International Journal of Management and Applied Science (IJMAS)
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Volume-5,Issue-9  ( Sep, 2019 )
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Statistics report
Oct. 2019
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 67
Paper Published : 4093
No. of Authors : 8411
  Journal Paper




Paper Title :
Stock market index predicti on using machine learning techniques. A case study of bucharest stock exchange

Author :Hakob Grigoryan

Article Citation :Hakob Grigoryan , (2017 ) " Stock market index predicti on using machine learning techniques. A case study of bucharest stock exchange " , International Journal of Management and Applied Science (IJMAS) , pp. 19-22, Volume-3,Issue-8

Abstract : Financial markets are complex systems and their behavior is characterized as non-stationary and volatile. In the presented paper, the potential of the machine learning techniques, in particular, adaptive network-based fuzzy inference system (ANFIS) model and Support Vector Machines (SVM) are investigated in forecasting task of stock market data. The performance of proposed models are evaluated with test data of Bucharest Stock Exchange (BVB) and results obtained are compared in terms of well known evaluation metrics. The comparative analysis leads to the conclusion that both models can be successfully applied to forecast the high-frequency stock data while SVM outperforms the ANFIS model in prediction accuracy. Index Terms— ANFIS, Fuzzy neural network, Support Vector Machines, Time series prediction, stock market

Type : Research paper


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