Name
Title | ||
|---|---|---|
Personalised modelling for multiple time-series data prediction: a preliminary investigation in Asia Pacific stock market indexes movement |
Abstract | ||
|---|---|---|
The behaviour of multiple stock markets can be described within the framework of complex dynamic systems (CDS). Using a global model with the Kalman Filter we are able to extract the dynamic interaction network (DIN) of these markets. The model was shown to successfully capture interactions between stock markets in the long term. In this study we investigate the effectiveness of two different personalised modelling approaches to multiple stock market prediction. Preliminary results from this study show that the personalised modelling approach when applied to the rate of change of the stock market index is better able to capture recurring trends that tend to occur with stock market data. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-642-02490-0_150 | ICONIP (1) |
Keywords | Field | DocType |
stock market data,preliminary investigation,dynamic interaction network,global model,indexes movement,complex dynamic system,different personalised modelling approach,asia pacific stock market,stock market index,multiple stock market prediction,personalised modelling,multiple time-series data prediction,multiple stock market,stock market,personalised modelling approach,kalman filter,rate of change,indexation,interaction network | Econometrics,Time series,Momentum (technical analysis),Computer science,Stock market index,Complex dynamic systems,Kalman filter,Interaction network,Artificial intelligence,Stock market,Stock market prediction,Machine learning | Conference |
Volume | ISSN | ISBN |
5506 | 0302-9743 | 3-642-02489-0 |
Citations | PageRank | References |
2 | 0.36 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Harya Widiputra | 1 | 32 | 4.12 |
| Russel Pears | 2 | 205 | 27.00 |
| Nikola K Kasabov | 3 | 3645 | 290.73 |