Using a unique high-frequency futures dataset, we characterize the response of U.S., German and British stock, bond and foreign exchange markets to real-time U.S. macroeconomic news. We find that news produces conditional mean jumps; hence high-frequency stock, bond and exchange rate dynamics are linked to fundamentals. Equity markets, moreover, react differently to news depending on the stage of the business cycle, which explains the low correlation between stock and bond returns when averaged over the cycle. Hence our results qualify earlier work suggesting that bond markets react most strongly to macroeconomic news; in particular, when conditioning on the state of the economy, the equity and foreign exchange markets appear equally responsive. Finally, we also document important contemporaneous links across all markets and countries, even after controlling for the effects of macroeconomic news.
How do markets arrive at prices? There is perhaps no question more central to economics. This paper focuses on price formation in financial markets, where the question looms large: How, if at all, is news about macroeconomic fundamentals incorporated in pricing stocks, bonds and foreign exchange?
Unfortunately, the process of price discovery in financial markets remains poorly understood. Traditional “efficient markets” thinking suggests that asset prices should completely and instantaneously reflect movements in underlying fundamentals. Conversely, others feel that asset prices and fundamentals may be largely and routinely disconnected. Experiences such as the late 1990s U.S. market bubble would seem to support that view, yet simultaneously it seems clear that financial market participants pay a great deal of attention to data on underlying economic fundamentals. The notable difficulty of empirically mapping the links between economic fundamentals and asset prices is indeed striking.
The central price-discovery question has many dimensions and nuances. How quickly, and with what patterns, do adjustments to news occur? Does announcement timing matter? Are the magnitudes of effects similar for “good news” and “bad news,” or, for example, do markets react more vigorously to bad news than to good news? Quite apart from the direct effect of news on assets prices, what is its effect on financial market volatility? Do the effects of news on prices and volatility vary across assets and countries, and what are the links? Are there readily identifiable herd behavior and/or contagion effects? Do news effects vary over the business cycle?
Just as the central question of price discovery has many dimensions and nuances, so too does a full answer. Appropriately then, dozens – perhaps hundreds – of empirical papers chip away at the price discovery question, but most fall short of our goals in one way or another. Some examine the connection between macroeconomic news announcements and subsequent movements in asset prices, but only for a single asset class and country (e.g., Balduzzi et al., 2001, who study the U.S. bond market). Others examine multiple asset classes but only a single country (e.g., Boyd et al., 2005, who study U.S. stock and bond markets). Still others examine multiple countries but only a single asset class (e.g., Andersen et al., 2003b, who study several major U.S. dollar exchange rates).
Now, however, professional attention is turning toward multiple countries and asset classes.1 Our paper is firmly in that tradition. We progress by studying a broad set of countries and asset classes, characterizing the joint response of foreign exchange markets as well as the domestic and foreign stock and bond markets to real-time U.S. macroeconomic news. We simultaneously combine: (1) high-quality and ultra-high frequency asset price data across markets and countries, which allows us to study price movements in (near) continuous time; (2) a very broad set of synchronized survey data on market participants' expectations, which allow us to infer “surprises” or “innovations” when news is announced; and (3) advances in statistical modeling of volatility, which facilitate efficient inference.
We proceed in straightforward fashion: In Section 2 we describe our data. In Section 3 we present our basic results, and in Section 4 we present results obtained using a generalized model specification. We conclude in Section 5.
We have characterized the real-time interactions among U.S., German and British stock, bond and foreign exchange markets in the periods surrounding U.S. macroeconomic news announcements. We found that announcement surprises produce conditional mean jumps; hence high-frequency stock, bond and exchange rate dynamics are linked to fundamentals.
Our results are especially intriguing as regards stock market responses to news, which display distinct state dependence. In particular, bad macroeconomic news has the traditionally-expected negative equity market impact during contractions, but a positive impact during expansions. This explains the small stock market news reaction effect when averaged across expansions and contractions, as reported in the exiting literature. The asymmetric responses manifest themselves in very different stock–bond return correlations across the business cycle. We verify that these distinct correlation patterns are not limited to the period around announcements; rather, they apply generally for trading day returns in expansions and contractions. We conjecture that such real-time correlation measures will be useful for more refined classification of the phase of the business cycle.
Finally, we pursue a generalized estimation approach that documents highly significant contemporaneous cross-market and cross-country linkages, even after controlling for macroeconomic announcement effects. These findings generally point toward important direct spillover effects among foreign and U.S. equity markets, revealed by virtue of our use of synchronous high-frequency futures data that let us observe the interaction of actively-traded financial assets around announcement times.
Among the many possible directions for future work, we are particularly intrigued by the idea of using high-frequency data to quantify the three separate channels of private information, contagion, and public information that link the markets. Several recent studies have highlighted the role of order flow in the price formation process, including Brandt and Kavajecz (2004), Evans and Lyons, 2003 and Evans and Lyons, 2005 and Pasquariello and Vega (2004). It would be interesting to exploit the information in order flow and other liquidity measures in concert with the new statistical procedures and rich high-frequency return and news announcement data employed here to further advance our understanding of the price discovery process and cross-market linkages.
