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Is Modern Portfolio Theory Obsolete?

Rachel Haig

Rachel Haig: I am Rachel Haig with I'm here today with Peng Chen, President of Ibbotson Associates. Previously we discussed whether diversification failed in 2008, and now we're back to talk about modern portfolio theory. Thanks for joining me today, Peng.

Peng Chen: No problem, Rachel.

Rachel: Typically with modern portfolio theory, the idea is that it balances risk and reward. Did it do that in 2008?

Peng: I think you're asking a really great question, and this really has to go back to what modern portfolio theory is. If you look at modern portfolio theory, one of the key things modern portfolio theory tries to do is really try to mitigate risk. The risk that it mitigates through diversification is the undiversifiable risk part, and the part of risk that it cannot mitigate is the systematic risk part.

So what happened in 2008, of course, the market came down quite a bit, and a lot of the portfolios following modern portfolio theory also suffered. If you look at it, a lot of people automatically draw the conclusion that modern portfolio theory didn't work, because the risk is still there.

But if you look at it, the risk really came in, in 2008, as a systematic risk part, which is the risk that modern portfolio theory did not claim or did not attempt to try to address.

So from that regard, actually, yes there was a lot of risk in 2008, but we believe modern portfolio theory actually continued to work. It's just that the risk happened to be the systematic risk part, and that is not what modern portfolio theory addresses.

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Rachel: All right. So then is Ibbotson changing anything with how they look at those statistics? It sounds like you think they worked, so are you looking at any of them in particular going forward, or just staying the same?

Peng: That's another good question. Even though we believe the fundamental principle of modern portfolio theory worked, we took a much detailed look at some of the measures, the risk measures, return measures, and examined them to see if they continued to be valid.

It's one thing to say modern portfolio theory, the principle, remained to work. It's another thing to examine the measures. So when we started looking at the measures, we realized, and this has been documented by many academics and practitioners, we also realized that one of the traditional measures in modern portfolio theory, in particular on the risk side, standard deviation, does not work very well to measure and present the tail risks in the return distribution.

Meaning that, when you have really, really bad market outcomes, modern portfolio theory purely using standard deviation underestimates the probability and severity of those tail risks, especially in short frequency time periods, such as monthly or quarterly. So with that being said, we understand there are some shortcomings within some of these specific measures.

We actually aggressively augmented our statistics and our calculations, by incorporating additional measures to specifically present tail risks, and the probability, and the severity. For example, one of the measures we use is the conditional value at risk. Today, we actually report that to all of our clients and use it actively in our portfolio construction, measuring risk tolerance, and so on and so forth.

Rachel: So in terms of thinking about risks, standard deviation no longer captures all of them?

Peng: That is correct. I would definitely say so, and if today, if we're only using standard deviation as your pure risk measure, it's probably no longer adequate, especially on the tail risk side. We would strongly encourage you to look at some of these tail risk measures while there's semi-standard deviation shortfall probability, conditional value at risk, and so on and so forth.

Rachel: All right, well thanks for sharing that research.

Peng: No problem, Rachel.

Rachel: For, I'm Rachel Haig. Thanks for watching.