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| Author | : Martin Martens |
| Publisher | : |
| Total Pages | : 28 |
| Release | : 1999 |
| Genre | : |
| ISBN | : |
| Author | : Martin Martens |
| Publisher | : |
| Total Pages | : 34 |
| Release | : 1999 |
| Genre | : |
| ISBN | : |
The use of close-to-close returns underestimates returns correlation because international stock markets have different trading hours. With the availability of 16:00 (London time) stock market series, we find dynamics of daily correlation and daily covariance, estimated using two non-synchroneity adjustment procedures, to be substantially different from their synchronous counterparts. We find volatility spillovers from the US to the UK and France, and there is also evidence of reverse spillovers which is not documented before. Daily covariance increases during volatile periods. But, unlike previous findings, the increase in daily correlation is prominent only under extremely adverse conditions when a large negative return has been registered.
| Author | : Francois M. Longin |
| Publisher | : |
| Total Pages | : 24 |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
Testing the hypothesis that international equity market correlation increases in volatile times is a difficult exercise and misleading results have often been reported in the past because of a spurious relationship between correlation and volatility. This paper focuses on extreme correlation, that is to say the correlation between returns in either the negative or positive tail of the multivariate distribution. Using ldquo;extreme value theoryrdquo; to model the multivariate distribution tails, we derive the distribution of extreme correlation for a wide class of return distributions. Using monthly data on the five largest stock markets from 1958 to 1996, we reject the null hypothesis of multivariate normality for the negative tail, but not for the positive tail. We also find that correlation is not related to market volatility per se but to the market trend. Correlation increases in bear markets, but not in bull markets.
| Author | : Rita L. D'Ecclesia |
| Publisher | : |
| Total Pages | : 24 |
| Release | : 2008 |
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| ISBN | : |
The interrelationship between international stock markets is becoming a key issue in international portfolio managment and risk measurement. The dynamics of security returns and their risk characteristics have a crucial role in the financial market's therory. Recent empirical studies have tested market efficiency measuring the degree of integration of international financial markets. These studies have shown that international markets react quickly to news but they are volatile and difficult to predict and with a changing correlation structure of security returns among countries.In this paper we analyze the nature of the relationship between the major international stock markets in Canada, Japan, U.K. and the U.S., using the common trends and common cycles approach. We investigate the presence of co-movements trying to detect a long-term stationary component, the common trend, and a short term stationary cyclical component, among international stock markets. The implications on international portfolio management are alos discussed.
| Author | : Lyudmila Grigoryeva |
| Publisher | : |
| Total Pages | : 36 |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
This paper introduces a method based on the use of various linear and nonlinear state space models that uses non-synchronous data to extract global stochastic financial trends (GST). These models are specifically constructed to take advantage of the intraday arrival of closing information coming from different international markets in order to improve the quality of volatility description and forecasting performances. A set of three major asynchronous international stock market indices is used in order to empirically show that this forecasting scheme is capable of significant performance improvements when compared with those obtained with standard models like the dynamic conditional correlation (DCC) family.
| Author | : Rosario N. Mantegna |
| Publisher | : Cambridge University Press |
| Total Pages | : 164 |
| Release | : 1999-11-13 |
| Genre | : Business & Economics |
| ISBN | : 1139431226 |
This book concerns the use of concepts from statistical physics in the description of financial systems. The authors illustrate the scaling concepts used in probability theory, critical phenomena, and fully developed turbulent fluids. These concepts are then applied to financial time series. The authors also present a stochastic model that displays several of the statistical properties observed in empirical data. Statistical physics concepts such as stochastic dynamics, short- and long-range correlations, self-similarity and scaling permit an understanding of the global behaviour of economic systems without first having to work out a detailed microscopic description of the system. Physicists will find the application of statistical physics concepts to economic systems interesting. Economists and workers in the financial world will find useful the presentation of empirical analysis methods and well-formulated theoretical tools that might help describe systems composed of a huge number of interacting subsystems.
| Author | : Saif Siddiqui |
| Publisher | : |
| Total Pages | : 24 |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
In the background of globalization, economic assimilation and integration among countries and their financial markets is evident. The interdependency among major world stock markets has also increased. This paper examines the relationships between selected Asian and US stock markets. It covers the period, 19/10/1999 to 25/04/2008, using daily closing data of twelve stock markets to investigate. The research methodology employed includes testing for stationarity, implementation of the Granger Causality test and Johansen Cointegration test. Stock markets under study are found to be integrated. The degree of correlation between all the markets, but Japan, varies between moderate to high. The findings also prove that stock markets returns are not normally distributed. The time series understudy also show non-stationary patterns. Furthermore, it provided that no stock market is playing a very dominant role in influencing other markets. The US influence is not as noticeable as in the earlier researches. Comparing this study with previous ones, It can be said that stock market integration in relation with US markets is time varying. The results of the present paper are useful for investors in management of their existing international portfolios.
| Author | : Roberto Moro Visconti |
| Publisher | : |
| Total Pages | : 47 |
| Release | : 1994 |
| Genre | : |
| ISBN | : |
| Author | : Hyung-Suk Choi |
| Publisher | : |
| Total Pages | : 19 |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
The main objective of this paper is to investigate the international linkages among local, country-specific stock market factors in order to better understand the dependence structure of increasingly integrated world financial markets. The seeming discordance between Fama and French (1998) and Griffin (2002) regarding the multi-factor model in the international stock markets motivates us to study the international relationship among local factors. With the individual stock data from the six major developed countries in the international stock market, we compose daily returns to the Fama-French three factors (i.e. market, size, and value) and the momentum factor over the period from January 2000 to June 2010. We investigate the international linkages among local stock market factors, focusing on their equilibrium relationship in the integrated world financial market. The cointegration analysis indicates that local factor indices, constructed from the cumulative factor returns, are cointegrated for each of the four factor classes. Thus, we conclude that local factors are globally bound to each other through a long-run equilibrium relationship and that although stock market factors may be local, rather than global, individual stock returns are driven by common global stochastic trends.
| Author | : Stuart Hyde |
| Publisher | : |
| Total Pages | : 34 |
| Release | : 2008 |
| Genre | : |
| ISBN | : |
This paper investigates the correlation dynamics in the equity markets of 13 Asia-Pacific countries, Europe and the US using the asymmetric dynamic conditional correlation GARCH model (AG-DCC-GARCH) introduced by Cappiello, Engle and Sheppard (2006). We find significant variation in correlation between markets through time. Stocks exhibit asymmetries in conditional correlations in addition to conditional volatility. Yet asymmetry is less apparent in less integrated markets. The Asian crisis acts as a structural break, with correlations increasing markedly between crisis countries during this period though the bear market in the early 2000s is a more significant event for correlations with developed markets. Our findings also provide further evidence consistent with increasing global market integration. The documented asymmetries and correlation dynamics have important implications for international portfolio diversification and asset allocation.
