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A dynamic scenario-driven technique for stock price prediction and trading

Thesia, Yash; Oza, Vidhey; Thakkar, Priyank - In: Journal of forecasting 41 (2022) 3, pp. 653-674

Persistent link: https://www.econbiz.de/10013166175

Forecasting of future stock prices using neural networks and genetic algorithms

Mitilineos, Stelios A.; Artikis, Panayiotis G. - In: International journal of decision sciences, risk and … 7 (2017) 1/2, pp. 2-25

Persistent link: https://www.econbiz.de/10011797297

Technical analysis forecasting and evaluation of stock markets : the probabilistic recovery neural network approach

Maniatopoulos, Andreas; Gazis, Alexandros; Mitianoudis, … - In: International journal of economics and business … 25 (2023) 1, pp. 64-100

Persistent link: https://www.econbiz.de/10014309021

Development of stock market trend prediction system using multiple regression

Asghar, Muhammad Zubair; Rahman, Fazal; Kundi, Fazal Masud - In: Computational and mathematical organization theory 25 (2019) 3, pp. 271-301

Persistent link: https://www.econbiz.de/10012098937

Zur Prognose des Deutschen Aktienindex DAX mit Hilfe von Neuro-Fuzzy-Systemen

Dichtl, Hubert - 1995 - 1. Aufl

Persistent link: https://www.econbiz.de/10000603402

Support vector regression based GARCH model with application to forecasting volatility of financial returns

Chen, Shiyi (contributor); Jeong, Kiho (contributor); … - 2008

In recent years support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving...