Modelling S&P 100 volatility: The information content of stock returns |
| |
| Affiliation: | 1. Dipartimento di Matematica “G. Peano”, Università degli Studi di Torino, Via Carlo Alberto 10, Torino, 10123, Italy;2. Institute of Physiology of the Czech Academy of Sciences, Videnska 1083, Prague 4, 14220, Czech Republic;3. Johannes Kepler University Linz, Altenbergerstraße 69, Linz, 4040, Austria;1. Nonlinear Scientific Research Center, Faculty of Science, Jiangsu University, Zhenjiang, Jiangsu 212013, PR China;2. Department of Mathematics, Ningbo University, Ningbo 315211, PR China;3. Department of Mathematics, Nanjiang University, Nanjing 210093, PR China;1. School of Finance, Yunnan University of Finance and Economics, Kunming 650221, PR China;2. Institute of Economic Institutions and Policies, Yunnan University of Finance and Economics, Kunming 650221, PR China |
| |
| Abstract: | Theoretical models that relate volatility to the quantity of information are extended to a multi-asset setting and it is deduced that stock returns may or may not have incremental information when modelling index volatility, depending on the sources of information that move stock prices. The first empirical study that can help resolve this theoretical uncertainty is presented. A detailed analysis of the daily volatility of the S&P 100 index from 1984 to 1998 shows there is some incremental volatility information in the returns from the 100 shares that define the index. This evidence is obtained from ARCH models that incorporate leverage effects, dummy variables for the 1987 crash and aggregate measures of stock return volatility. Significant differences between estimated volatilities are found for various stock measures and sub-periods. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
