A novel two-sample test within the space of symmetric positive definite matrix distributions and its application in finance

IF 0.8 4区 数学 Q3 STATISTICS & PROBABILITY
Žikica Lukić, Bojana Milošević
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引用次数: 0

Abstract

This paper introduces a novel two-sample test for a broad class of orthogonally invariant positive definite symmetric matrix distributions. Our test is the first of its kind, and we derive its asymptotic distribution. To estimate the test power, we use a warp-speed bootstrap method and consider the most common matrix distributions. We provide several real data examples, including the data for main cryptocurrencies and stock data of major US companies. The real data examples demonstrate the applicability of our test in the context closely related to algorithmic trading. The popularity of matrix distributions in many applications and the need for such a test in the literature are reconciled by our findings.

Abstract Image

Abstract Image

对称正定矩阵分布空间内的新型双样本检验及其在金融领域的应用
本文针对一大类正交不变正定对称矩阵分布提出了一种新颖的双样本检验。我们的检验是首个此类检验,并推导了其渐近分布。为了估计检验功率,我们使用了经速引导法,并考虑了最常见的矩阵分布。我们提供了几个真实数据示例,包括主要加密货币的数据和主要美国公司的股票数据。真实数据示例证明了我们的测试在与算法交易密切相关的环境中的适用性。我们的研究发现,矩阵分布在许多应用中的普及性和文献中对这种检验的需求是一致的。
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来源期刊
CiteScore
2.00
自引率
0.00%
发文量
39
审稿时长
6-12 weeks
期刊介绍: Annals of the Institute of Statistical Mathematics (AISM) aims to provide a forum for open communication among statisticians, and to contribute to the advancement of statistics as a science to enable humans to handle information in order to cope with uncertainties. It publishes high-quality papers that shed new light on the theoretical, computational and/or methodological aspects of statistical science. Emphasis is placed on (a) development of new methodologies motivated by real data, (b) development of unifying theories, and (c) analysis and improvement of existing methodologies and theories.
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