A new adaptive network-based fuzzy inference system with adaptive adjustment rules for stock market volatility forecasting

作者：Tan, Lijun; Wang, Shiheng; Wang, Ke^*

来源：Information Processing Letters, 2017, 127: 32-36.

DOI：10.1016/j.ipl.2017.06.012

• Algorithms
• Stock volatility
• Adaptive Network-Based Fuzzy Inference System (ANFIS)
• Fruit Fly Optimization Algorithm (FDA)
• Shanghai A-share stocks

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.

• 出版日期2017-11
• 单位上海大学