From: Survey of feature selection and extraction techniques for stock market prediction
Study | Types of features | Feature selection/extraction techniques | Prediction methods | Datasets |
---|---|---|---|---|
1. Haq et al. (2021) | Basic features, Technical indicators | LR, SVM, RF | Deep generative model | 88 stocks from NASDAQ |
2. Labiad et al. (2016) | Technical indicators | RF | Gradient boosted trees (GBT), SVM, RF | Moroccan stock market |
3. Rana et al. (2019) | Basic features | Decision tree classifier, Extra Tree classifier | LR, SVR, LSTM | Spanish stock market |
4. Aloraini (2015) | Open prices | Pearson correlation coefficient (PCC), Spearman correlation, Euclidean distance, Manhattan distance, Search AIC score | Lasso estimate | 11 equities in Saudi stock market |
5. Kumar et al. (2016) | Basic features, Technical indicators | Pearson correlation, Spearman correlation, Relief algorithm, Random forest (RF) | PSVM | 12 stock indices from different international markets |
6. Alsubaie et al. (2019) | Technical indicators | Gain ratio, Relief algorithm, Correlation, Cost-based Naive Bayesian, Accuracy-based Naive Bayesian | 9 different classifiers | 99 stocks and TASI market in-dex |
7. Li et al. (2022) | Technical indicators Fundamental indica- tors | PCC | Broad learning system | 4 stocks from Shanghai Stock Exchange |
8. Nabi et al. (2019) | Basic features | 9 different methods | 15 different classifiers | 10 stocks from NASDAQ |
9. Yuan et al. (2020) | Technical indicators, Fundamental indica-tors | RFE, RF | SVM RF ANN | Chinese A-share stocks |
10. Botunac et al. (2020) | Basic features, Technical indicators | RFE, Linear regression, Decision Tree, RF | LSTM | Apple, Microsoft, Facebook |
11. Shen et al. (2020) | Technical indicators | RFE PCA | LSTM | 3558 Chinese stocks |
12. Chen et al. (2017) | Technical indicators | Information gain | SVM | Chinese stock market indices |
13. Sun et al. (2019) | Technical indicators | FSMRMR, CMIM | ARMA-GARCH-NN | US stock market |
14. Singh et al. (2021) | Technical indicators, Fundamental indica-tors | PCA | 6 different classifiers | 505 stocks from S& P 500 |
15. Ampomah et al. (2020) | Basic features, Technical indicators | PCA | 6 tree-based Classifiers | 8 stocks from NYSE, NASDAQ, NSE |
16. Siddique et al. (2019) | Basic features | PCA | SVR | TATA motors stock index |
17. Iacomin (2015) | Technical indicators | PCA GA | SVM | 16 Forex stocks from Bloomberg |
18. Cai et al. (2012) | Basic features, Technical indicators | RBM | SVM | S& P 500 index |
19. Das et al. (2019) | Technical indicators | PCA, Factor analysis (FA), Firefly optimization (FO), Genetic algorithm (GA), FO with GA | ELM, OSELM, RBPNN | 4 different stock market indices |
20. Qolipour et al. (2021) | Basic features, Technical indicators | PCA | Decision tree, RF, Gradient boosted tree (GBT) | 2 stocks from Tehran stock exchange |
21. Ampomah et al. (2021) | Technical indicators | PCA, LDA, FA | Gaussian Naïve Bayes (GNB) | 7 stocks from NYSE, NASDAQ, NSE |
22. Chen et al. (2020) | Basic features, Technical indicators | Information gain | FW-SVM | 30 stocks |
23. Gunduz etal. (2017) | Technical indicators | Gain ratio Relief algorithm | Gradient boosting ma-chine (GBM) | 3 stocks in BIST market index |
24. Kumar et al. (2021b) | Basic features, Technical indicators | PCA | ANN | 3 stock indices |
25. Tang et al. (2018) | historical relative re-turns | PCA | KNN | CSI 300 index |
26. Barak et al. (2017) | Fundamental indica-tors | GA | Multiple classifiers | 400 stocks |
27. Farahani et al. (2021) | Technical indicators | GA | ANN | 5 stock indices |
28. Chong et al. (2017) | 10 lagged returns | Autoencoder | DNN | 38 stocks |
29. Bhanja et al. (2022) | Technical indicators | Autoencoder | 5 ML classifiers | 2 market indices |
30. Xie et al. (2021) | Fundamental indica-tors | Autoencoder | SVM | 5 market indices |
31. Dami et al. (2021) | Basic features | Autoencoder | LSTM | 10 stocks |
32. Gunduz (2021) | Technical indicators | Autoencoder | SVM LSTM | 8 stocks |