Continuous‐time models, realized volatilities, and testable distributional implications for daily stock returns
利用高频日内数据构建已实现波动率和非参数跳跃检验，提出一系列矩条件检验来评估日度收益的分布特征，并应用于道琼斯30只个股，发现时变扩散波动、跳跃和杠杆效应均很重要。
Abstract We provide an empirical framework for assessing the distributional properties of daily speculative returns within the context of the continuous‐time jump diffusion models traditionally used in asset pricing finance. Our approach builds directly on recently developed realized variation measures and non‐parametric jump detection statistics constructed from high‐frequency intra‐day data. A sequence of simple‐to‐implement moment‐based tests involving various transformations of the daily returns speak directly to the importance of different distributional features, and may serve as useful diagnostic tools in the specification of empirically more realistic continuous‐time asset pricing models. On applying the tests to the 30 individual stocks in the Dow Jones Industrial Average index, we find that it is important to allow for both time‐varying diffusive volatility, jumps, and leverage effects to satisfactorily describe the daily stock price dynamics. Copyright © 2009 John Wiley & Sons, Ltd.