Measuring and Testing the Impact of News on Volatility
引入新闻影响曲线来度量新信息如何融入波动率估计，利用日本日度股票收益数据比较多种ARCH模型，并引入部分非参数ARCH模型，发现GJR和EGARCH模型表现最佳。
This paper introduces the News Impact Curve to measure how new information is incorporated into volatility estimates. A variety of new and existing ARCH models are compared and estimated with daily Japanese stock return data to determine the shape of the News Impact Curve. New diagnostic tests are presented which emphasize the asymmetry of the volatility response to news. A partially non-parametric ARCH model is introduced to allow the data to estimate this shape. A comparison of this model with the existing models suggests that the best models are one by Glosten Jaganathan and Runkle (GJR) and Nelson's EGARCE. Similar results hold on a pre-crash sample period but are less strong.