PCA-Chinese Stocks

We examine the prediction performance using a principal component analysis (PCA). In particular, we perform a PCA to identify significant factors (principal components) and then use these factors to form predictions of stock price movements. We apply this strategy on the Chinese stock markets. Using data from January 2, 2019 till September 16, 2021, the empirical results show substantial out-performances from the PCA-based predictions against a naïve buy-and-hold strategy and also single time-series predictions of individual stocks

搜集汇总

背景与挑战

背景概述

PCA-Chinese Stocks数据集专注于利用主成分分析（PCA）预测中国股票市场的价格走势。研究通过PCA提取关键因素进行预测，实证结果表明该策略在2019年至2021年期间的表现优于传统买入持有策略和单只股票的预测方法。