Pratiti Mishra, Sumanjit Das , Mrs. Sumati Baral
Analysis and prediction of stock market is very interesting as this helps the financial experts in decision making and in turn profit making. In this paper an Adaptive Neuro-Fuzzy Inference System (ANFIS) model is initially considered for stock market prediction and its result is compared. The substance of the design of Adaptive Neuro-Fuzzy Inference System (ANFIS) can be seen as an optimization problem to find the best parameters with minimal error function. This proposed scheme proposes a combination of the Firefly Algorithm and Adaptive Neuro-Fuzzy Inference System. The fuzzy neural network model will be trained by the Firefly Algorithm, and applied to predict stock prices in the Vietnam Stock Market. The experiments will compare performance between the proposed system and ANFIS trained by the Hybrid Algorithm, Back Propagation and Particle Swarm Optimization (PSO). The experimental results show that the system has reasonable efficient performance. In this thesis Adaptive Neuro-Fuzzy Inference System (ANFIS) model is initially considered for stock market prediction and its result is compared. These techniques were tested with published stock market data of National Stock Exchange of India Ltd. for validation.
Anfis, Soft Computing, Prediction, Stock Market.