After the tech bubble burst in 2000, many investors fled to real estate. This strategy made sense as the two markets had little correlation and that played out for several years. Then the financial crisis of 2008 came, and it hit most world economies. The accompanying housing collapse caused a meltdown of mortgage-backed securities, the equity market, insurance companies, investment as well as commercial banks, and resulted in credit freezing up. Ultimately, the collapse of the real estate market in the United States was felt everywhere.
Markets that economists and financial practitioners thought had little overlap suddenly were joined at the hip. The oversight was a misinterpretation of the correlation coefficient that, when calculated over a long period of time, one-year or more, shows little or no-synchronization between these markets. As many have said, in times of crises, all correlations go to one. Analysts once again disregarded the well-established case that variable non-correlation over a specific time frame does not automatically imply independent variables on all time frames.
The S&P 500 is the accepted measure of the U.S. equity markets. This index and the Shanghai Stock Exchange (SSE) composite, which the SSE launched in 2004 as a reflection of performance of the most influential stocks in the Shanghai market, are good examples of indexes that have little correlation over longer time periods but demonstrate high correlation over shorter periods, implying possible profitable trading opportunities.
The S&P 500 and the SSE are two different markets for which the trading times of the cash equities do not overlap (see “Mixing markets,” below). When stocks are trading on the Shanghai market, the U.S. market is closed and vice versa. A stock trader in the United States can act on news of market moves in China in the same day, but with a time lag of hours. On the other hand, a stock trader in China will have to wait until the next day to act on news of market moves in the United States. But can the news in each country have a ripple effect on the markets of both countries? A correlation coefficient will help give an answer to this question.
The first step is to explore the statistical properties of both markets. We used daily returns for the S&P 500 and the SSE for the period of Jan. 3, 2007, to July 20, 2010. From the cash market daily values, we calculated the continuous compounded daily returns shown in “Return comparison” (below).