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Article overview
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Inverse statistics in stock markets: Universality and idiosyncracy | | Wei-Xing Zhou
; Wei-Kang Yuan
; | | Date: |
9 Oct 2004 | | Journal: | Physica A 353 (2005) 433-444 DOI: 10.1016/j.physa.2005.02.011 | | Subject: | Other | cond-mat.other | | Affiliation: | ECUST), Wei-Kang Yuan (ECUST | | Abstract: | Investigations of inverse statistics (a concept borrowed from turbulence) in stock markets, exemplified with filtered Dow Jones Industrial Average, S&P 500, and NASDAQ, have uncovered a novel stylized fact that the distribution of exit time follows a power law $p( au_
ho) sim au
ho^{-alpha}$ with $alpha approx 1.5$ at large $ au_
ho$ and the optimal investment horizon $ au_
ho^*$ scales as $
ho^gamma$ [1-3]. We have performed an extensive analysis based on unfiltered daily indices and stock prices and high-frequency (5-min) records as well in the markets all over the world. Our analysis confirms that the power-law distribution of the exit time with an exponent of about $alpha=1.5$ is universal for all the data sets analyzed. In addition, all data sets show that the power-law scaling in the optimal investment horizon holds, but with idiosyncratic exponent. Specifically, $gamma approx 1.5$ for the daily data in most of the developed stock markets and the five-minute high-frequency data, while the $gamma$ values of the daily indexes and stock prices in emerging markets are significantly less than 1.5. We show that there is of little chance that this discrepancy in $gamma$ stems from the difference of record sizes in the two kinds of stock markets. | | Source: | arXiv, cond-mat/0410225 | | Services: | Forum | Review | PDF | Favorites | |
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