A Lead-Lag Relationship and Forecast Research between China’s Crude Oil Futures and Spot Markets
Author(s) -
Chi Zhang,
Dandan Pan,
Mingyan Yang,
Zhengning Pu
Publication year - 2022
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2022/6162671
Subject(s) - futures contract , spot contract , econometrics , crude oil , predictive power , spot market , lead (geology) , lag , futures market , economics , hot spot (computer programming) , financial economics , computer science , electricity , computer network , philosophy , electrical engineering , epistemology , geomorphology , petroleum engineering , engineering , operating system , geology
The integration of the global economy has led to an increasingly strong connection between the futures and spot markets of commodities. First, based on one-minute high-frequency prices, this paper applies the thermal optimal path (TOP) method to examine the lead-lag relationship between Chinese crude oil futures and spot from March 2018 to December 2021. Second, we apply the Mixed Frequency Data Sampling Regression (MIDAS) model and indicators such as deviation degree to test the degree of prediction of high-frequency prices in the futures market to the spot market. The experimental results show that the futures markets lead the spot market most of the time, but the lead effect reverses when major events occur; 60-minute futures high-frequency prices are the most predictive of daily spot data; crude oil futures’ predictive power declined after the Covid-19 outbreak and is more predictive when night trading is available. This study has important implications, not only to guide investors but also to provide empirical evidence and valid information for policy makers.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom