High-frequency pairs trading in Chinese stock market: Based on Lévy-OU processes

被引：0
|
作者：
Zhao H. [1 ]
Luo P. [1 ]
Wang S. [2 ]
机构：
[1] School of Economics, Xiamen University, Xiamen
[2] Head Office, China Guangfa Bank Co., Ltd, Guangzhou
来源：
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2023年 / 43卷 / 08期
基金：
中国国家自然科学基金;
关键词：
heterogeneous autoregressive model; high-frequency pairs trading; Lévy-OU process;
D O I：
10.12011/SETP2022-2978
中图分类号：
学科分类号：
摘要：
The paper proposes the LOU-RV-HAR pairs trading strategy by the Lévy process of the double-exponential compound Poisson distribution to capture the jumps of stock pairs spread, the Ornstein-Uhlenbeck (OU) process to characterize the mean-reversion, stock pairs selection with the mean-reversion spread and realized volatility (RV), and the heterogeneous autoregressive (HAR) model to predict the volatility of the spread. The empirical results of the five-minute high-frequency data of the constituent stocks of the CSI 300 index show the LOU-RV-HAR strategy achieves a better pairs trading performance and the Sharpe ratio is 1.6072, greatly exceeding performance of the CSI 300 index during the same period. Comparing with the four comparative trading strategies established by adjusting the spread model, stock selection method and trading threshold, the annualized return and Sharpe ratio of the LOU-RV-HAR strategy are better than those of the comparative strategies. Further analysis shows that the LOU-RV-HAR strategy displays robust results in different market conditions or different trading thresholds, and the overall pairs trading performance of CSI 300 component stocks is higher than the performance of sub-industries. © 2023 Systems Engineering Society of China. All rights reserved.
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收藏
页码：2251 / 2265
页数：14
相关论文
共 43 条
  • [1] Gatev E, Goetzmann W N, Rouwenhorst K G., Pairs trading: Performance of a relative–value arbitrage rule[J], The Review of Financial Studies, 19, 3, pp. 797-827, (2006)
  • [2] Huck N., The high sensitivity of pairs trading returns[J], Applied Economics Letters, 20, 14, pp. 1301-1304, (2013)
  • [3] Vidyamurthy G., Pairs trading: Quantitative methods and analysis, (2004)
  • [4] Puspaningrum H, Lin Y X, Gulati C., Finding the optimal pre–set boundaries for pairs trading strategy based on cointegration technique[J], Journal of Statistical Theory and Practice, 4, 3, pp. 391-419, (2010)
  • [5] Huck N, Afawubo K., Pairs trading and selection methods: Is cointegration superior?[J], Applied Economics, 47, 6, pp. 599-613, (2015)
  • [6] Bui Q, Slepaczuk R., Applying hurst exponent in pair trading strategies on Nasdaq 100 index, Physica A: Statistical Mechanics and its Applications, 592, (2022)
  • [7] Elliott R J, Van Der Hoek J, Malcolm W P., Pairs trading[J], Quantitative Finance, 5, 3, pp. 271-276, (2005)
  • [8] Jing B Y, Kong X B, Liu Z., Modeling high–frequency financial data by pure jump processes[J], The Annals of Statistics, 40, 2, pp. 759-784, (2012)
  • [9] Jondeau E, Lahaye J, Rockinger M., Estimating the price impact of trades in a high–frequency microstructure model with jumps[J], Journal of Banking & Finance, 61, 2, pp. 205-224, (2015)
  • [10] Goncu A, Akyildirim E., A stochastic model for commodity pairs trading[J], Quantitative Finance, 16, 12, pp. 1843-1857, (2016)
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