Standard Deviation

I will be teaching the Investment course in the CFP certificate program at the University of Portland over the next several weeks. The course provides an overview of investing fundamentals. I encourage students to think of the class as a fast paced review of many concepts. We run through them quickly and rarely go very deep into any subject.

One area that merits a bit more attention is Modern Portfolio Theory. Most investment advisors rely on MPT to build and manage portfolios. The theory involves attempting to manage the relationship between risk and return in a basket of securities. Using various research sources (e.g. Morningstar) we can identify the risk and return characteristics of a given security. MPT tells us we should combine securities in a way that maximizes the risk adjusted return of the portfolio.

How do we measure risk? First, we need to define risk. This is the chance that the return from the security will not be what we expected. We are, of course, concerned with returns that fall below our expectation. We’re happy if returns exceed our expectations.

We can measure risk using Standard Deviation. This measures the dispersion of historical returns from its mean (i.e. average). We take the square root of the variance to calculate standard deviation.

If a security earned 8% year after year, there would be no dispersion and, therefore, no risk. The mean would be 8% and the standard deviation would be 0.

But if the security earned -12% one year, +16% the next and +20% the following year, the mean would still be 8%. But the dispersion (and the risk) would be much greater. In fact, the standard deviation for that security is 17. Which would you rather own?

Intelligent Investors understand MPT and they use it wisely to build and manage their portfolios. I will be discussing other concepts that underlie MPT in future posts.