ETF Bond Market Performance Since QE Began

Jun 07, 2012 in Bonds

The Federal Reserve has made a lot of money on its Treasury Bond purchases.  However, that is dwarfed by what high-yield bond investors have received over the last few years:

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Corporate Bonds vs MLPs

Jun 02, 2012


Treasury Bonds Are Going Parabolic.   But its not well reported that high-grade US corporate bonds are also in a strong rally.  It's not just treasuries.   Meanwhile,  Oil & Gas MLPs are having very poor run and should be a reminder of the difference between fixed-income securities and riskier assets.


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ETF Volatility Targeting

May 30, 2012 in Drawdown | Volatility

A new book in the Market Wizards series (by author Jack Schwager) has come out this month.  While these books are a collection of interviews of great money managers -- Schwager himself also does a nice job of summarizing some of the themes he personally has gleaned by incorporating his decades of experience into a series of observations.   

He also recently summarized a few of these observations on his twitter account (@jackschwager).  

A few of his takeaways from interviewing top money managers:


* It is not about predicting what will happen -- but rather recognizing what is happening


* Many go wrong by failing to adjust exposures to changing market volatility


This all conveniently ties into ETFreplay, using Relative Strength to help recognize what is happening is foremost.   But on the second point, we recently added a module to help think about how to adjust exposures to changing Market Volatility.  Let's look at one example of the latter.

Let's think about the Russell 2000 Index, the most popular index for small cap U.S. stocks, which is one of many important market segments we can access at ultra low-cost (never any redemption fees or lock-ups with ETFs) and it of course has total transparency and is deeply liquid.

Let's look back at 2010 for an interesting example of how this segment has traded.  

2010 was a very good year -- but you wouldn't have said that during the summer of 2010 when there was a large drawdown following a flash crash in May and yes, continual negative newsflow from... drumroll... Europe.    The final IWM return was very strong +27% but masks the mid-year washout and pain many investors felt.


Here is 2010 as full year snapshot. 

Go forward one year to 2011, the IWM final return of -4% for IWM also greatly masks the 'path-taken.'  Another large drawdown, this time -29% and about the same actually as the European index loss (VGK was off -30% from peak to trough).

This is very important and something that investors must study a great deal --- the long-term return of the markets is not all that great in relation to the often wild path taken to get that return.  That is, a long-term return of say +7% might have huge drawdowns along the way that cause investors to actually end up losing money if they don't learn how to deal with this.    

(In modern portfolio theory terms, you describe this situation (low return relative to high volatility) by saying simply that the Sharpe Ratio is not very good.)   

If the short-term S&P 500 sharpe ratio gets really high, just wait -- it's coming back in at some point.   This is what happened in Q1 2012 when the S&P 500 YTD sharpe ratio was over 3.00 at one point.   We noted this as an unsustainable figure on our Allocations board timeline.   And now we see the inevitable washout that occurs with assets that don't have good long-term sharpe ratios.   If you want a more efficient equity curve, then don't buy and hold stocks --- unless its part of a well thought-out allocation that adjusts to prevailing conditions.

On the Tools page is a new module 'Volatility Target Test.'  This module executes a convenient, clean performance backtesting report for you complete with detailed period-by-period weightings and return.   

It combines any ETF of your choosing (such as IWM) with a cash-like ETF (SHY) and allows you to therefore approximate a level of volatility for the combination based on changing (dynamic) market conditions.  It continually adapts to the current environment and records the performance of such a mechanical targeting approach.

It should be clear that if you target low volatility and the market goes up a lot -- then obviously it will underperform.   But if you target lower volatility and the market goes down a lot, it will obviously then outperform.    The point of the application is not to be an optimal weighting, it is to help us all understand how volatility targeting is working and how to avoid one of Schwagers main points repeated here

* Many go wrong by failing to adjust exposures to changing market volatility

Below is a single view screenshot of the new volatility Tool:

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Tactical Asset Allocation vs 'Market Timing'

May 14, 2012

Being tactical and market timing are not the same thing.  Let's review.

Market timing in its pure sense means choosing a beta where the beta of the market equals 1 and the beta of cash equals 0.  Asset allocation generally refers to a mix of 5-20 different types of investments.

