Most people are familiar with the concept of bell curves, standard deviations, distributions, means, etc. According to Wikipedia, “In probability theory, the normal (or Gaussian) distribution is a continuous probability distribution that has a bell-shaped probability density function, known as the Gaussian function or informally the bell curve.”

The accompanying illustration depicts a typical bell curve like most of us learn about in high school.

Probability theory has been applied to investing with the assumption that returns and volatility will fall within a normal distribution. In reality, that is rarely the case.

Investments with low volatility like short-term bonds have smaller expected returns and a tall, skinny-looking bell curve. Stocks have a higher expected return and a flatter curve. That is because they more often produce results that are much better or worse than average.

This is important in order to understand that investment risk does not adhere to a typical distribution pattern. Whether the curve is tall or flat, there are usually far more outliers than one would expect from a bell-shaped distribution.

Gary Elsner, Ph.D., the editor of an investment newsletter Achieve Profits wrote this about standard deviation:

“The standard deviation is a good measure of volatility, since it measures the amount of variation around the average and is probably the most widely used measure of financial risk. But the standard deviation has two weaknesses for financial instruments. First, it measures the variation from the average in both the up (good) direction as well as the down (bad) direction. Second, the standard deviation does not distinguish between short or long sequences of losses.. Investors are only concerned about downside risk (or the potential for losses), whereas upside changes or rapid increases in value create profits.”

Standard deviation is a measure of volatility regardless of whether it is above or below the mean. But when it comes to investing, investors have no problems with volatility when investments are moving up rapidly. Only the negative moves that cause concern.

Because of that investor bias, Peter G. Martin recognized the folly of using traditional volatility or standard deviation measures to measure risk aversion. In 1987 he created a tool called the ulcer index (UI) that focused exclusively on the negative side of volatility.

According to Martin, his index “measures the depth and duration of percentage drawdowns in price from earlier highs. The greater a drawdown in value, and the longer it takes to recover to earlier highs, the higher the UI. Technically, it is the square root of the mean of the squared percentage drawdowns in value. The squaring effect penalizes large drawdowns proportionately more than small drawdowns (the SD calculation also uses squaring). In effect, UI measures the severity of drawdowns.”

In other words, the UI considers the depth and duration of drawdowns. An investment that offers the same return as another investment that has more negative volatility will be more palatable to investors.

This concept is illustrated in the accompanying chart. Fund A and Fund B start and end at the same return over the same period of time. An investor who experienced the performance of Fund B, however, is likely to endure more stress because the drawdown is more severe and endures for a much longer period.

In addition to feeling more emotional stress and pain, an investor holding Fund B is more likely to succumb to investment anxiety and sell his position at the bottom. That would lock in his losses and possibly prevent him from recouping those losses when the fund turned upward again.

Martin and Byron B. McCann first described UI in their 1989 book, The Investor’s Guide To Fidelity Funds. In the ensuing years, it has gained wide acceptance as a superior means to measure investment risk.

For anyone who would like to learn more about UI–including the formula—a web search will turn up numerous sources of information.

Flint Stephens

So far in 2012 stocks have been advancing on a steep upward slope with no significant pauses or corrections. The situation in Europe threatens to disrupt the smooth ride, but the bumps have not yet been enough to derail the strong rally.

I have always acknowledged that I don’t have any predictive ability when it comes to knowing what the stock market will do and I don’t believe anyone else does either.

But I do believe that there are many technical indicators developed by extremely smart people that can help assess the strength and momentum of the markets. Today those indicators are about as strongly positive as they ever become.

The chart below of the S&P 500 (SPX) illustrates the current situation. The gold line on the top portion of the chart is a 50-day simple moving average (MA). I added it because it is a good indicator to help determine when a rally is losing steam. When the price movement drops to the 50-day MA, then one should be nervous about whether or not the advance will falter. Right now SPX is still trending well above its 50-day MA.

The next section of the chart is a moving average convergence divergence (MACD). Although this indicator has flattened out, it remains strongly positive and has not yet reached such an overbought extreme that a major correction appears likely. I like to compare this indicator to measuring the tension in a rubber band. Right now it is stretched tight, but it has not reached a breaking point.

The next chart section is a stochastic oscillator. It measures random market cycles and can be used to help pinpoint market turning points. It turned downward a couple days ago, but you can see that the past three times it turned down it was not able to complete a full cycle. That normally occurs when the market is in a strong advance.

Finally, the bottom portion of the chart is a relative strength index (RSI). Anytime the RSI is trending above 50, it means the market has the momentum and strength to sustain a longer-term rally. The RSI recently approached 80. Usually at that high level some sort of consolidation will take place. But there is currently nothing to indicate that the RSI will break below 50 anytime soon.

The advance since late December has been the strongest in more than a year. Like a tea kettle that has reached a full boil, it now needs to vent some steam to release pent-up pressure.

It would not be surprising to see a couple weeks of market consolidation or correction from this level. But so far there is nothing to indicate that a serious correction is on the immediate horizon.

Flint Stephens

The importance of diversifying one’s assets is not a new idea. Most people are familiar with the phrase “don’t put all your eggs in one basket.” I keep about two dozen chickens in my yard, so I understand clearly the origins of that expression.

If a person is out gathering eggs and the eggs are all together, a single misstep or drop can destroy all of the eggs at once. Long ago someone figured out that if the eggs were divided and the person carrying the eggs fell or dropped the basket, at least some eggs would remain for that day’s needs. Six eggs might not be as good as a dozen, but it is better than no eggs.

Unfortunately, diversifying investment assets can be more difficult than just separating eggs into different baskets. A few weeks ago I touched on this subject and pointed out that even assets than seem dissimilar sometimes are highly correlated in their movements.

http://www.marketowl.com/2012/01/13/the-importance-of-diversification-and-correlation/

This concept can be difficult to explain and to understand, so I’m going to use the illustration of a star to help. Each point of a star is separate and distinct from the other points. To achieve true investment diversification, we want asset categories that have a low correlation—that are separate and distinct from each other like the points on a star.

The image below shows five asset categories that generally have low correlation rates: U.S. equities (S&P 500), U.S. bonds/dollar, energy, precious metals, and emerging markets.

The flaw with most attempts to manage risk by diversifying assets is that investors choose assets that are highly correlated. For example, if we added small cap stocks, value stocks, large cap stocks, international stocks and high-yield bond funds to our star, they would all gravitate near the same point as the S&P 500 because they all behave about the same.

Below is a chart that shows how ETFs representing the five asset classes on our star have performed over the past six months. As you can see from the price movements, there have been periods when one or more of these asset categories have moved in concert. But over the six months spanned by this chart, there have also been separate, distinct movement from each.

An investor holding a portfolio of equal positions of each of these investments would have achieved a return of about 14% over the period represented. That is less than the 20% return that an investor could have earned by being invested solely in the S&P 500. But the investor would not have endured the 10% decline the S&P experienced from its peak in October to its November low.

Imagine that each of the performance lines on the chart above was a road. There are hills and valleys and lots of potholes. There are really only two choices when it comes to dealing with the bumps and obstacles in each road. An investor can try to avoid the bumps, but that is difficult simply because there are so many and some might be difficult to see in the road ahead. The other way to deal with the bumps is to try to mitigate their impact.

The purpose of diversification is to act like a shock absorber for a portfolio. The goal is to smooth out the ride so one can attain performance that is something like the green line shown on the chart.

Some market experts argue that this type of diversification dilutes returns in a rising market. That is true, but for conservative investors who cannot afford big drawdowns or who cannot endure volatility this type of diversification offers an option for reliable risk protection.

Flint Stephens