Post by Sapphire Capital on Oct 10, 2008 4:38:32 GMT 4
Risk Forecasting with Conditional Quantile Expected Shortfall
Sait Yilmazer
T-Bank, Istanbul
Alper Ozun
Isbank of Turkey
Atilla Cifter
Marmara University
The Icfai Journal of Applied Finance, Vol. 14, No. 9, pp. 54-67, September 2008
Abstract:
In emerging markets, prices of financial assets might display immediate and high changes. High volatility in returns leads investors to take nonlinear decisions on risk-return balance by disrupting their perceptions. Traditional Value-at-Risk (VaR) models might have difficulties in capturing the fat tails emerging from high volatilities in the asset prices. This study by employing daily closing values of the Istanbul Stock Exchange (ISE) National 100 Index between January 2003 and February 2007 estimates value at risk using expected shortfall with conditional threshold. Performance of the model is compared to those of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) with normal distribution and Generalized Pareto Distribution (GPD). The results reveal that expected shortfall with conditional threshold has better estimation performance in the middle and long run. The results of the backtests imply that expected shortfall with conditional threshold is more proper for the emerging markets because of their ability to capture the value-at-risk from a higher level. This study has originality in that it is the first research applying the expected threshold with conditional threshold effect into the Turkish equity markets.
papers.ssrn.com/sol3/papers.cfm?abstract_id=1263210
Sait Yilmazer
T-Bank, Istanbul
Alper Ozun
Isbank of Turkey
Atilla Cifter
Marmara University
The Icfai Journal of Applied Finance, Vol. 14, No. 9, pp. 54-67, September 2008
Abstract:
In emerging markets, prices of financial assets might display immediate and high changes. High volatility in returns leads investors to take nonlinear decisions on risk-return balance by disrupting their perceptions. Traditional Value-at-Risk (VaR) models might have difficulties in capturing the fat tails emerging from high volatilities in the asset prices. This study by employing daily closing values of the Istanbul Stock Exchange (ISE) National 100 Index between January 2003 and February 2007 estimates value at risk using expected shortfall with conditional threshold. Performance of the model is compared to those of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) with normal distribution and Generalized Pareto Distribution (GPD). The results reveal that expected shortfall with conditional threshold has better estimation performance in the middle and long run. The results of the backtests imply that expected shortfall with conditional threshold is more proper for the emerging markets because of their ability to capture the value-at-risk from a higher level. This study has originality in that it is the first research applying the expected threshold with conditional threshold effect into the Turkish equity markets.
papers.ssrn.com/sol3/papers.cfm?abstract_id=1263210