Asset pricing kernel reflects market preferences for risk and probabilities of market states. Risk premium and market states fluctuate continuously, thus, pricing kernel varies as time goes by.
Empirical pricing kernel can be estimated with realized prices of an asset. Rosenberg and Engle (2002) use S&P 500 index option data and assume that the pricing kernel is a power function dependent on index returns. In this paper, the methodology is the same as Rosenberg and Engle, and the data used for estimation is KOSPI 200 index option data.
In power function specification, risk aversion parameter is calculated explicitly. The time-series of the risk aversion supposed to be a proxy of market states. However, a multiple regression of the series on market variables turns out to be insignificant. Finally, one-day hedge ratio can be derived from the estimated pricing kernel. Hedging performance using time-variant pricing kernels is finer than using a constant pricing kernel and mostly better than using a traditional hedging method, Black-Scholes hedging. Thus, time-varying preferences and probabilities appear to be an important factor in the day-to-day pricing of KOSPI 200 options and power function pricing kernel is well replicates index option market.