id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
faba-298	Gbadebo, Adedeji	Stock Price Forecasting Using a Time-Series Long Short-Term Memory Model	2025	19	.pdf	application/pdf	7413	432	44	Similarly, Zeng and Liu (2018) emphasize the persistent difficulty of stock price prediction and highlight the importance of advanced methods such as LSTM for addressing the complexities inherent in financial markets. This introduction frames the application of LSTMs for stock price prediction within the Python programming environment.	cache/faba-298.pdf	txt/faba-298.txt