Investing for a living has a new home

Big news here today. I’ve moved the Investing For A Living blog from a WordPress hosted site to a self-hosted site.

If you’re a blog follower and want to keep up with new posts I’d like to ask you to do the following:

1/ RSS Followers -> If you’re getting my blog through RSS feed (e.g. Feedly or equivalent) please update your feed to www.investingforaliving.us/feed

2/ E-Mail Followers -> If you’re getting my blog through e-mails your e-mail should already be transferred to the new blog feed (in fact, I’m kinda hoping you get this e-mail from the new link). If you don’t get a new blog post from me in the next few days please go to the new site www.investingforaliving.us and re-sign onto the e-mail subscription (top right)

3/ Linkers -> If you’ve got my blog linked to your site somewhere, please update the link to www.investingforaliving.us.

Why the transfer? Basically, more freedom and flexibility. I hope to add some new cool content to the site over time to help individual investors navigate the crazy investment world we live in today. I also plan to focus on some more basic concepts for investment beginners.

I’m still working on re-catogorizing much of the blog content. My focus has shifted over the last 5 years to more of an automatic investment style and thus I need to do some reorganization. Have a look at the new blog and let me know what you think and/or if you find any errors. I’m happily open to suggestions & improvements. I like the new, fresher look but want to make sure you like it too. With any luck all new posts will be on the new platform.

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Bonds during the great rise in US interest rates

There is a severe lack of long term perspective by most financial market participants these days. Interest rates, and in particular the potential for a dramatic rise in future rates, is just the most recent example. Most analyses of rising rates don’t go back far enough to be really useful. Going back to the last rate increase by the FED in 2004 to 2007 is not good enough. Even going back to the 1970s is not good enough. For a better perspective you need to go back further. The best analysis I’ve seen is here. In this post I’ll take a look even further back in history at the great rise in US interest rates from 1941 to 1981 and look at the role of short term bonds vs long term bonds in portfolios. I think this period is a good analog to study the current environment.

First, lets frame what we’re discussing. The US experienced a dramatic rise in interest rates from the end of 1940 through 1981. The chart below is a graph of the US 10 yr note from 1927 to 2012.

US interest rates 1927 to 2012

A few items to point out. After the Great Depression it took 11 years for the US 10 yr note to bottom out. In late 1940 the US 10 year bottomed at 2.01%. It took a further 16 years, until 1956, for the 10 yr note to reach the its level prior to the Great Depression. That’s 27 years for the 10 yr note to reach the same level it was in 1929. Keep that in mind next time you hear about rapidly rising rates. Rates can stay lower a lot longer than you think as shown by history. OK, on to the focus area. Once rates bottomed in 1940 they began a 40 year rise that didn’t end until 1981 when the US 10 yr hit 13.7%! Now lets take a look at what that meant for bond returns during that period.

For this analysis I’ll compare short term bonds, using US Tbills, versus US long term bonds, using the US 10 yr note. Obviously, such a period of rising rates was bad for all bonds. 30 year period bond returns from 1940 to 1951 still stand as the worst long term periods for bonds. 30 year period returns during this time were between 1.9% and 2.7% for the 10 year bond, and between 2.34% to 4.37% for US Tbills. In general short term bonds out performed long term bonds. Coupled with rising inflation bond returns during this period were mostly negative on a real basis as well. So, why hold bonds at all during a rising rate environment? Let me table that for a later paragraph. One thing about this 40 year period is that it hides a lot of subtleties. We need to dive deeper for a better view. The chart below shows rolling 3 year returns for US Tbills and the US 10 year note during this period.

Rolling 3 yr returns bonds vs bills dec 2014

The point to this chart is that during the initial rise in rates long term bonds performed better than short term bonds. It wasn’t until rates rose to higher levels and then proceeded even higher that short term bonds really shone, while long term bonds were hurt. Bond returns are a combination of the level of rates plus the change in rates. Look at the last few years on the chart in particular. From 1976 to 1981 rates doubled! Now let’s look at it on a total return basis.

total return bonds vs bills 2014

Same basic picture except it shows the late cycle difference between bonds and bills even more clearly. During the initial more subtle long term increase in rates long term bonds were better than short term bonds. But as the rate increases took hold and accelerated short term bonds more than caught up. Up through 1976 the total return form bonds and bills was about the same. In the last 5 years bonds returns lagged the return of bills by approximately 30%. I think the important point here is that you have plenty of time to react to rising rates and during the initial rise long term bonds are better than short term bonds. Or better yet just use a bond momentum model as I discussed here. A simple annual bond momentum model that chose between Tbills and US 10yr bonds would have outperformed either with lower drawdowns.

