Common trends and convergence? South East Asian equity markets, 1988–1999

Manning, Neil

doi:10.1016/s0261-5606(01)00038-9

Cited by 106 publications

(59 citation statements)

References 33 publications

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“…The forecast error variance decomposition analysis finds that the degree of exogeneity for all countries indices has been reduced. Manning (2002) employs both the Johansen Maximum Likelihood approach and the Haldane and Hall Kalman Filter technique to examine the co-movement of equity markets in Southeast Asia and taking the U.S. to be the external market at the same time. The two samples analyzed comprise weekly and quarterly information on equity indices and US Dollar series for the US, Hong Kong, Japan, Indonesia, Malaysia, Korea Singapore, Taiwan, the Philippines and Thailand over the period January 1988 to February 1999.…”

Section: Literature Reviews On Asean-5 + 3 Stock Markets Integrationmentioning

confidence: 99%

ASEAN-5 + 3 and US Stock Markets Interdependence Before, During and After Asian Financial Crisis

Royfaizal¹,

Lee²,

Azali³

2009

IJEF

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The issues of international stock markets linkages had been investigated over the time. Since the Asian financial crisis in 1997, many economists are concerned about the relationship between Asian stock markets and others in the world. This paper is conducted to examine the linkages between ASEAN-5+3 namely Malaysia, Singapore, the Philippines, Thailand, Indonesia, China, Japan and Korea and US stock markets. The data consists of weekly stock indices data. The total samples are separated into three subperiods. First period is pre-crisis period spanning from January 1990 to June 1997. Second period is during-crisis period spanning from July 1997 to June 1998. Third period is post-crisis period spanning from July 1998 to May 2007. All the indices applied are expressed in local currencies. The empirical analysis begins with testing the stationarity properties of the data. All the countries are found to be stationary at first difference except for Japan for pre-crisis period. Next, cointegration test is employed to test the long-run stationary relationship among the stock markets. The number of significant cointegrating vector is higher during-crisis compare to other periods whereas the same number of cointegrating vector is found before and after crisis. Granger-causality based on VECM showed that Thailand is exogenous whereby Malaysia is the most endogenous at before and during the crisis. After the crisis, US become dominant compare to the other countries. In conclusion, we found that ASEAN-5+3 and US stock markets are interdependence during crisis and post-crisis periods and the impact of US stock market is effective in ASEAN-5+3 stock markets only for pre and during-crisis periods.

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Section: Literature Reviews On Asean-5 + 3 Stock Markets Integrationmentioning

confidence: 99%

ASEAN-5 + 3 and US Stock Markets Interdependence Before, During and After Asian Financial Crisis

Royfaizal¹,

Lee²,

Azali³

2009

IJEF

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“…There have been fewer investigations into stock market linkages among emerging economies with most focussing on Asia and Latin America (see for example, Koutmos and Booth 1995, Chen, Firth, and Rui 2002, Manning, 2002, Ng, 2002and Fujii 2005. Only a few studies have investigated comovement between the emerging economies of Central and Eastern Europe (CEE) and the developed markets of Western Europe.…”

Section: Introductionmentioning

confidence: 99%

Spillover effects from London and Frankfurt to Central and Eastern European stock markets

Harrison

Moore

2009

Applied Financial Economics

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This article investigates comovement in stock markets between the emerging economies of Central and Eastern Europe (CEE) and the developed markets of Western Europe. Three approaches are employed to examine this issue. The first two approaches, time-varying realized correlation ratios and cointegration statistics, use a two-step technique to derive time-varying estimates of the comovement between returns on CEE and EU stock exchanges. The first step uses common factor analysis to define the factors driving CEE stock exchanges, while the second step evaluates the relationship between the leading principal factor for CEE countries and the Deutsche Aktien Xchange (DAX) and Financial Times Stock Exchange (FTSE) using time-varying realized correlation and rolling cointegration statistics. The third approach employs Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) techniques to obtain estimates of mean and variance spillover effects.

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“…2 The results, however, are mixed. Kasa (1992), Arshanapalli and Doukas (1993), Corhay, Tourani Rad and Urbain (1993), Chou, Ng and Pi (1994), Richards (1995) and Manning (2002), inter alia, applied Engle-Granger and Johansen cointegration methods, with results di¤ering according to the method, the sample period and the markets considered.…”

Section: Introductionmentioning

confidence: 99%

“…Several methods have been employed, ranging from standard GARCH models (Longin and Solnik, 1995), adjusted measures of correlation Rigobon, 2001 and2002), switching ARCH methods (Ramchand and Susmel, 1998) or copula models (Rodriguez, 2007 andGarcia andTsafack, 2011, for example), just to name a few. Much of these studies focus on returns correlations, rather than prices (which are intrinsically nonstationary, unlike returns).…”

Section: Introductionmentioning

confidence: 99%