| Summary: | 碩士 === 國立高雄第一科技大學 === 金融營運所 === 92 === When we use futures to hedge a portfolio of risky assets, the most important objective is to estimate the optimal hedge ratio (OHR). When the futures price follows a martingale and investors have mean-variance utility, the OHR is equal to the minimum variance hedge ratio. Owing to time-varying volatility in financial asset returns, moving average, GARCH, or EWMA models are commonly employed to estimate OHR. All of the approaches to estimating the OHR described above are based on the sample variance and covariance estimators of returns. These are consistent estimators of the population variance and covariance, irrespective of the underlying distribution of data, but they are not in general efficient. In particular, when the distribution of the data is leptokurtic, these estimators will attach too much weight to extreme observations.
This paper uses the Power EWMA estimator of Guermat and Harris (2002) to estimate OHR. The Power EWMA estimator (that is, the robust estimator) can capture the leptokurtic distribution of the data. We also compare the results of the robust estimator to those based on the standard estimators. Our empirical analysis is restricted to the SGX-DT and the TAIFEX Taiwan stock index futures. The empirical results show that use of the robust estimator generates reductions in the variance of the hedged portfolio and the volatility of the OHR for the SGX-DT futures market, and for subperiod 1 of high kurtosis. It also reduce the transaction costs of rebalancing that are associated with changes in the OHR.
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