2021/06/13 by Liao Zhu, Zhu, Liao, Haoxuan Wu +3
Computer Science · Decision Sciences · Economics, Econometrics and Finance · Mathematics · #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #FOS: Economics and business #Financial Markets and Investment Strategies #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistical Finance (q-fin.ST) #Stock Market Forecasting Methods #cs.LG #q-fin.ST #stat.ME #stat.ML
paper · pdf · doi:10.48550/arxiv.2106.07103
arxiv created 2021/06/13 · openalex publication_date 2021/06/13 · arxiv updated 2021/06/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The paper proposes a new asset pricing model -- the News Embedding UMAP Selection (NEUS) model, to explain and predict the stock returns based on the financial news. Using a combination of various machine learning algorithms, we first derive a company embedding vector for each basis asset from the financial news. Then we obtain a collection of the basis assets based on their company embedding. After that for each stock, we select the basis assets to explain and predict the stock return with high-dimensional statistical methods. The new model is shown to have a significantly better fitting and prediction power than the Fama-French 5-factor model.