Forecasting the Correct Trading Actions

• Type: Article in International Conference Proceedings Book
• Date: 2015

Authors

Baía, L (Author) Other; Torgo, L (Author) FCUP

Conference proceedings International

Title: PROGRESS IN ARTIFICIAL INTELLIGENCE

Pages: 560-571

17th Portuguese Conference on Artificial Intelligence (EPIA)

Univ Coimbra, Coimbra, PORTUGAL, SEP 08-11, 2015

Indexing

ISI Web of Knowledge - 2 Citations

Scopus - 2 Citations

Other information

Authenticus ID: P-00G-VFJ

DOI: 10.1007/978-3-319-23485-4_55

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12