This paper reviews research that uses big data and/or machine learning methods to provide insight relevant for equity valuation. Given the huge volume of research in this area, the review focuses on studies that either use or inform on accounting variables. The article concludes by providing...

The study is a part of the series of financial models included in a doctoral dissertation completed at the Karachi University (Mehar: 1994). An Econometric model has been constructed in the study and a Three-Stage Least Square (3SLS) technique was applied for the estimation of the model. The...

The study is a part of the series of financial models included in a doctoral dissertation completed at the Karachi University (Mehar: 1994). An Econometric model has been constructed in the study and a Three-Stage Least Square (3SLS) technique was applied for the estimation of the model. The...

This paper focuses on one of the most determinant processes in business failure assessment: Variable selection. After a preselection of variables based on previous empirical literature, we perform a statistical variable selection on a sample of small firms using both mean and median differences....

The purpose of this paper represents the foundation of a score function, effective in the forecast of bankruptcy risk for companies in the Romanian economy. In order to achieve bankrupt / non-bankrupt discrimination in the econometric model, we have used relevant indicators regarding liquidity,...

The purpose of this paper is to use discriminant analysis to substantiate a score function effective in bankruptcy risk prediction of enterprises on Romanian economy example. For achieving discrimination between bankrupt and non-bankrupt in the scoring model we used relevant financial ratios...

The journal continues publishing the consultation of Professor Dean Fantazzini. In this issue econometric analysis of financial data in risk management is discussed. Basic concepts of credit risk management in the context of recent Basel-II agreement recommendations are introduced....

Nowcasting regards the inference on the present realization of random variables, on the basis of information available until a recent past. This paper proposes a modelling strategy aimed at a best use of the data for nowcasting based on panel data with severe deficiencies, namely short times...

This paper introduces a novel Bayesian time series model that combines the nonparametric features of an infinite hidden Markov model with the volatility persistence captured by the GARCH framework, to effectively model and forecast short-term interest rates. When applied to US 3-month Treasury...