But why hold bonds at all? Given the level of current rates future bond returns (short or long) are unlikely to be very good especially on a real basis. The answer is we hold bonds mainly as portfoflio diversifiers. Over time bonds act as the best diversification for stock market risk. During the period from 1941 to 1981 there were only 2 years where both stocks and 10 yr bonds had negative returns and there were zero years when stocks and Tbills both had negative returns. This diversification coupled with rebalancing enhances portfolio returns. The other reason to hold bonds is to minimize negative returns and drawdowns. Again, even during this unprecedented rise in rates bond reduced negative returns and drawdowns vs 100% stock portfolios by about half. This is especially important for retirees who are trying to make their portfolios last and maximize their safe withdrawal rates. As usual, Vanguard has a great piece on the role of bonds in portfolios.

In short, bonds are a key piece of any diversified portfolio, even during a long term rise in interest rates. And as history has shown rates can stay lower a lot longer than most think. Also, the choice between short term and long term bonds during rising rates is not as obvious as it may seem at first glance. During the initial rise in rates long term bonds can perform better than short term bonds.

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Increasing returns, lowering risk in GTAA portfolios

Warning. This post is kind of a finance geek out. I’ll try and keep it as basic as possible but I apologize in advance if I cause any heads to hit the keyboard…

In this post I’ll take a look at impact and potential benefits of adding volatility weighting and mean-variance optimization to tactical asset allocation portfolios similar to the IVY (GTAA) portfolios I discuss frequently on the blog. Most of the data and theory I present here comes from this great paper on Adaptive Asset Allocation. If you have any interest in applying the concepts here to your portfolio it’s a must read.

The basic theory here is the short-run estimates of returns, volatility, and correlation are better predictors than longer term estimates of the same parameters over most investor time frames. By using these short run estimates, portfolios can exhibit much better results than otherwise. For example, on the return side GTAA portfolios use momentum to weight the portfolio towards assets that are currently outperforming. This in contrast to having a constant weight to stocks, say 60%, because long term estimates of returns say that this is where we should be invested. We can use similar concepts for volatility and correlation to achieve better results. Lets begin.

The diversified portfolios used for this study all consist of 10 assets classes studied from 1995 to 2012: US stocks, European stocks, Japanese stocks, Emerging market stocks, US REITs, International REITs, US intermediate treasuries, US long treasuries, Commodities, and Gold. The first optimization is to use momentum to weight the portfolio to the best recent performing asset classes. Here only 6 month returns are used as opposed to average momentum used by the IVY portfolios. Momentum is a very strong factor and works when applied in many ways. The top 5 assets classes by 6 month return are bought each month in equal weights. Lets look at these results first.

GTAA Top 5 EW Dec 2014

As with the IVY portfolios, just using momentum works exceedingly well to increase returns and lower risk. But we still have quite a bit of volatility and drawdowns. Volatility weighting uses short run estimates of volatility to change the weights of the assets in the portfolio. The simplest method, without using leverage, is to reduce the weighting of the assets when they exhibit large volatility. Here we use daily returns over the last 60 days to generate our short term volatility estimates. The calculation is pretty simple and is included in the paper. I’ve also added it to my GTAA 13 portfolio tracking sheet which you can find here. Basically, the target is a 1% daily volatility for each asset class. If the asset class exhibits higher volatility over the preceding 60 days it’s weight is reduced in the portfolio. In the results below, I show a pure comparison of volatility weighting with equal weighting and then show volatility weighting combined with momentum.