A portfolio manager who is engaged in choosing country funds and makes a sale is not market timing, they are allocating assets.   To the extent that their return and/or risk expectations change about a country, they of course may alter the portfolios holdings.  Since they are making decisions on many different investments, it is not just based on changing between a beta and cash --- they are choosing and mixing many betas -- this is allocation.

Now let's review active vs passive.   The most purely passive investor would have some type of a global allocation and would not change the portfolio weights based on expectations because a passive strategy does not have tactical expectations.  It is having the ability to change your expectations of future returns that defines someone as active.  A passive investor simply doesn't change their expectations about the capital markets -- or at least if they do and don't do anything about it when they change --- they are acting passively.  

(Note that technically you can be passive and change the allocation, it would just have to be for some reasons other than capital markets expectations.  An example here would be that some type of financial event happens in your life and you now need to take less risk as you will have some extra liquidity need sometime soon.  The allocation could change to reflect this -- its just not due to investment related expectations).

Some people get confused and think that changing an allocation automatically means you are timing the market.  No, if you fall into the 'active' category and your expectations change about a particular segment of the market, then it is frankly inconsistent with basic logic to NOT change your allocation. You change when your expectations for returns between assets change.  

We think ETFs are interesting for their ability to alter portfolios efficiently, transparently and at ultra low-cost.  Whatever your investment process is -- try to remain open on how to improve it.  We think emphasizing portfolio management implementation techniques is what really matters most --- that is, allocation decisions.   You can augment this core idea with either stock-selection or some component of passive buy & hold allocation ideas.   There are no hard & fast rules on portfolio management other than this: favor reward/risk over just reward.

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Employment Trends

May 03, 2012

As we prepare for tomorrows big employment number, step back for the real issue in the world right now:  overall problems in Europe and inept policymakers are in a serious spiral.



Here is the last 10 months relative stock performance:


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What is the ETF land speed record to $2 billion anyway?

May 01, 2012

Once upon a time there were sales loads (they still exist).   Let's say you bought the PIMCO Total Return fund through a broker and paid a 3% load on Feb 29.    The appreciation of the fund still leaves you -1.5% underwater.   Meanwhile, the PIMCO Total Return ETF is up +3.8%.   In 2 months you have given up +530 basis points in performance relative to simply buying the ETF.   While fees like loads are not officially counted against Bill Gross' performance, trust that many investors have been paying ludicrous fees like this for years and years ---  and it still goes on.     If you think we are making this up, then you don't understand how the financial services industry works.



This ETF is likely going to blow through $1 billion and then head much higher.   $665 million in less than 50 trading days.



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S&P 500 Weightings 2006 vs 2012

Apr 26, 2012 in S&P 500

Quick look at how S&P 500 Weightings have changed.   Apple is a massive change obviously.   

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Q1 Benchmarks Ranked Vs History

Apr 03, 2012

Q1 2012 was a very good quarter for the S&P 500 --- but no, it was not an outlier.  

The bond market was flat.

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60-40 Stock-Bond Portfolio vs the Most Popular Hedge Fund Index

Apr 02, 2012 in Hedge Funds

In professional settings, seven years is considered enough time to constitute a relevant performance comparison because it usually encompasses different kinds of markets.

Recently there has been press about how hedge funds did not beat Treasury Bills during the last cycle.   We will not be so kind.   A 60-40 stock-bond index is a reasonable comparison benchmark.   Yes, it is U.S. based but it is a very plain-vanilla option and it is not considered an especially difficult benchmark to beat over the longer-term so this is not exactly an unfair comparison.

Next Blog: Q1 2012 Index Ranks vs History Chart

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Some Simple (But Useful) Math

Mar 22, 2012 in Volatility

A member wrote a question which spurred some thinking. Essentially, they wanted to understand not just the calculation of the sharpe ratio -- but why its a good metric.  So this blog starts on that topic and hopefully can serve as a reference -- it then extends into a longer piece which are thoughts that should help a few people that want to pursue this angle in general.

We are of the belief that you do not want to get bogged down in too much detail beyond this type of math below -- understanding the basic math can be very helpful in your ability to understand investing -- just as understanding the game of Bridge or Poker might be better if you have a basic understanding of the math associated with a deck of cards (total number of cards, number in each suit and how this translates to some basic understanding of odds).


