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The predictive bias

Mukul Pal 

In case you got the annual forecast wrong, don't punish yourself. The recent publication by Jason Hsu suggests, “2013 was not the year for Nobel-worthy investment ideas”. If the Nobel prize winners can have a poor annual forecast, does forecasting accuracy need to be re-understood and re-defined?

CAPE Failure

Index dividend yields and cyclically adjusted price-to-earnings ratios (CAPEs), among other aggregate variables, can predict future equity returns. According to Hsu, “Though (Eugene) Fama and (Robert) Shiller are on the other side of market efficiency; both conclude that market valuations ratios forecast five-year returns with satisfactory accuracy. High dividend yields and low CAPEs tend to predict above-average future returns. Conversely, low yields and high CAPEs signal below average returns at some point of time.”

According to the paper, “The Shiller CAPE spectacularly forecast the carnage of the 2000 tech." One of the goodwill drivers for Shiller; a forecast. “The CAPE was at 21 for the S&P 500 Index in January 2013. And given that it had a recent trend (high) at 22 and a long-term average at 16.5, the US equities appeared to be neutral to extremely overvalued. The US equity’s market returns of nearly 30 per cent in 2013 had pushed the CAPE toward 25. This appears decidedly expensive relative to the recent and long-term levels.” Emerging market (EM) equities on the other hand were CAPE cheap. “Their -1 per cent performance in 2013 has been one of the big disappointments for global equity investors.”

The paper questions “if we should shrug the 33 per cent outperformance of US equities over EM equities as a fluke or an outlier? Should we double down for 2014 by further re-balancing away from US equities towards EM stocks?”

Technical analysis 101?
What does the Hsu paper tell us regarding the Shiller CAPE indicator? First, the indicator was at an extreme. Second, extreme suggested overvalued Third, because the extreme worked last time in 2000 making Shiller a household name, it should have worked again. The indicator was supposed to revert and bring the down with it (or underperform), which did not happen.

Now there are assumptions here in CAPE and in its interpretation. First, CAPE as a measure is good and will predict. Second, extremes in CAPE are bound to reverse. Third, extremes though subjective should work objectively, and work as a timing indicator annually.

Are the fundamentalists and behavioural experts behaving like longer trend anticipating technicians? The indicator has reached an extreme, and it should turn now, bringing in underperformance. This is technical analysis 101, so prone to failure.

Predictive bias
Give us any measure, be it value, growth, beta, momentum, reversion, CAPE or dividend, etc and we can show you cycles of underperformance and outperformance and failures of the same across multiple time frames (three months to 60 months or more).

The fundamentalists or behavioural experts are trying to prove, how their respective variable (indicator) reverts to the mean. There is a clear coverage bias. This is my coverage, my discipline, my skill, my theory, which works. This solo-discipline work keeps us away from a holistic interdisciplinary approach to risk and keeps us glued to our genetic predictive bias, which is inherently rooted in mean reversion. If it has gone up, it's going to come down.

End of behavioural finance
In our take on Richard H Thaler's End of Behavioural Finance paper, we illustrated how behavioural finance is biased towards explaining all mean reversion failures as behavioural anomalies, while mean reversion failures are happening all over nature.

Total forecast
There is no "total forecast" and just because mean reversion did not work for Shiller CAPE in 2013 and worked in Fixed Income for the Fundamental Indexing team does not give mean reversion a predictive-ness. Mean reversion is prone to failure. This is why we see a maze of agreement and disagreement between conventionally different disciplines of study; convergence and divergence. are more about risk management than about predicting value versus growth; momentum versus reversion; high beta versus low beta; CAPM versus Fama and French, etc. We are no more in a single discipline; forecasting (risk) is an interdisciplinary science and till the time we reach there, mean reversion failure will keep us lost in our biased prediction models.

The author is CMT & founder, Orpheus Risk Management Indices, an indexing company based out of the UK

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First Published: Thu, February 20 2014. 22:44 IST