GTAA 10 Top 5 VW

Impressive results. As the table above shows volatility weighting alone mainly improves risk, sharpe ratios and drawdowns. Combined with momentum you get slightly lower returns than pure momentum alone but with lower drawdowns and a higher sharpe ratio as well. But we can do even better, albeit with an add in complexity. Volatility of assets classes matters, but in portfolios what matters even more is how assets move together, or the correlation of returns among the assets. This is the whole theory of diversification. Certain assets like stock and bonds tend to move in opposite directions. But just like returns and volatility these correlations can change and vary wildly over time so we’re better off using shorter term estimates of correlations to weight asset classes. Let’s see how we go about doing that.

Just like with volatility, we need to look at the last 60 days of returns for the asset classes. Then for whichever assets are in the portfolio we need to put together a covariance matrix, a table that tells us how these assets have ‘moved’ together over the last 60 days. Then we use these covariances to calculate the volatility of the overall portfolio. I’ve done this for the GTAA AGG3 and AGG6 portfolios that I track in the spreadsheet I linked to above. Here is the most recent snapshot.

GTAA MV Optimization Dec 2014

For the AGG3 portfolio the most recent 60 day covariances yield a portfolio volatility of 6.8% annualized with an equal weight of the top 3 asset classes. This will change every month. Now, we can do a couple of things. We can use Solver in excel (unfortunately the Google Sheets version won’t work for this) to either calculate the portfolio weights that give us the minimum volatility or better yet we can choose an acceptable level of volatility we’re willing to take and calculate the portfolio weights that yield this volatility. For example, if I put the above covariances for AGG3 into solver and target an 8% annual portfolio volatility I get portfolio weights of 58.5% for VNQ, 20.2% for VGLT, and 21.3% for MTUM. Quite different from an equal weighting. How does this kind of optimization perform over time. Below I’ve summarize all the optimizations we’ve discussed.

GTAA 10 Top 5 MV Dec 2014

The mean variance optimization gives us similar risk to the volatility weighting but about 1.6% extra points in annual returns. Is it worth it? That’s a very personal decision and is up to the individual investor. The good thing is once you master these calculations these changes are applied only once a month just like the all the GTAA signals and triggers.

That’s about it. Here I’ve showed how incorporating short term estimates of volatility and correlations can be used with the well known momentum factor to increase returns and reduce risk in portfolios.

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A trend following bond portfolio for any environment

Interest rates are going up. Interest rates are going down. The 30 year bull market in bonds is coming to an end. The FED cannot afford to raise rates significantly without killing the economy. Bonds will have negative real returns going forward. We’re in the biggest bond bubble of all time. Bonds are still the best diversifier of equity risk. Have you heard any of these lately? How about over the last few years? Probably incessantly.

There seems to be more hand wringing and fretting over the future of bonds than even equities. And that is saying something. We could jump into a bunch of fundamental and historical analysis to see which scenarios are more likely. We could look at international markets like Japan for analogues to the US situation, etc…But I really have zero interest in being an active bond picker again, or for that matter, a stock picker. As I detailed in this post, most of the time it’s not worth it and most of the time you can’t even get our of your own way. Can we then apply some of the same quant investing concepts that we use for equities to bonds and not have to fret over the future of bonds? The short answer is yes.

The most powerful factor, some people call it an anomaly, in investing is momentum. Eugene Fama, Nobel prize winner and one of the fathers of Efficient Market Theory, has called momentum the biggest challenge to the efficient market hypothesis.  And it applies just not to equities but to pretty much any asset class. I’ll just point you to the research by Antonacci and Moskowitz but basically momentum works across all asset classes, across different time frames, including bonds. In Antonacci’s book Dual Momentum, he specifically mentions applying a momentum approach exclusively to bonds as part of his GBM portfolio (page 129 if you want to follow along). Let’s see how that works.

The Antonacci bond trend following portfolio couldn’t be any easier. It chooses from the universe of US long treasuries, US high yield, Global government bonds, and US treasury bills. Then once a month it ranks these bond classes by 12 month return and choose the top one to invest in. Re-do once a month. It definitely improves the performance of the Antonacci GBM portfolio as described in the book. I took a look at just the bond portion of GBM to see how it did since 2007. Since the history of many ETFs is limited I was not able to go back very far. I used the following ETFs to represent the 4 basic bond classes; TLT, JNK, IGOV, and SHY. The results compared to Vanguard’s Total Bond Market ETF (BND) are shown below.

