Uncertainty in the capital market means the difference between the expected values ​​and the amounts that actually occur. Designing different analytical and forecasting methods in the capital market is also less likely due to the high amount of this and the need to know future prices with greater certainty or uncertainty. In order to capitalize on the capital market, investors have always sough...

Globalized companies seek growth while dealing with more complex and compelling challenges such as economic volatility, fluctuating commodity prices, supply-chain inefficiencies and increasing customer expectations. While companies cannot control all of these challenges, there is much they can do to remain competitive. Companies can gain competitive edge through improved demand forecasting and ...

EDDIE is a genetic programming based decision support tool for financial forecasting. EDDIE itself does not replace forecasting experts. It serves to improve the productivity of experts in searching the space of decision trees, with the aim to improve the odds in its user's favour. The efficacy of EDDIE has been reported in the literature. However, discovering patterns in historical data is onl...

The application of Internet-based virtual stock markets (VSMs) is an additional approach that can be used to predict shortand medium-term market developments. The basic concept involves bringing a group of participants together via the Internet and allowing them to trade shares of virtual stocks. These stocks represent a bet on the outcome of future market situations, and their value depends on...

This paper generalizes a recently proposed spatial autoregressive model and introduces a spatiotemporalmodel for forecasting stock returns.We support the view that stock returns are affected not only by the absolute values of factors such as firm size, book-to-market ratio and momentum but also by the relative values of factors like trading volume ranking and market capitalization ranking in ea...

Trend following (TF) is trading philosophy by which buying/selling decisions are made solely according to the observed market trend. For many years, many manifestations of TF such as a software program called Turtle Trader, for example, emerged in the industry. Surprisingly little has been studied in academic research about its algorithms and applications. Unlike financial forecasting, TF does ...

Standard forecasting criteria like the mean square error (MSE) compare point forecasts or a location parameter of the forecasting distribution with actual observations. Such criteria are less suited to comparing forecasts of volatile time series. Therefore we use the average predictive ordinate (APOC) criterion which evaluates the ordinate of the predictive distribution. Using the comparison to...

The forecasting models for stock market index using computational intelligence such as Artificial Neural networks(ANNs) and Genetic programming(GP), especially hybrid Immune Programming (IP) Algorithm and Gene Expression Programming(GEP) have achieved favorable results. However, these studies, have assumed a static environment. This study investigates the development of a new dynamic decision f...

This study analyzes the accuracy of forecasted target prices which are disclosed by leading investment banks within their analysts’ reports on German stocks for the period from 2002 to 2004. We compute a measure for target price forecast accuracy that evaluates the ability of analysts to exactly forecast the ex-ante (unknown) 12-months stock price. Overall, the target price forecasting accuracy...