Business is a diversified field with general areas of specialisation such as accounting, taxation, stock market, and other financial analysis. Artificial Neural Networks (ANN) have been widely used in applications such as bankruptcy prediction, predicting costs, forecasting revenue, forecasting share prices and exchange rates, processing documents and many more. This chapter introduces an Adapt...

The use of price–earnings ratios and dividend-price ratios as forecasting variables for the stock market is examined using aggregate annual US data 1871 to 2000 and aggregate quarterly data for twelve countries since 1970. Various simple efficient-markets models of financial markets imply that these ratios should be useful in forecasting future dividend growth, future earnings growth, or future...

Stock market forecasting research offers many challenges and opportunities, with the forecasting of individual stocks or indexes focusing on forecasting either the level (value) of future market prices, or the direction of market price movement. A three-stage stock market prediction system is introduced in this article. In the first phase, Multiple Regression Analysis is applied to define the e...

Conventionally, linear and univariate time series models are broadly used in earning forecast. However, their forecasting accuracies are seriously limited without considering sufficient important factors. On the other hand, using more variables does not guarantee to obtain better forecasting accuracy and may cause inefficiency. The Multi-Objective Genetic Algorithms (MOGA) have been shown to be...

In this paper, the concept of long memory systems for forecasting is developed. The Pattern Modelling and Recognition System (PMRS) and Fuzzy Single Nearest Neighbour (SNN) methods are introduced as local approximation tools for forecasting. Such systems are used for matching current state of the time-series with past states to make a forecast. In the past, the PMRS system has been successfully...

quantitative methods used to forecast the behaviour of financial markets often produce unsatisfactory if not dismal results given the complex interactions between a given market's behaviour and other economic phenomena. Part of the problem lies in the fact that the relationships existing between financial markets and the economy as a whole are often poorly understood. On top of this there are a...

This conceptual paper develops a model based on prospect theory that explores how the effort entrepreneurs expend developing financial forecasts may influence risk-taking and performance. It proposes more they forecasts, likely will be to use results of as reference points against which evaluate their ventures’ future Furthermore, we propose leads optimistic are less adjusted. Our suggests thes...

Although many macroeconomic time series are assumed to follow nonlinear processes, nonlinear models often do not provide better predictions than their linear counterparts. Furthermore, such models easily become very complex and difficult to estimate. The aim of this study is to investigate whether simple nonlinear extensions of autoregressive processes are able to provide more accurate forecast...