Table 1 A brief list of selected studies
From: An interval constraint-based trading strategy with social sentiment for the stock market
References | Forecasted goals | Data frequency | Forecasting Method | Evaluation Indicators |
|---|---|---|---|---|
Gupta et al. (2019) | UK stock-return | Quarterly | Quantile random forests | p-value |
Kim et al. (2019) | Norway Oslo Børs OBX index | Weekly | Panel data regressions | R2 |
Gu and Peng (2019) | Shanghai Composite Index, CITIC Securities | Weekly | TVPDM | CR |
Sadaei et al. (2016) | TAIEX, NASDAQ, DJI, S &P 500 | Daily | Hybrid model | RMSE, MAE |
Kao et al. (2013) | SSEC, BB, DJ, N225 | Daily | Wavelet-MAR-SVR | RMSE, MAE, MAPE, RMSPE |
Guo et al. (2022) | SH60000 stock | Daily | EEMD-Cluster SVR-PSO-LSTM | MAE, MSE, RMSE |
Ghosh et al. (2022) | S &P 500 | Daily | Random forests and LSTM | Sharpe ratio, standard deviation, VaR, average return |
Na and Kim (2021) | Korean stock market data | Daily | ANN | Annualized average returns Sharpe ratio, information ratio |
Deng et al. (2023) | Capital flow data | Daily | XGBoost, SHAP approach | F1-score, accuracy |
Maqbool et al. (2023) | Stock data of Reliance, Tata Motors, Tata Steel and HDFC | Daily | MLP-Regressor | MAPE,F1-score, accuracy |
Zhong and Enke (2019) | S &P 500 | Daily | ANN | MSE |
Liang et al. (2020) | Shanghai Stock Exchange Composite Index | Daily | HAR | R2 |
Yun et al. (2022) | Exxon Mobil stock | Daily | XGBoost | RMSE,MSE,MAE,R2 |
Zhang et al. (2018) | A-share market stocks | Daily | SVM,MLP | ACC, AUC |
Liu et al. (2021) | SSE 50 constituent stocks | Daily | LSTM | RMSE,MAPE |
Maqsood et al. (2020) | Stock exchangedata for 15 companies | Daily | LR,SVR,DL | RMSE,MAE |
This study | Five A-share stocks, SSEC | Daily | TCN/Gi-MLP | MAE, RMSE, MAPE |
References | Considering economic variables | Considering news sentiment | Considering practitioner sentiment | Considering the context of the event (e.g., public health event, terrorist attack, etc.) |
|---|---|---|---|---|
Gupta et al. (2019) | \(\checkmark\) | \(\times\) | \(\times\) | \(\times\) |
Kim et al. (2019) | \(\checkmark\) | \(\checkmark\) | \(\times\) | \(\times\) |
Gu and Peng (2019) | \(\times\) | \(\times\) | \(\times\) | \(\times\) |
Sadaei et al. (2016) | \(\times\) | \(\times\) | \(\times\) | \(\times\) |
Kao et al. (2013) | \(\checkmark\) | \(\times\) | \(\times\) | \(\times\) |
Guo et al. (2022) | \(\times\) | \(\times\) | \(\times\) | \(\times\) |
Ghosh et al. (2022) | \(\times\) | \(\times\) | \(\times\) | \(\times\) |
Na and Kim (2021) | \(\checkmark\) | \(\times\) | \(\checkmark\) | \(\times\) |
Deng et al. (2023) | \(\checkmark\) | \(\times\) | \(\checkmark\) | \(\times\) |
Maqbool et al. (2023) | \(\checkmark\) | \(\checkmark\) | \(\times\) | \(\times\) |
Zhong and Enke (2019) | \(\checkmark\) | \(\times\) | \(\times\) | \(\times\) |
Liang et al. (2020) | \(\checkmark\) | \(\checkmark\) | \(\times\) | \(\checkmark\) |
Yun et al. (2022) | \(\checkmark\) | \(\times\) | \(\times\) | \(\times\) |
Zhang et al. (2018) | \(\checkmark\) | \(\times\) | \(\checkmark\) | \(\times\) |
Liu et al. (2021) | \(\checkmark\) | \(\times\) | \(\checkmark\) | \(\times\) |
Maqsood et al. (2020) | \(\times\) | \(\checkmark\) | \(\times\) | \(\checkmark\) |
This study | \(\checkmark\) | \(\checkmark\) | \(\checkmark\) | \(\checkmark\) |