and post-crash samples are used, would the lack of causality continue to hold? Smith et al. 1993 have shown that, using a rolling Granger causality test,
somewhat greater causality existed after the crash their sample ends in June 1991. Even more high frequency data are now available to study the issue of both pre-
and post-crash comovements. Smith 1999 used cross spectral analysis along with a longer sample period. He found increased coherence among six major equity
markets, particularly among the three European markets studied UK, Germany, and France. Most pre-post-crash research described above has focused on the G-7
or a subset of the markets e.g. see Darbor and Deb 1997, Masih and Masih 1997 and Smith 1999.
1
It is the purpose of this paper to investigate these pre-post-correlations for Pacific Rim markets. This study includes two markets that are not part of the
Group of Seven. Cross spectral analysis is applied to eight pairwise combinations of coherence and phase leads from data for Australia and Hong Kong, as well as the
US, Canada, and Japan.
2. Data
The individual stock market indexes are constructed from country data compiled by Morgan Stanley International Capital Perspectives. The raw stock data for each
of the country markets consist of the daily value-weighted composite index level. Each index is composed of stocks that broadly represent the stock compositions in
the different countries. All indexes are normalized to unity at a common date January 1, 1970 = 100. Each normalized stock market level is converted to a rate
of return with the transformation lnP
i,t
− lnP
i,t − 1
= R
i,t
for the ith country, where P
i,t
and P
i,t − 1
are the levels of the index using closing prices in periods t and t − 1, respectively, for the ith country. The data are measured in local
currencies. Measuring the indexes in dollar terms would weaken the measurement of equity market integration by including exchange rate movements. Additionally,
funds are now able to effectively hedge exchange rate movements. For other studies using local currencies see Hamao et al., 1990; Malliaris and Urrutia, 1992;
Theodossiou and Lee, 1993; Koutmos and Booth, 1995.
The pre-crash sample runs from August 18, 1980 through May 29, 1987. The post-crash period runs from March 8, 1988 through December 16, 1994. Data were
available from May 1987 through March 1988. The period surrounding the crash is omitted from the sample. This is due to the volatility during this period. This
division in the sample is not completely arbitrary, given the institutional changes to the exchanges following the 1987 crash.
A problem arises when markets around the world open and close sequentially on any given day. The Asian markets close first. As of December 1987, Japan opens
first at 16:30 h and closes first at 23:30 h eastern standard time. Australia follows
1
An exception is the study by Najand 1996. This research concludes that ‘interactions’ among Asian markets Japan, Hong Kong, and Singapore increased after the crash.
by opening at 17:00 h, closing at 12:00 h. Hong Kong opens at 19:00 h, while closing at 01:30 h. These markets overlapped in terms of the trading day in real
time. Canada and the US market were both open simultaneously from 09:30 to 16:00 h. The problem arises when shocks to the US and Canadian markets
originate in the Asian markets. In calendar time this is measured as a contempora- neous shock, yet in real time this shock occurs with several hours of lag time.
Kayha 1997 shows that covariances between non-contemporaneous markets are somewhat upwardly biased. While noting this to be the case, any bias which exists
is exhibited in both the pre- and post-1987 crash period.
The data must be stationary to perform the appropriate analysis. Kwiatkowski et al. 1992 have shown that a test for stationarity adds to the robustness of
conclusions regarding unit root. This test is important due to the low power of Dickey – Fuller tests in rejecting the null hypothesis of unit root. These results are
reported in Table 1. Using the KPSS test, stationarity is rejected for the price series, while stationarity cannot be rejected for the return series.
3. Cross spectral analysis
