A new prediction NN framework design for individual stock based on the industry environment

Akbulaev, 2021, Analysis of the influence of the price of raw oil and natural gas on the prices of indices and shares of the Turkish stock exchange, Public Financ. Quart. Hungar, 66, 151 Baek, 2018, Modaugnet: a new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module, Expert Syst. Appl., 113, 457, 10.1016/j.eswa.2018.07.019 Calantone, 2010, The impact of industry environment on early market entry decisions by B2B managers in the U.S. and Japan, Ind. Market. Manag., 39, 832, 10.1016/j.indmarman.2009.10.002 Cho, 2014, On the properties of neural machine translation: encoder-decoder approaches, 103 Cyfert, 2020, The importance of dynamic capabilities in the processes of alignment of chemical industry enterprises to changes in the environment, Przem. Chem., 99, 953 Dragomiretskiy, 2014, Variational mode decomposition, IEEE Trans. Signal Process., 62, 531, 10.1109/TSP.2013.2288675 Gan, 2021, Application of the variational mode decomposition (VMD) method to river tides, Estuar. Coast Shelf Sci., 261 Geva, 2014, Empirical evaluation of an automated intraday stock recommendation system incorporating both market data and textual news, Decis. Support Syst., 57, 212, 10.1016/j.dss.2013.09.013 Gulzar, 2019, Financial cointegration and spillover effect of global financial crisis: a study of emerging asian financial markets, Econ. Res. Ekonomska Istaazivanja, 32, 187, 10.1080/1331677X.2018.1550001 Guresen, 2011, Using artificial neural network models in stock market index prediction, Expert Syst. Appl., 38, 10389, 10.1016/j.eswa.2011.02.068 He, 2022, Sudden shock and stock market network structure characteristics: a comparison of past crisis events, Technol. Forecast. Soc. Change, 180 Hochreiter, 1997, Long short-term memory, Neural Comput., 9, 1735, 10.1162/neco.1997.9.8.1735 Huang, 2009, A hybrid SOFM-SVR with a filter-based feature selection for stock market forecasting, Expert Syst. Appl., 36, 1529, 10.1016/j.eswa.2007.11.062 Jeff Rose, 2020 Jin, 2020, Deep hybrid model based on emd with classification by frequency characteristics for long-term air quality prediction, Mathematics, 8, 214, 10.3390/math8020214 Kao, 2013, Integration of nonlinear independent component analysis and support vector regression for stock price forecasting, Neurocomputing, 99, 534, 10.1016/j.neucom.2012.06.037 Kim, 2018, Forecasting the volatility of stock price index: a hybrid model integrating LSTM with multiple garch-type models, Expert Syst. Appl., 103, 25, 10.1016/j.eswa.2018.03.002 Lee, 2022, Research on the feasibility of applying GRU and attention mechanism combined with technical indicators in stock trading strategies, Appl. Sci. Basel, 12 Lei, 2018, Wavelet neural network prediction method of stock price trend based on rough set attribute reduction, Appl. Soft Comput., 62, 923, 10.1016/j.asoc.2017.09.029 Li, 2018, A hybrid model based on synchronous optimisation for multi-step short-term wind speed forecasting, Appl. Energy, 215, 131, 10.1016/j.apenergy.2018.01.094 Li, 2019, Does diversification help improve the performance of coal companies? Evidence from China’s listed coal companies, Resour. Pol., 61 (Jun.), 88, 10.1016/j.resourpol.2019.01.013 Li, 2019, Underdetermined blind separation of bearing faults in hyperplane space with variational mode decomposition, Mech. Syst. Signal Process., 120 (Apr.), 83, 10.1016/j.ymssp.2018.10.016 Li, 2021, A new hybrid VMD-ICSS-BiGRU approach for gold futures price forecasting and algorithmic trading, IEEE Trans. Comput. Soc. Syst., 8, 1357, 10.1109/TCSS.2021.3084847 Liu, 2022, Intra-industry information transfer in emerging markets: evidence from China, J. Bank. Finace, 