Modeling Liquidity Adjusted Value at Risk Using Quantile Regression Analysis
|Author:||Mgr. Dung Nguyen Quang|
|Year:||2015 - summer|
|Leaders:|| doc. PhDr. Jozef Baruník Ph.D.
|Work type:|| Economic Theory
|Awards and prizes:|
|Abstract:||The master’s thesis deals with modeling Value at Risk model adjusted by liquidity.
For this purpose we use quantile regression analysis and liquidity proxies.
We find out that Garman-Klass volatility estimator can be very useful in period
2000-2008 for the small and mid-size semiconductor companies but not in
period 2008-2015. The NASDAQ composite Garman-Klass volatility is useful
for all semiconductor companies for period 2008-2015. We might conclude that
from the outbreak of the crisis returns of all semiconductor companies might
depend on movement of NASDAQ composite index. We use Amihud and Roll
measures as the liquidity proxies but the results are not persuasive regardless
or size of companies and period we analyzed.