Multi-Layer Perceptron-Based Classification with Application to Outlier Detection in Saudi Arabia Stock Returns

Khudhayr A. Rashedi (), Mohd Tahir Ismail, Sadam Al Wadi, Abdeslam Serroukh, Tariq S. Alshammari and Jamil J. Jaber
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Khudhayr A. Rashedi: Department of Mathematics, College of Science, University of Hail, Hail 2440, Saudi Arabia
Mohd Tahir Ismail: School of Mathematical Science, Universiti Sains Malaysia, George Town 11700, Malaysia
Sadam Al Wadi: Department of Finance, School of Business, The University of Jordan, Aqaba 77110, Jordan
Abdeslam Serroukh: Department of Mathematics, Polydisciplinary Faculty of Larache, University Abdelmalek Essaadi, Tetouan 93000, Morocco
Tariq S. Alshammari: Department of Mathematics, College of Science, University of Hail, Hail 2440, Saudi Arabia
Jamil J. Jaber: Department of Finance, School of Business, The University of Jordan, Aqaba 77110, Jordan

JRFM, 2024, vol. 17, issue 2, 1-13

Abstract: We aim to detect outliers in the daily stock price indices from the Saudi Arabia stock exchange (Tadawul) with 2026 observations from October 2011 to December 2019 provided by the Saudi Authority for Statistics and the Saudi Central Bank. We apply the Multi-Layer Perceptron (MLP) algorithm for detecting outliers in stock returns. We select the inflation rate (Inflation), oil price (Loil), and repo rate (Repo) as input variables to the MLP architecture. The performance of the MLP is evaluated using standard metrics for binary classification, namely the false positive rate (FP rate), false negative rate (FN rate), F-measure, Matthews correlation coefficient (MCC), accuracy (ACC), and area under the ROC curve (AUC). The results demonstrate the efficiency and good performance of the MLP algorithm based on different criteria tests.

Keywords: outlier detection; Multi-Layer Perceptron (MLP) algorithm; metrics for binary classification; Saudi Arabia stock exchange (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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