Session:

Hybrid Algorithms for Function Approximation and Time Series Prediction
Sunday, February 29, 2004, 17.55 – 18.15

Session Chair:

Peter Anderson

Paper Title:

Turkish Stock Market Analysis using Mixture of Experts

Author(s):

F. Gurgen, Nesrin Okay Bogazici University, Turkey
M.Serdar Yumlu, Nesrin Okay Bogazici University, Turkey

Abstract:

This paper investigates the use of artificial neural networks (ANN) in risk estimation of asset returns. Istanbul Stock Exchange (ISE) index (XU100) is studied with a mixture of experts ANN architecture using daily data over a 12-year period. Results are compared to feed-forward neural networks, multilayer perceptron (MLP) and radial basis function (RBF) networks and recurrent neural networks (RNN). They are also compared to widely accepted Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) volatility model. These results suggest that mixture of experts (MoE) have the strength to capture the volatility in index return series and prepares a valuable basis for ¯financial decision making.