Signal Type	Trade Date	Return since issued
		World	U.S.
			Nasdaq 100 (QQQQ) Russell 2000 (IWM) S&P 500 (SPY)

Market Update

If stocks ended little changed during this holiday-shortened week, it was not for lack of action. Indeed, all major averages posted solid gains Monday on news that existing-home sales jumped 10% last month, far more than anticipated. An increase in commodity prices caused by a weakening dollar also helped push stocks higher. The S&P 500 gained 1.4% on the day. Good economic news, such as better-than-expected consumer spending in October, allowed stocks to advance modestly over the next two sessions, enough for the S&P 500 and Dow Jones Industrial Average to close Wednesday at their highest level of the year. While U.S. investors were enjoying Thanksgiving the next day, foreign bourses suffered stiff losses on news that Dubai might be unable to repay its debt, raising fears that the world economy could face yet another financial crisis. The news put pressure on stocks when U.S. markets reopened Friday, with the Nasdaq Composite starting the session 2.8% lower. Market participants obviously decided that the dip was a buying opportunity, as the major averages reversed course to recoup a good chunk of their losses, the Nasdaq Composite finishing 1.7% in the red Friday. The session's trading volume was very light as is always the case the day after Thanksgiving.

The Nasdaq 100 (QQQQ) and S&P 500 (SPY) respectively gained 0.16% and 0.13% this week. The two ETFs are located above both their 50-day and 200-day exponential moving averages (EMAs) while the Russell 2000 (IWM) still rests below its 50-day EMA after a 1.72% weekly loss.

For its part, our World portfolio posted a 0.61% loss this week. The portfolio consists of the 5 top-ranked world ETFs as of November 6, which marked the beginning of the current 4-week holding period.

Our current Buy signal remains in effect.

Trend Timing School

Sharpen your Sharpe Ratio

Four weeks ago (October 30, 2009) we wrote about the use of standard deviation as a measure of risk. You will recall that this article on risk and volatility ended with the general conclusion that risk, as expressed in terms of volatility and standard deviation, is not a very useful indicator by itself, but begs to be placed in the context of returns. While we vaguely remember that we have to accept higher risks in order to achieve higher returns, we also know that the better investments are the ones at the high end of the reward-to-risk scale. For example, what would be the point of holding an extremely low risk investment that consistently loses money, or to take disproportionate risks for mediocre returns?

Luckily, a fellow named William Sharpe came to the rescue by inventing the most widely used direct measure of reward-to-risk, the Sharpe Ratio. Besides getting to name the ratio he also received the Nobel Prize for his work. We wonder which he values the most.

The simple definition of the Sharpe Ratio is a measure of performance calculated as the average return divided by the variance of those returns, or risk adjusted performance.

The formula for the Sharpe Ratio is:

S(x) = ( r_x - R_f ) / StdDev(x)

where:

x is some investment
r_x is the annualized rate of return of x
R_f is the best available "risk-free" rate of return (e.g. T-bills)
StdDev(x) is the standard deviation of r_x

If the formula sounds too complicated, there is only one thing to remember: the higher the Sharpe Ratio, the better. The number will go up with larger annualized returns and/or lower risk/volatility. Understanding that you have better things to do with your week-end than crunching the Sharpe Ratios, we decided to run the numbers for you. We included our three preferred index ETFs QQQQ (Nasdaq 100) , IWM (Russell 2000) , SPY (S&P 500) and our World approach, showing side-by-side the Long Only, Long and Short and Buy and Hold strategies for comparison. For the "risk free" return, we have been using the 13-week T-Bill historical data (a good approximation to a typical money market return over time). We did the calculations over three different time periods, namely the last 12 months, the last 5 years and the last 9 years (more precisely from January 2001 until October 2009). Using various time periods will help us show that the results were not affected by a particular phase of the market cycle. The tables below summarize our findings with the Annualized Returns, Standard Deviations, and Sharpe Ratio sections separated out.

