• Conference Object  

      Application of artificial neural networks in the prediction of earnings 

      Falas, Tasos; Charitou, Andreas; Charalambous, Chris (IEEE, 1994)
      The feasibility of using artificial neural networks (ANNs) for predicting future earnings by stock market and capital market investors was evaluated. A multilayer perceptron feedforward neural network architecture with an ...
    • Article  

      Application of three bivariate time-varying volatility models 

      Vrontos, Ioannis D.; Giakoumatos, Stefanos G.; Dellaportas, Petros; Politis, Dimitris Nicolas (2001)
      The multivariate time-varying volatility models have recently attracted a lot of attention in the statistics/econometrics community. We apply two bivariate ARCH-GARCH models and a bivariate unobserved ARCH model to a series ...
    • Conference Object  

      Comparative analysis of artificial neural network models: Application in bankruptcy prediction 

      Charalambous, Chris; Charitou, Andreas; Kaourou, Froso (IEEE, 1999)
      This study compares the predictive performance of three neural network methods, namely the Learning Vector Quantization, Radial Basis Function, the Feedforward network that uses the conjugate gradient optimization algorithm, ...
    • Conference Object  

      Testing the predictability of the Cyprus Stock Exchange: The case of an emerging market 

      Andreou, Andreas S.; Neocleous, Constantinos C.; Schizas, Christos N.; Toumpouris, Costas (IEEE, 2000)
      A systematic investigation of the effect of different neural network architecture alternatives for predicting the future course of stock prices in the Cyprus Stock Exchange (CSE) market is conducted. This market exhibited ...