This week there were no position changes in the ETF Country Plus model. Our current three positions are FXI, TMF, and IFN. The stops and targets model was stopped out of TMF and will remain in cash until the model generates a fresh entry.
The MSCI World Index closed the week down -1.75%. The ETF Country Plus model ended the week up +0.55%. The ETF Country Plus Strategy is up +16.49% year-to-date compared to its benchmark, the MSCI World Index, which is now up +4.62% year-to-date.
This Week’s Strategy Lesson: Measuring Your Model (Part 3 of 4)
For this next installment of measuring your model, we will go through two important measures of risk, standard deviation and the Sharpe ratio.
Standard Deviation
Standard Deviation is a calculation of the dispersion of data points away from its average. In finance, this is a way to calculate the volatility of a holding. This calculation doesn’t care if the volatility is from positive or negative swings, it is only concerned with the average size of all the changes.
Standard deviation is based on a normal distribution. Many things in the world are normally distributed: Height and weight in humans, rainfall in a region, animal populations, even the distribution of stars around many types of galaxies.
The normal distribution is characterized by having a lot results clustered around the center with a severely steep drop-off in frequencies for extreme values. The average human height is 5’9’’. You would expect to find about 34 million men in the U.S. at that height but the frequency drops of severely from there as you go higher. Yao Ming is 7’5’’, fully six standard deviations higher than the average and there is only one other person in the world in his height range.
And the odds of seeing a 50 foot tall person? You might not expect to find him in the known universe if every planet was populated with earthlings.
Then there are things that are not normally distributed, like income or stock returns. Try your hardest, you may never run into a 50 ft. tall human, but you might run into one worth $50 billion.
Stock returns are not strictly normally distributed, but most of the time we can use standard deviation as a good approximation. In finance, it is used for this purpose for two reasons: the calculations are clean and simple and because we don’t actually know the real distribution of stock returns.
The monthly standard deviation for the SPY since 2007 is 5.5% and for the ETF Complete Portfolio is 4.6%. This means that there is roughly a 70% chance that your monthly return will be between -5.5% and +5.5% in any given month if you held the SPY.
This number may sound high, and it is in fact high in part because we are measuring the complete history as if the SPY was normally distributed. If you took out the five worst months for both models, the standard deviation of the two models is about the same around 4%. You could read this to say that most of the time the SPY is closer to resembling a normal distribution but occasionally it is less close to resembling a normal distribution.
The ETF Complete Portfolio has a lower average volatility than the SPY, but really the difference is being driven by a few months (most of them in the market crash of 2008) where the ETF models had smaller or fewer extremes than the SPY. In reality, most of the time you can expect them to have similar volatility.
Sharpe Ratio
Where you can expect the SPY and the ETF Complete Portfolio to differ is returns. This is where there is a big divergence between the two. The SPY had an average annual monthly return of 0.46% since 2007 while the ETF Complete Portfolio has an average monthly return of 1.92%, over four times higher on average.
The Sharpe ratio is a common ratio used to compare the annualized returns of a model or a fund to its volatility (standard deviation). Since it uses the standard deviation as a measure of volatility, and that is based on a normal distribution, it puts more emphasis on low and consistent volatility than some other measures of risk.
But because we know that stocks aren’t normally distributed (i.e. subject to potential big gaps or one days moves that dwarf the average), it also means that the Sharpe Ratio doesn’t tell you the “maximum” risk going forward, just the typical risk going forward if the future is similar to the past used in the sample.
Furthermore, the Sharpe ratio should be viewed in light of the other metrics we have examined because a high Sharpe ratio alone is not enough to know if a particular investment is right for you. A fund with a low return and an extremely low volatility might have a great Sharpe ratio, but at the end of the day, you are still getting a low return.
The ETF Complete Portfolio has a Sharpe ratio of 1.46. Typically a Sharpe ratio above 1 is considered good, but the primary way to use the Sharpe ratio is compare it to other funds or strategies since the calculation uses consistent terms no matter where it is calculated. The SPY has a Sharpe ratio of 0.29.
There are still other measures of risk. The Sortino Ratio is similar to Sharpe ratio, but instead of focusing on standard deviation of all the returns, it only looks at the downside volatility. Next week we will compare these two metrics and some of the important differences between them.
The Current Condition of the Model
For the country model, we are in FXI, IFN, and TMF. TMF was stopped out in the stop & targets model but it remains a position in the basic model and made a nice comeback this last week end on the highs for the week. FXI remains in fourth place and the gap between THD and FXI widened. We should expect a change should they diverge further in the next couple trading days.
Stay tuned to daily updates for any position changes.
Here is a summary of the weekly performance of all the ETFs that the strategy monitors:
Best wishes for your trading,
James Kimball
Trader & Analyst
MarketGauge