To be an effective and a successful investor, understanding your portfolio’s absolute sensitivity to market volatility is of great significance. After all, no investor would want to be largely exposed to a same source of risk, which would result in a mass destruction of his portfolio should the risk event occur.

One of the most important takeaways from the stock market crash during the Great Recession was to avoid being overly invested in any particular asset class, industry, or economy. Traded securities are usually related to each other, either positively or negativity, and no single security trades completely independent of others or broader market moves. As a result, awareness of correlations and their application to control your portfolio’s exposure can substantially reduce your risk by spreading it over several events the likelihood of all events triggering at the same time is considerably less.

Now, some of what we need to get out of the way first about correlation is going to be obvious. Just bear with me – there’s a reason we want to pull all the details on the table, so let’s just start at the beginning, shall we?

For the uninitiated, correlation is the statistical measure of relationship between two or more entities, in the financial world, between two or more securities. In other words, correlation measures the degree to which prices of securities move in tandem or in opposite directions. The correlation coefficient spans between -1 and +1, where a correlation of -1 indicates that the two securities move in the opposite directions 100 percent of the time and a correlation of +1 indicates that the two securities move in the same direction 100 percent of the time. Accordingly, a correlation of 0 indicates that relationship between the two securities is completely random. That said, perfect positive, negative or neutral correlations are highly improbable and are almost never reached.

Discernibly, all asset classes, industries, sectors, sub-sectors, and other such classifications are defined on the basis of correlations. It can be said that correlation between assets is the defining factor of an asset class in the first place. An asset class therefore, is just a group of securities that have comparable characteristics, possibly subject to same regulations, and display similar price fluctuations.

Several analysis platforms and charting packages provide correlation data today, yet one of the most easiest and effective ways of determining the correlation (coefficient) between two securities is by using the CORREL function in Microsoft (MSFT ) Excel. Basically, you’ll have to download historical daily prices of the securities you want to analyze, then transport the data into an Excel worksheet and find correlation by using the correlation formula; syntax: =CORREL(range1,range2).

In the chart above, we have calculated the correlations among S&P 500 Index. US Dollar Index. and Gold prices over different periods of time. In 2013, equities and gold prices showed strong negative correlation. Although the pair exhibited a decent positive correlation in Q1 this year, the larger negative trend still continues. Next, the pair of gold and US dollar-index showed strong negative correlation as well, which is not surprising as ounces of the yellow metal are priced in the U.S. Dollar. Lastly, the analysis of the US Dollar and US equities showed a neutral to positive correlation over the last few quarters. This implies the U.S. Dollar and the S&P 500 Index exhibit a week-but-positive correlation.

You can use the one-year, six-, three- and one-month trailing data to derive a comprehensive view of the similarities and differences in correlation over time. However, most securities will be positively correlated in the long haul. This is because all prices rise in the long term, at least by as much as inflation levels during that period (see chart above).

The most common application of correlation comes in the form of diversification. Strong positive correlation between two traded-securities (or any classifications) implies a common source of risk. Meaning, analysts or investors study assets correlations to avoid a common source of risk to their investments. As a matter of fact, market experts spend numerous hours in devising investment strategies that aim to achieve a positive return regardless of the market trend. In doing so, they thoroughly scrutinize the investments based on correlations. Needless to say, a sound understanding of correlation, its calculation and application can greatly reduce an investor’s risk. And even though preferences and risk tolerances vary from person to person, there is a risk-averse creature in every investor.

Source: www.moneywise.co.uk

The general rule of thumb is to reduce correlation of an investment portfolio, which bring back to the mind the traditional theory of diversification: “Don’t put all your eggs in one basket.”

Analysis of correlations will help you avoid taking positions that double up your risk or positions that cancel out each other. For instance, by knowing that AUD/USD and NZD/USD move in same direction nearly 100 percent of time, you would see that having a long position in both these pairs is similar to doubling up on the same positions since the correlations are strong. On the other hand, holding long EUR/USD and long USD/CHF is virtually a no-position – this is because the 2 currency pairs move in opposite directions almost all the time.

The concept of correlation is being used in many different ways in the financial markets. For instance, there are several investment instruments available today that have been devised to benefit from correlation or randomness of securities, including mutual funds, exchange traded funds, hedge funds, etc. That said, some of these instruments are only be available to certain types of investors.

An Example of Correlation Matrix

Correlation in stocks is usually represented by a statistical measure called ‘beta’. It is a popular indicator of risk that measures of stock’s volatility in relation to the market. By definition. the broader market has a beta of 1.0, and individual stocks are ranked according to how much they deviate from the market. Accordingly, investment strategies are based on beta similarities or differences of stocks. For example, a commonly used stock investing strategy dictates buying low-beta stocks while shorting high-beta stock in periods of market uncertainty. The basic premise here is that low-beta securities tend to outperform high-beta ones when uncertainty increases and therefore, will produce superior results. Likewise, several other asset classifications and instruments are traded for an overall ‘low’ correlation. If two pairs of assets, let’s say, Assets Pair A and Assets Pair B, are likely to offer the same return at the same risk, choosing the pair with low correlation decreases the overall risk of the portfolio.

Disclosure: The author has no positions in any stocks (or securities) mentioned, and no plans to initiate any positions within the next 72 hours. The author wrote this article herself, and it expresses her own opinions. The author is not receiving compensation for it (other than from Samrikir). The author has no business relationship with any company whose stock is mentioned in this article.