Journal ArticleDOI
Modeling the dynamic interdependence of major european stock markets
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In this paper, the authors provide evidence on the evolution of contemporaneous and lead/lag relationships among eight national stock markets and suggest that regional interdependencies have grown over time.Abstract:
The growing globalization of financial markets has been accompanied by a growing body of empirical research attempting to describe and quantify the ways in which financial markets within and across countries interact. Better understanding of the nature of cross market linkages and interactions could be of help to investors and policy makers alike. With respect to policy, aspects of market interaction that promote efficiency could, in principle, be facilitated whereas, those with undesirable side effects could be controlled. Likewise, investment and hedging strategies could be more effective if the nature of market interactions were better understood. The extant literature provides convincing evidence that financial markets do influence each other. For example, Koch and Koch (1991) provide evidence on the evolution of contemporaneous and lead/lag relationships among eight national stock markets. They suggest that regional interdependencies have grown over time. Becker, Finnerty, and Gupta (1990) show that information generated in the US stock market could be used to trade profitably in Japan, contrary to the market efficiency hypothesis. However, when transaction costs and transfer taxes are included into the analysis, excess profits vanish. Eun and Shim (1989) document that markets around the globe respond to innovations in a way that is consistent with the notion of informationally efficient international stock markets. King and Wadhwani (1990) use a rational expectations model with asymmetric information to test for 'contagion effects' i.e., the notion that valuation mistakes in one market can be transmitted to other markets.' More recent papers extend the scope of market interaction to include second moment linkages. This extension allows testing ofthe hypothesis that information generated in a given market at time / is useful in terms of predicting the conditional mean and variance in another market at time t+l. Hamao, Masulis and Ng (1990) examine first and second moment interdependencies in the three major stock markets (New York, Tokyo, and London) using univariate GARCH models. For the period after the October 1987 worldwide stock market crash, they find that innovations coming fromread more
Citations
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Journal ArticleDOI
Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns
TL;DR: This paper proposed a new generalized autoregressive conditionally heteroskedastic (GARCH) process, the asymmetric generalized dynamic conditional correlation (AG-DCC) model, which allows for series-specific news impact and smoothing parameters and permits conditional asymmetries in correlation dynamics.
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Volatility Spillover Effects in European Equity Markets
TL;DR: In this article, the authors quantified the magnitude and time-varying nature of volatility spillovers from the aggregate European (EU) and US market to 13 local European equity markets.
Journal ArticleDOI
Multivariate GARCH Modeling of Exchange Rate Volatility Transmission in the European Monetary System
Colm Kearney,Andrew J. Patton +1 more
TL;DR: In this article, a series of 3-, 4- and 5-variable multivariate GARCH models of exchange rate volatility transmission across the important European Monetary System (EMS) currencies including the French franc, the German mark, the Italian lira, and the European Currency Unit were constructed.
Journal ArticleDOI
Interrelationships among regional stock indices
TL;DR: In this paper, the authors investigated the short-run and long-run relationships among stock indices of the US, Europe, Asia, Latin America, and Eastern Europe-Middle East for the pre-Asian crisis and for the crisis period.
Journal ArticleDOI
Correlation in price changes and volatility of major Latin American stock markets
A. Christofi,A. Pericli +1 more
TL;DR: In this article, the authors investigate the short run dynamics between five major Latin American stock markets (Argentina, Brazil, Chile, Colombia and Mexico) and estimate the joint distribution of stock returns as a vector autoregression (VAR) with innovations following an exponential GARCH process.
References
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Journal ArticleDOI
Conditional heteroskedasticity in asset returns: a new approach
TL;DR: In this article, an exponential ARCH model is proposed to study volatility changes and the risk premium on the CRSP Value-Weighted Market Index from 1962 to 1987, which is an improvement over the widely-used GARCH model.
Journal ArticleDOI
Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model.
TL;DR: In this article, a multivariate time series model with time varying conditional variances and covariances but with constant conditional correlations is proposed, which is readily interpreted as an extension of the seemingly unrelated regression (SUR) model allowing for heteroskedasticity.
Journal ArticleDOI
Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test
Andrew W. Lo,A. Craig MacKinlay +1 more
TL;DR: In this article, the random walk model is strongly rejected for the entire sampleperiod (1962-1985) and for all subperiods for a variety of aggregate returns indexes and size-sorted porfolios.
Journal ArticleDOI
Permanent and Temporary Components of Stock Prices
Eugene F. Fama,Kenneth R. French +1 more
TL;DR: This article found that a slowly mean-reverting component of stock prices tends to induce negative autocorrelation in returns, which is weak for the daily and weekly holding periods common in market efficiency tests but stronger for long-horizon returns.
Posted Content
Stock Market Prices Do Not Follow Random Walks: Evidence From a Simple Specification Test
Andrew W. Lo,A. Craig MacKinlay +1 more
TL;DR: In this paper, the random walk model is strongly rejected for the entire sample period (1962-1985) and for all sub-periods for a variety of aggregate returns indexes and size-sorted portfolios.