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

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Mathematical and Statistical Methods for Actuarial Sciences and Finance (MAF 2022)

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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.

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Correspondence to David Edelman .

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Edelman, D., Mannion, D. (2022). Daily Trading of the FTSE Index Using LSTM with Principal Component Analysis. In: Corazza, M., Perna, C., Pizzi, C., Sibillo, M. (eds) Mathematical and Statistical Methods for Actuarial Sciences and Finance. MAF 2022. Springer, Cham. https://doi.org/10.1007/978-3-030-99638-3_37

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