The role of predictability of financial series in emerging market applications

Authors:
Gabriela Prelipcean;Nicolae Popoviciu;Mircea Boscoianu
Affiliations:
Faculty of Economic and Public Administration, Stefan cel Mare University of Suceava, Suceava, Romania;Faculty of Mathematics-Informatics, Hyperion University of Bucharest, Bucharest, Romania;Faculty of Economic and Public Administration, Stefan cel Mare University of Suceava, Suceava, Romania
Venue:
MCBE'08 Proceedings of the 9th WSEAS International Conference on Mathematics & Computers In Business and Economics
Year:
2008

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Abstract

A new metric that quantifies the predictability of financial time series based on a mixture between Kaboudan η -metric and Genetic Programming (GP)/ Artificial Neural Networks (ANN) is proposed. The new metrics overcomes the stationary problem and shows how the predictability changes over different subsequences in financial time series. The focus is to develop quantitative metrics that characterize time series according to their ability to be modeled by a particular method, such as the predictability of a time series using the GP approach or an ANN.