You’ve likely heard that diversification is the only “free lunch” the markets offer.  I’m hear to tell you that, without employing leverage, that isn’t true.

So why do we diversify?  The answer, from a mathematical perspective is easy: by incorporating non-correlated assets into your portfolio, you can increase your Sharpe ratio.  From a common-sense perspective, it just makes sense to not put all our eggs in one basket.

Which is great for when we are talking about nearly identical eggs.

But we aren’t.

We’re talking about asset classes with very different risk, return, and joint-behavior profiles.  Trading in a little bit of S&P 500 for U.S. Government Treasuries isn’t having two equal eggs in your basket.  You’ve traded in a higher risk, higher return asset for a lower-risk, lower-return asset.  Without employing leverage, such a decision is going to reduce total expected return in the portfolio.

Yet nearly all of us make this decision in our portfolio.  We all mix some bonds with our stocks.  And we accept the dampened total-return performance (“performance drag”) and sleep better at night.  Sounds a bit like … insurance.

And that’s what un-levered diversification is.  It is a form of insurance: we accept lower total returns (an implicitly paid premium) to reduce portfolio losses.

Unlike insurance, however, the reduction of portfolio losses isn’t guaranteed; we’ve all heard the phrase, “the only thing that goes up in a down market is correlation” (which, in my opinion, is a tautology).  The relationships between asset classes are non-stable: they are extremely regime dependent.

So we diversify asset classes.  We diversify factor exposure (see our old post, “The Ebb and Flow of Active Return Premia“).  We diversify manager risk.  Why don’t we diversify how we manage risk?

If we aren’t going to employ leverage to get our portfolios back to a target risk or return level, why do we not view asset-class diversification as an insurance premium?  Why do we not consider it versus the potential cost, but the guarantee, of using options?  What about employing tail-hedge strategies or go-to-cash strategies?  Each has their own implicit costs (like model whipsaw) and offers no true guarantee of protection.

If I think the expected return for stocks is 8%, with 15% volatility, and the expected returns for bonds is 5.5% with 6% volatility, can it ever make sense for me to simply be 100% long equities and buy a 1-year ATM put option if it costs less than 2.5% of my portfolio?  Would we even be willing to pay 3-3.5% since the loss protection is guaranteed?

Once we start looking at un-levered portfolio diversification as non-guaranteed portfolio insurance and measuring the cost of diversification, it starts to bring up a lot of questions.

The last month of bond performance has reminded everyone that the “economic hedge” that bonds represent is not free.  With a strong bull-market in bonds over the last 30 years, the insurance that bonds have offered has been near-free — if not a net benefit to the portfolio.  In fact, over the last decade, the total return of stocks and bonds has been nearly identical — with a much smoother ride in bonds.

But if we think that bonds are either (a) going to peak and start having negative expected performance in the short-term, or (b) become a much less effective hedge in the future (if, for example, markets became inflation risk driven instead of economic risk driven), we should begin asking ourselves: can we get this insurance elsewhere and at what cost?

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.