Analysis of covariance structure of the financial markets by use of high-frequency data

本研究旨在探讨利用高频数据估计金融市场方差-协方差结构的方法。主要研究者（PI）与东京大学的吉田中弘教授共同提出了所谓的Hayashi-Yoshida估计量，并对该估计量的统计理论进行了改进，探讨了其在实际金融风险管理中的适用性。与此同时，为了探索高频数据建模和分析的潜在方法和应用，PI对相关领域的现有研究进行了审查，并研究了使用高频数据量化金融风险的替代方法。

This project aims to investigate methodologies for estimating variance-covariance structure of the financial markets using high-frequency data, which has been getting more accessible and been utilized lately. The principal investigator (PI) has advances the statistical theory for the so-called Hayashi-Yoshida estimator, which PI proposed with Professor Nakahiro Yoshida of the University of Tokyo, and explored its applicability to the practical financial risk management. In the meantime, for exploring potential methodologies as well as applications of high-frequency data modeling and analysis, the PI has done reviews of the existing studies in related fields and he has investigated alternative approaches to quantify financial risks with high-frequency data.