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Submitted by: Paul Palmer
Paul Palmer is the Managing Partner of Cypress Advisory Services, Ltd, LLP, a comprehensive wealth management firm in Houston, Texas. Paul is a 23 year veteran of the financial services industry. Both he and his partner, Kurt Box are CERTIFIED FINANCIAL PLANNERŪ practitioners. The firm's comprehensive approach and unique institutional money management style give its clients peace of mind along with cutting edge financial advice.
Yes this is not fun to learn, but for those of you who have lost a great deal of money (over 30%) in the past, want to know why it may have been avoidable and ways to help prevent it the next time, read on!!
In part one of this series, we explained two measures of risk, standard deviation and beta. As we mentioned, standard deviation and beta are good measurements of the risk associated with individual assets on a stand-alone basis, but are not in and of themselves the primary keys to portfolio building.In fact, it is these assets' correlation that is the key driver of total portfolio risk. This is where many investors may miss the boat. While standard deviation and beta are relatively simple and easy to understand, this is not the case with correlation. Intuitively, correlation may not make sense, but you should understand this concept to help build an efficient portfolio and manage your overall risk. After all, your total portfolio risk can be the real key to success, but may be an area few investors understand or know how to manage.
Correlation Made Simple
Correlation is a statistical technique that indicates how strongly pairs of variables are related. These variables could be one asset and another asset, an asset and an index or your current portfolio and the asset you are thinking about adding to your portfolio. These assets or groups of assets may move together, in different directions or completely independently of each other. For example, a stock in the large blend category and the S&P 500 might have a correlation of 1.0, which means that their returns move together perfectly. A technology stock and a gold stock, however, may have a correlation of nearly –1.0, which implies perfect opposite movement. When constructing a portfolio, you should attempt to combine assets with low or even slightly negative correlation. That is the way to achieve true diversification. Indeed, if recent market volatility has made you nervous or uneasy, correlation can point to ways to restructure your portfolio to help reduce your overall risk without having to sacrifice return potential.
We won’t go into great detail here about how the correlation of the proposed investment to the portfolio as a whole is calculated (as it gets extremely complicated when you have more than two investments in the portfolio), but three very simple examples of how a portfolio’s standard deviation is calculated and how correlation plays into that calculation will demonstrate the importance of the correlation coefficient. In the examples below, the correlation figures indicate the correlation between each of the two assets involved in each portfolio; not between the portfolios themselves.
Portfolio #1: Assets #1 and #2 could represent large blend stocks.
Portfolio #2: Asset #1 could represent a large blend stock and Asset #2 could represent a publicly traded real estate investment trust (REIT).
Portfolio #3: Asset #1 could represent a large blend stock and Asset #2 could represent a commodity based trading account (note the higher return and standard deviation).
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*These hypothetical examples are for illustrative purposes only and are not intended to represent any specific investment. The examples do not consider any costs associated with investing. Investments involve risk and you may incur a profit or loss.
Thus, in Portfolio #1 we had two assets (but only one asset class) of equal risk, which, when combined resulted in a portfolio just as risky as the investments were on a stand-alone basis. However, in Portfolio #2, although we had two assets of equal risk (but two different asset classes), when we combined them the resulting portfolio contained 13% less risk than Portfolio #1. Finally, Portfolio #3 contained two assets of varying return and risk (two different asset classes) which when combined resulted in an expected return that was 25% greater than that of Portfolio #1 with 19% less risk. Thus by simply decreasing the correlation between the assets contained in the portfolios we have been able to lower risk while maintaining, if not increasing, return.
In our next article we’ll describe what some of these "alternative" asset classes are and how they could affect your portfolio.
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