【主讲】Haihan Tang (复旦大学泛海国际金融学院助理教授)
【主题】Estimation of a multiplicative correlation structure in the large dimensional case
【时间】2018年3月23日 (周五) 15：30-17：00
【地点】上海财经大学经济学院楼702室
【语言】英文
【摘要】We propose a Kronecker product model for correlation or covariance matrices in the large dimension case. The number of parameters of the model increases logarithmically with the dimension of the matrix. We propose a minimum distance (MD) estimator based on a log-linear property of the model, as well as a one-step estimator, which is a one-step approximation to the quasi-maximum likelihood estimator (QMLE). We establish the rate of convergence and a central limit theorem (CLT) for our estimators in the large dimensional case. A specification test and tools for Kronecker product model selection and inference are provided. In an empirical application to portfolio choice for S&P500 daily returns, we show that our model outperforms the sample covariance matrix and a linear shrinkage estimator.
