Financial forecasting is a difficult task due to the intrinsic complexity of the financial system. A simplified approach in forecasting is given by “black box” methods like neural networks that assume little about the structure of the economy. In the present paper we relate our experience using neural nets as financial time series forecast method. In particular we show that a neural net able to...

Unlike conditional volatility that has been investigated intensively, conditional correlations between financial assets have received only little attention in literature. Researchers have, for so long, focused mainly on estimating returns and risk, and have assumed that the correlations are constant and have therefore paid less attention on them. However, recent studies uncover that such correl...

Neural networks are good at classification, forecasting and recognition. They are also good candidates of financial forecasting tools. Forecasting is often used in the decision making process. Neural network training is an art. Trading based on neural network outputs, or trading strategy is also an art. We will discuss a seven-step neural network forecasting model building approach in this arti...

We propose a forecasting procedure based on multivariate dynamic kernels, with the capability of integrating information measured at different frequencies and at irregular time intervals in financial markets. A data compression process redefines the original financial time series into temporal data blocks, analyzing the temporal information of multiple time intervals. The analysis is done throu...

Abstract: Computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. Forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. Nowadays, despite the numerous time series forecasting mod...

FGP: A Genetic Programming Based Financial Forecasting Tool

Financial forecasting is an estimation of future financial outcomes for a company, industry, country using historical internal accounting and sales data. We may predict the future outcome of BSE_SENSEX practically by some soft computing techniques and can also optimized using PSO (Particle Swarm Optimization), EA (Evolutionary Algorithm) or DEA (Differential Evolutionary Algorithm) etc. PSO is ...

A new genetic-algorithm-b ased system is presented and applied to the task of predicting the future performances of individual stocks. The system, in its most general form, can be applied to any inductive machine-learning problem: given a database of examples, the system will return a general description applicable to examples both within and outside the database. This differs from traditional ...

This paper explores the relationship between the health of the financial sector and the rest of the economy. We develop an indicator of financial sector health using a distance-to-default measure based on a Merton-style option pricing model. Our measure spans over three decades and appears to capture periods when financial sector institutions were strong and when they were weak. We then use vec...