System identification: theory for the user
System identification: theory for the user
Introduction to Grey system theory
The Journal of Grey System
Time series forecasting using neural networks
APL '94 Proceedings of the international conference on APL : the language and its applications: the language and its applications
A rough set approach to attribute generalization in data mining
Information Sciences: an International Journal
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
Hybrid Intelligent Systems for Stock Market Analysis
ICCS '01 Proceedings of the International Conference on Computational Science-Part II
Rough Set Learning of Preferential Attitude in Multi-Criteria Decision Making
ISMIS '93 Proceedings of the 7th International Symposium on Methodologies for Intelligent Systems
Applying rough sets to market timing decisions
Decision Support Systems - Special issue: Data mining for financial decision making
Computers and Operations Research
Computers and Operations Research
A fusion model of HMM, ANN and GA for stock market forecasting
Expert Systems with Applications: An International Journal
A novel approach to fuzzy rough sets based on a fuzzy covering
Information Sciences: an International Journal
Computers & Mathematics with Applications
On the topological properties of fuzzy rough sets
Fuzzy Sets and Systems
Expert Systems with Applications: An International Journal
Grey system theory-based models in time series prediction
Expert Systems with Applications: An International Journal
Hybrid approaches and dimensionality reduction for portfolio selection with cardinality constraints
IEEE Computational Intelligence Magazine
Expert Systems with Applications: An International Journal
Automatica (Journal of IFAC)
A hybrid particle swarm optimization approach for clustering and classification of datasets
Knowledge-Based Systems
Single-step ahead prediction based on the principle of concatenation using grey predictors
Expert Systems with Applications: An International Journal
Determination of the threshold value β of variable precision rough set by fuzzy algorithms
International Journal of Approximate Reasoning
Information Technology and Management
An accurate signal estimator using a novel smart adaptive grey model SAGM(1,1)
Expert Systems with Applications: An International Journal
WSEAS Transactions on Information Science and Applications
Memory performance prediction of web server applications based on grey system theory
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
An approach to portfolio selection using an ARX predictor for securities' risk and return
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
In this study, the moving average autoregressive exogenous (ARX) prediction model is combined with grey systems theory and rough set (RS) theory to create an automatic stock market forecasting and portfolio selection mechanism. In the proposed approach, financial data are collected automatically every quarter and are input to an ARX prediction model to forecast the future trends of the collected data over the next quarter or half-year period. The forecast data is then reduced using a GM(1,N) model, clustered using a K-means clustering algorithm and then supplied to a RS classification module which selects appropriate investment stocks by applying a set of decision-making rules. Finally, a grey relational analysis technique is employed to specify an appropriate weighting of the selected stocks such that the portfolio's rate of return is maximized. The validity of the proposed approach is demonstrated using electronic stock data extracted from the financial database maintained by the Taiwan Economic Journal (TEJ). The predictive ability and portfolio results obtained using the proposed hybrid model are compared with those of a GM(1,1) prediction method. It is found that the hybrid method not only has a greater forecasting accuracy than the GM(1,1) method, but also yields a greater rate of return on the selected stocks.