Risk is generally associated with financial losses first, then problems associated with assets not keeping pace with inflation. Different life events that can create financial risk are addressed via insurance. Insuring a financial risk is probably one of the last things you are thinking about when managing a trade, but not protecting yourself could certainly add to trade stress.

Expected Portfolio Returns

Since an investor's portfolio returns do not generally track the S&P 500 Index one-for-one, the individual needs to think about expected returns by better dissecting their portfolio. An analysis on a single broad-based index does not consider how the different securities and asset types in the portfolio behave relative to each other. Instead, securities should be grouped into different asset types and classes, and a correlation analysis performed.

Once the portfolio is broken into representative asset classes/types, a reasonable proxy index can be identified for each and expected returns can then be calculated for the whole portfolio. A scenario analysis for each index will likely provide a more accurate value than a straight average return calculation. See last week's article to see one approach to a scenario analysis.

Example

Table 1 provides investment ranges for a sample portfolio by asset type, along with allocation percentages and proxy indexes for each. The portfolio provided and allocation ranges are for sample purposes only and do not represent a recommended portfolio. You need to consider your individual constraints and preferences when constructing investment allocations.

Table 1: Portfolio Detail by Asset Type/Class with Index Proxy

Table 2 provides the correlation values between the S&P 500 Index and each index using daily return data from August 1991 through April 2009 (more than 17.5 years). The values range from -0.062 (not correlated) to +0.852 (positive correlation). To better understand the implications of the correlations, complete a text article search on "correlation" in the Daily Articles section of Optionetics.com. Here, the =correl() function in Microsoft Excel was used on daily data downloaded from Worden Brothers TeleChart 2007 and the St. Louis Federal Reserve Bank's FRED database. Weekly correlations will provided stronger relationship data since shorter-term noise is reduced.

Table 2: Correlation Data

A portfolio constructed with securities that track the above indexes will not have the same returns as the S&P 500 Index over the long-term. Instead, each index should be used as part of a weighted average using allocation ranges or current allocations to get a better sense of expected returns. Due to space constraints, a straight average is used in the example since one potential scenario analysis using the S&P 500 Index was provided last week.

Table 3 provides return data by index for the portfolio's sample allocation.

Table 3: Return Data by Index
* Price fluctuations only.

The sum of the last column provides the investor with a rough estimate of the expected daily return of the portfolio (0.015%). While this value is less than four of the five proxy indexes, the portfolio as a whole will experience less volatility and will be less affected by the fat-tail returns (i.e. losses) of any single index. Asset allocation is a generally accepted means of managing portfolio risk.

Inflation

One main reason people invest in the stock market is to realize gains that will outpace inflation. Fixed income returns are considered insufficient to overcome this inflation risk. Part of knowing your risk means understanding inflation trends and the extent to which market returns outpace the rising cost of goods.

Figure 1 displays the continuously compounded monthly rate of change data for the Consumer Price Index for All Urban Consumers (All Items) from the St. Louis Fed from 1910 through June 2009. It is not seasonally adjusted. The chart is displayed in this manner to highlight shorter-term trends in general as well as recent increases in volatility for the measure.

Figure 1: Monthly CPI Data 1910 - 2009 from the St. Louis Federal Reserve Bank

More information on how the data is constructed is available at the website displayed with the chart. In addition to a variety of chart views, easily downloaded monthly data is also available from the site. The most recent five years of data is displayed in Figure 2.

Figure 2: Monthly CPI Data 2004 - 2009 from the St. Louis Federal Reserve Bank

In recent decades there were extended periods of time when consumers were minimally impacted by rising costs. Although the most recent volatility spike resulted in lower costs, there are no guarantees that volatility will only persist in one direction, if at all. Investors should understand CPI data construction and view past trends to identify reasonable expected inflation for the future when determining if returns will outpace rising costs.

Vive le Tour.

To access other articles written by Clare White, please click here.

Clare White
Contributing Writer and Options Strategist
Optionetics.com ~ Your Options Education Site
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