{"title":"Fundamental Analysis of Detailed Financial Data: A Machine Learning Approach","authors":"Xi Chen, Yang Ha Cho, Y. Dou, B. Lev","doi":"10.2139/ssrn.3741015","DOIUrl":"https://doi.org/10.2139/ssrn.3741015","url":null,"abstract":"We conduct a fundamental analysis of detailed financial information to predict earnings. Since 2012, all U.S. public companies must tag quantitative amounts in financial statements and footnotes of their 10-K reports using the eXtensible Business Reporting Language (XBRL). Leveraging machine learning methods, we combine the high-dimensional XBRL-tagged financial data into a summary measure for the direction of one-year-ahead earnings changes. The measure shows significant out-of-sample predictive power concerning the direction of earnings changes. Hedge portfolios are formed based on this measure during 2015-2018. The annual size-adjusted returns to the hedge portfolios range from 5.02 to 9.7 percent. Our measure and strategies outperform those of Ou and Penman (1989), who extract the summary measure from 65 accounting variables using logistic regressions. Additional analyses suggest that the outperformance stems from both nonlinear predictor interactions missed by regressions and the use of more detailed financial data.","PeriodicalId":134520,"journal":{"name":"ERPN: Finance (Innovation) (Sub-Topic)","volume":"167 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116109368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Novel Machine Learning application for Sustainable Investments using ESG Framework","authors":"Akshat Gupta, U. Sharma","doi":"10.2139/ssrn.3808136","DOIUrl":"https://doi.org/10.2139/ssrn.3808136","url":null,"abstract":"Analysis of ESG data along with financial parameters from 34 stock market indices across the globe. This work is done to study the effect of ESG score variables on the prediction of financial growth indicators for the top publicly traded companies of the world. This aims to give socially conscious investors a better view when investing in companies while looking at the broader sustainability that an organization practices while operating.","PeriodicalId":134520,"journal":{"name":"ERPN: Finance (Innovation) (Sub-Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134201486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Measuring the Social Responsibility Discount for the Cost of Equity Capital: Evidence from Benefit Corporations","authors":"Craig R. Everett","doi":"10.2139/ssrn.2143414","DOIUrl":"https://doi.org/10.2139/ssrn.2143414","url":null,"abstract":"In 2010, Maryland became the first state to allow firms to incorporate as “benefit corporations,” which are for-profit entities with a social purpose. Since then, nineteen other states have followed. Using survey data from the population of 94 benefit corporations existent at the time of the survey, this paper directly measures the “social responsibility discount” – the degree to which investors in a benefit corporation have a lower required return on equity than they would have for traditional firms. This paper finds that the discount is approximately 35%. This paper also provides unique descriptive statistics about benefit corporations and their founders.","PeriodicalId":134520,"journal":{"name":"ERPN: Finance (Innovation) (Sub-Topic)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124306666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}