Journal ArticleDOI
Measuring firm performance using financial ratios: A decision tree approach
TLDR
Sensitivity analyses indicated that Earnings Before Tax-to-Equity Ratio and Net Profit Margin are the two most important variables, and the CHAID and C5.0 decision tree algorithms produced the best prediction accuracy.Abstract:
Determining the firm performance using a set of financial measures/ratios has been an interesting and challenging problem for many researchers and practitioners Identification of factors (ie, financial measures/ratios) that can accurately predict the firm performance is of great interest to any decision maker In this study, we employed a two-step analysis methodology: first, using exploratory factor analysis (EFA) we identified (and validated) underlying dimensions of the financial ratios, followed by using predictive modeling methods to discover the potential relationships between the firm performance and financial ratios Four popular decision tree algorithms (CHAID, C50, QUEST and C&RT) were used to investigate the impact of financial ratios on firm performance After developing prediction models, information fusion-based sensitivity analyses were performed to measure the relative importance of independent variables The results showed the CHAID and C50 decision tree algorithms produced the best prediction accuracy Sensitivity analysis results indicated that Earnings Before Tax-to-Equity Ratio and Net Profit Margin are the two most important variablesread more
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The Interaction Effect of Financial Leverage on the Relationship Between Board Attributes and Firm Performance; Evidence of Non-financial Listed Companies of Pakistan
TL;DR: In this article, the authors investigated the link between the board size, outside directors, and Tobin's Q (Tobin's Q) in non-financial firms from the year 2012 to 2015.
Journal ArticleDOI
Implementing artificial intelligence in forecasting the risk of personal bankruptcies in Poland and Taiwan
Tomasz Korol,Anestis K. Fotiadis +1 more
TL;DR: In this paper , six models were developed to forecast the risk of insolvency: three for Polish households and three for Taiwanese consumers, using fuzzy sets, genetic algorithms, and artificial neural networks.
Journal ArticleDOI
Factors Affecting the Performance of F&B Industry in Malaysia and Indonesia
TL;DR: In this article, the influence of financial ratios on company performance in Malaysia and Indonesia F&B industry period 2011-2018 was investigated by using multiple regression analysis for panel data, the study revealed that CR and DER had no influence on ROA, while TAT and NPM had positive effect on ROE.
Diferenças nos índices de análise das demonstrações financeiras
TL;DR: In this paper, a comparative study of indices of desempenho in the literatura brasileira e internacional is presented, focusing on the differences between the indices of analise das demonstracoes financeiras of empresas.
Journal Article
Machine learning techniques used in big data
TL;DR: This paper presents some machine learning algorithms and techniques used in big data, because it runs at scale machine and works very well with large data sets.
References
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Book
Discovering Statistics Using SPSS
Andy P. Field,Jeremy N.V. Miles +1 more
TL;DR: Suitable for those new to statistics as well as students on intermediate and more advanced courses, the book walks students through from basic to advanced level concepts, all the while reinforcing knowledge through the use of SAS(R).
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Classification and Regression Trees.
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TL;DR: A complete guide to the C4.5 system as implemented in C for the UNIX environment, which starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting.
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Data Mining: Practical Machine Learning Tools and Techniques
TL;DR: This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.
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Classification and regression trees
TL;DR: This article gives an introduction to the subject of classification and regression trees by reviewing some widely available algorithms and comparing their capabilities, strengths, and weakness in two examples.