S&P 500 First Day Of Month Tendency

Mar 31, 2011 in S&P 500

Quick shot of how often S&P 500 has traded up vs down on first trading day of a new month.   While the S&P 500 has traded up more often than down, 2010 was not a 'normal' year.   Remember not to draw conclusions off just recent experience.  



Snapshot of 25 Exchange Traded Products -- Total Return For Q1 2011


New eBook on ETF Rotation:

Profiting From ETF Rotation Strategies In Turbulent Markets


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Getting A Feel For The DB Commodity Index: DBC

Mar 26, 2011 in Commodities

The business cycle favors different segments of the investment landscape at different times. Good relative strength analysis helps read money flows to give a view on how the market is indicating where we are in the business cycle in terms of stocks, bonds & commodities.

We highlighted the Deutsche Bank Commodity Index ETN (DBC) late last month and let's now take a closer look. One thing about the exchange traded market is that unlike being a stock generalist where various names turn over and you may never come back to some of them, what you learn now about the core ETF/ETN products will likely remain relevant for the rest of your investing life. One such family of indexes to get to know is the Deutsche Bank Commodity indices.

The DB Commodity index has four distinct components: Energy, Agriculture, Base Metals & Precious Metals. Each component has the convenient symbol structure of DB_ with the final letter telling you what it is. ie, DB[E] is Energy.

Deutsche Bank built DBC based on fourteen of the most heavily traded and important physical commodities in the world. "The Index commodity components were chosen based on the depth and liquidity of their markets and to provide diversified commodity performance." It makes sense that since Energy is the most economically important commodity group in the world, it should get the largest weight. That said, Deutsche Bank found a balance for diversification purposes and kept the energy component at 55%.

Below is a graph of the components and performance for this month. You can see that while precious metals have been strong (particularly Silver SLV), that the 10% weighting of Precious Metals is relatively small. The real driver here has been energy. Agriculture ( DBA) is down for the month but this has been dwarfed by the strength in the energy complex.


While commodities are less correlated to stocks than many other indices are to stocks, it should be pointed out that both commodities and stocks are at the core related to economic strength. That is, a bad economy reduces demand for commodities and also hurts corporate earnings, which negatively affects stocks. Correlations over time can be erratic so we need to be careful on assuming too much with regard to the diversification benefits of commodities.


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Backtests Become Forward Tests

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:

1. Install a (Quantitative) Method To Rank A Relevant Universe of Securities
2. Take The Top-Ranked Securities And Do Further Research
3. Construct a Portfolio Using Securities That Pass The First 2 Steps
4. Monitor And Update The Portfolio
5. 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.

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Commodity ETF Products At A Glance

Mar 03, 2011 in Commodities

ETF investors have been especially fond of energy stock ETFs. Here is a combined look at the growing popularity (and underlying appreciation) of energy equity ETFs from the 'Big 3' (SPDR, iShares and Vanguard).


But perhaps more important is the continued growth of commodity exchange-traded products. Many tactical participants consider commodites to have cleaner trending behavior than stocks and therefore somewhat easier to trade. We won't attempt to try to show this within a blog. We will point out though that there are also options markets made on commodity ETPs as another way to access these markets.

It's interesting to take a look at the amount of money being made off these growing asset bases by the providers. This has become significant. Even excluding Gold products (GLD, IAU, DBP etc...) and only using the top 13 as a sample, we see these products generating approximately $220 million in annualized fees at current (February month-end) levels. If you include GLD and others, this number more than doubles --- call it $450 million. While that sounds like a lot, consider that these products charge less than 1/2 of what mutual funds charge on a percentage basis. And mutual funds have $9 trillion in assets. (note that Vanguard has not entered the commodity ETN space or else things might be different).


By viewing assets, we see the combination of price strength and investor inflows/outflows -- which has caused this group to rise very quickly. I put these 13 together to show the growth in assets since the middle of 2009:


Finally, I used the free Backtest Portfolio Allocations App to create my own custom equal-weighted master index that shows the actual investor ETN return since the middle of 2010 (excludes USCI because its history is too short).


List of Commodity ETFs


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Notice: New Feature Added To Backtesting

Feb 25, 2011 in Backtest | Relative Strength

Last summer, we added a feature to the portfolio relative strength backtest application. We added a line that showed what the 'provisional picks' would be if the update period had just ended. The provisional picks listed are the exact same as if you ran the ETF screener using the same list of ETFs and same parameters. We added this feature just as a convenience so it wouldn't be necessary to open another tab and check what was strongest now -- rather than at the last update period.

Depending on the list you use, it is of course possible that the 'provisional pick' is not the final pick (hence the term 'provisional'). But what if we just looked up the provisional pick on the next-to-last day of a given month and bought that ETF the next day on the close and held it for the subsequent period? What would the performance look like assuming we did that? Would it be similar?

Let's look at a simple example just to discuss the mechanics of what we mean. We will compare using the 'next-to-last day picks' with the 'last day picks.' The holding periods will be the exact same, we are just reading the picks of the ETF screener with a one day offset. Of course, for many periods the picks (and therefore performance) will be the exact same.

In this example, we will use one of the Ivy Portfolio lists of 5 basic ETFs and a semi-monthly update period. We are choosing the top 1 of 5 and holding it on 2-week intervals. The settings are the exact same except we are checking the box "Invest in next to last day pick(s) near the top of images below.

Using Regular 'Last Day' Picks:

Using Next To Last Day Picks:

We can see that the returns follow similar paths but that there was a difference -- even for this list of just 5 ETFs. In this case, the next-to-last day picks actually performed better -- which means very little in and of itself. We simply are pointing out the mechanics of how it works. Users should test this using their lists across various other settings and draw their own conclusions. Our view is that this doesn't change anything -- if your backtest is well thought-out, then this extra analysis will very likely show a result that is in the same ballpark as the original method.

