• TUCS Publication Series
• How to Publish in TUCS Series
• Publication Search
• Publication Graph
• Publication Input
• Publication Input Guide
• JuFo Browser

Probabilistic Modeling of State Transitions on the Self-Organizing Map: Some Temporal Financial Applications

Peter Sarlin, Zhiyuan Yao, Tomas Eklund, Probabilistic Modeling of State Transitions on the Self-Organizing Map: Some Temporal Financial Applications. In: Ralph H. Jr. Sprague (Ed.), Proceedings of the 45th Hawaii International Conference on System Sciences, 1128–1137, IEEE Press, 2012.

Abstract:

Self-organizing maps (SOM) have been commonly used in temporal financial applications. This paper enhances the SOM paradigm for temporal data by presenting a framework for computing, summarizing and visualizing transition probabilities on the SOM. The framework includes computing matrices of node-to-node and node-to-cluster transitions and summarizing maximum state transition. The computations are visualized using feature plane representations. The future state transitions can also be used for finding low- and high-risk profiles as well as for assessing the evolution of probabilities over time, where the cluster centers express the representative financial states while the probability fluctuations represent their variation over time. We demonstrate the usefulness of the framework on two previously presented SOM models for temporal financial analysis: financial benchmarking of banks and monitoring indicators of currency crises.

BibTeX entry:

@INPROCEEDINGS{inpSaYaEk12a,
  title = {Probabilistic Modeling of State Transitions on the Self-Organizing Map: Some Temporal Financial Applications},
  booktitle = {Proceedings of the 45th Hawaii International Conference on System Sciences},
  author = {Sarlin, Peter and Yao, Zhiyuan and Eklund, Tomas},
  editor = {Sprague, Ralph H. Jr.},
  publisher = {IEEE Press},
  pages = {1128–1137},
  year = {2012},
}

Belongs to TUCS Research Unit(s): Data Mining and Knowledge Management Laboratory

Publication Forum rating of this publication: level 1

Edit publication