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Signal Update
Current Signal Performance as of
Signal Type
Trade Date
Index
Return since issued
Nasdaq 100
Russell 2000
S&P 500
QQQQ

Cumulative Returns since First TimingCube Live Signal () as of
Index
Long Only
Long Only
with
Margin
Long & Short
Long & Short
with
Margin
Buy & Hold
Nasdaq 100
Russell 2000
S&P 500
QQQQ

Note: QQQQ returns are included for continuity sake.

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Market Update
With the markets closed today for Good Friday, the Holiday-shortened week saw lower than usual volume, as expected, but turned out to continue the negative bias we have seen recently. Despite an upbeat profit outlook from GE and some M&A (Merger & Acquisition) excitement over the completion of Kmart's acquisition of Sears, the rallies attempted on Wednesday and Thursday faded by the close on growing inflation worries, interest rates hikes by the Fed, and continued crude oil price concerns. For the week, the large cap companies in the S&P 500 suffered the most with a loss of 1.53%, followed by the Russell 2000 and the Nasdaq 100 shedding 1.17% and 0.97% respectively.

What's more, on Thursday we officially moved to bear market territory with the Nasdaq Composite Index 10-day EMA dipping below the 200-day EMA and in the process shifted us to Quadrant 3 Bear/Sell (please refer to our October 31 and December 19, 2003 Trend Timing School articles for more information on our definition of bull and bear markets and Trend Timing Quadrants). While the index is in the close vicinity of its 10 and 200-day EMAs we can easily slip in and out of the bear market definition, but being this low constitutes a clear bearish statement in its own right. This week's market action has gone to reinforce our active Sell signal.

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Trend Timing School
Risk and volatility

We have frequently discussed risk in these pages as well as methods to manage the risks we take, such as diversification. A good overview of our views and positions regarding risks and rewards can be found in the May 14, 2004 article. Unlike gains and losses which are real, risk is in general just a vague and abstract notion, on a scale ranging from low to high. We instinctively know that in order to achieve superior returns we have to take higher risks. For example, a money market fund or government treasury fund would have a very low risk but also lower returns than say a portfolio of blue-chip large companies which, for comparatively more risk, will also deliver higher returns. At the high-end of the risk/reward curve you can find small cap indices or funds with the highest return potential but at the cost of high volatility. Today we will attempt to get at the metrics which characterize risk and how it can be measured.

Risk can be viewed in many different ways: as volatility of price, as risk of losing the investment, or simply the possibility that something different than expected will happen. To demonstrate the shifty nature of what is meant by risk, we take the example of keeping a large part of our assets in cash. You could say that the risk is non-existent because you are guaranteed to have the same amount of cash in the future (except for fires and thieves, of course), or you could say the risk is infinite because you have the certainty of steadily losing money or purchasing power to inflation by keeping your assets in cash. In this case our opportunity risk is what counts, because cash holdings are not actively growing our wealth as they should be.

Most of the time risk is linked or even equated to volatility. When an investment rises and falls drastically over short period of times it is also considered high risk because its performance could change quickly in either direction at any time. If two investments provide the same return, we clearly prefer the one that does so with the least amount of volatility. By far the most common and widespread volatility measurement is what statisticians call standard deviation. It is the measure of how widely dispersed from the mean a series of values are. The values can be anything such as price or return of an investment or index. All it takes is a number of data samples at fixed intervals over a period of time, and a good dose of elbow grease.

The best way to explain the standard deviation calculation is to use an example, and in our case it is to look at the 5-year TimingCube returns of the Nasdaq 100 with a Long and Short strategy (see Chart below). The steps are:

  • Calculate the average (mean) annual return over the 5 years (sum divided by 5)
  • Find deviation for each period (return minus 5-year mean return)
  • Calculate the square of each period's deviation (deviation times deviation)
  • Sum all the squared deviations
  • Divide by 5
  • Take the square root of that number to get the standard deviation

Standard Deviation (volatility) of TimingCube Returns for the Nasdaq 100 Index,
'Long and Short' Strategy

 
Return
Deviation
Deviation squared
2000
116.88%
0.50
0.25
2001
110.69%
0.44
0.20
2002
61.59%
-0.05
0.00
2003
38.27%
-0.28
0.08
2004
4.75%
-0.62
0.38
     
5-year mean return
66.43%
  
Sum of squared deviations
  
0.91
Sum of squared deviations/5
  
0.18
Standard deviation
0.43

In the example, the 5-year standard deviation is 0.43 which does not mean anything by itself.
Since you could vary the intervals and the time period, say from 5 years to 36 months, to obtain a different standard deviation number, what really counts is comparisons with other references. In general a higher number means a more volatile and risky item. Indeed, the same calculations for the S&P 500 5 years, Long and Short strategy yields a much less volatile 0.14. Another comparison sheds some light on a major flaw of standard deviation, which is that it is directionless. Looking at an investment gaining exactly 10% every year, its standard deviation is zero because none of the years deviate from the 5-year average. Ironically, an investment losing 10% every year has the same perfect standard deviation of zero!

Standard deviation really measures volatility by how much the individual samples deviate from the average of all samples, with no regard to gains or losses. This is best demonstrated by looking at the same 5-year period for the Nasdaq 100 but this time with a Buy and Hold strategy (which lost 56.84% as compared with the Long and Short gain of 924.26%) we get a standard deviation of only 0.34, substantially better than the 0.42 obtained when following the market trend.

This just goes to prove that risk or volatility by themselves have really little meaning and that what we should focus on instead is risk adjusted performance, which just happens to be next week's topic. Who says we don't believe in coincidences?

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FAQ of the Week
Question: How can I verify that I receive your e-mails correctly?

A number of you have not received the recent Sell signal e-mail message that we sent to all subscribers on the evening of March 16, 2005. Alas, on our end we can only ensure that we send the notification to the e-mail address(es) listed in your "My Profile" page, but we cannot guarantee they are properly delivered and received.

If you have an "Unwanted Mail", "Spam" or "Bulk" folder of some kind, you might want to check its contents to see if our message was not stored in it by mistake because of some over-zealous anti-spam filtering. You might also want to check with your ISP to see what happened. Some ISPs provide safe lists in which case you should add
info@timingcube.com, support@timingcube.com, and sales@timingcube.com
to make sure our messages are not filtered out as spam.

You can send yourself a test e-mail by clicking on the corresponding button at the bottom of the "Current Signal" page after you log in. We also recommend using your "Alternate e-mail address" which could give you an additional message routed through a different ISP.

Warm wishes and until next week.

The TimingCube Staff

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