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- W1990661506 abstract "The stock market is a highly complex market and an important way to raise funds forinvestors. Investors aim to achieve maximum profit. Thus, the purchase or sale of sharesmust be made on time. To achieve this goal, prediction techniques can be applied to thestock market in order to predict their behavior. There are several techniques that showpromising results for prediction on the stock market, but each one has particularadvantages and limitations. Thus, these techniques require a large number of variables anda complex architecture. This paper describes a new prediction model aiming to raise thechances of the stock’s payback. The proposed model uses a hybrid approach byestablishing a committee of learning machines that combine the advantages of the threetechniques (statistical, neural network and technical indicators) in order to overcome theirrespective limitations." @default.
- W1990661506 created "2016-06-24" @default.
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- W1990661506 date "2013-06-12" @default.
- W1990661506 modified "2023-09-27" @default.
- W1990661506 title "A HYBRID MODEL FOR PREDICTING THE BEHAVIOR OF STOCK MARKET" @default.
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- W1990661506 doi "https://doi.org/10.5748/9788599693094-10contecsi/rf-477" @default.
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