Decomposing the Global Financial Crisis: A Self-Organizing Time Map

被引：0
|
作者：
Sarlin, Peter [1 ]
机构：
[1] Abo Akad Univ, Dept Informat Technol, Turku Ctr Comp Sci TUCS, FIN-20520 Turku, Finland
来源：
ADVANCES IN KNOWLEDGE-BASED AND INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS | 2012年 / 243卷
关键词：
financial crisis; Self-Organizing Time Map; exploratory temporal structure analysis; structural changes; financial stability surveillance;
D O I：
10.3233/978-1-61499-105-2-798
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A key starting point for financial stability surveillance is understanding past, current and possible future risks and vulnerabilities. Through temporal data and dimensionality reduction, or visual dynamic clustering, this paper aims to presents a holistic view of cross-sectional patterns over time with no explicit dependence on historical data. We propose using in financial stability surveillance the Self-Organizing Time Map (SOTM), a recent adaptation of the Self-Organizing Map for exploratory temporal structure analysis, which disentangles cross-sectional data structures over time. This paper uses the SOTM for decomposing and identifying temporal structural changes in macro-financial data before, during and after the global financial crisis of 2007-2009.
引用
收藏
页码：798 / 806
页数：9
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