用半参数估计的LSTAR-ANLSTGARCH方法检验法国ETF市场的弱形式效率

IF 0.7 Q2 AREA STUDIES
Mohamed Chikhi, C. Diebolt
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引用次数: 0

摘要

本文采用半参数极大似然方法,将创新分布替换为基于核密度函数的非参数估计,通过带有ANSTGARCH误差的LSTAR模型检验法国ETF市场的弱形式效率。在本文中,我们考虑2009年至2020年的每日xtracker CAC 40 UCITS进行分析,因为与其他法国股票市场相比,它应该捕获更多信息。在应用不同的统计检验后,我们发现价格波动表现为短暂冲击的结果,LSTAR-ANLSTGARCH模型在一定时间范围内的预测效果优于其他模型。该模型的预测结果也优于随机漫步模型;因此,XCAC 40价格是整个时期有效市场的一个不弱形式,因为它的连续回报是非线性依赖的,并且不是随机产生的。利用其渐近分布进行双谱估计。括号内的数字是临界概率。在自回归中,采用Tsay Ori-F检验来检验被忽略的非线性。我们使用4个延迟对STAR进行更具体的测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Testing the weak form efficiency of the French ETF market with the LSTAR-ANLSTGARCH approach using a semiparametric estimation
The present research aims to test the weak-form efficiency of the French ETF market through a LSTAR model with ANSTGARCH errors, by using semiparametric maximum likelihood where the innovation distribution is replaced by a nonparametric estimate based on the kernel density function. In this paper, we consider the daily Xtrackers CAC 40 UCITS from 2009 to 2020 for the analysis as it is supposed to capture more information compared to other French stock markets. After application of different statistical tests, we show that the price fluctuations appear as the result of transitory shocks and the predictions provided by the LSTAR-ANLSTGARCH model are better than those of other models for some time horizons. The predictions from this model are also better than those of the random walk model; accordingly, the XCAC 40 price is a not weak form of an efficient market for the entire period because its successive return is nonlinearly dependent and does not generate randomly. bispectrum estimates by exploiting its asymptotic distribution. The numbers in the parenthesis are critical probabilities. 𝐹 𝑇𝑠𝑎𝑦4 is the Tsay Ori-F test for neglected non-linearities in an autoregression. We test more specifically against STAR using 4 lags.
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来源期刊
CiteScore
1.30
自引率
16.70%
发文量
3
审稿时长
10 weeks
期刊介绍: The Eastern Journal of European Studies (EJES) seeks to provide a forum for multidisciplinary and interdisciplinary dialogue between ideas, and a framework for theoretical and empirical analyses covering major topics in European studies: European history, politics, European economy and European policies, EU community law, European culture and society. EJES encourages studies focusing on Central and Eastern Europe (including Eastern Neighbourhood) in order to better understand its transformations induced by the integration process and to address its specific challenges by supporting scientific debates on the general European theory and practice. Furthermore, the editorial board regularly invites distinguished guest editors to coordinate thematic issues.
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