Connectedness between G10 currencies: Searching for the causal structure

Timo Bettendorf and Reinhold Heinlein

No 06/2019, Discussion Papers from Deutsche Bundesbank

Abstract: This paper presents a new approach for modelling the connectedness between asset returns. We adapt the measure of Diebold and Y¸lmaz (2014), which is based on the forecast error variance decomposition of a VAR model. However, their connectedness measure hinges on critical assumptions with regard to the variance-covariance matrix of the error terms. We propose to use a more agnostic empirical approach, based on a machine learning algorithm, to identify the contemporaneous structure. In a Monte Carlo study we compare the different connectedness measures and discuss their advantages and disadvantages. In an empirical application we analyse the connectedness between the G10 currencies. Our results suggest that the US dollar as well as the Norwegian krone are the most independent currencies in our sample. By contrast, the Swiss franc and New Zealand dollar have a negligible impact on other currencies. Moreover, a cluster analysis suggests that the currencies can be divided into three groups, which we classify as: commodity currencies, European currencies and safe haven/carry trade financing currencies.

Keywords: connectedness; networks; graph theory; vector autoregression; exchange rates (search for similar items in EconPapers)
JEL-codes: C32 C51 F31 (search for similar items in EconPapers)
Date: 2019
New Economics Papers: this item is included in nep-cmp and nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/192934/1/1049244249.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:bubdps:062019

Access Statistics for this paper

More papers in Discussion Papers from Deutsche Bundesbank Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().