PCA-Chinese Stocks

Published: 7 June 2023| Version 1 | DOI: 10.17632/bpxfvzxzg2.1
Contributor:
Leon Xing Li

Description

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

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Finance, Financial Mathematics

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