Abstract
This paper addresses the problem of decision making in the context of financial markets. More specifically, the problem of forecasting the correct trading action for a certain future horizon. We study and compare two different alternative ways of addressing these forecasting tasks: i) using standard numeric prediction models to forecast the variation on the prices of the target asset and on a second stage transform these numeric predictions into a decision according to some pre-defined decision rules; and ii) use models that directly forecast the right decision thus ignoring the intermediate numeric forecasting task. The objective of our study is to determine if both strategies provide identical results or if there is any particular advantage worth being considered that may distinguish each alternative in the context of financial markets.
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© 2015 Springer International Publishing Switzerland
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Baía, L., Torgo, L. (2015). Forecasting the Correct Trading Actions. In: Pereira, F., Machado, P., Costa, E., Cardoso, A. (eds) Progress in Artificial Intelligence. EPIA 2015. Lecture Notes in Computer Science(), vol 9273. Springer, Cham. https://doi.org/10.1007/978-3-319-23485-4_55
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DOI: https://doi.org/10.1007/978-3-319-23485-4_55
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