Influence of stock market variables on correlations among S&P sectors
| Autor: | Mgr. Matěj Coufal |
|---|---|
| Rok: | 2022 - letní |
| Vedoucí: | PhDr. František Čech Ph.D. |
| Konzultant: | |
| Typ práce: | Diplomová Finance, finanční trhy a bankovnictví |
| Jazyk: | Anglicky |
| Stránky: | 100 |
| Ocenění: | |
| Odkaz: | https://dspace.cuni.cz/handle/20.500.11956/174002 |
| Abstrakt: | This thesis investigates the influence of the exogenous variables (S&P 500 Index, 10-year US Treasury Note, crude oil, and CBOE Volatility Index (VIX)) on the dynamics of correlations among S&P sectors. We concentrate on daily and weekly investment horizons, and employ the bivariate Dynamic Conditional Correlation (DCC) model. Changes in correlations implied by the DCC model are further modelled using the exogenous variables. The results indicate that VIX has the best ability to predict future changes in correlations. An increase in VIX on day (week) t is expected to cause a rise in correlations on day (week) t + 1. Next, correlations of the Energy sector tend to increase in weeks when crude oil prices are falling. Further, correlations of the Information Technology sector are likely to increase on days of rising yield on the 10-year US Treasury Note. Although we detect a certain power to predict future changes in correlations, very little of these changes is actually explained. |
