Video Reports

Embed this video

Copy Code

Link to this video

Get LinkEmbedLicenseRecommend (-)Print
Bookmark and Share

By Andrew Gogerty | 05-02-2013 10:00 AM

Overcoming Hurdles in ETFs

Dr. Gerald Buetow of Innealta Capital details the flexibility ETF managed portfolios have in taking on multiple investment styles and also says ETFs could wipe out a lot of mutual funds.

Andrew Gogerty: Think of the ETF wrapper as a technology, not an investment, when considering ETF managed portfolios. Hi. I'm Andrew Gogerty, ETF managed portfolio strategist for Morningstar. The ETF, when viewed as a technology, allows for quantitative analysis across multiple asset classes, sectors, and even geographies, in a very cost-effective manner. Joining me today for insight into how this is being done in practice inside a strategy is Dr. Gerald Buetow, portfolio manager of the sector, opportunistic, and country rotation strategies at Innealta Capital.

Dr. Buetow, thank you for joining me today.

Gerald Buetow: Thanks for having me.

Gogerty: So, quantitative analysis allows for great scalability. A firm builds an investment model, they could very easily apply it to sectors, geographies, fixed income, almost any gamut of asset-class combinations. How should advisors be looking at firms to make sure that they are not trying to be everything to anyone? How do you stay inside your circle of confidence when you have that leverage from quantitative analysis?

Buetow: Well, I think, foremost you must realize what the underlying theory and the concepts are that we use to develop the model. I think as quants and Ph.D.s and physicists, we have a tendency to decouple from the underlying theory and get caught up in the statistics and any kind of metrics and move away from what our overall objective is in trying to find a discriminator between risk and return across asset classes. So, I think just a reality check and reminder. You can't be everything to everyone.

I mean, what we do is fairly simple in theory, and it's a very basic hypothesis, and that is, when we look at individual equity exposure, not at the corporate level, at some sort of aggregate level--because we don't feel that if you get to a level of too much granularity, you're starting to pick stocks and you're starting to look at unsystematic risk, we don't think anybody can do that consistency for a terribly long time. What we look at is our beta duration decision, that is, does the beta exposure look more attractive than the duration exposure in any particular point in time.

So, our hypothesis is when we feel that beta exposure, beta being equity, looks more attractive on a risk-adjusted basis, and a particular fixed-income exposure that we feel is optimal at that point in time, then we will put that beta on. We do not in any way, shape, or form pretend to be experts in commodities. We get questions all the time, "Why don't you just apply it there and apply it there?" Well, because the underlying theory has always been a beta-versus-duration hypothesis. So, we could develop models in theory that would look at commodities and look at other risky exposures. The difficulty with that, of course, is that you need a valuation metric or framework, or supposed framework, right.

I don't think valuing equities is a particularly easy task. But I do think looking at beta and looking at aggregate equity exposure and determining whether or not that is a worthwhile investment at any particular time--not that it's easy--I do think tactical calls are far more important, first of all, than determining what particular equity pieces you want. I think most literature would agree with that.

The commodities space, and these other alternative spaces, there is no underlying valuation metric. There is no perpetuity of cash flows. There is no discount rate. It's a supply and demand. There is short-term and there is long-term types of effects. If you look at even interest rates or currencies, there is equilibrium effects, and then there is transitionary effects. Those are extraordinarily complicated and I think impossible to model consistently. But when you have a valuation metric, a way to look at beta in terms of how much did you spend and what are you paying for, and you compare that to what you can get in the fixed-income market, intuitively it makes sense. So we built a very sophisticated model really in an effort to try to look at that hypothesis in many dimensions, looking at the macroeconomic backdrop, the fundamentals, and so on.

I don't think you can do that consistently looking at other asset classes. Not to say that other people don't do it well, it's just not what we do. I think sometimes hubris seeps in and you say, "Well, heck, there is demand for a product, we think we can get that client if we are able to do this." That's where you start moving off the reservation, and I think we’ve been very careful to make sure that our product development matches what we are good at.

Read Full Transcript
{1}
{1}
{2}
{0}-{1} of {2} Comments
{0}-{1} of {2} Comment
{1}
{5}
  • This post has been reported.
  • Comment removed for violation of Terms of Use ({0})
    Please create a username to comment on this article
    Username: