Estimating Risk Factors with High Frequency Data through Principle Component Analysis

Abstract

This paper proposes a unique estimation method of Jump Factor with high frequency data. Our method employs bi-power variation technique and principle component analysis. Proposed method is unique and exhibits a new measure for financial risk. In this study, we calculated four Jump Factors in United States and Germany and integrated them through principle component analysis. In addition, we could confirm the influence of Jump Factors on financial markets by using the proposed method.