140 Liu, 2020, Adaptive wavelet transform model for time series data prediction, Soft Comput., 24 (Apr.), 5877, 10.1007/s00500-019-04400-w Liu, 2019, Novel volatility forecasting using deep learning–long short term memory recurrent neural networks, Expert Syst. Appl., 132, 99, 10.1016/j.eswa.2019.04.038 Liu, 2020, Non-ferrous metals price forecasting based on variational mode decomposition and LSTM network, Knowl. Base Syst., 188 (Jan.) Long, 2019, Deep learning-based feature engineering for stock price movement prediction, Knowl. Base Syst., 164, 163, 10.1016/j.knosys.2018.10.034 Lu, 2020, A CNN-LSTM-based model to forecast stock prices, Complexity, 2020 Maharshi, 2021, Study on investment strategies stipulated on technical analysis: reference to indian pharmaceutical stocks, Pac. Bus. Rev. Int., 14, 71 Tatpornpan, 2022, Information quality of investment services with social media, J. Comput. Inf. Syst. Available at: Teti, 2019, The relationship between twitter and stock prices. evidence from the us technology industry, Technol. Forecast. Soc. Change, 149 Tian, 2019, A hybrid vibration signal prediction model using autocorrelation local characteristic-scale decomposition and improved long short term memory, IEEE Access, 7, 60995, 10.1109/ACCESS.2019.2916000 Tsai, 2010, Combining multiple feature selection methods for stock prediction: union, intersection, and multi-intersection approaches, Decis. Support Syst., 50, 258, 10.1016/j.dss.2010.08.028 Vanstone, 2019, Do news and sentiment play a role in stock price prediction?, Appl. Intell., 49, 3815, 10.1007/s10489-019-01458-9 Wang, 2021, Efficient English translation method and analysis based on the hybrid neural network, Mobile Inf. Syst., 2021 Wang, 2015, Forecasting stock market indexes using principle component analysis and stochastic time effective neural networks, Neurocomputing, 156, 68, 10.1016/j.neucom.2014.12.084 Wang, 2011, Forecasting stock indices with back propagation neural network, Expert Syst. Appl., 38, 14346, 10.1016/j.eswa.2011.04.222 Wimble, 2018, Understanding cross-level interactions of firm-level information technology and industry environment: a multilevel model of business value, Inf. Resour. Manag. J., 31, 1, 10.4018/IRMJ.2018010101 Yang, 2014, The impacts of top management team characteristics on entrepreneurial strategic orientation the moderating effects of industrial environment and corporate ownership, Manag. Decis., 52, 378, 10.1108/MD-03-2013-0140 Kim, 2019, Feature visualization in comic artist classification using deep neural networks, J. BIG Data, 6 Zhang, 2018, Combining weather condition data to predict traffic flow: a GRU-based deep learning approach, IET Intell. Transp. Syst., 12, 578, 10.1049/iet-its.2017.0313 Zhang, 2018, Use long short-term memory to enhance internet of things for combined sewer overflow monitoring, J. Hydrol., 556, 409, 10.1016/j.jhydrol.2017.11.018 Zhang, 2018, A novel data-driven stock price trend prediction system, Expert Syst. Appl., 97 (May), 60, 10.1016/j.eswa.2017.12.026 Zhao, 2018, Machine health monitoring using local feature-based gated recurrent unit networks, IEEE Trans. Ind. Electron., 65, 1539, 10.1109/TIE.2017.2733438 Zhu, 2021, The gambling preference and stock price: evidence from China’s stock market, Emerg. Mark. Rev., 49 Zhu, 2019, Carbon price forecasting with variational mode decomposition and optimal combined model, Phys. Stat. Mech. Appl., 519 (Apr.), 140, 10.1016/j.physa.2018.12.017 Zhu, 2022, Static or dynamic? Characterize and forecast the evolution of urban crime distribution, Expert Syst. Appl., 190 Zhu, 2019, A hybrid VMD–BiGRU model for rubber futures time series forecasting, Appl. Soft Comput., 84, 105739, 10.1016/j.asoc.2019.105739