A rank test for the number of factors with high-frequency data
A rank test for the number of factors with high-frequency data
复制标题
高频数据因素数量的排名检验
DOI:
10.1016/j.jeconom.2019.03.004
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发表时间:
2019-08
影响因子:
6.3
通讯作者:
Wang Zhou
中科院分区:
文献类型:
--
作者:
Xin-Bing Kong;Zhi Liu;Wang Zhou
In the literature, consistency of the estimates of the number of factors for large-dimensional factor models had been extensively studied recently. But the second-order property of the estimator has long been unsolved due to lack of limiting distribution of the estimators. In this paper, we propose a rank test of the number of factors using large panel high-frequency data contaminated with microstructure noise. The rank test is realized by forming a fixed number of portfolios which reduce the dimension to a finite number. In the process of constructing portfolios, the number of factors is equal to the rank of the volatility matrix of the diversified portfolios asymptotically. Via estimating the volatility rank of a low-dimensional price dynamics of the portfolios, we establish a central limit theorem of the estimated factor number. We then apply the asymptotic normality to testing on the number of factors. Numerical experiments including the Monte-Carlo simulations and real data analysis justify our theory.
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DOI:
10.2139/ssrn.2669506
发表时间:
2016-10
期刊:
Econometric Modeling: Capital Markets - Risk eJournal
影响因子:
--
作者:
Yacine Ait-Sahalia;D. Xiu
通讯作者:
Yacine Ait-Sahalia;D. Xiu
DOI:
10.2139/ssrn.2584172
发表时间:
2018-05
期刊:
ERN: Estimation (Topic)
影响因子:
--
作者:
Markus Pelger
通讯作者:
Markus Pelger
DOI:
10.2139/ssrn.2920693
发表时间:
2017-10
期刊:
Capital Markets: Market Microstructure eJournal
影响因子:
--
作者:
Chaoxing Dai;Kun Lu;D. Xiu
通讯作者:
Chaoxing Dai;Kun Lu;D. Xiu
DOI:
10.3390/risks4010005
发表时间:
2016-02
期刊:
--
影响因子:
--
作者:
Harley Thompson
通讯作者:
Harley Thompson
影响因子:
6.3
作者:
Kim, Donggyu;Kong, Xin-Bing;Wang, Yazhen
通讯作者:
Wang, Yazhen