Abstract
Abstract Background: In light of the latest global financial crisis and the ongoing sovereign debt crisis, accurate measuring of market losses has become a very current issue. One of the most popular risk measures is Value-at-Risk (VaR). Objectives: Our paper has two main purposes. The first is to test the relative performance of selected GARCH-type models in terms of their ability of delivering volatility estimates. The second one is to contribute to extend the very scarce empirical research on VaR estimation in emerging financial markets. Methods/Approach: Using the daily returns of the Macedonian stock exchange index-MBI 10, we have tested the performance of the symmetric GARCH (1,1) and the GARCH-M model as well as of the asymmetric EGARCH (1,1) model, the GARCH-GJR model and the APARCH (1,1) model with different residual distributions. Results: The most adequate GARCH family models for estimating volatility in the Macedonian stock market are the asymmetric EGARCH model with Student’s t-distribution, the EGARCH model with normal distribution and the GARCH-GJR model. Conclusion: The econometric estimation of VaR is related to the chosen GARCH model. The obtained findings bear important implications regarding VaR estimation in turbulent times that have to be addressed by investors in emerging capital markets
Highlights
The impetus for Value-at-Risk (VaR), the most well-known financial risk measurement, came from failures of financial institutions and the responses of regulators to these failures
We are focusing upon the use of selected Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models to estimate and forecast daily VaR of the Macedonian stock exchange in turbulent times
In this paper we examine the relative performance of selected symmetric GARCH models, such as, the GARCH [1,1] model with normal and Student’s t-distribution and the GARCH-M model and the asymmetric GARCH models, such as, the Exponential GARCH (EGARCH) [1,1] with normal and Student’s t-distribution and the Asymmetric Power ARCH (APARCH) [1,1], model with regard to evaluation and forecasting VaR in the Macedonian stock exchange under crisis times
Summary
The impetus for Value-at-Risk (VaR), the most well-known financial risk measurement, came from failures of financial institutions and the responses of regulators to these failures. The first regulatory measures that evoke Value-at- Risk, were initiated in the 80s, when the Securities Exchange Commission (SEC) tied the capital requirements of financial service firms to the losses that would be incurred, with 95% confidence over a thirty-day interval, in different security classes. As a consequence of the big financial disasters that occurred between 1993 and 1995, there was a growing need for a response to those market losses by banks and other financial institutions, central bankers and academics in terms of building accurate models for measuring market risk. The first is to test the relative performance of selected GARCH-type models in terms of their ability of delivering volatility estimates.
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