Jul 21, 2011
in Total Return
Total return is a concept that is surprisingly misunderstood. We get emails asking why does our moving average not match Yahoo or Tradestation?
Most Internet data sources and brokerage software platforms don't track total return -- yet total return is how all index returns are stated. In 2010, the SPDR S&P 500 index fund (SPY) was not +12.8%, it was up 15.1%. Vanguards investment grade bond fund (VCIT) was not +5.1% in 2010, it was +10.0% (and had some nice tactical swings throughout the year). The difference was distributions (which come in 2 forms: dividends and capital gains distributions).
One common thing we see is for various people to compare their performance to the price-only +12.8% and then footnote it saying 'dividends excluded'? To us, this is just as bad as mutual funds that claim the expense ratio is 1.2% and then footnote it saying you will be charged a 3% redemption fee if you sell the fund in first 5 years. There are no hidden fees with ETFs -- no sales loads, no purchase or redemption fees, no 12-b-1 fees. The 'A-class' 'B-class' 'C-Class' 'H-Class' 'I-class' mutual fund system is non-sensical in the ETF world --- there is only a single class of an ETF.
Here is another one: the Vanguard 60-40 stock-bond balanced fund returned +20.1% for the 10 years ended June 30th, 2011 [1]
[1] excludes dividends
Well, a large part of owning a bond in the first place is the coupon. As it turns out, that index fund (VBINX) was +59.7% INCLUDING dividends. So it is entirely disingenuous to compare to a number that is one-third of the actual index return.
While this is all obvious to some -- it is clearly still not understood by many.
We created a free Comparison Tool to make it easy to view this concept as we feel the only REAL way to truly understand something fully is to interact with it through an application -- rather than just read about in a paper or on a blog.
Try a few out. Be aware that even if its not a large dividend payer, any capital gains distribution will also affect the return.
Bond ETFs:
Others:
Jun 29, 2011
in Video
A brief introduction to the versatile yet easy-to-use 'Compare Portfolios' application located on the backtest page
Mar 18, 2011
in Backtest
It is well accepted in professional money management that having a quantitative aspect to your investment process is additive. That is, quantitative methods can greatly help in screening and monitoring lists of securities into a manageable ranking for further analysis. The vast majority of institutional-oriented firms do this kind of thing.
The classic, basic steps of an investment process involve:
- Install a (Quantitative) Method To Rank A Relevant Universe of Securities
- Take The Top-Ranked Securities And Do Further Research
- Construct a Portfolio Using Securities That Pass The First 2 Steps
- Monitor And Update The Portfolio
- Repeat
We view backtesting as a very practical and useful part of the research process. The way you rank securities should be based on something consistent with your beliefs on what actually works.
Once you have done some research and found a method to rank securities, run some backtests. You will learn about your method greatly and can understand more aspects and characteristics of such strategies. You will speed up your understanding and you will be forced to think through all the details of how you are going to execute your process.
Once you have created a portfolio (per Step 3 above), that portfolio effectively now becomes a ‘forward-test.’ Monitoring these portfolios and seeing these various rotation strategies behave is a crucial part of the process. Track your various rotation strategies. You can learn a lot by running many simultaneous ‘forward tests’ at once. Importantly, you will get a feeling for the ‘short-term noise’ that occurs around your strategy. Even for professionals, the psychological aspects of short-term volatility will cause them to doubt themselves. Back/Forward tests will make you much more aware of the kind of thing you will face in the future. You must get used to this as psychological aspects to investing are absolutely critical.
Back/forward-testing accelerates the learning process and you can then feed the incremental improvements you discover back into your actual portfolio. The point is that just doing a backtest and then ‘stopping your research’ is very limiting. Don’t stop learning, don’t stop improving. Small incremental improvements add up over time.
We are entering the golden age of active indexing. The specialized, targeted index fund is really a somewhat new phenomenon. Index funds in the 1980s were all very broad vehicles. Many specialized index products (Vanguard REIT index mutual fund, country fund ETFs) actually only have histories back to 1996. You can simulate prior performance -- but they weren't so inexpensively accessible. TIPS securities weren’t even issued by the Treasury until 1997. The World Equity Index products (mutual fund AND etf) didn’t launch until 2008.
