Abstract

PurposeRisk aversion is considered as an important factor in predicting asset prices. Many studies have proved that there exists important price information spillover among crude oil, precious metals and agricultural markets. Then there naturally follows the question: Is the risk aversion of investors in crude oil market predictable for the returns of precious metals and agricultural products? The purpose of this paper is to answer this question. For this reason, the authors explore the directional predictability and the cross-quantile dependence between risk aversion of crude oil market investors and returns of precious metals and agricultural products.Design/methodology/approachTo better describe the risk aversion of investors, this paper uses high-frequency data and model-free calculation method to obtain variance risk premium of crude oil. Then, this paper uses the cross-quantilogram method to investigate the directional predictability and cross-quantile dependence between risk aversion of crude oil market investors and returns of precious metals and agricultural products. Meanwhile, it employs the partial cross-quantilogram (PCQ) method to test the impact of control variables on the empirical results.FindingsFirstly, risk aversion of crude oil market investors has directional predictability for returns of precious metals and agricultural products. Secondly, different degrees of risk aversion of crude oil market investors have different impacts on returns of precious metals and agricultural products. A low (high) degree of crude oil market investors' risk aversion has negative (positive) predictability for returns of precious metals and agricultural products. Finally, during the sample period, the returns of precious metals are more affected by risk aversion of crude oil market investors than returns of agricultural products.Originality/valueFirst of all, this paper studies the impact of risk aversion of crude oil market investors on returns of precious metals and agricultural products. It updates previous relevant studies on the factors influencing the prices of precious metals and agricultural products, and provides a new idea for the forecast of those commodity returns. Secondly, this paper provides the evidence that different degrees of risk aversion of investors have different effects on the returns of commodities, and expands the research on the topic of commodity returns prediction. Finally, high-frequency data are employed in this paper to better capture the risk aversion of investors than commonly used daily data.

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