A Neural Network Analysis of Accounting Variables and Stock Price: The Case of Real Estate Companies in the Philippines
DOI:
https://doi.org/10.54536/ajebi.v3i3.3280Keywords:
Accounting Variables, Neural Networks, Philippines, Real Estate Companies, Stock PriceAbstract
This research examines the importance of various accounting variables in predicting stock price changes for the top three real estate companies on the 2024 Philippine Stock Exchange. The study uses artificial neural network (ANN) analysis to focus on the current ratio, return on assets, return on equity, net profit margin, operating profit margin, and debt-to-equity ratio. Quarterly financial reports and stock prices from 2018 to 2023 were analyzed with a feedforward back-propagation ANN model in SPSS 25. Results show that the net profit margin is the most significant predictor of stock prices, highlighting profitability as crucial. The operating profit margin is significant for Mega World Corporation, while the current ratio is critical for SM Prime Holdings. The debt-to-equity ratio is moderately important across all companies. These findings emphasize the varied impact of profitability, operational efficiency, leverage, and liquidity on stock prices, aiding investment decisions and strategic planning.
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