Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4950866 | Information Processing Letters | 2017 | 8 Pages |
Abstract
Forecasting stock volatility is crucial to many fundamental problems of financial field, such as risk management, asset pricing and asset allocation etc. This paper proposes a new Adaptive Network-Based Fuzzy Inference System (ANFIS) which adaptively adjusts fuzzy inference rules by using Fruit Fly Optimization Algorithm (FOA). Empirical analysis is made on the Shanghai A-share sample stocks. Compared with ANFIS, the experimental results reveal that this new model can accurately and successfully forecast the sample stocks' volatility.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Lijun Tan, Shiheng Wang, Ke Wang,