Journal articles on the topic 'Stock price forecasting – Computer simulation'
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Agung, Ignatius Wiseto Prasetyo. "Input Parameters Comparison on NARX Neural Network to Increase the Accuracy of Stock Prediction." JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING 6, no. 1 (July 21, 2022): 82–90. http://dx.doi.org/10.31289/jite.v6i1.7158.
Full textRath, Smita, Binod Kumar Sahu, and Manoj Ranjan Nayak. "Application of quasi-oppositional symbiotic organisms search based extreme learning machine for stock market prediction." International Journal of Intelligent Computing and Cybernetics 12, no. 2 (June 10, 2019): 175–93. http://dx.doi.org/10.1108/ijicc-10-2018-0145.
Full textWang, Xiang, Shen Gao, Yibin Guo, Shiyu Zhou, Yonghui Duan, and Daqing Wu. "A Combined Prediction Model for Hog Futures Prices Based on WOA-LightGBM-CEEMDAN." Complexity 2022 (February 27, 2022): 1–15. http://dx.doi.org/10.1155/2022/3216036.
Full textPanella, Massimo, Francesco Barcellona, and Rita L. D'Ecclesia. "Forecasting Energy Commodity Prices Using Neural Networks." Advances in Decision Sciences 2012 (December 31, 2012): 1–26. http://dx.doi.org/10.1155/2012/289810.
Full textZhang, Daxing, and Erguan Cai. "Improving Stock Price Forecasting Using a Large Volume of News Headline Text." Computers, Materials & Continua 69, no. 3 (2021): 3931–43. http://dx.doi.org/10.32604/cmc.2021.012302.
Full textGöçken, Mustafa, Aslı Boru �°pek, Mehmet Özçalıcı, and Ayşe Tuğba Dosdoğru. "Comparison of harmony search derivatives for artificial neural network parameter optimisation: stock price forecasting." International Journal of Data Mining, Modelling and Management 14, no. 4 (2022): 335. http://dx.doi.org/10.1504/ijdmmm.2022.10051603.
Full textÖzçalıcı, Mehmet, Ayşe Tuğba Dosdoğru, Aslı Boru �°, N. A. pek, and Mustafa Göçken. "Comparison of harmony search derivatives for artificial neural network parameter optimisation: stock price forecasting." International Journal of Data Mining, Modelling and Management 14, no. 4 (2022): 335. http://dx.doi.org/10.1504/ijdmmm.2022.126664.
Full textYing, Jun, Lynn Kuo, and Gim S. Seow. "Forecasting stock prices using a hierarchical Bayesian approach." Journal of Forecasting 24, no. 1 (January 2005): 39–59. http://dx.doi.org/10.1002/for.933.
Full textarman, Sup, Yahya Hairun, Idrus Alhaddad, Tedy Machmud, Hery Suharna, and Mohd Saifullah Rusiman. "Forecasting Software Using Laplacian AR Model based on Bootstrap-Reversible Jump MCMC: Application on Stock Price Data." Webology 18, Special Issue 04 (September 30, 2021): 1045–55. http://dx.doi.org/10.14704/web/v18si04/web18180.
Full textCheng, Ching-Hsue, Ming-Chi Tsai, and Chin Chang. "A Time Series Model Based on Deep Learning and Integrated Indicator Selection Method for Forecasting Stock Prices and Evaluating Trading Profits." Systems 10, no. 6 (December 3, 2022): 243. http://dx.doi.org/10.3390/systems10060243.
Full textObot, Okure Udo, Uduak David George, and Victoria Sunday Umana. "A Decision Support Tool (DST) for Inventory Management." International Journal of Decision Support System Technology 11, no. 2 (April 2019): 27–47. http://dx.doi.org/10.4018/ijdsst.2019040103.
Full textReddy, Dinesh, and Abhinav Karthik. "Forecasting Stock Price using LSTM-CNN Method." International Journal of Engineering and Advanced Technology 11, no. 1 (October 30, 2021): 1–8. http://dx.doi.org/10.35940/ijeat.a3117.1011121.
