ABSTRACT
This paper compares two types of Value-at-Risk models
in measuring market risk which are integrated together with either the
volatility updating namely GARCH(1,1) and EGARCH(1,1). The models are estimated
on Malaysian non-financial sectors data in which seven sectors are chosen to
estimate the relevant parameters. To complement the estimates, several
conservatism tests namely the Mean Relative Bias (MRB) and Root Mean Squared
Relative Bias (RMSRB) are conducted to identify the riskiest position. The
results show that although t-distribution theoretically is appropriate in
handling any reasonable
amount of fat tail or asymmetric biases, its appropriateness and conservative
behavior in VaR application depends on the type of volatility model which has
been integrated together with MCS and also the nature of the non-financial
sectors involved.
Keywords: Value-at-Risk,
conservatism test.
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