Daily Academic Alpha: Warren Buffett Market Predictions By Wesley R. Gray, Ph.D., Alpha Architect, Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors.
Last week we had a fairly long post on a valuation based asset allocation strategy that might actually work. This post followed a couple of other research projects on the issue, which showed limited evidence for simple valuation-based timing strategies.
Now there is a new paper on Warren Buffett’s favorite timing mechanism, Market Cap/ GNP (or GDP). We’ve discussed this metric in 2013, which suggested one get out of the market, and the out-of-sample results were horrific–the market has been on a tear!
Below is a link to the new paper and abstract (h.t. CXO advisory).
Select quotes from the paper:
Our analysis shows that Warren Buffett’s market value of all publicly traded securities as a percentage of GNP (MV/GNP), and its parent the lorgarithm of the market value of all publicly traded securities as a percentage of GNP (lnMV/GNP), can be a statistically significant predictors of future market downturns. However, for these measures to work, we need to use time-varying confidence-based thresholds rather than fixed thresholds.
The authors continue:
This conclusion dispels a common myth about the MV/GNP ratio: that absolute level matters. This myth has led market commentators and investment practitioners to suggest that the level of the MV/GNP is the harbinger of an impeding market meltdown.
The authors examine a bevy of measures:
- MV/GNP with a fixed threshold at a 120% level;
- MV/GNP with a threshold computed using a standard 95% one-tail confidence interval based on a Normal distribution;
- MV/GNP with a threshold computed using Cantelli’s inequality;
- logMV/GNP with a fixed threshold at a 120% level;
- logMV/GNP with a threshold computed using a standard 95% one-tail confidence interval based on a Normal distribution;
- logMV/GNP with a threshold computed using Cantelli’s inequality;
And here are the core results, highlighting that absolute measures stink, but time-varying metrics may be promising:
Conclusion: The results are mixed (absolute doesn’t work while time-varying works) when it comes to tactically allocating assets based on market valuations. This result is in line with much of our own research.
We provide more information on our take on tactical asset allocation and our summary of various concepts.
