Joel Dresang: Kyle, when we talk about Modern Portfolio Theory, it shows us that the major determinant in how investments do in a risk/reward basis is asset allocation. And you’ve got statistical tools that help measure that. Let’s talk about some of the fundamental tools. And start with the Greek alphabet – alpha, beta.
Kyle Tetting: Absolutely. Well, we’ll start with beta. I think it’s the easiest way to kind of measure the risk of a portfolio. The one thing about beta is it’s measuring the portfolio’s risk relative to some benchmark.
Most typically, we would use the S&P 500 or a broader stock or stock-and-bond measure, but really beta is the risk relative to that benchmark.
And then we get into alpha. Alpha’s really the measure of return relative to that level of risk. So, if you’re taking the risk of the index, but you’re underperforming the index, that would be negative alpha. You’re not getting the return you should, relative to the level of risk you’re taking.
Joel: So if I have an alpha of one, what does that mean?
Kyle: It means that you have one additional unit of return for the level of risk you’re taking. But where were really start to get excited is alphas of two, alphas of three. That’s when it’s really worth it to take that next unit of risk.
Joel: So, we’ve got beta and alpha. We also have R-squared?
Kyle: Yeah. So R-squared, the co-efficient of determination, if you really want to get specific with your statistics concepts.
Alpha and beta are great, but again, it’s a measure relative to some benchmark. And if your portfolio isn’t easily explained relative to that benchmark – if the two aren’t very well-correlated – the alpha and the beta don’t mean much. The performance (the alpha) and the risk (the beta) aren’t really a factor, based on the benchmark that you’re tracking.
So the higher the R-squared, relative to 100 being a perfect correlation between the two or a perfect co-efficient determination, the better – the more likely that alpha and beta are a product of that relationship.
Joel: So the R-squared helps us determine how accurate the alpha and the beta are.
Kyle: That’s right.
Joel: So alpha, beta, R-squared, those all involve benchmarks. You also have some tools that are not using benchmarks?
Kyle: You know, there’s really two tools we look at. In addition to the return of the portfolio, there’s two tools we look at that kind of stand alone.
The first, the standard deviation of the portfolio, which is really the volatility around that average level of return. So the higher the standard deviation, the more volatile the portfolio.
And then the second piece of that, the Sharpe ratio, which really gives us the return relative to that standard deviation. Are we getting value for the risk we’re taking? Or is our return purely that we’re taking more risk?
And I say they’re stand-alone ratios. You can compare them to the standard deviation and Sharpe of another portfolio, another index, another benchmark. So they aren’t relative to another thing but they can be compared to other things.
Joel: And these are all tools that investment professionals use. Are they very accessible to investors themselves?
Kyle: They are very accessible. For our own clients, we publish regularly statements for them that include a Morningstar snapshot, which has all of those measures available right on the second page. It’s part of our regular review process and something we look at inside of our own firm as we talk about the investments and how we put them together.
Kyle Tetting is director of research at Landaas & Company.
Joel Dresang is vice president-communications at Landaas & Company.
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Watch Kyle Tetting in Talking Money: Modern Portfolio Theory
(initially posted April 10, 2014)
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