Macro News and Commodity Returns

• Author: Guglielmo Maria Caporale,Nicola Spagnolo,Fabio Spagnolo
• Date: 01 January 2017
• Published date: 01 January 2017
• DOI: http://doi.org/10.1002/ijfe.1568

INTERNATIONAL JOURNAL OF FINANCE AND ECONOMICS

Int. J. Fin. Econ.22: 68–80 (2017)

Published online 11 October 2016 in Wiley Online Library

(wileyonlinelibrary.com). DOI: 10.1002/ijfe.1568

MACRO NEWS AND COMMODITY RETURNS

GUGLIELMO MARIA CAPORALE,, FABIO SPAGNOLO and NICOLA SPAGNOLO

Department of Economics and Finance, Brunel University London, Uxbridge, UK

ABSTRACT

This paper adopts a vector autoregression-generalized autoregressive conditional heteroscedasticity approach to model the

dynamic linkages between both mean and variance of macro news and commodity returns (Gold, Corn, Wheat, Soybeans,Silver,

Platinum, Palladium, Copper, Aluminium and Crude Oil) over the period 01/01/2001–26/09/2014. The chosen specification

also controls for the effect of the exchange rate. The results can be summarized as follows. Mean spillovers running from news

to commodity returns are positive with the exception of Gold and Silver.Volatility spillovers are bigger in size and affect most

commodity returns. Both first-moment and second-moment linkages are stronger in the post-September 2008 period. Overall,

our findings confirm that commodities, despite not being financial assets, are sensitive to macro news (especially their volatility)

and also suggest that the global financial crisis has strengthened such linkages. Copyright © 2016 John Wiley & Sons, Ltd.

Received 17 September 2015; Revised 11 April 2016; Accepted 13 September 2016

JEL CODE: C32; F36; G15

KEY WORDS: macro news; commodity prices; VAR-GARCH model

1. INTRODUCTION

The existing literature on the effects of macro news mainly focuses on the stock and bond markets and typically

considers two sources of news effects: scheduled macroeconomic announcements that do not correspond to agents’

expectations (the announcement effect) and unscheduled announcements (the surprise effect). Most studies analyse

the former, calculating the difference between news releases and their expected value, and then defining positive

and negative news accordingly (Kocendaand Hanousek, 2011, and Hanousek et al., 2009). Stock prices have been

shown to be affected by news about monetary variables such as money growth and interest rates (e.g. Chen, 1991;

Cornell, 1983; Pearce and Roley, 1983, 1985), and in some cases also by real-sector news (e.g. McQueen and

Roley, 1993, and Boyd et al., 2005). Birz and Lott (2011) use newspaperheadlines and also find that news on GDP

and unemployment affect stock returns. Caporale et al. (2014a) consider both mean and volatility spillovers in the

case of the euro area.

Various studies have also been carried out for bond markets. For instance, Gurkaynak et al. (2005) show that

long-term interest rates respond to the unexpected component of macro and monetary news releases, Balduzzi et al.

(2001) and Andersen et al. (2005) find effects on US Treasury bond futures contracts, and Brenner et al. (2009) on

bond return volatility. Beetsma et al. (2013) examine the impact of newson interest rate spreads vis-à-vis Germany

in various countries in the euro area, and Caporale et al. (2014b) provide evidence of dynamic linkages in both first

and second moments.

Fewer studies have examined the effectsof macro news on commodity prices. Despite not being financial assets,

the latter have been shown to be affected by variables such as interest rates (Frankel, 2008) and the US dollar

exchange rate, both of which are known to respond to news announcements. Frankel and Hardouvelis (1985)

provide evidence of a statistically significant response to US money supply announcements; effects of macro news

on various commodity prices are also found by Cai et al. (2001), Hess et al. (2008), Kilian and Vega (2008);

Correspondence to: Guglielmo Maria Caporale, Department of Economics and Finance, Brunel University London, Uxbridge, UK.

E-mail:Guglielmo-Maria.Caporale@brunel.ac.uk

Copyright © 2016 John Wiley & Sons, Ltd.