First -- let us state that the Sharpe Ratio is not a perfect measure by any means (hint: there are no perfect measures) --- but it is a useful framework to start with because it factors in volatility well.  High volatility is best associated with large drawdowns, a major concept to keep in mind.  What do funds with huge losses all have in common?  They were all very volatile.  

Drawdowns are obviously your enemy.  Trust though that you CAN control your drawdowns somewhat by controlling your volatility.  Sometimes you hear how investors want to pair their trades with short-selling.   Few investors actually do well with this structure, especially when they pay a big fee.  Yes, it's important to hedge your volatility --- but no, you do not need to pay a big fee to a short-selling fund just to reduce your volatility.  You can reduce volatility anytime you want and as much as you want and the cost is (should be) very, very low -- they are called short-term bonds.  (It goes beyond this post but you can do quite well by using some basic short-term credit strategies -- and then pair these with your core equity/risk strategies that are designed to deliver long-term return).   

You DO need to take on some volatility in order to generate some return -- but nobody who actually knows what they are doing is going to be impressed with making X% if you do it with massive drawdowns. 

So let's look at some basic math:

1) Compounding returns:

Let's start at some very basics, skip this and go to #2 volatility if you so desire.

Let's start with a 10% annual return. To convert 10% to a daily return, you only need to know how many days there are in a year.  Most traders will know that there are 252 equity trading days in most years (fixed-income and foreign markets like China have far fewer trading days due to extra holidays but this actually doesn't matter because the ETFs are open for trading on exchanges even when the underlying market is closed). 

So to take 10% down to a daily level in a spreadsheet:  place 0.10 in cell A2 and then in B2 type  =(1+A2)^(1/252)-1.  Now you have a daily figure of approximately 0.0378%.  Then practice by reversing it back to the annual 10%.  It may be easiest like this   =((1+.0378)^252)-1 = 10.000%.  

How is this equation useful?  Well, for each $100,000 in your account, a 10% annual return would be about the equivalent of 40 bucks a day (lower in the early days and higher in the later days due to compounding for an average just under $40).   $40 doesn't seem like much does it?  A lousy ~$40 on my $100,000?  Yes, that is what 10% a year feels like from a daily compounding perspective (40x250= $10,000). 

Let's move to a monthly figure as we find this to be a very useful timeframe, you will see why when we discuss volatility.  252 trading days in a year means 252 / 12 months = 21 days per month, on average.  Let's take 10% and convert to a 1 month (21-day) figure =((1+.10)^(1/12))-1 = 0.797% per month.  

Just to do the math a different way,  let's go from daily to monthly (from above) =  (1+0.0378)^21 = ~0.797% per month.

So that is return basics, now let's look at volatility.  If you can just get these 2 items (return and volatility math), you will have the 2 major Sharpe Ratio components:

2) Volatility is a slightly different animal but isn't as hard to think about as you suspect.  If something goes up a little bit ON AVERAGE each day (like the stock market) but not steadily compounding as in example above, then there is a different dynamic to understand.

Volatility grows not at time -- but at the square root of time.  It sounds scary but its not.  All that means is that even though the market moves around a lot on a day to day basis, if you look at it over a longer time period, much of those days offset each other and so you can't compound volatility like before because volatility relates to the path taken rather than just the final return result.   Think of it as more 3-dimensional analysis.  It's trickier -- but it's very important information.

Whenever you take the square root of a number greater than 1, the number is going to get smaller so  =sqrt(12) is obviously a lot smaller than 12.  This reduction is taking into account the fact that up and down days (volatility) offset each other to a significant extent.  So up +10%, down -10%, down -10%, down -10%, up +30% is an awful lot of movement but only gets you back a little positive.  The final return of +4.2% doesn't tell you about the path taken. 

So if we look at the S&P 500, we can say something like -- over the past X years, the annual volatility has been about [16%] (brackets just mean fill in whatever number you would like, this is just an example). 

Volatility is always discussed as an annualized amount.  But we can of course convert 16% to a daily figure using an equation like this  =(0.16)/sqrt(252) = ~1%.  

So given a forecast of 16% volatility, we would now not be at all surprised to see the market go up or down +/-1% tomorrow.   There are of course many other possibilities --- but we would not 'expect' it to move 5% --- because if it did, that would be too far from our baseline range of expectations.  Yes, it could happen but then that would be associated with rising volatility far above the example 16% used -- our 'forecast' of 16% was wrong in that case.  Remember, we are just trying to understand the mechanics of the Sharpe Ratio, we are not trying to forecast 1-day movement. 

