Special Announcement

We’ll be hosting our usual monthly strategy review webinar on Monday, July 13th at 2:00PM ET. This month we will be covering unconstrained income investing, including both unconstrained fixed- income as well as alternative-income portfolios.

You can register at https://attendee.gotowebinar.com/register/6169968140877147393.

Market Recap

After last Monday’s Greece-related sell-off, chatter about volatility is on the rise again.

At Newfound, we spend a lot of time talking about volatility because it is a key ingredient to our momentum models.  But volatility is a complicated topic.  And I find there is no better way to dissect a complicated topic than through a conversation … with myself.

So, what is volatility?
The dictionary definition or the technical, finance definition?

Is there a difference?

Okay – what’s the technical definition?
In finance, volatility is measured as the standard deviation of an asset class’s returns.

Basically it is a statistical measure that captures the dispersion of an asset’s returns from its long-term mean.

Still gibberish.
Uh … it measures how varied returns can be?

Okay.  What about the dictionary definition?
“Liable to change rapidly and unpredictably…”

Okay, so pretty much the same thing.
“…especially for the worse.”

Yes.  So, like most mathematical definitions, there is no positivity or negativity judgment – but in English the word carries with it a negative connotation.  Nobody says, “you have a volatile personality” as a compliment. 

So an asset that being highly volatile just means it jumps around a lot?
Around its expected mean return – yes.

So if it jumps around a lot, doesn’t that mean it is riskier?
Riskier than what?

Than something that is less volatile?
I suppose it depends on your definition of risk.

Really?  We’re going there?

Fine.  Let’s define risk as the probability of losing a lot of money.  Wouldn’t a highly volatile asset class be riskier?
It depends.

Thanks, very helpful.
I try.

But to provide a counter-point to your question, consider two stocks: one with an expected return of 10% a year and one with an expected return of 4% a year.  The first stock has a 4% volatility and the second has a 3% volatility.  Would you really consider the first stock to be riskier?

Well … no.

Because the expected return is so much higher.
Right.  Volatility is the deviation around the expected return.

Okay, but don’t risk and reward normally go hand-in-hand?  Wouldn’t we expect stocks with a higher expected return to be more volatile?
It is definitely one of those fundamental concepts in finance.  As an investor, we theoretically would demand a higher expected return if we are going to take on more risk.  But, for a variety of theoretical reasons, it hasn’t always worked out that way empirically.  Consider the low volatility anomaly in stocks that was discovered in the last decade as evidence to the contrary.

But if we have two stocks with the same expected returns and different volatilities, don’t we have a higher probability of losing more money in the more volatile asset class?
Not necessarily.

You’re driving me insane.
Which is safer: a highly innovative company, making progress in leaps and bounds, or a staunch, entrenched business with incremental growth? Certainly the first will be more volatile, as the latter is more predictable. But which do we think is more resilient in the face of sweeping industry change?

I sense some a bout of Nassim Taleb coming on…
Most turkey’s live very happy, stable, predictable lives.  Until Thanksgiving.

…and there it is.
It’s not a bad point.  Volatility has always been inadequate in capturing the fat tails and tragic events.

I think your definition of risk is too narrow anyway.

Yes.  I agree that investors generally mean “lose money” when they say “risk” – but there is more than one way to lose money.  Loss of capital is one way.  Failing to keep up with inflation is another.

Inflation?  Who cares about inflation?  Inflation hasn’t been an issue for decades now.
Do you invest more in stocks or bonds?


In his paper “Rethinking Risk,” Javier Estrada says that investors focused on uncertainty are more likely to view stocks as riskier than bonds – but those focused on long-term terminal wealth are likely to view stocks as less risky than bonds, even after considering tail risks.

So whether higher volatility is riskier depends on your investment horizon?
I think Warren Buffett would agree with that.  In his 2011 letter to shareholders, he said: “The riskiness of an investment is not measured by beta…but rather by the probability…of that investment causing its owner a loss of purchasing power of his contemplated holding period. Assets can fluctuate greatly in price and not be risky as long as they are reasonably certain to deliver increased purchasing over the holding period. And… a non- fluctuation asset can be laden with risk.”

Does that work out mathematically?
Yes.  Expected returns grow linearly with time while volatility grows with the square-root of time.

What?  What do you mean by “grows with time”?
So if we have a stock with an expected annualized return of 5% and volatility of 12%, then if we hold the stock for 10 years, we have an expected return of 50% – or 5% times 10 – and a volatility of 37.9% – or 12% times the square-root of 10. 

So if our investment horizon is long enough, volatility drops in proportion to expected return rather significantly.

Okay.  So, in summary: with a long time horizon, when we are more sensitive to inflation, we can embrace high volatility, but with a shorter time horizon, when we are more sensitive to capital loss, we should embrace low volatility.

You’ve got to be kidding me.
A straight line down has no volatility.

Stop speaking gibberish.
Consider Japan.

Excuse me?
Japanese equities just went thought a sideways 20-year period of returns – whether you’re measuring in dollars or yen.  And volatility was pretty low the whole time.

Let’s pretend Japan was a strange, once-in-a-lifetime outlier.
Low volatility may still not be safe.

There is a concept called normalcy bias.  Chris Cole at Artemis Capital sums it up beautifully:

 “A quirk of the human condition is for the mind to desire normalcy so intensely as to consciously or subconsciously disregard knowledge that is disruptive to a pre-conditioned reality. This phenomenon is an important part of crisis management and market psychology. The consequence of a normalcy bias is that warning signs of a potential crisis go unnoticed or are interpreted optimistically. When a crisis occurs people are so overwhelmed by events inconsistent with a desired reality they lose their ability to make decisions. Researchers believe when the mind encounters an entirely new experience or event it attempts to match that reality to relevant experiences from the past. If there are no matching experiences the mind enters into a kind of feedback loop resulting in passivity. This lack of action as a response to risk is called negative panic and it culminates in a dangerous inability to act assertively in crisis. In essence, the psyche struggles to come to terms with what is really happening. Paralysis follows.”

So low volatility may actually be a sign of high risk?

And high volatility can actually be a sign of low risk?
You got it.

That’s … confusing.
That’s volatility.

In Our Models

We made changes in our Tailwinds Moderate portfolio this week based on underlying changes to our Multi-Asset Income portfolio.  Most significantly, exposures to international dividends, mortgage REITs, long-dated Treasuries, and U.S. REITs were eliminated.

With the removal of these exposures, we increased exposure to bank loans, preferreds, convertibles, S&P buy-write, international REITs, emerging market debt, and U.S. dividend stocks.

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.