GBM bond vs BND 2007 to 2014

Not bad. 60% higher returns over the total bond market. And you never need to worry about rising rates, falling rates, etc.. The model gets you into the best performing bond market segment. It’s a great model but I think it has some difficulties for the individual investor. First, though over time 12 month returns has been the best predictor of future returns markets seem to move faster these days. In addition, investors don’t seem to have the patience to wait for 12 month returns to signal an investment change. And finally, I think most investors would not be able to stick with switching their entire bond portfolio between 1 ETF. So, I took a look at a few permutations of the basic model. In the first permutation I simply used 6 month returns vs 12 month returns in the original model. In the second permutation, I added some more segments of the fixed income market to the portfolio and chose the top 1. I added intermediate US gov’t bonds, US inflation protected bonds, US corporate bonds, and US municipal bonds. In the final permutation I expanded the portfolio to the top 3 ETFs by 6 month returns instead of the top 1. I think more investors could stick with such a portfolio. The results of the various permutations are shown below.

Various GTAA Bond Models Dec 2014

Simply going to 6 month returns (GBM Bond 6mo) increases returns and sharpe/sortino ratios significantly. Adding more segments of the bond market (GTAA Bond 1) doesn’t do much when only choosing the top 1 ETF. Finally, choosing the top 3 ETF (GTAA Bond 3) from the expanded universe has the best risk adjusted return ratios, Sharpe and Sortino, and the lowest drawdowns and risk (standard deviation). This is probably the portfolio most easily implemented by the majority of investors.  Below I show the year by year results of the GTAA Bond 3 portfolio vs the original GBM Bond and the total bond index (BND).

Summary of GTAA vs GBM Bond Models Dec 2014

There you have it. An automatic quantitative bond model for any interest rate environment. No need to worry. No need to fret over the FED’s next decision. Apply one of these bond models with your favorite quant equity strategy and you’re probably going to do OK.

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Tactical asset allocation – december update

11 months down, 1 to go in 2014. Here are the tactical asset allocation portfolio updates for this month.

Starting with the most basic portfolios, below are the December updates for the GTAA5 and the Permanent Portfolio. I keep a spreadsheet online that is update automatically. There were no changes from last month.

IVY5 timing model Dec 1 2014 update

Perm Port timing update dec 1 2014

Now for the more broadly diversified GTAA13 portfolio and the aggressive versions. Online spreadsheet for this and the GTAA AGG3 and GTAA AGG6 portfolios.

GTAA13 timing update dec 1 2014

There were also no changes for the GTAA13 moderate portfolio. The AGG3 and AGG6 updates are below – no changes for this month as well.

GTAA6 GTAA3 Dec 1 2014 update

These portfolios signals are valid for the whole month of December.

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Putting together quant portfolios

One of the more overlooked areas of quantitative investing is how to integrate quant strategies into a diversified portfolio. Let’s look at a few of the issues involved and some possible solutions.

I’ve discussed the big allocation decision already, i.e. how much to put into quant strategies vs bonds already. I think this decision should be primarily driven by how much risk one is willing to take. I use maximum portfolio drawdown as the primary metric to judge how much risk I’m willing to take. Here is the max drawdown table from that post.

Quant system vs max DD nov 2014

For example, to limit annual drawdowns to less than 10% and 30% quant portoflio 70% bond portfolio would be the appropriate allocation. If a 15% max DD is more suited to your risk tolerance then you can go up to a 70% quant portfolio 30% bond portfolio allocation. Of course, this is dependent on the type of quant strategies used but surprisingly it doesn’t matter as much as you may think. The XLP/XLU quant strategy is one of the most conservative strategies while TV is one of the most aggressive and best performing yet in terms of max DD there is not that big a difference. OK, now for some of the subtle details of building quant portfolios.

First, why pick more than one quant strategy? Shouldn’t you just pick the best one with respect to whatever metric you want? I would argue no mainly due to behavioral factors. Investors have a hard time with under performance no matter what the long term track record of a strategy may be. Lets take this year as an example and compare one of the best performing quant strategies over time, a value and momentum microcap stock quant portfolio, to a conservative utility value strategy. The micro cap quant strategy has returned over 22% a year since the late 60s as compared  16% a year for the utility value strategy. In 2014 the micro cap strategy is up 3% while the utility strategy is up over 29%! That kind of divergence is hard to swallow for most investors and leads to performance chasing. The best way to avoid this is to choose multiple strategies and choose strategies with high base rates. At the simplest level using more strategies increases the odds the at least one is outperforming and thus lessens the odds of making behavioral mistakes.

