The title of this blog post comes from Aaron Brown's book, Red-Blooded Risk.  While I've always been a strong proponent of having a firm, intuitive grasp of our models, I agree with Aaron.

For Newfound, two days ago was one of those days: for the first time ever in the history (of both our backtest and live signals) of our Absolute Exposure model, we received a negative recommendation on short-term U.S. treasuries (using the ETF proxy SHY).

That was surprising, to say the least.

Now, the signal has to be put in perspective: because the model is adaptive to each asset, it uses the volatility and relative rates of returns to determine "normal" market moves.  While SHY has only lost 24bp (yes, not even 1%) since it peaked on June 1st, the magnitude and speed of the drop was so abnormal for SHY, it triggered our model to remove its long-standing positive recommendation.  Surprising?  Yes.  Worrying?  Maybe not.  Different?  Definitely.

Taking a look at the internals of our model, we see that the dynamic window we use to measure our data, driving how quickly we react to market changes, has dropped dramatically over the quarter for many assets:

Dynamic Window 6-28-2013

It also caused us to look at our nightly market metrics with a bit more scrutiny and saw some interesting dynamics developing:

  1. Once again, panic selling and liquidation has led to increased correlations and a curious look on everyone's face as we ask ourselves, "man, this diversification thing has really stopped working, huh?"  sp_sector_correlations 6-28-2013
    efa_country_correlations 6-28-2013
    eem_country_correlations 6-28-2013
  2. While a decline in implied inflation expectations has been consistent since January, what is unique is the degree to which 5 - 20 year expectations have converged.inflationary_expectations 6-28-2013
  3. Dramatic spikes in reported and derived ZCB treasury yields and their vol
    reported_yield_curve 6-28-2013
    zcb_yield_curve 6-28-2013
  4. The failure for the Risk-on / Risk-off trade to materialize.  In the last several years, the RORO trade was identifiable by increased correlations between risk-on asset classes and their increasingly negative correlations to risk-off asset classes.  What we've seen since Q2 2012 is a massive decrease in cross-asset correlations, with the most recent drop being driven by the inversion of the negative US Equity and Government Bond return correlation.
    roro_correlations 6-28-2013

"But this time is different!" is normally the death knell of any asset manager, but we prefer to always be prepared for when "different" has finally arrived.  It is this sort of environment, unprecedented in recent history, that drives us to create adaptive & reactive models to drive our rule-based, outcome-oriented strategies.  It is in these sort of environments that static models will break and predictive models will fall on their face as traditional relationships break down.

This market environment reminds me of one night, last summer, when standing under a highway underpass during a torrential downpour, my friend leaned over and delivered the particularly philosophical comment: "It's interesting how windshield wipers never seem to break when you don't need them."  At that moment, I think we both would have preferred to have been surprised by a "windshield wipers broken" warning light a couple of hours before when it was still sunny.

At the end of the day, this month may mark the precipice of the bond bull market, or it may just be remembered as a weird period of global-asset whipsaw.  We aren't so bold as to predict how markets will turn out -- but we believe, at the very least, it marks the importance of a flexible, dynamic, and objective investment process.

Corey is co-founder and Chief Investment Officer of Newfound Research, a quantitative asset manager offering a suite of separately managed accounts and mutual funds. At Newfound, Corey is responsible for portfolio management, investment research, strategy development, and communication of the firm's views to clients.

Prior to offering asset management services, Newfound licensed research from the quantitative investment models developed by Corey. At peak, this research helped steer the tactical allocation decisions for upwards of $10bn.

Corey is a frequent speaker on industry panels and contributes to, ETF Trends, and’s Great Speculations blog. He was named a 2014 ETF All Star by

Corey holds a Master of Science in Computational Finance from Carnegie Mellon University and a Bachelor of Science in Computer Science, cum laude, from Cornell University.

You can connect with Corey on LinkedIn or Twitter.