Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data
提出一种将高频资产收益分解为连续、小跳跃和大跳跃成分的方法，并分析跳跃活跃度等特征，适用于股票、指数等数据，对金融计量和风险管理研究者有参考价值。
This paper reports some of the recent developments in the econometric analysis of semimartingales estimated using high frequency financial returns. It describes a simple yet powerful methodology to decompose asset returns sampled at high frequency into their base components (continuous, small jumps, large jumps), determine the relative magnitude of the components, and analyze the finer characteristics of these components such as the degree of activity of the jumps. We incorporate to effect of market microstructure noise on the test statistics, apply the methodology to high frequency individual stock returns, transactions and quotes, stock index returns and compare the qualitative features of the estimated process for these different data and discuss the economic implications of the results.