Full textHyup Roh, Tae. "Forecasting the volatility of stock price index." Expert Systems with Applications 33, no. 4 (November 2007): 916–22. http://dx.doi.org/10.1016/j.eswa.2006.08.001.
Full textHoang Vuong, Pham, Trinh Tan Dat, Tieu Khoi Mai, Pham Hoang Uyen, and Pham The Bao. "Stock-Price Forecasting Based on XGBoost and LSTM." Computer Systems Science and Engineering 40, no. 1 (2022): 237–46. http://dx.doi.org/10.32604/csse.2022.017685.
Full textSun, Guang, Jingjing Lin, Chen Yang, Xiangyang Yin, Ziyu Li, Peng Guo, Junqi Sun, Xiaoping Fan, and Bin Pan. "Stock Price Forecasting: An Echo State Network Approach." Computer Systems Science and Engineering 36, no. 3 (2021): 509–20. http://dx.doi.org/10.32604/csse.2021.014189.
Full textHe, Wu, Lin Guo, Jiancheng Shen, and Vasudeva Akula. "Social Media-Based Forecasting." Journal of Organizational and End User Computing 28, no. 2 (April 2016): 74–91. http://dx.doi.org/10.4018/joeuc.2016040105.
Full textAmiens, Ernest Oseghale, and Ifuero Osad Osamwonyi. "Stock price forecasting using hidden Markov model." International Journal of Information and Decision Sciences 14, no. 1 (2022): 39. http://dx.doi.org/10.1504/ijids.2022.122721.
Full textAmiens, Ernest Oseghale, and Ifuero Osad Osamwonyi. "Stock price forecasting using hidden Markov model." International Journal of Information and Decision Sciences 14, no. 1 (2022): 39. http://dx.doi.org/10.1504/ijids.2022.10047265.
Full textSTÁDNÍK, Bohumil, Jurgita RAUDELIŪNIENĖ, and Vida DAVIDAVIČIENĖ. "FOURIER ANALYSIS FOR STOCK PRICE FORECASTING: ASSUMPTION AND EVIDENCE." Journal of Business Economics and Management 17, no. 3 (June 7, 2016): 365–80. http://dx.doi.org/10.3846/16111699.2016.1184180.
Full textZhang, Qunhui, Mengzhe Lu, and Liang Dai. "On Mixed Model for Improvement in Stock Price Forecasting." Computer Systems Science and Engineering 41, no. 2 (2022): 795–809. http://dx.doi.org/10.32604/csse.2022.019987.
Full textRammurthy, Shruthi Komarla, and Sagar B. Patil. "An LSTM-Based Approach to Predict Stock Price Movement for IT Sector Companies." International Journal of Cognitive Informatics and Natural Intelligence 15, no. 4 (October 2021): 1–12. http://dx.doi.org/10.4018/ijcini.20211001.oa3.
Full textBabirath, Julia, Karel Malec, Rainer Schmitl, Kamil Maitah, and Mansoor Maitah. "Forecasting based on spectral time series analysis: prediction of the Aurubis stock price." Investment Management and Financial Innovations 17, no. 4 (December 4, 2020): 215–27. http://dx.doi.org/10.21511/imfi.17(4).2020.20.
Full textTang, Xiaobin, Nuo Lei, Manru Dong, and Dan Ma. "Stock Price Prediction Based on Natural Language Processing1." Complexity 2022 (May 6, 2022): 1–15. http://dx.doi.org/10.1155/2022/9031900.
Full textKhoa, Bui Thanh, and Tran Trong Huynh. "Forecasting stock price movement direction by machine learning algorithm." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (December 1, 2022): 6625. http://dx.doi.org/10.11591/ijece.v12i6.pp6625-6634.
Full textGuo, Yanhui, Siming Han, Chuanhe Shen, Ying Li, Xijie Yin, and Yu Bai. "An Adaptive SVR for High-Frequency Stock Price Forecasting." IEEE Access 6 (2018): 11397–404. http://dx.doi.org/10.1109/access.2018.2806180.
