题名

FINANCIAL RATIOS AND STOCK RETURN PREDICTABILITY-AN INNOVATIVE APPROACH OF OBJECT-CENTERED REGRESSION ALGORITHM

DOI

10.6293/AQAFA.202212_(19).0004

作者

Beom S. Lee；Jinsoo Lee；Christos Pantzalis；Jung Chul Park

关键词

Fintech ； Object-Centered Regression ； Future Return Prediction ； Market Efficiency

期刊名称

Advances in Quantitative Analysis of Finance and Accounting

卷期/出版年月

19期（2022 / 12 / 31）

页次

103 - 144

内容语文

英文
中文摘要

We propose an innovative but simple method to predict the monthly returns of individual stocks utilizing solely past and publicly available information. This technique adopts the concept of the person-centered approach that has been widely used in psychological analysis of individual human behavior. Our approach employs underlying hidden correlation structures among all relevant factors or predictors available, which is different from the conventional studies that mainly focus on identification of certain factors or predictors themselves. Choosing a generic set of financial ratios as predictors, the portfolios constructed based on our method produce economically sizeable monthly abnormal returns up to 1.81% after incorporating transaction costs in various asset pricing models.
主题分类 社會科學 > 經濟學
社會科學 > 財金及會計學
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