The investor behavior and futures market volatility: A theory and empirical study based on the OLG model and high‐frequency data
Abstract
Purpose
The purpose of this paper is to examine whether the futures volatility could affect the investor behavior and what trading strategy different investors could adopt when they meet different information conditions.
Design/methodology/approach
This study introduces a two‐period overlapping generation model (OLG) model into the future market and set the investor behavior model based on the future contract price, which can also be extended to complete and incomplete information. It provides the equilibrium solution and uses cuprum tick data in SHFE to conduct the empirical analysis.
Findings
The two‐period OLG model based on the future market is consistent with the practical situation; second, the sufficient information investors such as institutional adopt reversal trading patterns generally; last, the insufficient information investors such as individual investors adopt momentum trading patterns in general.
Research limitations/implications
Investor trading behavior is always an important issue in the behavioral finance and market supervision, but the related research is scarce.
Practical implications
The conclusion shows that the investors' behavior in Chinese future market is different from the Chinese stock market.
Originality/value
This study empirically analyzes and verifies the different types of trading strategies investors could; investors such as institutional ones adopt reversal trading patterns generally; while investors such as individual investors adopt momentum trading patterns in general.
Keywords
Citation
Wang, Y., Hua, R. and Zhang, Z. (2011), "The investor behavior and futures market volatility: A theory and empirical study based on the OLG model and high‐frequency data", China Finance Review International, Vol. 1 No. 4, pp. 388-407. https://doi.org/10.1108/20441391111167496
Publisher
:Emerald Group Publishing Limited
Copyright © 2011, Emerald Group Publishing Limited