Jan 20, 2013
Earnings | Sectors
In the last blog post, we showed how S&P 500 earnings were tracking vs past years. This blog looks at 2 of the major sectors that generate those earnings.
All of the major banks have reported earnings for Q4 and given guidance for 2013, so estimates for those companies are up to date. Meanwhile, tech companies for the most part will be reporting over the next 2 weeks. Nevertheless, in the chart below you can see how tech is pulling the overall S&P 500 earnings down while Financials have been a positive influence since Sep 30.
Below is a comparison of the recent returns for these 2 key sectors:
Since many XLF components have reported earnings recently, here is a look at the components:
Note how Goldman Sachs is the leader here. The largest negative contributor to S&P earnings has been Apple -- having missed the September quarter and analysts have continued to cut estimates since. Below compares GS to AAPL for a striking difference:
Feedback is welcome -- please let us know if you like this kind of detail on key ETF holdings or if you have any comments or questions: Contact Us
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Jan 03, 2013
Earnings | S&P 500
As we head to earnings season, let's look at what has happened in past years EPS progression for the S&P 500. We have indexed everything to begin on Sep 30 of each year and show the change coming from that starting point.
2009 was a massive outlier so we excluded it ---- earnings estimates totally collapsed that year in delayed fashion to the 2008 financial crisis. Stocks that year of course cratered from January to March and then turned hard and ended 2009 with a very big up year. A financial crisis of that magnitude isn't going to happen again anytime soon and it is certainly nothing like the set-up we have coming into 2013. Someday maybe again -- and if it does begin tracking that during the next few months, we will be sure to let you know. :)
The point of the above is to show that the relationship between earnings and the stock market should not be taken so confidently. Said another way, the volatility of the P/E multiple dwarfs changes in actual fundamentals (as defined by something like index earnings estimates). Whenever you have something very volatile, it will be hard to make precise sense of it from a pure fundamental basis. Fundamentals are important --- but there are good reasons why the market is much more volatile than underlying earnings and this has to due to so many other factors --- including behavioral issues dealing with confidence, fear, greed, missing out etc...
Here is a snapshot of S&P 500 and 2012 earnings overlaid on the same chart to see what happend in the most recent year relative to what are now historical earnings.
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Jan 02, 2013
S&P 500 | Total Return
There is always confusion over this so we'll just answer it here rather than responding to a lot of emails.
The S&P 500 is a total return index (all indexes are total return indexes). If you want to refer to the S&P 500 without dividends --- you call this the 'S&P Cash Index' (or just 'price return') --- that is not the S&P 500 though. SPY is the ETF version of the S&P 500 index and varies very slightly due to the nuances of an actual traded investment product on a public excange that you trade during open market hours vs an index value that is determined based on official closing prices and isn't finalized until after the close.
You don't have to take our word for it though, this is from Standard and Poors itself (we continually run reports to check our returns vs key sources, we take data integrity seriously):
We have a free page so that you can understand ETF distributions as many charting services have architectural issues with displaying this correctly. Note that the vast majority of technical services were built for short-term traders, not investment managers. Dividends might not seem important to you -- but 2-3% a year compounds into a big number over a lifetime of investing. Moreover, there are many ETFs that pay much higher than 3% -- you need to compare investments based on the total return series.
Total Return vs Price Return Free Page
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Jan 01, 2013
One of the silliest things we read in the media is how some investors are paying 2+20% to hedge funds in order to reduce volatility. This is very likely just financial writers that don't know what they are talking about --- nobody pays high fees just to reduce volatility -- you pay a high fee because the manager is actually going to deliver a strong (risk-adjusted) return. Some managers are worth such fees --- but most aren't and investors are just making a bunch of fund managers rich via their own clients money by overpaying. The old saying 'you get what you pay for' is just not true in the financial industry -- there are countless examples where the same exact product can cost 20 basis pts if purchased through one particular channel and 3%+ if purchased through an alternate sales channel.
Back to a simple vol-reduction example. Our allocations board portfolios were long financials during the 2nd half of 2012. We liked financials because of their improving fundamentals, low valuations and attractive relative strength characteristics. While we weren't long KBWB in particular, let's look at how you could effectively take something you like fundamentally -- and overlay a risk-reducing strategy that would fit more in line with a hedge fund profile.
We use KBWB -- a bank ETF from PowerShares for this. We observe the most recent volatility and reduce our position until that volatility equals 10% (these calculations are automated using dividend-adjusted total return series within the app). We chose as a default to mix the selected ETF (KBWB) with SHY, a low duration fixed-income ETF from iShares.
If you look at a typical hedge fund marketing slidedeck, it will often give a target of 5-10% volatility with a return objective of 10-15%. In this example, we liked financials and believed in an annualized return objective above 10%. (The reason hedge funds and their investors like low volatility is because drawdowns are lower).
We know financials have been the most volatile sector around -- but that doesn't make it uninvestable. You don't have to do any risk-parity calculations here between SHY and KBWB (though you could, risk-parity is an option within our core-satellite app). In this case, we simply reduce the dollar amount invested until the mix of KBWB and SHY is close to our risk objective of 10% (again, we chose 10% as that is a common benchmark within the hedge fund community --- its just an example -- you could instead choose 8% or 12%)
Note that the actual achieved volatility here was 11.1%, above the 10% target. This is because we are using historical volatility as an estimate for the next period and dynamically re-weighting the pair. If you wanted to be more exact and come closer to the target, you could choose to do your updates on a weekly schedule -- or daily for that matter. However, that will generate a huge amount of trades that are needless. In this case, the max drawdown for this strategy was -8.5%. Note that banks in past years have been stuck with enormous drawdowns, much higher than in 2012 -- so that is not meant as a worst case scenario, that is only what happened in a relatively calm year like 2012. The max drawdown for 100% KBWB stock was -18.0%.
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