| Research Title |
SET Index Forecast Using Bayesian Belief Networks |
| Date of Distribution |
30 January 2020 |
| Conference |
| Title of the Conference |
the 2020 - 12th International Conference on Knowledge and Smart Technology (KST) |
| Organiser |
KST Research Lab, Faculty of Informatics, Burapha University |
| Conference Place |
โรงแรม Amari Pattaya |
| Province/State |
ชลบุรี |
| Conference Date |
29 January 2020 |
| To |
1 February 2020 |
| Proceeding Paper |
| Volume |
- |
| Issue |
- |
| Page |
30-35 |
| Editors/edition/publisher |
- |
| Abstract |
Statistical time-series forecasting faces the problem of accuracy if the data deviate from a normal distribution. In literature, stock indexes are not of normal distribution. This paper presents the Bayesian Belief Network (BBN) in forecasting the Stock Exchange of Thailand (SET Index) in comparison with statistical forecasting techniques. To model BBN, SET index distribution is discretized using a number of clustering techniques for comparison. Then, BBN is constructed using the transforming data in a P/E ratio via the K2 algorithm based on the training dataset gathered from January 2013 through July 2019. For performance evaluation, the proposed model was compared with the statistical forecasting algorithms using RMSE and the correlation coefficient (CC). The results show that the proposed BBN with a particular clustering algorithm provided better results than the statistical forecasting techniques. |
| Author |
|
| Peer Review Status |
มีผู้ประเมินอิสระ |
| Level of Conference |
นานาชาติ |
| Type of Proceeding |
Full paper |
| Type of Presentation |
Oral |
| Part of thesis |
true |
| Presentation awarding |
false |
| Attach file |
|
| Citation |
0
|
|
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Publication
Journal Publication
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