Abstract
This paper proposed a new way to measure variance risk premium by applying the fractional cointegration relationship between implied variance and realized variance. To find the fractional cointegration coefficient between implied variance and realized variance, we proposed a searching method by minimizing the score test statistic proposed by Robinson(1994). We used daily, weekly and monthly data of 5 stock market indexes (SP500, SP100, DJIA, NASDAQ100 and Russell2000) and their volatility indexes from CBOE. We find our new measurement could improve the return prediction power of variance risk premium both in-sample statically and out-of-sample dynamically, and the result is robust for the monthly data among all 5 indexes.
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