On Stock Market Return Co-Movements: Macroeconomic News, Dispersion of Beliefs, and Contagion

Connolly, Robert A.; Wang, F. Albert

doi:10.2139/ssrn.233924

Cited by 37 publications

(34 citation statements)

References 10 publications

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“…In this setting, I showed that: (i) a portion of the speculators' demand is uninformative, hence consenting trading in equilibrium even in the absence of liquidity shocks z [similarly to Diamond and Verrecchia (1981)] and (ii) speculators' ''impatience'' ð > 0Þ leads to financial contagion in the presence of endowment shocks (e.g., early redemptions by mutual fund investors), regardless of their degree of information heterogeneity. Recent studies by Connolly and Wang (2000) and Schmukler (2000, 2001) provide empirical support for this propagation channel. 15 According to Calvo and Mendoza (2000), this modeling approach is especially relevant for emerging economies, in view of the short history of prices available for their domestic capital markets under financial integration.…”

Section: Equilibriummentioning

confidence: 88%

“…I find this definition appealing because it allows to distinguish contagion from mere interdependence, the propagation of common external shocks (such as changes in oil prices or international interest rates) across countries due to real cross-market 20 Nonetheless, varðP 1 Þ is only a fraction of AE because the order flow is only partially revealing of the speculators' private information. 21 An incomplete list includes Shiller (1989), King and Wadhwani (1990), Rotemberg (1990, 1993), King, Sentana, and Wadhwani (1994), Karolyi and Stulz (1996), Baig and Goldfajn (1999), Bekaert and Harvey (2000), Connolly and Wang (2000), Boyer, Kumagai, and Yuan (2002), Corsetti, Pericoli, and Sbracia (2002), Forbes and Rigobon (2002), Pasquariello (2002, 2005), Kallberg and Pasquariello (2004), Barberis, Shleifer, and Wurgler (2005), Bekaert, Harvey, and Ng, (2005), and Pasquariello (2005).…”

Section: International Financial Contagionmentioning

confidence: 99%

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Imperfect Competition, Information Heterogeneity, and Financial Contagion

Pasquariello

2006

Rev. Financ. Stud.

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This study examines how heterogeneity of private information may induce financial contagion. Using a model of multi-asset trading in which the three main channels of contagion through financial linkages in the literature (correlated information, correlated liquidity, and portfolio rebalancing) are ruled out by construction, I show that financial contagion can still be an equilibrium outcome when speculators receive heterogeneous fundamental information. Risk-neutral speculators trade strategically across many assets to mask their information advantage about one asset. Asymmetric sharing of information among them prevents rational market makers from learning about their individual signals and trades with sufficient accuracy. Incorrect cross-inference about terminal payoffs and contagion ensue. When used to analyze the transmission of shocks across countries, my model suggests that the process of generation and disclosure of information in emerging markets may explain their vulnerability to financial contagion (JEL D82, G14, G15).Many recent financial crises were initiated by episodes of ''local'' turmoil (e.g

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Section: Equilibriummentioning

confidence: 88%

Section: International Financial Contagionmentioning

confidence: 99%

Imperfect Competition, Information Heterogeneity, and Financial Contagion

Pasquariello

2006

Rev. Financ. Stud.

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“…12 As mentioned earlier, it is argued there that the impact of news arrivals on asset prices occurs through any of the following three factors: Expected cash flows from the assets, the appropriate discount rates, and their risk premia. The impact on government bond prices is the least controversial; for example, the general equilibrium model 10 A list of recent contributions includes Shiller (1989), King and Wadhwani (1990), Rotemberg (1990, 1993), Karolyi and Stulz (1996), Connolly and Wang (2000), Barberis et al (2002), Forbes and Rigobon (2002), and Kallberg and Pasquariello (2004). 11 Kyle and Xiong (2001) and Kallberg and Pasquariello (2004) (1986) were the first to explicitly identify an empirical link between several macroeconomic variables and expected stock returns in the context of a multi-factor cross-sectional asset pricing model.…”

Section: (3)mentioning

confidence: 99%

“…Fleming et al (1998) consider the volatility linkages of stocks, bonds, and money market instruments, but do not specifically relate the estimated volatility spillovers to macro news announcements. Connolly and Wang (2000) and Andersen et al (2004) examine the impact of these news only on cross-country linkages, not crossdomestic market linkages, and only among mean asset returns.…”

Section: Introductionmentioning

confidence: 99%

“…Nonetheless, we measure the corresponding market expectations using the thirty-day interest rate futures contract traded on the Chicago Board of Trade (CBOT), since changes in the Fed funds futures rate, an intuitive aggregation of market-wide policy expectations, have been shown to represent more efficient predictors of FOMC's target rate changes. 21 We employ the algorithm devised by Kuttner (2000) to estimate the one-day rate surprise from the one-day change in the spot-month futures rate around FOMC announcements. Yet, because CBOT futures prices are available only from October 3, 1988, we use MMS forecasts for the first three years of the sample.…”

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confidence: 99%

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Financial Markets and the Macroeconomy

Chiarella¹,

Flaschel²,

Franke³

et al. 2009

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The objective of this paper is to provide a deeper insight into the links between financial markets and the real economy. To that end, we study the short-term anticipation and response of U.S. stock, Treasury, and corporate bond markets to the first release of U.S. macroeconomic information. Specifically, we focus on the impact of these announcements not only on the level, but also on the volatility and comovement of those assets' returns. For that purpose, we estimate several extensions of the parsimonious amended GARCH model of Engle (2002) for the excess holding-period returns on seven portfolios of these asset classes. We find that the process of price formation in the U.S. financial markets appears to be driven by fundamentals; yet, "excessive" volatility and comovement play an important role in return dynamics as well. Further, our analysis reveals a statistically and economically significant dichotomy between the reaction of the stock and bond markets to the arrival of unexpected fundamental information. However, we also show that stock and bond returns tend to react to the expected component of these announcements. Overall, the above results often differ from earlier studies where the surprise portion of those releases was not identified, and shed new light on the mechanisms by which information is incorporated into prices.JEL classification: C32; G14

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