How Much Money Can You Stand to Lose?
I’ve always said that there is a disconnect when it comes to defining and understanding risk between the investor and the industry.
- Disconnect number 1. When the bear market hits and a mutual fund looses 15%, the industry says that is good because the market lost 20% and the average loss for a comparable fund is – 18%. In relative terms the fund lost less than a comparable benchmark. The investor on the other hand thinks that losing 15% is not a good deal no matter what everyone else thinks.
- Disconnect number 2. The industry looks at standard deviation as the proper definition of risk. Standard deviation is the amount of fluctuation that can occur day to day, week to week, month to month or year to year. The investor cares less about fluctuation and more about loss. If you think about it, it is possible that you can have a fund that fluctuates between 0% and 100%, which is considered a high standard deviation, and by industry terms high risk. An investor however looks at the chance of loss and says that this fund has no risk. While this example is extreme, it illustrates the disconnect between the industry and investor.
Researching the downside risk
With the reality of this disconnect, the investment industry needs to do a better job offering research solutions to help investors evaluate risk from their perspective. One of the best ways to analyze risk is to look at downside risk data.
What is downside risk data?
I’ll often compare downside risk analysis to lifeboat drills. When we plan activities in the water, we have to prepare ourselves for the worst – like drowning. Since emotion is a huge part of decision-making, doing such drills can make difficult situations easier to manage.
We put investments, like a mutual fund through lifeboat drills by simply back testing them in periods of distress or negativity – like corrections or bear markets. By seeing how they perform during the worst times, we have a better understanding of how these investments will react to future periods of stress. By predicting the worst, the investor gains insight. If future problems do arise, they can likely be handled with more logic, greater comfort and less emotion.
For example, if we study how an investment has done following the crash of ’87, the Mexican peso crisis of ’94, or the world currency crisis of ’98, or best yet, the technology bust of 2000, we can better predict how that investment will react in future crisis. It won’t guarantee success, but it will give better understanding and therefore lead to better decisions.
Morningstar (Paltrak) data
When looking at downside risk data, I always refer to Paltrak (by Morningstar). Paltrak is a subscription-based program that has data they call All Time Periods (ATP) analysis. In this data they have the worst 1-year return. Essentially, this is the worst return a fund has had over any 12-month period on a rolling monthly basis. Let’s take a look at some of the data:
- With downside risk analysis, it is always better to look at funds with a longer time frame and ideally funds that have gone through a period of distress. As a result, I tend to take out funds that do not have at least 5 years of history. Any fund today with a 5 year history will have gone through the big bad bear of 2000 to 2002. As of December 31, 2003, there are 1817 funds that meet this criterion.
- The 5-year return for all 1817 funds ranged from a high of 44.3% (Okumus Opportunity Fund) to a low of -49.1% (@rgentum US Master Portfolio Fund).
- Only 154 funds (of the 1817 funds) have zero downside risk. This means they never lose money. All of these funds except 3 were fixed income funds with the majority being money market funds.
- There were 291 funds with downside risk of less than -5%. Essentially there were 291 of the 1817 funds that never lost more than 5% over any 12-month period.
- 27% of the funds (491) had a downside risk of less than -10%.
- 50% of the funds (887) had a downside risk of less than -20%.
- Amazingly 30% of all funds that have been around for at least 5 years have lost 30% or more over some 12 month period.
The bottom line
When you express risk in these terms, investors (especially conservative ones) might have made some very different decisions. Far too often we place too much emphasis on performance and not enough emphasis on risk. To compound the problem further, when we do try to take risk into account, it is usually the wrong risk data.