In this study, we attempt to model and predict the direction of return on market index of the
Taiwan Stock Exchange, one of the fastest growing financial exchanges in developing Asian …

It has been widely accepted by many studies that non-linearity exists in the financial markets
and that neural networks can be effectively used to uncover this relationship. Unfortunately …

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 …

Ability to predict direction of stock/index price accurately is crucial for market dealers or
investors to maximize their profits. Data mining techniques have been successfully shown to …

Time series prediction has been widely applied to the finance industry in applications such
as stock market price and commodity price forecasting. Machine learning methods have …

We study the validity of uncovered interest-rate parity by constructing ultra-long time series
that span two centuries. The forward-premium regressions yield positive slope estimates …

The study of financial markets has been addressed in many works during the last years.
Different methods have been used in order to capture the non-linear behavior which is …

We examine the ability of the standard intertemporal asset pricing model and a model of
noise trading to explain why the forward foreign exchange premium predicts the future …

In this paper, the first study using exponential smoothing methods and the Box-Jenkins
method for forecasting consumer potato prices in Turkey is conducted. The exponential …

During the last few years there has been growing literature on applications of artificial neural
networks to business and financial domains. In fact, a great deal of attention has been …