Learning smooth graphs with sparse temporal variations to explore long-term financial trends

Cécile Bastidon (), Myriam Bontonou (), Pierre Borgnat (), Pablo Jensen (), Patrice Abry () and Antoine Parent
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Myriam Bontonou: LBMC UMR 5239 - Laboratoire de biologie et modélisation de la cellule - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - INSERM - Institut National de la Santé et de la Recherche Médicale - CNRS - Centre National de la Recherche Scientifique, Phys-ENS - Laboratoire de Physique de l'ENS Lyon - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - Université de Lyon - CNRS - Centre National de la Recherche Scientifique
Pierre Borgnat: Phys-ENS - Laboratoire de Physique de l'ENS Lyon - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - Université de Lyon - CNRS - Centre National de la Recherche Scientifique
Pablo Jensen: Phys-ENS - Laboratoire de Physique de l'ENS Lyon - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - Université de Lyon - CNRS - Centre National de la Recherche Scientifique
Patrice Abry: Phys-ENS - Laboratoire de Physique de l'ENS Lyon - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - Université de Lyon - CNRS - Centre National de la Recherche Scientifique

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Abstract: The return of inflation raises the issues of assessing cross-dependencies in the interest rates of long-term government bonds. Learning cross-dependencies directly from data is framed here as a graph learning problem that requires to address the issues of bond rates heterogeneous and nonstationary evolutions, with sharp changes along time and across countries, and of managing missing samples. As a first contribution, the present work devises a data driven time-dependent graph for bonds markets, specifically based on risk premia. As a second contribution, it shows the relevance of such constructions when applied to a broad database of 29 countries over 6 decades (1960-2020), that includes the high inflation episode of the 1970s.

Date: 2024-08-25
New Economics Papers: this item is included in nep-his
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Published in 32st European Signal Processing Conference (EUSIPCO), EURASIP, Aug 2024, Lyon, France

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