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  IMPROVING THE PREDICTION ACCURACY OF FINANCIAL TIME SERIES BY USING MULTI-NEURAL NETWORK SYSTEMS AND ENHANCED DATA PREPROCESSING

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by Roy Schwaerzel
http://www.cs.utsa.edu/~rschwaer/thesis.ps
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Abstract:

My thanks go to my adviser, Professor Bruce E. Rosen, for his guidance and support throughout the work of this thesis. His insights and discussions has been very valuable for this thesis and for myself. I am grateful to Professor Robert Hiromoto, for many helpful discussions that enhanced the application perspective of this thesis. Thanks for his personal and professional support. I would like to sincerely thank all my teachers through the years, especially Professor Samir Das who always had time for a short question. A special acknowledgment is devoted to the Friedrich Naumann Foundation (Germany) who supported my studies in the United States. My studies would have never been possible without their support. The most important acknowledgment belongs to my parents. Their lifelong support and confidence have always strengthened me through many tough times, God bless them. ROY SCHWAERZEL

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