Final note is that today is Friday, February 25th -- so the next-to-last days picks will be locked in and known after todays close. The final picks will update using Monday's (Feb 28) closing price. In both cases, the backtests will assume the cost-basis for March performance is the closing price as of Feb 28.


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Summary of ETF Performance Since Just Before Fed Embarked on QE2

Feb 15, 2011


Back in beginning of November,  the Fed began QE2 --- though it was extremely well telegraphed in advance as yields had already dropped substantially.   Since that time, here is quick snapshot of how various indexes have performed:




The Outperformance of Economically Sensitive Groups in Developed Markets

Feb 10, 2011


Divergences have developed in the marketplace.    There will be rotations ahead at some point but real-time relative strength analysis has greatly aided portfolio positioning.   These themes have been ongoing for months now:  Economically sensitive segments in developed markets (ie U.S. Industrials and U.S Energy) outperforming.   Inflation fears have caused India (INP, EPI) Brazil (EWZ,BRF) and other emerging markets to roll over.  The money flows show up in relative strength.   






Snapshot From Our Relative Strength Reader Application ( RS Reader Tools Page)


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ETF Movement as Research For Understanding Bigger Themes

Feb 03, 2011 in Strategy

"I measure what’s going on, and I adapt to it.” - Martin Zweig

ETFs represent well-defined baskets of securities --- indexes --- and we can use these index movements to better understand money flows and trends. The following list is a blend of ETFs that was based on the most popular securities at ETFreplay. This list of 15 ETFs represent a good sampling of bonds, stocks, commodities etc... Some editing to avoid duplicate indexes from different providers was used.

First lets take a look at what happened if we just held all 15 in equal-weight for the entire year 2010 using the Backtest Portfolio Allocations App (you can hand-input up to 10 symbols in the free version of the page).

Auto-Load Symbols From An Existing Portfolio:


Press 'Test Strategy' Button on Right To Run Chart Of Portfolio:

Scan Supporting Statistics:

Note that the correlation of this equal-weight portfolio is 0.97 to the S&P 500 (see SPY correlation figure in the top-middle of the 3rd chart image above) . This reading actually isn't that big of a surprise. Most buy & hold ETF allocations that contain a large allocation to equities will result in high correlation to an equity index like the S&P 500.   

Now let's take a look a little deeper at how one particular tactical asset allocation (TAA) strategy found leadership in 2010. We will study 2010 by creating a model and then observing which ETFs were held the most during the year within that model. Whatever was held most might be considered a 'theme' for the time period under discussion.

What relative strength does is tries to understand what is strongest and hopefully thereby find ETFs that are beginning to trend. Every leading ETF starts out with relative strength and then either trends or mean-reverts. Judgment based on experience will be necessary ultimately -- but having a quantitative process locate the strongest ETFs will give you thematic ideas as they develop to consider.

We used a monthly rebalance schedule and a basic 3-factor model to choose among the 15 ETFs. We set the backtest to include the top 3 at the end of each month and hold until they fall out of the top 3, at which point they are replaced with the new top 3.

The next table summarizes which ETFs were held using this strategy for 2010:

As this model correctly identified at the time, U.S. Tech stocks (QQQQ) U.S. Midcaps (MDY) were themes. Bonds had strong relative strength bull move into the summer and Treasuries (IEF) and U.S Corporate Bonds (LQD) both show significant days of being held. Using this strategy, Europe (VGK) was NOT held for even a single day during 2010. Below is a chart of a comparison of these 3 ETFs (QQQQ, MDY, IEF). You can easily visualize what the model was picking up.

Forwarding to more recent action, emerging markets have moved down the relative strength rankings while agricultural commodities remain highly ranked. Underweighting emerging markets equities and overweighting agriculture have been recent themes. Will this continue? It is to be determined --- but this is where a quantitative backtest would say to be --- but there will be future rotations in 2011 so we will just have to continue to...measure what is going on and adapt to it.





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Undifferentiated Asset Allocations

Jan 26, 2011

With the growth of the ETF market, you see increasing amounts of discussion of asset-allocations. While this is a good thing, a few realities need to be addressed more often.

An allocation that has no particular bias to it does not do much good.  Yes, it is possible to create a fully-diversified portfolio for very low cost these days. But while having a little exposure to everything might be ok to use as a benchmark, let's not forget that you do actually have to materially bias your portfolio to differentiate it from the benchmark. 

Let's look at an example --- I saw a recent article that attempted to use the "wisdom of the market" to tell you how to set your allocation.   The methodology took the asset allocations from a number of other sources, averaged them and came up with this:



It looks diversified.  It's definitely low-cost.  But that is about all you can say about it.   Using our (free) Backtest Portfolio Allocations App, I ran the above allocation and here is how it looks for the past two years relative to the S&P 500 index:



As you can see, an allocation that has no bias or particular bets just reverts you back to the same basic overall market exposure.  Outperformers and underperformers just offset each other for the most part in this particular portfolio.  It is not just that the overall return is the same --- but the chart makes it clear the path from start to end is the same as well.  If you didn't run the chart and see this for yourself, you probably would have thought that the allocation was actually doing something it is not.

Summary: The hot topic these days is about asset-allocation --- however, don't necessarily assume that just because it's an 'asset-allocation' that it actually is differentiated in any way, shape or form.  Many asset-allocations just ultimately mimic the same basic exposure.   It doesn't take much testing or research to determine this -- but it does take a little.

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Various ETF Performances From The Past 2 Years on S&P 500 Down Days

Jan 19, 2011 in S&P 500

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

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