For as long as people have been working to save food, money, or supplies for a later date, they have also made a tireless effort to protect what they have saved. Take, for example, the Mayan civilization in which they stored water in underground chultuns for later seasons when precipitation decreased. Another more current example is the Strategic Petroleum Reserve (SPR) which is the world’s largest stockpile of crude oil held for extreme circumstances. Arguably, perhaps the most pertinent example of all would be saving of monetary funds for emergencies, or high cost items like children’s education and/or retirement. If saving money for a later date is not hard enough, there comes a point in your investment time-line where a checking account, mutual fund, or a good stock pick simply are not enough. To fully protect your assets, diversification becomes critical to your savings. It is impossible to speak of correlation and diversification, without mentioning “the father” of such work, Harry Markowitz, the recipient of the Nobel Prize for his pioneering work with diversification. Subsequent theories, we cover in later articles, buttress his work, such as Capital Market Line, Securities Market Line, Efficient Frontier and C.A.P.M., ultimately brought the financial world to what we know today as Modern Portfolio Theory. A prudent portfolio using fundamental analysis in a top down approach is a timely exercise but very rewarding on many levels. To start off with, you will have more confidence in the industry and companies you have chosen due to your analysis. This, in turn, will help fortify you as you experience economic cycles and if done properly, you may be able to reduce your overall risk exposure and maintain your return within a reasonable range. To diversify your portfolio, you must select securities whose relative movements to one another are inversely related. In other words, when one security’s rate of return goes up, the other security’s rate of return goes down in equal proportions. Such movement would give you a perfectly negative correlation coefficient (see chart 1). In theory, correlation coefficient can have a value between “-1” to “1,” where “-1” represents an inverse relationship and “1” represents both securities moving in tandem as seen above in chart 2. Between the range of “-1” and “1” there are an infinite number of relationships securities may hold with one another. Please note, I did not state a security’s price but return; this is a common misconception among new investors. In fact, using Microsoft’s Excel correlation function is the same as using Pearson’s Correlation. Without getting into an immense amount of statistics regarding the different types or methods of correlation calculations, let us begin with a simple example. Starting with a portfolio equally weighted in Crude Oil and Gold and using a monthly average price data set from February 2008 to June 2009, you take the monthly prices to create a monthly return. Then you can calculate a monthly correlation between these two commodities. From a more technical stand point, prices are log-normal and hence if you take the natural log of the rate of return, you would achieve a normal distribution, which will allow for later financial models whom need such an assumption (in later articles I will dispel this assumption of normality). You can see graphically, these two commodities tend to offset each other and have a correlation coefficient of .0926 using Microsoft Excel Correlation function. Conceptually, correlation is easy to understand and follow in a virtual vacuum. However, to apply this concept on a portfolio of 100 securities or even 10 becomes very daunting. Much computing power is needed to calculate a correlation matrix while avoiding the many pitfalls needed to create a semi-definite positive matrix. Although correlation is arguably the most important factor of a successful diversified portfolio, it is one of many pieces of our mosaic that we are creating.

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