Multiscale Hedging with Crude Oil Futures Based on EMD Method

Studying the impact of the different components in data on hedging can provide valuable guidance to investors. However, the previous multiscale hedging studies do not examine the issue from the data itself. In this study, we use the empirical mode decomposition (EMD) method to reconstruct the crude oil futures and spot returns into three different scales: short-term, medium-term, and long-term. Then, we discuss the crude oil hedging performance under the dynamic minimum-CVaR framework at different scales. Based on the daily prices of Brent crude oil futures contract from August 18, 2005, to September 16, 2019, the empirical results show that the extracted scales comprise different information of original returns, short-term information occupies the most important position, and hedging is mainly driven by short-term information. Besides, hedging relying on long-term information has the best hedging performance. Removing some information related to short-term noise from the original returns is helpful for investors.

Hedging performance and the heterogeneity among market participants

Purpose This paper aims to apply the heterogeneous autoregressive model of realized volatility (HAR-RV) model to minimum-variance hedge ratio estimation and compares the hedging performance of presenting a model with that of a conventional rolling ordinary-least-square (OLS) hedging model. Moreover, this paper empirically analyzes the relationship between hedging performance and the heterogeneity of investors with different trading frequency in forming the expectation for the spot volatility, futures volatility and the covariance in the market. Design/methodology/approach Use HAR-RV to form expectations of participants of spots and futures market for the next period volatility based on two parts. One is the current observable realized volatility at the same time scale. The other is the expectation for the next longer time scale horizon volatility. Compare hedging performance with rolling OLS model and HAR-RV model. Present a three-times-scale-length (daily, weekly and monthly) HAR-RV model for the spot and futures returns and volatility to analyze the relationship between the hedging performance and the heterogeneity among participants in each market. Findings The empirical results show that HAR-RV model outperforms the rolling OLS in terms of variance reduction and expected utility in the out-of-sample period. The results also indicate that the greater variance reduction occurs when investors with different trading frequency have a less heterogeneous expectation for spot volatility and more heterogeneous expectation for futures volatility and the covariance. In addition, the expected utility increases along with lower heterogeneity in spot volatility and higher in futures volatility and the covariance. Hedging performance improves along with decreasing heterogeneity of investors in spot volatility and increasing heterogeneity in futures volatility and the covariance. Originality/value This paper considers the heterogeneity of participants in spot and futures market, the authors apply HAR-RV model to MVHR estimation and compare the hedging performance of presenting a model with that of conventional rolling OLS hedging model, providing more evidence in hedging literature. This paper analyzes in depth the relationship between hedging performance and the heterogeneity in the market.