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This study investigates the usefulness and efficacy of a multiobjective decision method for financial trading guided by a set of seemingly diverse analysts' forecasts. The paper proposes a goal programming (GP) approach which combines various forecasts based on the performance of their previous...
Persistent link: https://www.econbiz.de/10012735690
Predicting currency movements has always been a problematic task as most conventional econometric models are not able to forecast exchange rates with significantly higher accuracy than a naive random walk model. For large multinational firms which conduct substantial currency transfers in the...
Persistent link: https://www.econbiz.de/10012735715
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...
Persistent link: https://www.econbiz.de/10012735716
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...
Persistent link: https://www.econbiz.de/10012739205
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...
Persistent link: https://www.econbiz.de/10012783954
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...
Persistent link: https://www.econbiz.de/10012787640
In this study, we examine the forecastability of a specific neural network architecture called General Regression Neural Network (GRNN) and compare its performance with a variety of forecasting techniques, including Multi-Layered Feedforward Network (MLFN), multivariate transfer function, and...
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