Daily Trading of the FTSE Index Using LSTM with Principal Component Analysis

David Edelman () and David Mannion ()
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David Edelman: University College Dublin
David Mannion: University College Dublin

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2022, pp 228-234 from Springer

Abstract: Abstract This study comprises a preliminary investigation into the use of Long Short-Term Memory (LSTM) methodology when used in conjunction with Principal Component Analysis (PCA) for producing trading signals for daily returns of the the FTSE100 index. The model is trained on approximately 35 years of daily data and validated on six months of testing data, demonstrating a high degree of risk-adjusted trading efficacy.

Keywords: Deep learning; Recurrent networks; Time series; Ensembling (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-99638-3_37

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DOI: 10.1007/978-3-030-99638-3_37

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