Now, what practical use does this all have?  Well for one, don't try to pinpoint exactly why the market went up or down 1%, it's not a significant enough move when you are looking at it in the context of a few months.  Yes, there may be some headline news that day -- but many times the market will do the exact opposite of the nature of the morning headline.  It's just short-term volatility in play and it's normal.  

We think it makes a lot of sense to look beyond daily movement and toward longer windows of time -- but not too long.  A lot of modules on the website are set-up with this in mind.   We need a time-period that allows some of that offsetting volatility to work itself out.  There is no single magic time-period but various academic papers that we've been reading for the last 15 years point to 1 to 12 months as a good time-period to study.  Shorter than 1 month is too noisy and at 12 months or longer, the edge evaporates.

So let's take an example.  Let's assume a 2% 1-month return and 16% ANNUAL volatility estimate. 

First annualize the return:  =((1+.02)^12)-1 = 26.8%.    A quick comparison of 26.8% to 16% = 1.68,  that is a measure of return divided by a measure of risk.  You are risk-adjusting the return into a pretty straightforward ratio.  That is, you are incrementally penalizing the return if it took a wild path to get there.   If that makes sense to you on a conceptual level then you are 95% of the way there.

You should quickly see that 26.8% is an unsustainably high number.   You may have a great year  where you do far better than 26.8% --- but you won't be able to compound at this number for the long-term.   So here is the logic, since 26.8% annual is unsustainable -- that means 2% a month is unsustainable (it's the same number).   And while you may have many months far better than +2%, in order to get a good return/risk situation, you are going to have to also spend a little time thinking about the volatility -- you won't be able to do a good sharpe ratio based on return alone (over the long-run).  And of course, the real reason to control volatility is so that you don't experience large drawdowns.

Now let's look at a leveraged fund as that is an interesting phenomenon to think about.  A leveraged fund is DESIGNED to have 2x or 3x the daily return of the unlevered fund.  The funds will re-balance daily (if necessary) to achieve the next days targeted change.  As you should be able to see from above, we know it's a bad idea to trade off 1-day movement because historically (and consistent with the concept of volatility), the market doesn't go up at its long-term rate, it goes up and down in offsetting nature and then only over a larger sample period can we see a return figure that is not so highly skewed.  

What this means is that leveraged funds rebalancing daily is a serious long-term flaw and should not ever be held for significant periods of time.   This by the way is exactly what the trading in these funds indicates as most of the leveraged funds have low assets relative to their high daily volume amounts.  There is much trading during the day and then a lot of people flee before the close. 

Back to the Sharpe Ratio.  The ideas in this blog have gone into some math but should be thought about more conceptually in our opinion.  So to speak from these basic concepts, you could put this into a practical statement in a few different ways (just by re-arranging the key factors):

1.  We target a return of 10% a year.  We target volatility just below that.  (This implies on a conceptual level a reward-risk ratio of 1.0 or better).

2.  Volatility has been about 10%, we think we should be able to do a sharpe ratio of 1.0 so that means we think we will do 10% in return or better.

3.  We target a sharpe ratio of 1 or better -- we are tactical so volatility will fluctuate up and down -- we aren't going to micro-manage it but we can say that we will manage volatility such that it is no higher than the [S&P 500] index volatility.  This means/implies that our drawdowns should always be lower, too.


Now, let's pretend you were rotating between 3x leveraged funds.  How would you rationalize this if in a client meeting??

"Our funds volatility has been running 45% so hey, if we can just do a 0.5 sharpe ratio -- then expect us to compound at 22.5% per year"

Uhh no, the meeting would end there and you would be laughed out of the room.   Again, you can and should have some big individual years that put up some nice performance numbers if you execute your strategy well.  But we aren't talking about that, we are talking about long-term compounding.

Lastly, let's make sure we end on some common sense.  Don't get too mathematical about all this.  At the end of the day, this is about growing your account balance.  Making new all-time highs in your account balance and not having large drawdowns is efficient money management.  If you do that, who really cares whether you did X% or X+1%?  Don't lose sight of the big picture by getting too bogged down in the exact math.  An understanding of the concepts is needed -- an exact knowledge of every nuance in the calculations is not.

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