Using neural networks to forecast the systematic risk of stocks
Article Abstract:
Seven traditional models based on regressions, averages, etc., for forecasting a stock's systematic risk, were compared with two neural network models. The financial statements of 67 German companies from 1967 to 1986 were used as data. While the inclusion of fundamental variables together with the previous year's beta into the forecast model gave the best results for the traditional procedures, the general regression neural network with the previous year's beta as the only input variable (G1) functioned better than the G2 network using fundamental variables.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 1996
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Sequential buying policies
Article Abstract:
A dynamic model is used to illustrate a purchasing department problem. The decision maker must purchase a certain amount of a particular product at the lowest price during specific time periods. The purchasing department manager must decide whether to pay a fee to search for a new source of the product, realizing that the price established by the manager could be rejected.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 2000
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Application of SVM and ANN for image retrieval
Article Abstract:
A new scaling and rotation invariant encoding scheme for image retrieval is developed using support vector machines and artificial neural networks.
Publication Name: European Journal of Operational Research
Subject: Business, international
ISSN: 0377-2217
Year: 2006
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