OK, now that we’re going to choose multiple quant strategies we need to avoid a few pitfalls. The two big ones for me are over diversification and excessive fees. The quant strategies I’ve presented on the blog usually have 25 individual stocks in a portfolio. If  you’re going to go with 3 quant strategies then we’re talking about 75 individual stocks. Besides paying way more in fees by holding too many stocks we reduce the power of the quant strategies. Two great post on this subject are, Avoid Diworsification, and You need to Dare to be Great. Here is the money pic.

return vs number of stocks for quant systems nov 2014

 

10-15 individual stocks gives about the best bang for the buck for any one of the individual quant systems. So lets say we go a bit crazy and choose 5 different quant systems that we’d like in our overall portfolio. We’ll choose the TV2 systems, the EDY system, the Large stock SHY system, the XLP system, and the XLU system. I’ve posted all of these systems before. See here for a list of all my quant posts. 10 stocks each. Yearly holding period and go back as far as we can, Dec 2008, for the P123 book simulation tool that I use. I’ll call this the Quant 5. Results of the overall quant portfolio are below.

the quant 5 performance nov 2014

Pretty impressive results. Over the full period all of the quant systems beat the market handily. But there have been significant periods of under performance for several of the systems. For example, over the last 3 years, the EDY systems and the XLU system have under performed the market and the other systems. The top quant system over the full period from 2008 turned out to be the large stock SHY system even though going back further to 1999 other systems have performed better. Of course, how could you know that before hand? You can’t.

Bottom line. It pays to diversify, but not too much. Not just in terms of risk adjusted returns but probably more importantly in terms of an investor being able to stick with quant investing over the long term.

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Tactical asset allocation november update

It’s been a while since I’ve done updates for the various IVY portfolios. I’ve noticed that investors still have trouble implementing these portfolios so I decided to start doing the updates again. At least for a few months. Hopefully this helps investors who are trying to implement these portfolios or are just starting their research into these strategies. Also, I’ve changed the name to tactical asset allocation update because these strategies are independent of the ‘IVY’ models popularized by Meb Faber. As I mentioned in my last post you can apply these strategies to many other diversified portfolios. For now, I’ve added the Permanent Portfolio to my IVY portfolio updates. In the future, I will probably add other tactical asset allocation strategies. In particular, I will probably be adding a volatility weighting to some of these strategies. On to the November update.

Starting with the most basic portfolios, below are the November updates for the GTAA5 and the Permanent Portfolio. I keep a spreadsheet online that is update automatically.

IVY5 timing model Nov 1 2014 update

Perm Port timing update nov 1 2014

Now for the more broadly diversified GTAA13 portfolio. Online spreadsheet for this and the GTAA3 and GTAA6 portfolios.

GTAA13 timing update nov 1 2014

And finally for the more aggressive GTAA3 and GTAA6 portfolios.

GTAA6 GTAA3 Nov 1 2014 update

These portfolios signals are valid for the whole month of November. Also, I’m considering replacing the MTUM momentum ETF with a better option. My concern with MTUM is the small market cap and low liquidity. There are potentially some better options out there. I’m considering IUSG or PDP for the US momentum ETF and am even considering adding an international momentum ETF, for example PIE.

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One portfolio to rule them all?

Unfortunately, portfolios are not like a certain type of ring, forged with magical powers to rule over the world, man/hobbit/elf kind, and all other types of investment portfolios. There is no one portfolio to rule them all. There are many different styles and types of portfolios with very different characteristics, asset allocations, and histories. Most importantly, the appropriate type of investment portfolio can and should change for different types of investors. Investors have different risk tolerances, goals, biases, starting points, end points, etc… In this post I want to present a summary of various investment portfolios that I track and discuss a few of their characteristics and the types of investors that they could be suited for. Also, I hope the data and discussion dissuade investors from becoming dogmatic in their portfolio choices or recommendations. All right, let’s get to it.

