In the last decade, neural networks have drawn noticeable attention from many computer and operations researchers. While some previous studies have found encouraging results with using this artificial intelligence technique to predict the movements of established financial markets, it is...

Many studies have found underpricing of initial public offerings (IPOs) and attributed the underpricing to information asymmetry either between issuers and underwriters or between informed and uninformed investors. However, by observing the distribution of initial returns on stocks after their...

In recent years, there has been a growing trend of using multiobjective techniques. The primary advantage of using multiobjective techniques in decision making is, as stated in Spronk (1981), quot;that most of these (single objective) models and methods are unsuitable for decision situations in...

Predicting exchange rates has long been a concern in international finance as most standard econometric methods are unable to produce significantly better forecasts than the random walk model. Recent studies provide some evidence for the ability of using multivariate time series models to...

Although there exists some studies which deal with the issues of forecasting stock market index and development of trading strategies, most of the empirical findings are associated with the developed financial markets (e.g., U.S., U.K., and Japan). Currently, many international investment...

Despite abundant research which focuses on estimating the level of return on stock market index, there is a lack of studies examining the predictability of the direction/sign of stock index movement. Given the notion that a prediction with little forecast error does not necessarily translate...

Although there exists a vast number of articles addressing the predictability of stock market return, most of the proposed models rely on accurate forecasting of the level (i.e., value) of the underlying stock index or its return. In most cases, the degree of accuracy and the acceptability of...

In the last decade, neural networks have emerged from an esoteric instrument in academic research to a rather common tool assisting auditors, investors, portfolio managers and investment advisors in making critical financial decisions. A better understanding of the network's performance and...