我国A股股票低位放量后收益的随机森林分析

Random Forest Analysis of Returns of Chinese A-Share Stocks after Low Volume Increase

摘要: 股票收益率的影响因素众多，大盘、板块、个股的财务指标、K线形态、量价关系等对于股票收益率都有一定的影响，对于众多的自变量对于一个因变量的影响关系的研究，传统意义上的很多模型不再适用。本文采用随机森林模型分析经历过底部放量之后的大盘、个股K线形态、量价关系等对于后续股票收益率的影响，同时考虑了A股不同牛熊阶段的各种影响因素的权重的排序。本文的研究对于证券理论是一个有益的拓展，对于股票实盘操作也有一定的借鉴意义。

Abstract: There are many factors that affect stock returns, including financial indicators of the overall market, sectors, and individual stocks, K-line patterns, and volume price relationships. Traditional models are no longer applicable to the study of the impact of numerous independent variables on a dependent variable. This article uses a random forest model to analyze the impact of the overall market, individual stock K-line patterns, volume price relationships, and other factors on subsequent stock returns after experiencing bottom volume increases. At the same time, the ranking of the weights of various influencing factors in different bull and bear stages of A-shares is considered. The research in this article is a beneficial extension of securities theory and has certain reference significance for stock trading operations.