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.

中文翻译：

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倍数和股票价格，通过神经网络进行相对估值的新方法

人工神经网络 (ANN) 已被用作一种强大的预测建模技术。在本研究中，通过神经网络结合金融模型，在巴基斯坦证券交易所 100 指数上研究了倍数与股价之间的关系。目的是开发基于倍数的估值模型，以检查倍数是否是预测股票走势的可行因素。使用神经网络开发了预测模型。对所开发的预测模型的预测准确性进行了评估。研究结果表明，与线性回归相比，神经网络的表现优于线性回归，并且以 98% 的准确率预测股票价格。