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An artificial walk down Wall Street : can intraday stock returns be predicted using artificial neural networks?

Bøvre, Jens Olve; Viervoll, Peder Kristian
Master thesis
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Bovre og Viervoll 2009.pdf (464.7Kb)
URI
http://hdl.handle.net/11250/168291
Date
2009
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  • Master Thesis [3749]
Abstract
Financial markets are complex evolved dynamic systems. Due to its irregularity,

financial time series forecasting is regarded as a rather challenging task. In recent

years, artificial neural network applications in finance, for such tasks as pattern

recognition, classification, and time series forecasting have dramatically increased.

The objective of this paper is to present this powerful framework and attempt to use

it to predict the stock return series of four publicly listed companies on the New York

Stock Exchange. Our findings coincide with those of Burton Malkiel in his book, A

Random Walk down Wall Street; no conclusive evidence is found that our proposed

models can predict the stock return series better than a random walk.

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