Forecasting volatility and capturing downside risk of the Taiwanese futures markets under the financial tsunami

Purpose-The purpose of this paper is to apply alternative GARCH-type models to daily volatility forecasting, and apply Value-at-Risk (VaR) to the Taiwanese stock index futures markets that suffered most from the global financial tsunami that occurred during 2008. Design/methodology/approach-Rather than using squared returns as a proxy for true volatility, this study adopts three range-based proxies (PK, GK and RS), and one return-based proxy (realized volatility), for use in the empirical exercise. The forecast evaluation is conducted using various proxy measures based on both symmetric and asymmetric loss functions, while back-testing and two utilitybased loss functions are employed for further VaR assessment with respect to risk management practice. Findings-Empirical results demonstrate that the EGARCH model provides the most accurate daily volatility forecasts, while the performances of the standard GARCH model and the GARCH models with highly persistent and long-memory characteristics are relatively poor. In the area of risk management, the RV-VaR model tends to underestimate VaR and has been rejected owing to a lack of correct unconditional coverage. In contrast, the GARCH genre of models can provide satisfactory and reliable daily VaR forecasts. Originality/value-The unobservable volatility can be proxied using parsimonious daily price range with freely available prices when applied to Taiwanese futures markets. Meanwhile, the GARCH-type models remain valid downside risk measures for both regulators and firms in the face of a turbulent market.