Much evidence supports that financial markets have the ability to aggregate information. When tied to a random variable, a financial market can forecast the value of the random variable. It then becomes a prediction market. We establish a simple model of prediction markets with aggregate uncertainty that theoretically characterizes some fundamental properties of prediction markets. Specifically...

The financial system plays a crucial role in economic development. Financial crises are recurrent phenomena in modern financial systems. The literature offers several definitions of financial instability, but it is well known that a financial crisis with a banking crisis is the most common example of financial instability. In this paper we introduce a novel model for detection and prediction of...

The model of financial risk prediction we developed and present in our paper is based on the theoretical assumption that there exists a significant relationship between actual economic situation values. This confirmed by research influences potential behaviour it becomes especially case changing life conditions. concept data received from 3768 respondents questioned across Czech Republic. Measu...

This research project investigates the ability of neural networks, specifically, the backpropagation algorithm, to integrate fundamental and technical analysis for financial performance prediction. The predictor attributes include 16 financial statement variables and 11 macroeconomic variables. The rate of return on common shareholders’ equity is used as the to-be-predicted variable. Financial ...

Prediction in financial domains is notoriously difficult for a number of reasons. First, theories tend to be weak or non-existent, which makes problem formulation open ended by forcing us to consider a large number of independent variables and thereby increasing the dimensionality of the search space. Second, the weak relationships among variables tend to be nonlinear, and may hold only in limi...

1 Introduction Over the last decade, a considerable literature on biologically inspired algorithms (BIA) has emerged. These powerful algorithms can be used for prediction and classification, and have clear application for use in financial modelling and in the development of trading systems. Financial markets represent a complex, ever-changing, environment in which a population of investors are ...