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Forecasting the S & P 500 index volatility using investor sentiment
| Content Provider | Semantic Scholar |
|---|---|
| Author | Byuna, Suk Joon Chob, Hangjun |
| Copyright Year | 2014 |
| Abstract | We examine several approaches to obtain the volatility forecast for the S&P 500 index: the GARCH-type models, an implied volatility, and their linear combinations. Based on the results, we document that linear combination outperforms the individual models. This result is consistent with existing literature. We also investigate the effect of the regime-switching method using investor sentiment. According to the results, we suggest that the regimeswitching method using investor sentiment makes the volatility forecast value more efficient. EFM classification: 450, 350, 720 |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.efmaefm.org/0EFMAMEETINGS/EFMA%20ANNUAL%20MEETINGS/2014-Rome/papers/EFMA2014_0160_fullpaper.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |