AN INVESTIGATION OF THE HYBRID FORECASTING MODELS FOR STOCK PRICE VARIATION IN TAIWAN

45 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Adapted Neuro-Fuzzy Inference System on indirect approach TSK fuzzy rule base for stock market analysis (2010, background): “As Chang et al. (2004) says, seven technical indexes are illustrated as shown in Table 3.1.”
Fuzzy Delphi and back-propagation model for sales forecasting in PCB industry (2006, methodology): “Keywords: Sale forecasting; Fuzzy theory; Neural network; Fuzzy back-propagation network”
A Hybrid System Integrating a Wavelet and TSK Fuzzy Rules for Stock Price Forecasting (2008, unknown): “In this approach, ANNs have been employed as the predictor, see, e.g., [5], [10], [14], [16], [17], [27], [32], [37], [42], [48], [63], and [64].”
Forecasting East Asian Indices Futures via a Novel Hybrid of Wavelet-PCA Denoising and Artificial Neural Network Models (2016, background): “[21] believe ANNs are limited due to the complexities of the chaotic behaviors associated with financial markets, the multivariate signals emitted by the time series, the risk of model over-fitting, and the noise in time series.”
A TSK type fuzzy rule based system for stock price prediction (2008, methodology): “However by using a better prediction model to forecast the future price variation of a stock, the systematic risk can be minimized if it is not totally eliminated.”