英文文献：Roughing It Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility-粗糙化:在回报波动的测量、建模和预测中包含跳跃成分
英文文献作者：Torben G. Andersen,Tim Bollerslev,Francis X. Diebold
英文文献摘要：
A rapidly growing literature has documented important improvements in financial return volatility measurement and forecasting via use of realized variation measures constructed from high-frequency returns coupled with simple modeling procedures. Building on recent theoretical results in Barndorff-Nielsen and Shephard (2004a, 2005) for related bi-power variation measures, the present paper provides a practical and robust framework for non-parametrically measuring the jump component in asset return volatility. In an application to the DM/$ exchange rate, the S&P500 market index, and the 30-year U.S. Treasury bond yield, we find that jumps are both highly prevalent and distinctly less persistent than the continuous sample path variation process. Moreover, many jumps appear directly associated with specific macroeconomic news announcements. Separating jump from non-jump movements in a simple but sophisticated volatility forecasting model, we find that almost all of the predictability in daily, weekly, and monthly return volatilities comes from the non-jump component. Our results thus set the stage for a number of interesting future econometric developments and important financial applications by separately modeling, forecasting, and pricing the continuous and jump components of the total return variation process.

快速增长的文献证明，通过使用由高频收益构建的已实现的变异测度，结合简单的建模程序，在财务收益波动度量和预测方面取得了重要的改进。基于最近Barndorff-Nielsen和Shephard (2004a, 2005)关于相关双功率变化测度的理论结果，本文为非参数度量资产回报波动中的跳变成分提供了一个实用而稳健的框架。在对DM/美元汇率、标准普尔500市场指数和30年期美国国债收益率的应用中，我们发现跳跃不仅非常普遍，而且明显不如连续样本路径变化过程持久。此外，许多大幅上涨似乎与特定宏观经济消息的发布直接相关。在一个简单但复杂的波动率预测模型中，我们发现几乎所有的每日、每周和每月收益波动的可预测性都来自于非波动成分。因此，我们的结果通过对总收益变化过程的连续和跳跃成分分别建模、预测和定价，为一些有趣的未来计量经济学发展和重要的金融应用奠定了基础。