Forecasting Bank Stock Trends Using Artificial Intelligence: A Deep Dive into the Neural Prophet Approach

Noviandy, Teuku Rizky
Hardi, Irsan
Idroes, Ghalieb Mutig

The International Journal of Financial Systems
Vol. 2 No. 1 (2024)

This research aims to use Neural Prophet, a deep learning tool, to predict stock prices in the banking sector with high accuracy and useful insights. The model's capability in managing intricate temporal patterns differentiates it, garnering attention from researchers. The significance of this research lies in its potential to enhance stock price prediction precision, especially in the context of banking stocks, offering stakeholders’ deeper insights. The model's efficacy spans stable and volatile market behaviours, making it a valuable tool for informed decision-making in finance. Accurate predictions benefit risk management, facilitating well-informed investment choices in dynamic markets.