Multiscale Hedging with Crude Oil Futures Based on EMD Method

Chengli Zheng,Kuangxi Su,Bekir Sahin

doi:10.1155/2020/8869839

Chengli Zheng, Kuangxi Su + Show 1 more

Open Access

https://doi.org/10.1155/2020/8869839

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Abstract

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.

Highlights

As “the blood of industry,” crude oil has become an important energy source that can affect economic activity and financial markets [1,2,3]; over the last decades, numerous market participants chose crude oil futures to avoid adverse spot price fluctuations [4]
We select the Conditional Value-at-Risk (CVaR), variance, returns, and utility as the criteria to provide an in-depth and comprehensive assessment of the hedging performance at different scales. e empirical results show that the extracted scales comprise different information of original returns, Secondly, short-term information occupies the most important position, and hedging is mainly driven by short-term information
The hedging performance based on a short-term scale is similar to that based on original returns, implying that hedging is mainly driven by short-term information

Summary

Introduction

As “the blood of industry,” crude oil has become an important energy source that can affect economic activity and financial markets [1,2,3]; over the last decades, numerous market participants chose crude oil futures to avoid adverse spot price fluctuations [4]. The previous multiscale hedging studies ignore this important issue; in this paper, we divide the data into short-, medium-, and long-term scales and explore the impact of different scales on hedging. The impact of different scales on hedging is mainly discussed under the minimum-CVaR framework Another important issue focusing on hedging is the dependence of the optimal hedge ratio on the data with different frequencies. EMD has been widely applied to decompose financial data [20,21,22] Based on these superior properties of EMD, we use EMD to decompose futures and spot returns and further construct three different scales. The EMD technology is first introduced to decompose crude oil futures and spot returns; the decomposition terms are reconstructed into three different scales: short-term, medium-term, and long-term.

Model and Methodology

Conclusion and suggestion

Data Resource

Empirical Analysis

Conclusions