The high frequency risk attitude implied by the volatility risk premium

Abstract

Risk attitude measures risk preference, determines micro subjects’ investment portfolios and ultimately affects the macro financial market structure, and is commonly measured by risk aversion coefficient. However, constant or lower frequency risk attitude data makes it difficult to match financial variables in frequency. The risk aversion coefficient characterizes the risk premium of unit risk, so there should be a risk attitude behind each volatility and its risk premium. Based on this principle, this paper introduces risk aversion into the continuous-time stochastic volatility model and establishes a state-space model to separate the implied risk attitude time series from the high-frequency volatility and its risk premium time series, which solves the problem of mismatch between the low-frequency risk aversion and the high-frequency market data in the literature.