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
Citations
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Journal ArticleDOI
Integration of Monte Carlo simulation and chi-square automatic interaction detector algorithm for modelling and estimation of conventional power plant construction volumes
TL;DR: This study presents an integrated approach based on chi-square automatic interaction detector (CHAID) algorithm, computer simulation and statistical tools for optimum modelling and estimation of power plant construction volumes and introduces CHAID for estimation of construction volumes.
Dissertation
Application of Textual Feature Extraction to Corporate Bankruptcy Risk Assessment
TL;DR: This thesis focuses on the application of a text mining system known as TP2K which stands for Text Pattern to Knowledge System, developed by my supervisor Professor Andrew K.C. Wong, to the finance industry.
Journal ArticleDOI
Fast Linear Model Trees by PILOT
TL;DR: PILOT as mentioned in this paper is a new algorithm for linear model trees that is fast, regularized, stable and interpretable, which preserves the intuitive interpretation of decision trees and at the same time enables them to better capture linear relationships, which is hard for standard decision trees.
Journal ArticleDOI
Impact of Privatisation On Financial Performance and Efficiency of State Owned Enterprises
Bilal Ahmed,Sadaf Alam +1 more
TL;DR: In this article, a study designed for inspecting the potential effect of privatization on the financial performance and efficiency of the Cement Sector (Kohat Cement Company and Dandot Cement company), Oil and Gas Sector (PPL and NRL) and Service Sector(PTCL and KESC).
Journal ArticleDOI
Accounting information and stock returns in Vietnam securities market: Machine learning approach
TL;DR: In this article , the authors studied the relationship between accounting information reflected in financial statements and stock return in Vietnam Stock Market. And they proposed a research model to define the relationship and made some recommendations for investors, firms, and policy makers.
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).
Journal ArticleDOI
Classification and Regression Trees.
Book
C4.5: Programs for Machine Learning
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.
Book
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.
Journal ArticleDOI
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.