基于协整方法和LSTM网络的农林板块配对交易研究

Paired Trading of Agriculture and Forestry Blocks Based on Cointegration Method and LSTM Network

以A股沪深两市的农林板块股票作为研究样本,以2021-2024年为实证研究区间,首先,运用协整方程选择在配对期的价格序列上具有共同移动趋势的农林板块股票,然后,对具有协整关系的股票价差序列进行平稳性检验,对于符合平稳性要求的资产对,计算其周度已实现波动率、已实现偏度和峰度,使用LSTM网络预测股票对在短期内的残差收敛水平,最后在测试期对符合条件的资产组合进行模拟交易,将收益率水平与基准收益率进行比较。研究发现,基于协整方法和LSTM网络构建的农林板块配对交易资产组合能够在风险得到控制的同时获得超额收益。

Taking the agricultural and forestry sector stocks of A-shares in the Shanghai and Shenzhen stock markets as research samples,with the period from 2021 to 2024 as the empirical research interval,the cointegration equation was used to select agricultural and forestry sector stocks with a common moving trend in the price series during the pairing period;and then,the stationarity test was conducted on the price difference series of stocks with cointegration relationship.For asset pairs that meet the stationarity requirements,their weekly realized volatility,realized skewness,and kurtosis are calculated,we used LSTM network to predict the residual convergence level of stock pairs in the short term,and finally simulated trading on eligible asset portfolios during the testing period,comparing the return level with the benchmark return.The paired trading asset portfolio of agricultural and forestry sectors constructed based on cointegration methods and LSTM networks can achieve excess returns while controlling risks.