{"title":"Financial Factors Affecting Price-to-Earnings Ratios in Canada","authors":"Natalia Popa Antalovschi, Raymond A. K. Cox","doi":"10.47941/IJF.660","DOIUrl":null,"url":null,"abstract":"Purpose: The purpose of this study is to ascertain which financial factors affect the price-to-earnings ratios of Canadian firms. \nMethodology: A sample of 578 Canadian firms, across 11 industries, listed on the Toronto Stock Exchange during 2011 to 2018 is examined. Stock prices and financial statements accounts data is collected from S & P Capital IQ. We compute 27 financial factors to use as independent variables to regress on the price-to-earnings ratio dependent variables employing the Statistical Package for Social Sciences (SPSS) utilizing the software program’s forced, forward, and backward selection methods. Robustness tests are conducted using alternative dates (after the fiscal year end) to discover which model of financial factors best explains the forward price-to-earnings ratio as well as other statistical methods such as analysis of variance. \nResults: We find a unique model for each of the 3 models based on the forward price-to-earnings ratio date. The financial factors that explain each of the dates after the end of the fiscal year (1 month, 2 months, and 3 months) are the 4 variables: net profit margin, return on investment, total asset turnover, and the natural logarithm of the total assets. For model 3 (1 month after fiscal year end), in addition to the previous 4 factors, the dividends per share is part of the regression equation. All 3 models have strong statistically significant results at an alpha level of one percent. Further, industry effects are deduced and presented. \nUnique contribution to theory, policy, and practice: The results are unique to a Canadian sample of firms post- International Financial Reporting Standards (IFRS) adoption. Companies can utilize the empirical findings to manage their financial performance to maximize their price-to-earnings ratio. A product of a firm’s higher price-to-earnings ratio is a lower cost of capital which expands the corporation’s investment opportunities. Investors can apply this research to develop investment strategies hinged on price-to-earnings ratios to augment investment returns.","PeriodicalId":53549,"journal":{"name":"International Journal of Banking, Accounting and Finance","volume":"46 1","pages":"43-61"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Banking, Accounting and Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47941/IJF.660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: The purpose of this study is to ascertain which financial factors affect the price-to-earnings ratios of Canadian firms.
Methodology: A sample of 578 Canadian firms, across 11 industries, listed on the Toronto Stock Exchange during 2011 to 2018 is examined. Stock prices and financial statements accounts data is collected from S & P Capital IQ. We compute 27 financial factors to use as independent variables to regress on the price-to-earnings ratio dependent variables employing the Statistical Package for Social Sciences (SPSS) utilizing the software program’s forced, forward, and backward selection methods. Robustness tests are conducted using alternative dates (after the fiscal year end) to discover which model of financial factors best explains the forward price-to-earnings ratio as well as other statistical methods such as analysis of variance.
Results: We find a unique model for each of the 3 models based on the forward price-to-earnings ratio date. The financial factors that explain each of the dates after the end of the fiscal year (1 month, 2 months, and 3 months) are the 4 variables: net profit margin, return on investment, total asset turnover, and the natural logarithm of the total assets. For model 3 (1 month after fiscal year end), in addition to the previous 4 factors, the dividends per share is part of the regression equation. All 3 models have strong statistically significant results at an alpha level of one percent. Further, industry effects are deduced and presented.
Unique contribution to theory, policy, and practice: The results are unique to a Canadian sample of firms post- International Financial Reporting Standards (IFRS) adoption. Companies can utilize the empirical findings to manage their financial performance to maximize their price-to-earnings ratio. A product of a firm’s higher price-to-earnings ratio is a lower cost of capital which expands the corporation’s investment opportunities. Investors can apply this research to develop investment strategies hinged on price-to-earnings ratios to augment investment returns.