Survey on combined swarm intelligence and ANN for optimized daily stock market price

Abstract

Swarm intelligence (SI) is powerful, newly emerged domain belongs to the field of Artificial Intelligence. The SI is inspired from the behavior of biological entities such as honey bee, fireflies, bat, cuckoo, ant etc. The basic idea of SI is that, the collective behavior of agents with a very limited set of rules. In recent SI is applied in various kind of application including appropriate stock market price movement. This paper makes survey of the use of SI in a stock market application. The paper initially describes the details of a stock market, SI and its various types of algorithm and finally describes some recent SI algorithm based approaches for stock market prediction. From this survey, we found that to improve the efficiency of SI and make optimized results, SI is combined with other approaches like Artificial Neural Network (ANN), Machine Learning ML etc. We found that the combination of SI and ANN produce more accurate and optimized results for stock price prediction than the combination of SI and machine learning. Finally paper provides the comparative analysis of recent techniques on the basis of a type of SI used, the algorithm with which SI is combined, comparable algorithm, the dataset used for performance evaluation, its advantages and future trend for each technique. Future trend will be used for further research in the field of SI and stock market applications.