Short-term drifts in stock (as well as bond, commodity and currency) prices have been well- documented in the academic literature. The fact that prices fully adjust to new information gradually, over time, rather than instantaneously, is a violation of the efficient markets hypothesis.
On the other hand, Andrew Lo’s adaptive markets hypothesis acknowledges that while the efficient markets hypothesis may not necessarily hold in the short run, it does predict that inefficiencies will self-correct over time as, post-publication, arbitrageurs exploit them. Thus, financial markets trend toward efficiency in the long run.
Adaptive Markets Evidence
Chan Wung Kim, Xiao Li and Timothy Perry, authors of the study “Adaptation of the S&P 500 Index Effect,” which was published in the Summer 2017 issue of the Journal of Index Investing, provide us an interesting test of Lo’s adaptive markets hypothesis.
Research from the 1970s and 1980s had found economically and statistically significant abnormal returns (of about 3%) in the stocks newly added to the S&P 500 Index (by the committee) on the first day of trading following the announcement (i.e., the effective date). To reduce order imbalances on the day when the S&P 500 was changed, Standard and Poor’s began preannouncing additions in 1989.
As a result, the announcement of an addition led to price increases in the days prior to the effective change in the index. The anomalous behavior of upward price drifts resulted in positive abnormal returns that could be exploited by short-term traders.
What has been termed the “S&P game” arises because institutional fund managers whose portfolios track the index, to reduce the risk of tracking error, wait to rebalance their portfolios until the change is actually effective. A similar, though much greater, problem had occurred when the Russell 2000 was reconstituted (Russell has taken some steps to reduce that effect).
After the 1989 change, research showed that, between 1989 and 2001, additions to the S&P 500 Index were experiencing large positive abnormal returns (between about 6% and 9%) in the period between the market’s close on the announcement date and the market’s close on the effective date. Interestingly, this anomaly persisted despite the problem being well-documented in the literature—contrary to the adaptive markets hypothesis.
It’s also contrary to the findings of Paul Calluzzo, Fabio Moneta and Selim Topaloglu, who contributed to our understanding of how markets work and become more efficient over time (in other words, the adaptive markets hypothesis) with their 2015 study, “When Anomalies Are Publicized Broadly, Do Institutions Trade Accordingly?”
The authors hypothesized: “Institutions can act as arbitrageurs and correct anomaly mispricing, but they need to know about the anomaly and have the incentives to act on the information to fulfill this role.” Their study, which covered 14 well-documented anomalies, found that, on average, there was a 32% relative reduction in returns post-publication.
Effects Of Academic Research
These findings were confirmed by R. David McLean and Jeffrey Pontiff, authors of the 2016 study “Does Academic Research Destroy Stock Return Predictability?” They, too, found that factor premiums fell, on average, 32% post-publication.
McLean and Pontiff re-examined 97 factors published in tier-one academic journals and were able to replicate the reported results for 85 of them. That the remaining 12 factors were no longer significant may be due to a variety of reasons, such as incomplete detail in the original paper or changes in a database.
They found that portfolios containing stocks that are costlier to arbitrage decline less post-publication. This is consistent with the idea that costs limit arbitrage and protect mispricing.
The authors note: “Decay, as opposed to disappearance, will occur if frictions prevent arbitrage from fully eliminating mispricing.” They also write that “strategies concentrated in stocks that are costlier to arbitrage have higher expected returns post-publication.”
Returning to Kim, Li and Perry’s study, stocks in the S&P 500 Index are not costly to arbitrage. Thus, the anomaly should have disappeared. Yet it persisted long after publication. With the adaptive markets hypothesis in mind, the authors extended the research to include the period from 2010 through 2013.
They found that, on average, a newly added stock’s abnormal return between the market’s close on the announcement date and the market’s close on the effective date was now just a statistically insignificant 97 basis points (p-value of 0.33).
S&P 500 Effect Diminishing
Importantly, they also no longer found any evidence of price drift from the open on the day following the announcement to the close on the effective day. They did find, however, that the return between the close on the announcement date and the open on the following morning is a statistically significant 3.09%. In other words, the overnight return is similar to what was found in prior studies of earlier periods.
This is consistent with markets having incorporated new information instantly. They also found no evidence of an exploitable price drift from the open on the day following the announcement to the close on the effective day. The return gap from the open on the day following the announcement to the close on the effective day is a statistically insignificant 42 basis points.
Moreover, the authors found that “the return from the open to the close on the day following the announcement is a statistically significant negative 55 basis points!”
Diminishing S&P 500 Effect
Kim, Li and Perry concluded: “We find no evidence of a positive price drift between the announcement day and the effective day for stocks added to the S&P 500. Additionally, we find little evidence of a meaningful positive return associated with index inclusion.” They add: “The S&P 500 effect is diminishing (and will possibly disappear eventually).”
Their findings not only offer support for the adaptive markets hypothesis, but provide another example of what my co-author Andrew Berkin and I called “The Incredible Shrinking Alpha.” The “S&P game” once provided a rich source of alpha for hedge funds and actively managed mutual funds.
But as we show in our book, sources of alpha are disappearing as academics convert what once was alpha into beta (a common factor or trait) and arbitrageurs incorporate the latest findings. That’s why, 20 years ago, 20% of actively managed funds were generating statistically significant alpha, while today that figure is about 2%, and shrinking.
This commentary originally appeared October 6 on ETF.com
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