This study investigates the ability of three versions of Altman's Z-Score model (Z, Z', and Z”) of distress prediction developed in the U.S. to predict the corporate distress in the emerging market of Sri Lanka. The results show that these models have a remarkable degree of accuracy in...

This study is motivated by the continuing popularity of the Altman Z-score as a measure of distress risk. Altman first introduced the ‘Z' score in 1968 and 50 years later it is still going strong as a means to predicting bankruptcy. During these 50 years, academicians have studied the...

The slow diffusion of information hypothesis has emerged as a more convincing explanation for lead-lag patterns in assets returns compared to traditional explanations such as non-synchronous or thin trading, liquidity factor, or size factor, etc. We provide further support to slow diffusion of...

We estimate and test several default risk models using new and unique data on corporate defaults in the German stock market. While defaults were extremely rare events in the 1990s, they have been a characteristic feature of the German stock market since the early 2000s. We apply the structural...

We analyze the stock market return predictability for three different periods. We evaluate the conditional variance (CV) and the variance risk premium (VRP) as predictors of stock market returns for which we are using well-established versions of the heterogeneous auto-regressive (HAR) model and...

The purpose of this paper is to make a quantitative and qualitative critical analyse regarding the three important aspects of stock market evolution. First, the forecasting problems are presented and analyse in order to establish the main problems and the potential solutions. Second, the...

Using Internet search volume of dividend-related keywords to measure investor preference for dividends that varies over time and across states, we show that dividend sentiment affects corporate policies and asset prices. Investors search more for dividends when economic conditions are poor, with...

This paper presents a study of Artificial Neural Network (ANN) and Bayesian Network (BN) for use in stock index prediction. The data from Nigerian Stock Exchange (NSE) market are applied as a case study. Based on the rescaled range analysis, the neural network was used to capture the...