Work detail

Value at Risk: GARCH vs. Stochastic Volatility Models: Empirical Study

Author: Mgr. Viktória Tesárová
Year: 2012 - summer
Leaders: PhDr. Petr Gapko Ph.D.
Consultants:
Work type: Finance, Financial Markets and Banking
Masters
Language: English
Pages: 98
Awards and prizes:
Link:
Abstract: The thesis compares GARCH volatility models and Stochastic Volatility (SV)
models with Student's t distributed errors and its empirical forecasting performance
of Value at Risk on ve stock price indices: S&P, NASDAQ Composite,
CAC, DAX and FTSE. It introduces in details the problem of SV models Maximum
Likelihood examinations and suggests the newly developed approach
of Ecient Importance Sampling (EIS). EIS is a procedure that provides an
accurate Monte Carlo evaluation of likelihood function which depends upon
high-dimensional numerical integrals.
Comparison analysis is divided into in-sample and out-of-sample forecasting
performance and evaluated using standard statistical probability backtestig
methods as conditional and unconditional coverage.
Based on empirical analysis thesis shows that SV models can perform at
least as good as GARCH models if not superior in forecasting volatility and
parametric VaR.
Downloadable: DT Tesárová

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