	Annualized Returns (%)
	Index	Long Only	Long & Short	Buy & Hold *
9 years Jan 01 - Oct 09	Nasdaq 100 (QQQQ)	16.0	30.9	-3.4
	Russell 2000 (IWM)	18.2	26.7	3.8
	S&P 500 (SPY)	10.3	17.4	-1.1
	World	22.2	38.8	9.6
5 years Oct 04 - Oct 09	Nasdaq 100 (QQQQ)	11.7	15.2	4.0
	Russell 2000 (IWM)	11.7	13.0	2.1
	S&P 500 (SPY)	7.3	8.2	0.2
	World	21.5	25.8	8.8
1 year Oct 08 - Oct 09	Nasdaq 100 (QQQQ)	31.9	31.9	9.0
	Russell 2000 (IWM)	34.4	34.4	-9.0
	S&P 500 (SPY)	24.9	24.9	-8.3
	World	32.7	32.7	-5.6
*: Showing the "Buy & Rebalance" strategy for the World approach

	Standard Deviations
	Index	Long Only	Long & Short	Buy & Hold *
9 years Jan 01 - Oct 09	Nasdaq 100 (QQQQ)	0.16	0.19	0.28
	Russell 2000 (IWM)	0.13	0.15	0.22
	S&P 500 (SPY)	0.10	0.12	0.17
	World	0.15	0.20	0.23
5 years Oct 04 - Oct 09	Nasdaq 100 (QQQQ)	0.13	0.13	0.22
	Russell 2000 (IWM)	0.13	0.14	0.23
	S&P 500 (SPY)	0.09	0.09	0.17
	World	0.17	0.18	0.26
1 year Oct 08 - Oct 09	Nasdaq 100 (QQQQ)	0.11	0.11	0.32
	Russell 2000 (IWM)	0.13	0.13	0.41
	S&P 500 (SPY)	0.11	0.11	0.32
	World	0.21	0.21	0.41
*: Showing the "Buy & Rebalance" strategy for the World approach

	Sharpe Ratio
	Index	Long Only	Long & Short	Buy & Hold *
9 years Jan 01 - Oct 09	Nasdaq 100 (QQQQ)	0.9	1.5	-0.2
	Russell 2000 (IWM)	1.2	1.6	0.1
	S&P 500 (SPY)	0.8	1.3	-0.2
	World	1.3	1.9	0.3
5 years Oct 04 - Oct 09	Nasdaq 100 (QQQQ)	0.7	1.0	0.1
	Russell 2000 (IWM)	0.7	0.7	0.0
	S&P 500 (SPY)	0.5	0.6	-0.2
	World	1.1	1.3	0.2
1 year Oct 08 - Oct 09	Nasdaq 100 (QQQQ)	2.8	2.8	0.3
	Russell 2000 (IWM)	2.6	2.6	-0.2
	S&P 500 (SPY)	2.3	2.3	-0.3
	World	1.6	1.6	-0.1
*: Showing the "Buy & Rebalance" strategy for the World approach

First, when observing the standard deviations we note that, surprisingly, the Buy and Hold strategy is actually more volatile than the Long and Short one, which contradicts the general belief that Trend Timing is riskier than the no-brainer Buy and Hold approach. The Long Only strategy is also marginally less volatile than its Long and Short counterpart.

But the revelation comes with the Sharpe Ratio numbers which, by factoring in the performance (annualized return), totally debunk the myth about Buy and Hold being less risky than market timing, or trading techniques such as selling short. The numbers clearly reveal that in terms of reward-to-risk, all our Trend Timing strategies beat Buy and Hold across the board, by big margins. The numbers also confirm that in every case the Long and Short strategy offers the best Sharpe Ratio, or reward-to-risk ratio, which justifies its continued position as our mainstream strategy. It is also worth mentioning that our timing system works best with the World approach, beating the U.S. index ETFs on the Sharpe reward-to-risk scale, the only exception being the recent 12-month period where its higher volatility put it behind.

FAQ of the Week

Question: What investment vehicles are your performance numbers based on?

We are often asked how the performance numbers on the 'Results' page are calculated.

First, with the intent to better match the reality of your trading, we do not use the market indexes themselves, but their corresponding ETFs instead: QQQQ for the Nasdaq 100, IWM for the Russell 2000 and SPY for the S&P 500.

Second, we always start each trade using the open value on the day that immediately follows a signal change. We do the same thing for the World approach, using the open price of each ETF on the trading day that immediately follows the signal change.

Finally, Sell signal performance numbers are calculated using the traditional shorting method, which can bring slightly different results than the use of inverse ETFs (for more on this, please visit the article we wrote on January 23, 2009: What to expect from Inverse and Leveraged ETFs?).

Warm wishes and until next week.

The TimingCube Staff