基于缩减措施的半马尔可夫方法

IF 0.7 4区数学 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Advances in Complex Systems Pub Date : 2021-06-23 DOI:10.1142/S0219525920500204

G. D’Amico, Bice di Basilio, F. Petroni

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引用次数: 2

摘要

在本文中，我们评估了加权指数半马尔可夫链(WISMC)在研究高频金融数据风险度量方面的适用性。考虑的措施是固定水平的下降、崩溃时间、崩溃速度、恢复时间和恢复速度;它们为投资组合管理和投资选择提供了有价值的信息。将WISMC模型的实现结果与基于实际数据的结果以及GARCH和EGARCH模型的结果进行了比较。在全球范围内，对于所有考虑的度量，WISMC模型比其他计量经济学模型表现得更好，除非在审查单位的百分比超过30%的情况下，模型的行为相似。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Semi-Markovian Approach to drawdown-based Measures

In this paper we assess the suitability of weighted-indexed semi-Markov chains (WISMC) to study risk measures as applied to high-frequency financial data. The considered measures are the drawdown of fixed level, the time to crash, the speed of crash, the recovery time and the speed of recovery; they provide valuable information in portfolio management and in the selection of investments. The results obtained by implementing the WISMC model are compared with those based on the real data and also with those achieved by GARCH and EGARCH models. Globally, the WISMC model performs much better than the other econometric models for all the considered measures unless in the cases when the percentage of censored units is more than 30% where the models behave similarly.

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来源期刊

Advances in Complex Systems 综合性期刊-数学跨学科应用

CiteScore

1.40

自引率

0.00%

发文量

121

审稿时长

6-12 weeks

期刊介绍： Advances in Complex Systems aims to provide a unique medium of communication for multidisciplinary approaches, either empirical or theoretical, to the study of complex systems. The latter are seen as systems comprised of multiple interacting components, or agents. Nonlinear feedback processes, stochastic influences, specific conditions for the supply of energy, matter, or information may lead to the emergence of new system qualities on the macroscopic scale that cannot be reduced to the dynamics of the agents. Quantitative approaches to the dynamics of complex systems have to consider a broad range of concepts, from analytical tools, statistical methods and computer simulations to distributed problem solving, learning and adaptation. This is an interdisciplinary enterprise.