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Equation Discovery for Financial Forcasting in Context of Islamic Banking

 

Amer Alzaidi, Dimitar Kazakov

 

 

Computer Science, University of York, York YO10 5DD, United Kingdom

 

Abstract-This paper describes an equation discovery approach  based on machine learning using LAGRAMGE as an equation discovery tool, with tw o sources of input, a dataset and model presented in context-free grammar. The  approach is searching a large range of potential equations by a specific model.  The parameters of the equation are fitted to find the best equations. The experi ments are illustratedwith commodity prices from the London Metal Exchange for th e period of January-October 2009. The outputs of the experiments are a lar ge number of equations; some of the equations display that the predicted prices  are following the market trends in perfect patterns.

 

Key words-machine learning; equation discovery; LAGRAMG E; forcasting; islamic banking

 

Manuscript Number: 1674-8042(2010)01-0093-05

 

dio: 10.3969/j.issn.1674-8042.2010.01.19

 

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