochastic algorithms schemes in estimating multivariate shortfall risk measure and prove that the resulting estimators are consistent and asymptotically normal. We also test numerically the performance of these algorithms on several examples.
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来源期刊
SIAM Journal on Financial Mathematics
SIAM Journal on Financial Mathematics MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
2.30
自引率
10.00%
发文量
52
期刊介绍: SIAM Journal on Financial Mathematics (SIFIN) addresses theoretical developments in financial mathematics as well as breakthroughs in the computational challenges they encompass. The journal provides a common platform for scholars interested in the mathematical theory of finance as well as practitioners interested in rigorous treatments of the scientific computational issues related to implementation. On the theoretical side, the journal publishes articles with demonstrable mathematical developments motivated by models of modern finance. On the computational side, it publishes articles introducing new methods and algorithms representing significant (as opposed to incremental) improvements on the existing state of affairs of modern numerical implementations of applied financial mathematics.
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