{"title":"Trading on trends: How the ordering of historical volume predicts Chinese stock returns?","authors":"","doi":"10.1016/j.irfa.2024.103518","DOIUrl":null,"url":null,"abstract":"<div><p>In examining return prediction strategies in China’s stock market, we find that the chronological return ordering is ineffective within a one-month window. To overcome this limitation, we introduce a more robust measure, named chronological turnover ordering (<span><math><msub><mrow><mtext>CTO</mtext></mrow><mrow><mn>3</mn></mrow></msub></math></span>), calculated using turnover in the past three months. As anticipated, <span><math><msub><mrow><mtext>CTO</mtext></mrow><mrow><mn>3</mn></mrow></msub></math></span> demonstrates statistically significant predictability for returns, indicating a tendency among investors to overvalue stocks with high recent and low distant turnover. Bivariate portfolio analysis reveals that <span><math><msub><mrow><mtext>CTO</mtext></mrow><mrow><mn>3</mn></mrow></msub></math></span> performs more effectively during high-sentiment periods and on stocks with high investor attention. This research contributes significantly to understanding investor behavior and market dynamics in China.</p></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":null,"pages":null},"PeriodicalIF":7.5000,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Financial Analysis","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1057521924004502","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
In examining return prediction strategies in China’s stock market, we find that the chronological return ordering is ineffective within a one-month window. To overcome this limitation, we introduce a more robust measure, named chronological turnover ordering (), calculated using turnover in the past three months. As anticipated, demonstrates statistically significant predictability for returns, indicating a tendency among investors to overvalue stocks with high recent and low distant turnover. Bivariate portfolio analysis reveals that performs more effectively during high-sentiment periods and on stocks with high investor attention. This research contributes significantly to understanding investor behavior and market dynamics in China.
期刊介绍:
The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.