Full textLv, Jiehua, Chao Wang, Wei Gao, and Qiumin Zhao. "An Economic Forecasting Method Based on the LightGBM-Optimized LSTM and Time-Series Model." Computational Intelligence and Neuroscience 2021 (September 28, 2021): 1–10. http://dx.doi.org/10.1155/2021/8128879.
Full textLi, Hui, Jinjin Hua, Jinqiu Li, and Geng Li. "Stock Forecasting Model FS-LSTM Based on the 5G Internet of Things." Wireless Communications and Mobile Computing 2020 (June 20, 2020): 1–7. http://dx.doi.org/10.1155/2020/7681209.
Full textGao, Ya, Rong Wang, and Enmin Zhou. "Stock Prediction Based on Optimized LSTM and GRU Models." Scientific Programming 2021 (September 29, 2021): 1–8. http://dx.doi.org/10.1155/2021/4055281.
Full textChandar, S. Kumar. "Forecasting intraday stock price using ANFIS and bio-inspired algorithms." International Journal of Networking and Virtual Organisations 25, no. 1 (2021): 29. http://dx.doi.org/10.1504/ijnvo.2021.117754.
Full textChandar, S. Kumar. "Forecasting intraday stock price using ANFIS and bio-inspired algorithms." International Journal of Networking and Virtual Organisations 25, no. 1 (2021): 29. http://dx.doi.org/10.1504/ijnvo.2021.10041248.
Full textWANG, HONG-YONG, HONG LI, and JIN-YE SHEN. "A NOVEL HYBRID FRACTAL INTERPOLATION-SVM MODEL FOR FORECASTING STOCK PRICE INDEXES." Fractals 27, no. 04 (June 2019): 1950055. http://dx.doi.org/10.1142/s0218348x19500555.
Full textMumini, Omisore Olatunji, Fayemiwo Michael Adebisi, Ofoegbu Osita Edward, and Adeniyi Shukurat Abidemi. "Simulation of Stock Prediction System using Artificial Neural Networks." International Journal of Business Analytics 3, no. 3 (July 2016): 25–44. http://dx.doi.org/10.4018/ijban.2016070102.
Full textHossain, Mohammad Raquibul, and Mohd Tahir Ismail. "EMPIRICAL MODE DECOMPOSITION BASED ON THETA METHOD FOR FORECASTING DAILY STOCK PRICE." Journal of Information and Communication Technology 19, Number 4 (August 20, 2020): 533–58. http://dx.doi.org/10.32890/jict2020.19.4.4.
Full textSyukur, Abdul, and Aris Marjuni. "Stock Price Forecasting Using Univariate Singular Spectral Analysis through Hadamard Transform." International Journal of Intelligent Engineering and Systems 13, no. 2 (April 30, 2020): 96–107. http://dx.doi.org/10.22266/ijies2020.0430.10.
Full textHUANG, WEI, KIN KEUNG LAI, YOSHITERU NAKAMORI, SHOUYANG WANG, and LEAN YU. "NEURAL NETWORKS IN FINANCE AND ECONOMICS FORECASTING." International Journal of Information Technology & Decision Making 06, no. 01 (March 2007): 113–40. http://dx.doi.org/10.1142/s021962200700237x.
Full textZaheer, Shahzad, Nadeem Anjum, Saddam Hussain, Abeer D. Algarni, Jawaid Iqbal, Sami Bourouis, and Syed Sajid Ullah. "A Multi Parameter Forecasting for Stock Time Series Data Using LSTM and Deep Learning Model." Mathematics 11, no. 3 (January 22, 2023): 590. http://dx.doi.org/10.3390/math11030590.
Full textDong, Jichang, Wei Dai, Ying Liu, Lean Yu, and Jie Wang. "Forecasting Chinese Stock Market Prices using Baidu Search Index with a Learning-Based Data Collection Method." International Journal of Information Technology & Decision Making 18, no. 05 (September 2019): 1605–29. http://dx.doi.org/10.1142/s0219622019500287.
