outputs/Why is feature engineering important in financial forecasting/research--8811703707667059559.txt

[{"title": "Survey of feature selection and extraction ... - Financial Innovation", "href": "https://jfin-swufe.springeropen.com/articles/10.1186/s40854-022-00441-7", "body": "In stock market forecasting, the identification of critical features that affect the performance of machine learning (ML) models is crucial to achieve accurate stock price predictions. Several review papers in the literature have focused on various ML, statistical, and deep learning-based methods used in stock market forecasting."}, {"title": "(PDF) Feature Selection for Forecasting - ResearchGate", "href": "https://www.researchgate.net/publication/369035848_Feature_Selection_for_Forecasting", "body": "This work investigates the importance of feature selection for improving the forecasting performance of machine learning algorithms for financial data. Artificial neural networks (ANN ..."}, {"title": "Stock index trend prediction based on TabNet feature selection ... - PLOS", "href": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0269195", "body": "Fig 4 shows feature importance masks mask[i] that indicates feature ... Cui L. Deep learning-based feature engineering for stock price movement prediction. Knowledge-Based Systems. 2019; 164: 163-173. ... Ming LJ, Sumei R, Shuping Z. A hybrid model for financial time series forecasting\u2014integration of EWT, ARIMA with the improved ABC ..."}]