Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/174442 
Year of Publication: 
2016
Series/Report no.: 
Working Papers No. 2016-12
Publisher: 
Banco de México, Ciudad de México
Abstract: 
This paper proposes a systemic risk index based on Functional Data Analysis (FDA), overcoming salient shortcomings of standard methodologies related to data usage, data sparseness, and high dimensionality issues. Using Mexican data, a set of systemic risk indexes are constructed and we show that the proposed functional index captures new information, and through simulations, that it outperforms previous methods when the indicators become increasingly nonlinear. Finally, we show which indexes serve as complements, and which are the best early warning indicators.
Subjects: 
Systemic Risk
Functional Data Analysis
Dimensionality Reduction
Signal Informativeness
JEL: 
G01
G10
G17
G18
Document Type: 
Working Paper
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