Important new areas of future investment may come from newly investable products. For example, the emerging markets small cap index might become as mainstream a product as some other well-accepted benchmarks are today. Understanding the important indices of tomorrow might be as good an idea as understanding REIT and emerging markets indices when they were new PRODUCTS (ie, investable and tradeable at reasonable cost).
Understanding and processing relative performance, relative volatilities and observing relative drawdowns in present ‘forward-test’ environment strikes us as a pretty good idea.
iShares is bringing to market an Internationally focused preferred stock index. Wisdomtree just launched an Asia-Pacific regional intermediate bond ETF. Remember that at one point, the emerging markets index mutual fund was brand new (1994). Today it is a primary index everyone follows. Growth vs value wasn’t mainstream until the 1990s -- and indexing these products came later. The world evolves. Embrace the change and learn from it – let many simultaneous forward tests accelerate the learning.
Jan 19, 2011
in Down Days
As we enter a period of higher volatility after a long sustained move up in equities, we ran some statistics on 25 of the largest ETFs in the world to see how they performed on a relative basis when the S&P drops X%.
In this case, we chose to use 10 S&P pts, which works out to about 0.75%. How did various ETFs perform on just those particular down days?
Since the March 2009 low, the S&P 500 has dropped in excess of -0.75% eighty-five times. The average S&P 500 loss for these 85 days was -1.68%. Here are some results for 25 ETFs which summarize their performance on just those 85 days:
You can see that among the worst for this period were REITs (VNQ), U.S. financials (XLF), Brazil (EWZ) and U.S. Small Cap Stocks (IWM). It makes sense, these are all higher volatility market segments. Technology stands out for doing a bit better than you might have expected.
Bond indexes have low standard deviation and low correlation to U.S. stocks so they generally rose --- but as you can see, very modestly and not nearly enough to offset much of the loss in equities.
Gold, Preferred Stocks and High-Yield Bonds all show losses on average -- but more modest losses given their lower correlations with stocks. Dividend ETFs (DVY, SDY) were down on all 85 days (85 for 85) -- which isn't a big surprise. The dividend indexes didn't do particularly well on a relative basis however and lost almost as much as the S&P 500.
Now let's look at todays (Jan 19th) drop in various markets:
At the bottom of the list of todays (1-Day) performance are the exact same ETFs as the first list.
A couple of ideas here:
1) If you think you are going to get any diversification benefit from owning REITs in a down S&P market, we would tend to doubt that.
2) Bonds don't provide much absolute protection in S&P 500 down days --- but they do obviously serve their purpose of stabilizing a portfolio.
3) Dividend stocks may offer only modest protection in down markets.
Note that the China ETF (FXI) went up slightly today -- so there is the outlier of the day (of course no conclusion to draw here off 1 day of data).
Summary: it helps to study volatility and down markets. Todays performance was quite consistent with the same relative stats of the last two years.
Update: The first screenshot is now available in application form -- because it runs by auto-loading your user-created portfolios, it needs a login to access the page: ETFreplay Tools Page
Jan 11, 2011
in Relative Strength, Moving Average
We have added an optional moving average (MA) filter feature to the RS backtest app. With the recently expanded date start and stop functionality, the applications continue to get more versatile.
Combining a long-term moving average within the construct of relative strength has been highly requested and we wanted to discuss one idea when considering whether to use it (note that you can just leave it set to ‘off’ as well).
If you build a relative strength list of say 10 ETFs and you are choosing the top 2, you could protect your portfolio by including 2 bond funds. You don’t need a moving average filter because the bond funds will naturally be the ones with the relative strength when equity markets are dropping. This method actually can get more interesting because you can make better use of more type of ETFs. Rather than just use cash-like bond funds, you might want to extend the potential holdings to an intermediate bond fund like IEF (7-8 year duration) or others. You don't HAVE to restrict yourself to just stocks and cash.
Another way to test is by using a moving average. If you do it this way, then you will inherently be out of ETFs as they go into extended downtrends. You don’t have to proportionally keep X number of bond funds in your list if you do it this way.
But a lot of indexes can go above or below a long-term moving average and still not really be a source of market leadership and enhance your return. Moreover, you may save a lot of money between the time ETFs lose relative strength and the time they actually cross below the moving average. For these reasons, we believe adding relative strength to a MA strategy will generally be more robust. Adding MA to a RS strategy is optional -- and you may find works better or worse than your existing method. Continuous testing leads to better decisions.
