A PDF version of this commentary can be downloaded here.

Market Thoughts

We would venture that there is a strong correlation between the amount of ink spilled about an asset class or sector and its volatility. So given that the energy sector fell nearly 5.5% in the last month without much interest is somewhat curious.

Or, is it?

First, let’s establish whether our initial assumption has merit. Below we plot the trailing 21-day realized volatility in the energy sector and interest in the search term “oil prices” (source: Google Trends). We use “oil prices” as our proxy here as it was the primary driver behind energy sector re-pricing in the last 12-months.

2015-06-01 - Figure 1

We can see a clear similarity in shape.  As volatility has died, so has search interest.

Yet a near 5.5% loss in a single month seems fairly significant. So how can we reconcile what seems to be a fairly significant deviation in market interest? Is everyone just tired of talking about energy?

Our perspective is that it all comes down to how you measure volatility.

Traditionally, volatility is measured by taking some trailing standard deviation of close-to-close (log) price changes.  So “high volatility” means large day-to-day price swings.

At Newfound, we use volatility to give context to price changes within our momentum models.  This means we end up looking at, and measuring, volatility a bit differently.  In line with our model of making our market-derived estimates time agnostic, we prefer a scenario based approach.

Consider the scenarios our algorithms have identified in the energy sector over the last 12 months.

2015-06-01 - Figure 3

We can see that the scenarios, generally, identify local peaks and troughs.  For us, the length of the scenario is less relevant than the total return during the scenario.

For each scenario, however, we can find the average daily price change to get an understanding of what day-to-day volatility was like during that period.

2015-06-01 - Figure 4

The definitive trend we see is that as time has marched on, the average daily price change has diminished, which echoes our significant drop in realized volatility.

And that’s how we have the simultaneous existence of low volatility and a near 5.5% loss in the energy sector in the last month: the sector has just churned slightly lower every day. Slow, subtle, but still significant.

And without the fireworks, everyone’s lost interest.

The danger of measuring volatility in the traditional sense, however, is that you lose sight of how far the market can potentially move in the same direction without reversal or consolidation.  As we like to say: a straight line down has zero volatility.

If instead of asking about the average daily experience in each scenario, we look at the scenario’s return in aggregate (thereby totally ignoring time as a component of our analysis), we get a very different story.

2015-06-01 - Figure 5

What we see is that volatility hasn’t dried up at all. In fact, volatility in the energy sector is still going quite strong. Nine of the prior ten scenarios have been near, or over, 10% moves.

This is why our momentum models still see volatility as being so highly elevated in the energy sector and why our signal for the energy sector has remained off.  While the March and April rally in the sector seemed significant in the context of traditional volatility measures, when normalized by our volatility measures it was still well within the context of being market noise.

And while 5.5% in a month seems like a fairly significant price move, recent scenario changes tell us we may only be half-way home.

In Our Models

Our Tailwinds Moderate model rebalanced this week to align with recent accrued changes within our Multi-Asset Income portfolio. Therefore, the majority of the changes happened within the Multi-Asset Income sleeve of the portfolio, leaving the equity profile alone.

Most significantly, we increased our exposure to bank loans while reducing our exposure to preferreds, mortgage REITs, and corporate bonds. We also eliminated our small exposure to 20+ Year US Treasuries due to waning momentum strength.

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.com, ETF Trends, and Forbes.com’s Great Speculations blog. He was named a 2014 ETF All Star by ETF.com.

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.

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