This commentary is available as a PDF here.


  • Most investment strategies can be broken down into the risk premia they wish to harvest, whether it is vanilla like the equity risk premium or more exotic, like the value premium.
  • Different risk premia mature at different rates.  Value can take years to mature while momentum can take only a few weeks.
  • Aligning your approach to rebalancing with how long you expect the premium to take to mature is critical to ensure you fully capture the opportunity.
  • This not only affects actively managed portfolios, but strategic allocations as well.

Before we dive into this metaphor, it is worth pointing out that neither of us would consider ourselves avid wine drinkers – so for those of you who are oenophiles, please pardon any vernacular hiccups.

We begin with three oenophiles, all looking to buy the newest vintage of wine which should, they all believe, achieve peak readiness in five years.

The first oenophile enters the store, buys the newest vintage, and locks it up in his temperature controlled fridge for five years.  In five years he takes it out and enjoys the fruits of his patience.  Once finished, he returns to the store and buys another bottle of wine – the newest vintage – and locks it up for another five years.

The second oenophile enters the very same store and buys the very same vintage.  He locks it up in his temperature controlled fridge, but a year later becomes impatient, opens the bottle and drinks it.  While the wine has matured, it had not yet reached peak.  He returns to the store to buy another bottle of wine.  Again he plans to store it for five years, but ends up opening it a year later.

The third oenophile enters the very same store and buys the very same vintage.  She locks it up in her temperature controlled fridge.  A year later she returns to the store and buys the newest vintage, which she locks up next to the bottle she bought the prior year.  She does this every year until five years later, when she opens her oldest bottle, enjoys it at peak maturity, and replaces it with a new one from the store.

Now let’s compare their experiences.

Every bottle of wine the first oenophile drank was at peak maturity, but he was only able to enjoy a bottle every five years and may have missed some very fine vintages that came in-between.

The second oenophile was able to enjoy every vintage of wine throughout his life, but never enjoyed any wine at peak maturity.

The third oenophile, on the other hand, is able to enjoy each and every vintage and enjoy them all at their peak maturity.

So what in the world does this have to do with investing?

Consider a value stock picker that starts a new fund.  In order to not significantly lag the market from the get go, he feels pressured to invest all his capital at once.  He buys many deeply under-valued stocks that he expects to take years to revert to his target price.  Diligent, he sits on his hands until they start maturing at which point he sells them and re-invests the proceeds.

This fund has become inherently tied to a vintage – just like the first oenophile.

Let’s consider a second scenario – one which might be more common.  At the end of the year, a client meets with her financial advisor.  The advisor has taken a look at all the best institutional research and using 10-year forecasts developed a strategic asset allocation.  The client and the advisor agree to rebalance the portfolio.

At the end of the next year, the same meeting takes place, with the advisor building a new strategic allocation optimized to the new 10-year forecast.  The client and the advisor both agree to rebalance.

The client and the advisor are now acting like the second oenophile, building portfolios designed to be optimal for the next ten years, but selling them merely a year later.

To truly demonstrate the impact of what may seem like simple rebalancing decisions, we built three value long/short portfolios (so we can capture both the impact of identifying what is expensive and what is cheap).  The portfolios are built from sector data coming from the Kenneth French data library and use current yield versus historical yield as a valuation proxy.

The cheap portfolio is equal weight the two cheapest sectors while the expensive portfolio is equal weight the two most expensive portfolios.

So what are our expectations?  We expect method #1 to be able to fully harvest the value premium, but it’s success or failure will be entirely dependent on the state of value (the vintage) of when it rebalances.  Method #2, on the other hand, will never let the value premium fully mature, and so unless it matures early, the portfolio will more or less go sideways.  Method #3, on the other hand, should fairly consistently capture the premium, but will never create outsized returns from a single good vintage the way method #1 might.
Some quick summary statistics and visualization:


Method #12.22%12.38%47.53%
Method #21.54%12.89%56.73%
Method #32.22%6.74%29.67%

Long-Short Comparisons
The above graph is for example purposes only.  Performance is back-tested and hypothetical.  The performance does not reflect any strategy currently managed by Newfound Research.  Returns are gross of any fees and transaction costs that might be incurred in implementing such strategies.  Returns assume the re-investment of dividends.  Please see important disclosures at the end of this paper.

Some high level thoughts:

  • Methods #1 and #3 both end up in the same place, but method #3 gets there with nearly half the volatility.  Ending up in the same place is a coincidence – method #1 could dramatically out- or under-perform method #3 depending on which vintage of value it got.
  • Method #2 – rebalancing annually – completely failed to harvest any value premium from 1967 to 1997 – a 30 year period.
  • Method #2 did capture a significant amount of value premium during the dot-com bust as the premium matured at an accelerated rate.  Method #3 caught a bit less and method #1 failed to capture any.  Why?  Method #1, which only rebalanced every five years, rebalanced on 12/1997 and 12/2002.  In other words, for method #1, the dot-com boom and bust didn’t even exist.
  • Because method #2 just happened to rebalance on 12/2007, it aligned itself with a vintage that did particularly well through 3/2009 – and then cratered into early 2011.  Timing luck giveth and timing luck taketh away.

The most important takeaway here is that if we build a portfolio designed to benefit from holding it over a certain period, then we should hold it over that period.  Operationally, this can be difficult – especially when we are getting it started – but it can be easily approximated.

For example, let’s assume we build our strategic asset allocations from 10-year forward estimates.  Ideally what we want is to hold the portfolio for 10 years.  To do so without being like the first oenophile, we have to hold overlapping portfolios.

To bootstrap this process today, we would go back and use data from December 2006 to re-create the 2007-2016 recommended portfolio.  Then do the same for 2008-2017, 2009-2018, and so on and so forth until we create the newest portfolio, 2016-2025.  We would then just average these 10 portfolios together to get our recommended holdings for January 2016.

At the end of 2016, we’d drop the 2007-2016 portfolio from the mix and replace it with 2017-2026 estimates.  We would then average the 10 portfolios together to get the recommendation for January 2017.

As with the third oenophile, we will now have a chance to experience the full maturation of our initial expectations while ensuring that we are capitalizing on new views as they develop. By constructing a portfolio in this fashion, we can reduce the risks of missing good vintages simply because we are waiting for our older views to come to fruition.

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 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.