Comparing the Performance of Long Short-Term Memory Architectures (LSTM) in Equity Price Forecasting: A Research on the Mexican Stock Market

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The Anáhuac Journal
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Published: Jun 26, 2024
DOI: https://doi.org/10.36105/theanahuacjour.2024v24n1.06
Keywords:
forecast, stocks, univariate, multivariate, LSTM

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Samuel García
EGADE Business School, Tecnológico de Monterrey, Mexico

Abstract

This study compares the performance of univariate and multivariate Long Short-Term Memory (LSTM) to predict next-day closing prices on four stocks in the consumer retail sector of the Mexican Stock Exchange. Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Median Absolute Percentage Error (MdAPE), and Root Mean Squared Error (RMSE) are used to test the networks’ performance. Results show a better performance on multivariate price forecasts when using 20-day and 15-day length sequences, generating consistent results for the sample, including illiquid and liquid stocks. On the other hand, univariate LSTM discloses lower forecast performance when predicting the price of illiquid stocks.

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How to Cite
García, S. (2024). Comparing the Performance of Long Short-Term Memory Architectures (LSTM) in Equity Price Forecasting: A Research on the Mexican Stock Market. The Anáhuac Journal, 24(1), Págs. 160–179. https://doi.org/10.36105/theanahuacjour.2024v24n1.06
Issue
Vol. 24 No. 1 (2024): The Anáhuac Journal, Vol. 24, num. 1, 2024, First Semester
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Artículos
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

This work is licensed under a Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional.

 

Author Biography

Samuel García, EGADE Business School, Tecnológico de Monterrey, Mexico

Samuel García is Mexican and has earned two master’s degrees: the first in Economics and Technological Change and the second in Finance, and a Bachelor’s in Business Administration. He has 25 years of experience in national and international financial institutions. He is a senior executive with knowledge of market surveillance, compliance, risk management, structured finance, financial products, and strategic management. Samuel worked at Citi for 16 years, where he was responsible for building and providing strategic direction for the ICRM Surveillance program, covering sales and trading as well as banking businesses across the Latin American Region—with more than 20 countries, including Mexico.

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