Forecasting volatility of the U.S. oil market |
| |
| Institution: | 1. Business School of Sichuan University, Chengdu, China;2. School of Economics & Management, Southwest Jiaotong University, Chengdu, China;3. School of Economics and Commerce, South China University of Technology, China;1. School of Economics & Management, Southwest Jiaotong University, Chengdu, China;2. Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, Canada;1. Faculty of Informatics and Statistics, Department of Statistics and Probability, University of Economics, Prague, Czech Republic;2. University of Stavanger, UiS Business School, Stavanger, Norway;3. Faculty of Finance and Accounting, Department of Monetary Theory and Policy, University of Economics, Prague, Czech Republic |
| |
| Abstract: | We examine the information content of the CBOE Crude Oil Volatility Index (OVX) when forecasting realized volatility in the WTI futures market. Additionally, we study whether other market variables, such as volume, open interest, daily returns, bid-ask spread and the slope of the futures curve, contain predictive power beyond what is embedded in the implied volatility. In out-of-sample forecasting we find that econometric models based on realized volatility can be improved by including implied volatility and other variables. Our results show that including implied volatility significantly improves daily and weekly volatility forecasts; however, including other market variables significantly improves daily, weekly and monthly volatility forecasts. |
| |
| Keywords: | Oil prices Realized volatility Implied volatility Volatility forecasting G14 G13 Q47 L94 |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
