We study the possibility of completing data bases of a sample of governance, diversification and value creation variables by providing a well adapted method to reconstruct the missing parts in order to obtain a complete sample to be applied for testing the ownership-structure / diversification...

The purpose of this paper is to examine if there are calendar anomalies in the Greek Stock market and to confirm the findings of other researches. Specifically two models are presented, one for the day of the week effect test and other for the month of the year effect. We provide GARCH...

This paper investigates the nonlinear predictability of technical trading rules based on a recurrent neural network as well as a neurofuzzy model. The efficiency of the trading strategies was considered upon the prediction of the direction of the market in case of NASDAQ and NIKKEI returns. The...

In this paper we design the neural network consumer credit scoring models for financial institutions where data usually used in previous research are not available. We use extensive primarily accounting data set on transactions and account balances of clients available in each financial...

Predicting currency movements has always been a problematic task as most conventional econometric models are not able to forecast exchange rates with significantly higher accuracy than a naive random walk model. For large multinational firms which conduct substantial currency transfers in the...

The article investigates the use of adaptive learning algorithms in constructing dynamic portfolios replicating the return characteristics of a given hedge fund. The emphasis is on out of sample conditional predictive capabilites as necessary to serve as a valuable risk management tool, rather...

In the last decade, neural networks have drawn noticeable attention from many computer and operations researchers. While some previous studies have found encouraging results with using this artificial intelligence technique to predict the movements of established financial markets, it is...

The purpose of this study is to forecast option prices with simple backpropagation neural networks and to compare the results between conventional Black-Scholes model, the Black-Scholes model with pure implied volatility and neural network models over a seven-year period. This longitudinal study...