Conditional violation of weak-form market efficiency
Purpose: Many prior tests of market efficiency, which occurred decades ago, were limited by data and did not employ methodology to correct for leptokurtosis in the stock return distribution. Furthermore, these studies did not test many aspects of conditional market efficiency. One aspect of a potential conditional violation of market efficiency is whether stock markets are efficient conditional on the level of stock return. Design/methodology/approach: This paper uses quantile regressions to control for leptokurtosis in the stock return distribution and simultaneous quantile regressions to test whether markets are efficient conditional on the level of the market return. This paper uses market-level stock return data to bias against finding significant results in the efficiency tests. Furthermore, the author uses data from 1926 through 2018, providing the longest time period to date under which market efficiency is tested. Findings: This paper presents evidence that the autoregressive coefficient decreases across return levels in stock market indices. The autoregressive coefficient is positive around highly negative returns and negative or insignificant around highly positive returns, which suggests that when stock returns are low they are more likely to continue lower, and when stock returns are high they are more likely to reverse. Results additionally suggest that market efficiency is not time-invariant and that stock markets have become more efficient over the sample period. Originality/value: This paper extends the literature by finding evidence of a violation of weak-form market efficiency conditional on the level of stock returns. It further extends the literature by finding evidence that the stock market has become more efficient between 1926 and 2018.
Year of publication: |
2020
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Authors: | Jansen, Benjamin |
Published in: |
Managerial Finance. - Emerald, ISSN 0307-4358, ZDB-ID 2047612-7. - Vol. 46.2020, 7 (12.03.), p. 935-954
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Publisher: |
Emerald |
Saved in:
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