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Forecasting stock index returns using ARIMA-SVM, ARIMA-ANN and ARIMA-random forest hybrid models
Kumar, Manish; Thenmozhi, M. - In: International journal of banking, accounting and finance 5 (2013/2014) 3, pp. 284-308
Persistent link: https://www.econbiz.de/10011474500
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Forecasting Nigerian stock market returns using ARIMA and artificial neural network models
Isenahd, Godknows M.; Olubusoye, Olusanya E. - In: CBN journal of applied statistics 5 (2014) 2, pp. 25-48
The study reports empirical evidence that artificial neural network based models are applicable to forecasting of stock … the artificial neural network based models outperformed the ARIMA based model in forecasting future developments of the … can be used as predictors for forecasting future values of the stock market returns given that the returns has memory of …
Persistent link: https://www.econbiz.de/10011488820
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SENSEX price fluctuation forecasting comparison between global indices and companies making it
Sharma, Aviral; Bhatnagar, Vishal; Bansal, Abhay - In: Journal of global information management : an official … 26 (2018) 3, pp. 90-104
Persistent link: https://www.econbiz.de/10011926114
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Optimised hybrid CNN bi-LSTM model for stock price forecasting
Patnaik, Deepti; Rao, N. V. Jagannadha; Padhiari, … - In: International journal of intelligent enterprise 11 (2024) 3, pp. 248-273
Persistent link: https://www.econbiz.de/10015065340
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Optimised hybrid CNN-LSTM model for stock price prediction
Patnaik, Deepti; Rao, N. V. Jagannadha; Padhiari, … - In: International journal of management and decision making … 23 (2024) 4, pp. 438-460
Persistent link: https://www.econbiz.de/10015067129
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Forecasting movement of the Nigerian Stock Exchange All Share index using artificial neural and Bayesian networks
Bola, Adetunji Abigail; Adesola, Aderounmu Ganiyu; … - In: Journal of finance and investment analysis 2 (2013) 1, pp. 41-59
This paper presents a study of Artificial Neural Network (ANN) and Bayesian Network (BN) for use in stock index prediction. The data from Nigerian Stock Exchange (NSE) market are applied as a case study. Based on the rescaled range analysis, the neural network was used to capture the...
Persistent link: https://www.econbiz.de/10009746063
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Comparison of financial models for stock price prediction
Islam, Mohammad Rafiqul; Nguyen, Nguyet - In: Journal of risk and financial management : JRFM 13 (2020) 8/181, pp. 1-19
Time series analysis of daily stock data and building predictive models are complicated. This paper presents a comparative study for stock price prediction using three different methods, namely autoregressive integrated moving average, artificial neural network, and stochastic process-geometric...
Persistent link: https://www.econbiz.de/10012321966
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Volatility analysis of Bitcoin price time series
Pichl, Lukáš; Kaizoji, Taisei - In: Quantitative finance and economics 1 (2017) 4, pp. 474-485
Persistent link: https://www.econbiz.de/10012137891
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Determinants of the index of prices and quotations on the Mexican stock exchange : sensitivity analysis based on artificial neural networks
Valdivia, Stephanie; Morales, Arturo - In: Global journal of business research : GJBR 10 (2016) 2, pp. 27-32
Persistent link: https://www.econbiz.de/10011618334
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Volatility forecasting using hybrid GARCH Neural Network models : the case of the Italian stock market
Kartsonakis Mademlis, Dimitrios; Dritsakis, Nikolaos - In: International journal of economics and financial issues … 11 (2021) 1, pp. 49-60
Persistent link: https://www.econbiz.de/10012436893