Name
Title | ||
|---|---|---|
Application of a case base reasoning based support vector machine for financial time series data forecasting |
Abstract | ||
|---|---|---|
This paper establishes a novel financial time series-forecasting model, by clustering and evolving support vector machine for stocks on S&P 500 in the U.S. This forecasting model integrates a data clustering technique with Case Based Reasoning (CBR) weighted clustering and classification with Support Vector Machine (SVM) to construct a decision-making system based on historical data and technical indexes. The future price of the stock is predicted by this proposed model using technical indexes as input and the forecasting accuracy of the model can also be further improved by dividing the historic data into different clusters. Overall, the results support the new stock price predict model by showing that it can accurately react to the current tendency of the stock price movement from these smaller cases. The hit rate of CBR-SVM model is 93.85% the highest performance among others. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-04020-7_32 | ICIC (2) |
Keywords | Field | DocType |
support vector machine,historical data,historic data,technical index,financial time series data,future price,case base reasoning,forecasting model,cbr-svm model,stock price movement,new stock price,clustering,indexation,prediction model,forecasting,data clustering,classification | Hit rate,Time series,Data mining,Stock price,Computer science,Support vector machine,Artificial intelligence,Stock (geology),Cluster analysis,Case-based reasoning,Finance,Machine learning | Conference |
Volume | ISSN | ISBN |
5755 | 0302-9743 | 3-642-04019-5 |
Citations | PageRank | References |
1 | 0.35 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pei-Chann Chang | 1 | 1752 | 109.32 |
| Chi-Yang Tsai | 2 | 84 | 5.46 |
| Chiung-Hua Huang | 3 | 2 | 1.05 |
| Chin-Yuan Fan | 4 | 473 | 28.27 |