Pitfalls in VAR Based Return Decompositions: A Clarification

Shorter and revised version published in: Journal of Banking & Finance, Vol. 36, Nr. 5, 2012, s. 1255–1265.

34 Pages Posted: 23 Feb 2010 Last revised: 28 Feb 2013

See all articles by Tom Engsted

Tom Engsted

University of Aarhus - CREATES

Thomas Quistgaard Pedersen

Aarhus University - CREATES

Carsten Tanggaard

affiliation not provided to SSRN

Date Written: September 27, 2010

Abstract

We analyze the pitfalls involved in VAR based return decompositions. First, we show that recent criticism of such decompositions is misplaced and builds on invalid VAR models and erroneous interpretations. Second, we explain the requirements needed for VAR decompositions to be valid. A crucial - but often neglected - requirement is that the asset price needs to be included as a state variable in the VAR. Finally, we clarify the intriguing issue of the role of the residual component in return decompositions. In a properly specified VAR, it makes no difference whether return news and cash flow news are both computed directly or one of them is backed out as a residual.

Keywords: Return variance decomposition, news components, VAR model, information set, predictive variables, redundant models

JEL Classification: C32, G12, G17

Suggested Citation

Engsted, Tom and Pedersen, Thomas Quistgaard and Tanggaard, Carsten, Pitfalls in VAR Based Return Decompositions: A Clarification (September 27, 2010). Shorter and revised version published in: Journal of Banking & Finance, Vol. 36, Nr. 5, 2012, s. 1255–1265.. Available at SSRN: https://ssrn.com/abstract=1557591 or http://dx.doi.org/10.2139/ssrn.1557591

Tom Engsted (Contact Author)

University of Aarhus - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Thomas Quistgaard Pedersen

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Carsten Tanggaard

affiliation not provided to SSRN

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