Application of quantile autoregressive models in minimum Value at Risk and Conditional Value at Risk hedging
| Autor: | Mgr. Michal Svatoň |
|---|---|
| Rok: | 2015 - letní |
| Vedoucí: | doc. PhDr. Jozef Baruník Ph.D. |
| Konzultant: | |
| Typ práce: | Diplomová Finance, finanční trhy a bankovnictví |
| Jazyk: | Anglicky |
| Stránky: | 76 |
| Ocenění: | |
| Odkaz: | https://is.cuni.cz/webapps/zzp/detail/138369/ |
| Abstrakt: | Futures contracts represent a suitable instrument for hedging. One consequence of their standardized nature is the presence of basis risk. In order to mitigate it an agent might aim to minimize Value at Risk or Expected Shortfall. Among numerous approaches to their modelling, CAViaR models which build upon quantile regression are appealing due to the limited set of assumptions and decent empirical performance. We propose alternative specifications for CAViaR model - power and exponential CAViaR, and an alternative, flexible way of computing Expected Shortfall within CAViaR framework - Implied Expectile Level. Empirical analysis suggests that exponential CAViaR yields competitive results both in Value at Risk and Expected Shortfall modelling and in subsequent Value at Risk and Expected Shortfall hedging. |
