Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
An adaptive recurrent fuzzy system for nonlinear identification
Applied Soft Computing
Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems
Information Sciences: an International Journal
A fuzzy logic-based computational recognition-primed decision model
Information Sciences: an International Journal
A neural network ensemble method with jittered training data for time series forecasting
Information Sciences: an International Journal
Adaptive signal processing of asset price dynamics with predictability analysis
Information Sciences: an International Journal
Intelligent Threshhold Garch Model Applied to Stock Market of Transmissions that Volatility
ICCIT '07 Proceedings of the 2007 International Conference on Convergence Information Technology
Hybridization of intelligent techniques and ARIMA models for time series prediction
Fuzzy Sets and Systems
Numerical solution of a system of fuzzy polynomials by fuzzy neural network
Information Sciences: an International Journal
Prediction of uncertain structural responses using fuzzy time series
Computers and Structures
Adaptive controller with fuzzy rules emulated structure and its applications
Engineering Applications of Artificial Intelligence
Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons
Information Sciences: an International Journal
Two-Mode Adaptive Fuzzy Control With Approximation Error Estimator
IEEE Transactions on Fuzzy Systems
Multi-variable fuzzy forecasting based on fuzzy clustering and fuzzy rule interpolation techniques
Information Sciences: an International Journal
Information Sciences: an International Journal
On the robustness of Type-1 and Interval Type-2 fuzzy logic systems in modeling
Information Sciences: an International Journal
Hybrid Kansei-SOM model using risk management and company assessment for stock trading
Information Sciences: an International Journal
Identification of stock market forces in the system adaptation framework
Information Sciences: an International Journal
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In this paper, we derive a new class of flexible threshold asymmetric Generalized Autoregression Conditional Heteroskedasticity (GARCH) models. We use this tool for analysis and modeling of the properties that are apparent in many financial time series. In general, the transmission of volatility in the stock market is time-varying, nonlinear, and asymmetric with respect to both positive and negative results. Given this fact, we adopt the method of fuzzy logic systems to modify the threshold values for an asymmetric GARCH model. Our simulations use stock market data from the Taiwan weighted index (Taiwan), the Nikkei 225 index (Japan), and the Hang Seng index (Hong Kong) to illustrate the performance of our proposed method. From the simulation results, we have determined that the forecasting of volatility performance is significantly improved if the leverage effect of clustering is considered along with the use of expert knowledge enabled by the GARCH model.