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This study examines the integration of nine Asian stock markets using the new methodology of wavelet multiple correlation and multiple cross-correlation proposed by Fernandez (2012). This novel approach eliminates several limitations which are encountered when conventional pairwise wavelet correlation and cross-correlation are used to assess the comovement of a set of stock indices. Our results show that Asian stock markets are highly integrated at lower frequencies and comparatively less integrated at higher frequencies. From the perspective of international investors, the Asian stock markets therefore offer little potential gains from international portfolio diversification especially for monthly, quarterly, and biannual time horizon investors, whereas, higher potential gains are expected at intraweek, weekly, and fortnightly time horizons.

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In this paper, the dynamics of Standard and Poor's 500 (S&P 500) stock price index is analysed within a time-frequency framework over a monthly period 1791:08-2015:05. Using the Empirical Mode Decomposition technique, the S&P 500 stock price index is divided into different frequencies known as intrinsic mode functions (IMFs) and one residual. The IMFs and the residual are then reconstructed into high frequency, low frequency and trend components using the hierarchical clustering method. Using different measures, it is shown that the low frequency and trend components of stock prices are relatively important drivers of the S&P 500 index. These results are also robust across various subsamples identified based on structural break tests. Therefore, US stock prices have been driven mostly by fundamental laws rooted in economic growth and long-term returns on investment. JEL C22 G10

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