Table 4. Stock market prediction using other techniques.
| Authors | Scope | Input features | Feature extraction | Prediction algorithm |
|---|---|---|---|---|
| Wang et al. (2022b) | SSE | Price data | Normalization | LSTM/3D-CNN/GC-CNN & AD-GAT |
| Oyewola et al. (2021) | NGX | Price data | Technical indicators | AA/LR/SVM/FFN/RNN/SDE & GBM |
| Zhao & Wang (2015) | SSE | Price data | Tick-by-tick data | Outlier mining algorithm/Cluster algorithm |
| Vlasenko et al. (2018) | Global | Price data | NA | MIMO neuro-fuzzy model with multidimensional Gaussian functions |
| Jindal et al. (2021) | NSE/NYSE/MOEX | Price data | Scaling raw data | DT/RF & SVR |
| Umadevi et al. (2018) | NYSE | Stock score | NA | ARIMA |
| de Carvalho Tavares, Ferreira & Mendes (2022) | B3/NYSE | Price data | Scaling raw data | Hybrid fuzzy time series model with red–black tree data structure |
| Wang et al. (2022a) | SSE/NYSE/HKEX/TSE | Price data | Normalization | RNN/CNN/LSTM/Transformer |
| Sharma & Juneja (2017) | NSE/BSE | Technical indicators | Exponential smoothing | LS-RF |