Presenting a combinative model based on Learning Classifier Systems, Rough Set Theory and GA for predicting the value of stocks

چکیده مقاله

Investment has played an important role in the economic development of the country. The importance of this factor and its role can be clearly seen in the country with a capitalist system. Stock is, without a doubt, an important factor in order to gain small investments and to use them in greater growth of a company. Investors expect people to achieve their expected profits. So the most important thing in this context is to buy a share with a lower price and to sell it with a higher price. The stock market has nonlinear and chaotic systems that rely on politics, economics and psychology and this has caused various methods of predicting values of stocks such as neural networks and fuzzy anticipations and genetic algorithms to arise. This study presents an innovative way to predict the value of stocks including LCS, RST and GA algorithms.Investment has played an important role in the economic development of the country. The importance of this factor and its role can be clearly seen in the country with a capitalist system. Stock is, without a doubt, an important factor in order to gain small investments and to use them in greater growth of a company. Investors expect people to achieve their expected profits. So the most important thing in this context is to buy a share with a lower price and to sell it with a higher price. The stock market has nonlinear and chaotic systems that rely on politics, economics and psychology and this has caused various methods of predicting values of stocks such as neural networks and fuzzy anticipations and genetic algorithms to arise. This study presents an innovative way to predict the value of stocks including LCS, RST and GA algorithms.

دریافت لینک دانلود مقاله