阅读|我国股指期货收益波动率的非线性特征分析—基于沪深300股指期货的高频数据
The nonlinear characteristics of Chinese stock index futures yield volatility: Based on the high frequency data of CSI300 stock index futures
我国股指期货收益波动率的非线性特征分析—基于沪深300股指期货的高频数据
Xuebiao Wang, Xi Wang and Bo Li
Dongbei University of Finance and Economics, Dalian, China, and
Zhiqi Bai
School of Accounting,
Dongbei University of Finance and Economics, Dalian, China
Citation:
Wang, X., Wang, X., Li, B. and Bai, Z. (2019), "The nonlinear characteristics of Chinese stock index futures yield volatility: Based on the high frequency data of CSI300 stock index futures", China Finance Review International, Vol. 10 No. 2, pp. 175-196. https://doi.org/10.1108/CFRI-07-2018-0069
摘要
本文以我国2012-2017年的沪深300股指期货当月连续5分钟交易数据为样本，分别通过Hurst指数及GPH检验、A-J及J-O跳跃性检验和Realized-EGARCH模型对市场收益波动率的基本特征进行分析，结果表明沪深300股指期货市场收益波动率存在明显的长记忆性、跳跃性和不对称性等非线性特征。研究发现LHAR-RV-CJ模型对于研究我国沪深300股指期货已实现波动率的预测效果较好。结论表明：沪深300股指期货市场存在异质性，即市场长期投资者更加关注于市场长期波动，而非短期波动；中短期跳跃成分对市场波动率的影响较为有限，长期跳跃对市场波动的负向影响较大；长周期收益率的负向冲击对于短期市场波动的影响有限，随着周期延长，长周期负向冲击的影响逐步增大。
Purpose
The purpose of this paper is to consider that the model of volatility characteristics is more reasonable and the description of volatility is more explanatory.
Design/methodology/approach
This paper analyzes the basic characteristics of market yield volatility based on the five-minute trading data of the Chinese CSI300 stock index futures from 2012 to 2017 by Hurst index and GPH test, A-J and J-O Jumping test and Realized-EGARCH model, respectively. The results show that the yield fluctuation rate of CSI300 stock index futures market has obvious non-linear characteristics including long memory, jumpy and asymmetry.
Findings
This paper finds that the LHAR-RV-CJ model has a better prediction effect on the volatility of CSI300 stock index futures. The research shows that CSI300 stock index futures market is heterogeneous, means that long-term investors are focused on long-term market fluctuations rather than short-term fluctuations; the influence of the short-term jumping component on the market volatility is limited, and the long jump has a greater negative influence on market fluctuation; the negative impact of long-period yield is limited to short-term market fluctuation, while, with the period extending, the negative influence of long-period impact is gradually increased.
Research limitations/implications
This paper has research limitations in variable measurement and data selection.
Practical implications
This study is based on the high-frequency data or the application number of financial modeling analysis, especially in the study of asset price volatility. It makes full use of all kinds of information contained in high-frequency data, compared to low-frequency data such as day, weekly or monthly data. High-frequency data can be more accurate, better guide financial asset pricing and risk management, and result in effective configuration.
Originality/value
The existing research on the futures market volatility of high frequency data, mainly focus on single feature analysis, and the comprehensive comparative analysis on the volatility characteristics of study is less, at the same time in setting up the model for the forecast of volatility, based on the model research on the basic characteristics is less, so the construction of a model is relatively subjective, in this paper, considering the fluctuation characteristics of the model is more reasonable, characterization of volatility will also be more explanatory power. The difference between this paper and the existing literature lies in that this paper establishes a prediction model based on the basic characteristics of market return volatility, and conducts a description and prediction study on volatility.
文章结构
Introduction
Asymmetry, long memory and jumping of high frequency data realized volatility
2.1 Asymmetry of high frequency data realized volatility
2.2 Long memory and jumping of high frequency data realized volatility
Empirical research
3.1 Non-linear characteristics of return volatility of CSI 300 stock index futures market
3.2 Prediction and comparison based on LHAR-RV-CJ model
Research conclusions
研究成果
5-min logarithmic yield of the CSI 300 stock index futures market
Descriptive statistical results of 5-min logarithmic yield of CSI 300 stock index futurestics by country
Statistical results of volatility description have been achieved for CSI 300 stock index futures
Different realized volatility construction methods, descriptivestatistics and timing diagrams
CSI 300 stock index futures markets realized volatility R/S test and GPH test results
Statistical characteristics of significant daily jump variance of CSI 300 stock index futures market at different confidence levels
Time-series diagram of significant jump variance sequence and realized volatility in daytime
Contribution degree analysis of jump variance to population variance jump
J-O test analysis of significant jump proportion and jump variance contribution in years
Estimation results of realized-EGARCH model in CSI 300 stock index futures and spot markets
Residual histogram of CSI 300 stock index futures market model
Information impact curve of CSI 300 stock index futures market
Information impact curve of CSI 300 stock index
Realized volatility autocorrelation and the correlation between positive, negative returns and significant jump components and realized volatility
Model estimation results of LHAR-RV-CJ
Variation of periodic volatility coefficient α estimated by different realized volatility
Changes in periodic negative return coefficient γ of different realized volatility estimates
Prediction capability analysis of the model
文章下载
作者简介
王雪标(1958—)，男，辽宁大连人，东北财经大学数学学院教授，博士生导师，经济学博士，主要研究方向是数量金融与风险管理；
王晰(1990—)，女，辽宁大连人，东北财经大学经济学院博士研究生，主要研究方向是宏观经济与货币政策；
李博(1993—)，男，辽宁大连人，东北财经大学经济学院硕士研究生，主要研究方向是期货与计量分析。
白智奇(1990—)，男，山西吕梁人 ，东北财经大学会计学院，主要研究方向是公司金融与公司治理。
（下图为王雪标教授）
《中国金融评论》介绍
Background
The China Finance Review International is published in association with the Antai College of Economics and Management at Shanghai Jiao Tong University, one of the top universities in Asia. The journal publishes quality empirical and theoretical research on financial and economic issues.
The China Financial Review International aims to promote discussions and publish works on important finance and economic issues in the world. We encourage ground-breaking research related to new and niche areas in finance, such as Fintech and socially responsible investments. Critical thinking is a key area the journal emphasizes. We welcome critiques of existing literature and comparative analysis between emerging markets and developed economies.
Aims and Scope
The journal acts as a medium between China's finance scholars and international financial economists to share their views and investigate a wide range of issues including:
• Asset pricing
• Financial intermediation
• Derivatives
• Corporate finance
• Corporate governance
• Fintech and financial innovations
• Financial econometrics
• International finance
• Market microstructure
• Macro finance
• Household and personal finance
• Behavioral finance
• Risk management and insurance
Good reasons to publish in China Finance Review International
• Fast and high quality peer review and rapid publication upon acceptance
• Widest possible global dissemination of your research
• No article-processing charges (APC)
• Indexed by ESCI, ABI/INFORM Complete, Scopus
Submit your research now!
The journal operates a double-blind peer review system. There is no submission fee. To submit to the journal, please use the CFRI’s online submission and review system at: http://mc.manuscriptcentral.com/cfri.
To plan your submissions, please see Author Guidelines at: https://www.emeraldgrouppublishing.com/products/journals/author_guidelines.htm?id=cfri
For more information on the journal, please visit: http://www.emeraldgrouppublishing.com/cfri.htm
If you would like to discuss your paper prior to submission, or seek advice on the submission process please contact the CFRI, Editorial Office, at the following email address: cfr@sjtu.edu.cn