Media Content And Sovereign Credit Risk
Imperial College Business School
Nina Mara Gotthelf
University of Zurich – Department of Banking and Finance
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University of Zurich – Department of Banking and Finance
Imperial College London
June 9, 2016
We explore the impact of media content on sovereign credit risk. Our measure of media tone is extracted from the Thomson Reuters News Analytics database. As a proxy for sovereign credit risk we consider Credit Default Swap (CDS) spreads, which are decomposed into their risk premium and default risk components. We find that media tone explains and predicts CDS returns and is a mixture of noise and information. Its effect on risk premium induce a temporary change in investors’ appetite for credit risk exposure whereas its impact on the default component lead to reassessments of the fundamentals of sovereign economies. This is consistent with prevailing theories of investor over- and under reaction.
Media Content And Sovereign Credit Risk – Introduction
Does the linguistic content of news items impact sovereign credit risk? Does it improve our understanding of countries’ fundamentals? Does it proxy for investor sentiment? We investigate these questions by using an extensive sovereign credit default swap (CDS) dataset and the ratings of news content (i.e. sentiment) from Thomson Reuters News Analytics (TRNA). We consider sovereign CDS contracts as a proxy for country specific credit risk. These represent an insurance contract against sovereign default or restructuring events and are generally more liquid than the underlying bond. In the TRNA database news items are rated in terms of sentiment (positive or negative) in real time using a highly sophisticated neural network which provides an improvement over traditional approaches (such as bag-of-words). Furthermore, TRNA reflects a more accurate representation of the news set used by actual investors, as it is a commercial product that is sold directly to subscribers.
Numerous studies have explored sovereign credit risk and its determinants, which include Edwards (1984, 1986); Berg and Sachs (1988); Boehmer and Megginson (1990); Duffie, Pedersen, and Singleton (2003), Longstaff, Pan, Pedersen, and Singleton (2011); Pan and Singleton (2008); Remolona, Scatigna, and Wu (2007); Jeanneret (2013) and Badaoui, Cathcart, and El-Jahel (2013); Monfort and Renne (2013). In particular Longstaff, Pan, Pedersen, and Singleton (2011) highlight the high level of commonality in sovereign credit spreads and find that they are explained along with their components: default risk and risk premium1 by global factors2 to a greater extent than country-specific fundamentals. Coupled with global factors, behavioral measures such as market sentiment have also been found to influence sovereign credit risk (Georgoutsos and Migiakis, 2013; Tang and Yan, 2013). To the best of our knowledge, the impact of media tone (sentiment) on sovereign credit risk has yet to be explored.
The ability of media content to impact equity markets has recently received considerable attention in the literature. In particular, Tetlock (2007) examines how qualitative information is incorporated in aggregate market valuations and Garcia (2013) shows that the predictability of stock returns using news content is concentrated in recessions. Dougal, Engelberg, Garcia, and Christopher (2012) identify a causal relationship between financial reporting and stock market performance. Engelberg and Parsons (2011) find that local media coverage strongly predicts local trading, and that local trading is strongly related to the timing of local reporting. Uhl, Pedersen, and Malitius (2015) find a longer-run effect of news sentiment on equities with weekly data. Tetlock, Saar-Tsechansky, and Macskassy (2008) examine the impact of negative words on individual S&P 500 firms and Hillert, Jacobs, and Muller (2014) find that firms particulary covered by media exhibit stronger momentum and that this effect depends on media tone. Hence, media coverage exacerbates investor biases.
To investigate the role of media in the sovereign CDS market, we first construct a global “news sentiment” variable from TRNA by filtering according to global debt markets news, US news and regional news pertaining to Europe, Latin America and Asia. The motivation for a global “news sentiment” variable is built on results established in the literature which are suggestive of increasing economic integration across countries, growing dependence on global markets and a spill-over effect from the US to other sovereign countries.3 Second, we decompose the CDS spread into risk premium and default risk components for each country using an affine sovereign credit risk model in line with Pan and Singleton (2008) and Longstaff, Pan, Pedersen, and Singleton (2011). This allows for a better understanding of the role of media and helps shed light on whether media tone could convey information about countries’ fundamentals. Finally, we conduct a principal component analysis, fixed effect panel regression and panel vector autoregressive model (VAR). Panel VARs are able to capture the dynamic interdependencies present in the data using a minimal set of restrictions. They also allow impulse response analyses to be constructed in a relatively straightforward way.
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