Inspiring Market Efficiency Results…NOT!

///Inspiring Market Efficiency Results…NOT!

Inspiring Market Efficiency Results…NOT!

By |2017-08-18T17:02:59+00:00August 20th, 2014|Research Insights|

Yes, it is true, lower risk securities have historically outperformed higher risk securities. We’ve seen this in a variety of academic research pieces, but sometimes you gotta grind the data on your own to really understand and get comfortable with the results. A recent paper and this paper and some of our own internal research has suggested that the “low vol” anomaly might be bunk. We are on a data adventure to get to the bottom of this anomaly…

Legend:

  • Col 1 = high idiosyncratic stocks, monthly rebalanced, equal-weight, mid/large cap only, 1927 to 2013
  • Col 2 = high beta stocks, monthly rebalanced, equal-weight, mid/large cap only, 1927 to 2013
  • Col 3 = low idiosyncratic stocks, monthly rebalanced, equal-weight, mid/large cap only, 1927 to 2013
  • Col 4 = low beta stocks, monthly rebalanced, equal-weight, mid/large cap only, 1927 to 2013

The chart below is part of a larger study we’ll be sharing in the near future (click to enlarge):

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

In the meantime, gleam over the numbers.

There is definitely a counter-intuitive relationship between risk and return. Higher risk, lower return; lower risk, higher return.

The difference between IVOL and BETA are trivial and highly correlated (90%+).

But are these spreads robust? Are they other anomalies in drag? We are going to find out…

 


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About the Author:

Wesley Gray, PhD
Wes Gray has published multiple academic papers and four books, including Quantitative Value (Wiley, 2012), DIY Financial Advisor (Wiley, 2015), and Quantitative Momentum (Wiley, 2016).After serving as a Captain in the United States Marine Corps, Dr. Gray earned an MBA and a PhD in finance from the University of Chicago where he studied under Nobel Prize Winner Eugene Fama. Next, Wes took an academic job in his wife’s hometown of Philadelphia and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management firm that delivers affordable active exposures for tax-sensitive investors. He is a contributor to multiple industry publications and regularly speaks to professional investor groups across the country. Wes currently resides in the suburbs of Philadelphia with his wife and three children.
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