Full textMa, Guifen, Ping Chen, Zhaoshan Liu, and Jia Liu. "The Prediction of Enterprise Stock Change Trend by Deep Neural Network Model." Computational Intelligence and Neuroscience 2022 (August 2, 2022): 1–9. http://dx.doi.org/10.1155/2022/9193055.
Full textZhang, Xiaoyong, and Li Zhang. "Forecasting Method of Stock Market Volatility Based on Multidimensional Data Fusion." Wireless Communications and Mobile Computing 2022 (April 25, 2022): 1–14. http://dx.doi.org/10.1155/2022/6344064.
Full textZhang, Xiaoyong, and Li Zhang. "Forecasting Method of Stock Market Volatility Based on Multidimensional Data Fusion." Wireless Communications and Mobile Computing 2022 (April 25, 2022): 1–14. http://dx.doi.org/10.1155/2022/6344064.
Full textKhashei, Mehdi, and Zahra Hajirahimi. "A comparative study of series arima/mlp hybrid models for stock price forecasting." Communications in Statistics - Simulation and Computation 48, no. 9 (May 8, 2018): 2625–40. http://dx.doi.org/10.1080/03610918.2018.1458138.
Full textXiao, Daiyou, and Jinxia Su. "Research on Stock Price Time Series Prediction Based on Deep Learning and Autoregressive Integrated Moving Average." Scientific Programming 2022 (March 31, 2022): 1–12. http://dx.doi.org/10.1155/2022/4758698.
Full textChang, To-Han, Nientsu Wang, and Wen-Bin Chuang. "Stock Price Prediction Based on Data Mining Combination Model." Journal of Global Information Management 30, no. 7 (September 2022): 1–19. http://dx.doi.org/10.4018/jgim.296707.
Full textYu, Xinpeng, and Dagang Li. "Important Trading Point Prediction Using a Hybrid Convolutional Recurrent Neural Network." Applied Sciences 11, no. 9 (April 28, 2021): 3984. http://dx.doi.org/10.3390/app11093984.
Full textLiu, Hui, Liangchen Qi, and Mingsong Sun. "Short-Term Stock Price Prediction Based on CAE-LSTM Method." Wireless Communications and Mobile Computing 2022 (June 22, 2022): 1–7. http://dx.doi.org/10.1155/2022/4809632.
Full textFu, Yizheng, Zhifang Su, Boyu Xu, and Yu Zhou. "Forecasting Stock Index Futures Intraday Returns: Functional Time Series Model." Journal of Advanced Computational Intelligence and Intelligent Informatics 24, no. 3 (May 20, 2020): 265–71. http://dx.doi.org/10.20965/jaciii.2020.p0265.
Full textLivieris, I. E., T. Kotsilieris, S. Stavroyiannis, and P. Pintelas. "Forecasting stock price index movement using a constrained deep neural network training algorithm." Intelligent Decision Technologies 14, no. 3 (September 29, 2020): 313–23. http://dx.doi.org/10.3233/idt-190035.
Full textGu, Wentao, Yongwei Yang, and Zhenshan Liu. "Forecasting Stock Returns Based on a Time-Varying Factor Weighted Density Model." Journal of Advanced Computational Intelligence and Intelligent Informatics 22, no. 6 (October 20, 2018): 831–37. http://dx.doi.org/10.20965/jaciii.2018.p0831.
Full textSun, Mei, Qingtao Li, and Peiguang Lin. "Short-Term Stock Price Forecasting Based on an SVD-LSTM Model." Intelligent Automation & Soft Computing 28, no. 2 (2021): 369–78. http://dx.doi.org/10.32604/iasc.2021.014962.
Full textChen, Yu, Ruixin Fang, Ting Liang, Zongyu Sha, Shicheng Li, Yugen Yi, Wei Zhou, and Huilin Song. "Stock Price Forecast Based on CNN-BiLSTM-ECA Model." Scientific Programming 2021 (July 8, 2021): 1–20. http://dx.doi.org/10.1155/2021/2446543.
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