累积收益贝塔的非对称性检验:金融危机与原油价格的影响

IF 1.3 Q2 STATISTICS & PROBABILITY

Statistics & Risk Modeling Pub Date : 2017-01-01 DOI:10.1515/strm-2016-0010

P. Kokoszka, Hong Miao, Ben Zheng

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引用次数: 0

摘要

摘要引入函数因子模型，研究单项资产累积收益曲线对市场和其他因素的依赖关系。我们提出了一个新的统计检验来确定两个样本周期的相关性是否相等。通过渐近理论和仿真验证了该检验的统计性质。我们运用这个检验来研究最近的金融危机和油价趋势对个股和板块etf的影响。我们的分析揭示了每日原油期货曲线的重要性以及它们对个股和行业etf的不同影响。它还表明，函数方法具有不同于从点对点返回的标量因子模型获得的信息内容。

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Testing for asymmetry in betas of cumulative returns: Impact of the financial crisis and crude oil price

Abstract We introduce a functional factor model to investigate the dependence of cumulative return curves of individual assets on the market and other factors. We propose a new statistical test to determine whether the dependence in two sample periods are equal. The statistical properties of the test are established by asymptotic theory and simulations. We apply this test to study the impact of the recent financial crisis and trends in oil price on individual stock and sector ETFs. Our analysis reveals the significance of the daily oil futures curves and their different impact on individual stocks and sector ETFs. It also shows that the functional approach has an information content different from that obtained from scalar factor models for point-to-point returns.

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来源期刊

Statistics & Risk Modeling STATISTICS & PROBABILITY-

CiteScore

1.80

自引率

6.70%

发文量

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.