Evaluating the Accuracy of Valuation Multiples on Indian Firms Using Regularization Techniques of Penalized Regression
This research study is conducted on companies in threeprominent sectors: Automobile, Banking and Steel—all threediverse and affected by different economic, fiscal and financial policies. Theauthor Gupta  attempts to extend the scope of study done earlier usingsimple linear regression for valuation of companies. Highlighting thelimitations of linear regression: multicollinearity and normality, the presentstudy is conducted by applying regularization techniques of machine learning. Ridge regression, LASSO and elastic nettechniques are employed to underscore this commonality of the set ofvaluation multiples. Theseregularization techniques are tested on data of Indian listed firms spanningacross twelve years from FY 07 to FY 2018 and the four multiples identified forthe study are 1) price to earnings (P/E), 2) price to sales (P/S), 3)enterprise value to earnings before interest tax depreciation and amortization(EV/EBIDTA) and 4) price to book value (P/BV). The empirical findings are bas......
【作者名称】: Vandana Gupta
【关 键 词】: Valuations
, Book Value
, Enterprise Value
【上篇论文】: 外军国防科技报告 - Institutional Determinants to Climate Variability Adaptation by Smallholder Irish Potato Farmers in Rubanda District, South Western Uganda
【下篇论文】: 外军国防科技报告 - Cloning and Expression Analysis of TTG1 Gene Related to Rosa rugosa Trichomes Formation
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The TTG1 transcription factor plays an important role in the formation of plant trichomes. Based on the R. rugosa transcriptome data, this study cloned a R. rugosa TTG1 gene, named RrTTG1, and carried [<,i>,R. rugosa<,/i>,Trichome,<,i>,RrTTG<,/i>,1,Gene Expression]......
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