MULTIPLES AND STOCK PRICE, NEW APPROACH FOR RELATIVE VALUATION THROUGH NEURAL NETWORK

Saira Yamin and Saqib Gulzar
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Saira Yamin: Department of Management Sciences, COMSATS University Islamabad, Wah Campus, Wah Cantt, Pakistan
Saqib Gulzar: Department of Management Sciences, COMSATS University Islamabad, Wah Campus, Wah Cantt, Pakistan

The Singapore Economic Review (SER), 2025, vol. 70, issue 04, 953-971

Abstract: Artificial Neural Networks (ANNs) has been used as a powerful modeling technique for forecasting. In this study, the relationship between multiples and stock prices has been investigated on the Pakistan Stock Exchange 100 Index by incorporating financial modeling through neural network. The aim is to develop multiple-based valuation model to check whether multiples are viable factor in predicting stock movements. Forecasting model has been developed by using neural network. Prediction accuracy of the developed forecasting model has been evaluated. Findings reveal that neural network outperforms in comparison to linear regression and forecasts stock prices with 98% accuracy.

Keywords: Financial forecast; multiples; neural network; stock market; stock price; valuation (search for similar items in EconPapers)
JEL-codes: C45 C53 E37 F47 G17 M41 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1142/S0217590820480045

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