股票收益随机波动模型研究

Abstract

Abstract: Analyzing the characteristics of financial data and pointing out the drawbacks of GARCH models,the paper describes the volatilities of daily stock return by stochastic volatility model and employs GMM to estimate the parameters in the model.In the final,the paper carries out a emprical analysis of daily stock return volatilties in Shanghai stock market to figure out the effects of price limits posed on daily price of stocks listed in Shanghai Stoke Exchange on volatility and distribution pattern of stock return.

Key words: fat tail, volatility clustering, GARCH, stochastic volatility, price limits

CLC Number:

C931:F832

SHEN Gen-xiang. The Stochastic Volatility Model for Stock Return[J]. Chinese Journal of Management Science, 2003, (2): 16-20.

[1]	WANG Chao, CHEN Le-yi, LI Yu-shuang. The Characteristics and Macroeconomic Effects of China's Financial Cycle [J]. Chinese Journal of Management Science, 2020, 28(12): 12-22.
[2]	WANG Jia, JIN Xiu, WANG Xu, LI Gang. Research on Variance Minimization Hedging Based on Time-Varying Markov DCC-GARCH Model [J]. Chinese Journal of Management Science, 2020, 28(10): 13-23.
[3]	LIU Feng-gen, WU Jun-chuan, YANG Xi-te, OUYANG Zi-sheng. Long-run Dynamic Effect of Macro-economy on Stock Market Volatility Based on Mixed Frequency Data Model [J]. Chinese Journal of Management Science, 2020, 28(10): 65-76.
[4]	WANG Zheng-xin, YAO Pei-yi. Dynamic Spillovers Effects of Economic Policy Uncertainty of China [J]. Chinese Journal of Management Science, 2019, 27(5): 78-85.
[5]	ZHENG Zun-xin, WANG Hua-ran, ZHU Fu-min. Studies on Volatility Features and Jump Behavior of Shanghai 50ETF Market Based on Levy-GARCH Model [J]. Chinese Journal of Management Science, 2019, 27(2): 41-52.
[6]	WU Xin-yu, ZHAO Kai, LI Xin-dan, MA Chao-qun. Option Pricing Under Time-Varying Risk Aversion: An Empirical Study Based on SSE 50ETF Options [J]. Chinese Journal of Management Science, 2019, 27(11): 11-22.
[7]	LING Ai-fan, CHEN Xiao-yang. The B1ack-Litterman Portfolio Model Embedded GARCH to Estimate Volatility [J]. Chinese Journal of Management Science, 2018, 26(6): 17-25.
[8]	WANG An-xing, TAN Xian-ming. The Analysis of Chinese Stock Volatile Risk Factors based on Mixture Distribution [J]. Chinese Journal of Management Science, 2018, 26(2): 86-95.
[9]	XIA Ting, WEN Yue-chun. Does Economic Uncertainty Matter for Stock Market Volatility? An Analysis Based on GARCH-MIDAS [J]. Chinese Journal of Management Science, 2018, 26(12): 1-11.
[10]	LIU Xiao-qian, WANG Jian, WU Guang. The Forecasting Analysis of HS300 Index based on HAR-CVX Model of High Frequency Data [J]. Chinese Journal of Management Science, 2017, 25(6): 1-10.
[11]	WU Xin-yu, LI Xin-dan, MA Chao-qun. Threshold Realized Stochastic Volatility Model and its Empirical Test [J]. Chinese Journal of Management Science, 2017, 25(3): 10-19.
[12]	HAN Chao, YAN Tai-hua. Risk analysis of Foreign Exchange Portfolios Based on High-dimensional Dynamic Vine Copula [J]. Chinese Journal of Management Science, 2017, 25(2): 10-20.
[13]	CAO Dong, ZHANG Jia. The Impact of Index Future on Stock Market Volatility Based on the GARCH-M Model [J]. Chinese Journal of Management Science, 2017, 25(1): 27-34.
[14]	ZHANG Gui-sheng, ZHANG Xin-dong. A SVM-GARCH Model for Stock Price Forecasting Based on Neighborhood Mutual Information [J]. Chinese Journal of Management Science, 2016, 24(9): 11-20.
[15]	ZHOU Yan-li, WU Yang, GE Xiang-yu. The Study of Real Option Valuation Method on the Patent Value in the High Technology Firms: Modelling and Simulation of American Optionwith Jump Diffusion and Stochastic Volatility [J]. Chinese Journal of Management Science, 2016, 24(6): 19-28.

The Stochastic Volatility Model for Stock Return

PDF (PC)

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 15

Metrics

Comments

Recommended 10