Stock Price Prediction With the Informer Model

The capacity to foresee future stock prices can substantially augment the potential profits of investors; thus, the subject of stock price prediction assumes significance within the investment industry. The present study employs the Informer model for the purpose of predicting stock prices. The results obtained from this research demonstrate that the Informer model's performance is contingent upon the dataset employed, suggesting that its applicability might be limited to particular categories of stock market data. The optimal outcomes were achieved using the BNI dataset, suggesting that although the model exhibits promise, it must be tailored to specific datasets and selected accordingly in order to optimize its performance.