In May of this year I posted a summary of the portfolios I had been tracking up to that point. Since then I’ve expanded the number of portfolios that I track and added some more statistics as well. I collect all the data from varied array of free sources, e.g. Shiller, MSCI, the Federal Reserve, generous financial professionals, and my own data. I grouped the portfolios into types; equity only, diversified buy and hold, tactical asset allocation, and bond only. The data is from the 1973 to 2013 period. Within each type the portfolios are sorted by compounded annual return (CAGR), the number most investors look to first. Without further ado, here is the data.

Diversified Portfolio Summary Data Oct 31 2014

Lots of data, I know. In the equity only portfolios there are the basic SP500 index and the MSCI world stock index (ex US). I also added two of the best quant portfolios I’ve discussed on the blog many times before. The diversified buy and hold portfolios show the most common and popular portfolios. The traditional 60/40 or 70/30 US stock US bond portfolios are the most basic and maybe the most common asset allocations for US investors. They are definitely the most talked about allocations, partially because they have the longest historical record. There are several portfolios named after their namesake advocate/creator; Bernstein, El-Erian, Arnott, Swenson, and Tobias. The IVY buy and hold portfolios, and the Permanent Portfolio are also shown on the list.  I also added two diversified buy and hold portfolios created with the quant equity strategies. The tactical asset allocation section shows the various trend following, risk manage IVY portfolios discussed on the blog many times. I then show various bond portfolios and inflation mainly for comparison purposes.

Phew! Now, what to make of all this? First, notice that within a broad swath of the diversified buy and hold portfolios they are all very similar in terms of returns and risk. One thing I see all the time is investors becoming overly zealous and even dogmatic in their portfolio choices. IVY is the best or 60/40 is the best because such and such. Don’t do this. Spend your time and energy somewhere else. There is not that great a difference in returns across the various portfolios and more importantly no guarantee those differences will persist over time. What about the first two portfolios on the diversified list? They show great return and risk characteristics. These are examples of low beta, high tilt portfolios. I chose the allocation among the quant portfolios and bonds specifically to limit risk to a max drawdown of approx 10%. Great returns and low risk. Problem is 90% of investors can’t or won’t implement these. In my opinion, more investors should look into these portfolios but I’ll leave that topic for another post. Overall, 4 of the buy and hold portfolios stand out – the top 2 quant/bond portfolios, the Permanent Portfolio, and the Risk Parity portfolio. They stand out because they have great returns and very low risk (low drawdowns, high sharpe/sortino ratios). The low risk characteristics of these portfolios make them much easier to stick to than the other diversified portfolios that can have very bad years. It also makes them attractive to retirees where bad years can have a huge impact on retirement.

Now for the tactical asset allocation category. These portfolios take the diversified buy and hold portfolios, in particular the IVY portfolios, and apply trend following and momentum to increase returns and reduce risk. Trend following and momentum could also be applied to other asset allocations which would also improve risk adjusted returns. What makes these portfolios appealing is the incredibly strong risk adjusted returns, without sacrificing too much in absolute returns. Again, that makes the portfolios easier to stick with and more suitable for retirees. And there is even more that can be done with these types of portfolios as I’ll explore in future posts. This is an area of active research for me.

There you have it. Enough portfolio data to drive one nuts. Use it as a reference, a starting point for further research, etc… I’ll keep these portfolios updated as best I can in the future and publish updates periodically.

 

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Using dividends to cushion against market gyrations

Early in 2013 I presented a quantitative strategy based on dividend paying stocks from OShaughnessy’s What Works On Wall Street. The Enhanced Dividend Yield strategy. The strategy provides market beating returns, higher sharpe ratios, and a healthy dividend stream. One of the best things about this strategy is it’s high stick-to-it-iveness. That’s a highly technical financial term that means that it is one of the easier quant strategies to adhere to and implement because of the high income stream from the strategy. The income stream provides a cushion that helps investors weather the tough times. Now, about 22 months after I first presented it I thought it would be good to go back and look at the strategy in some detail to point out it’s strengths and weaknesses. Also, we’ll look at the different results of this strategy for an investor pre-retirement who is focused on building wealth and for a retired investor spending the income from this strategy.

The Enhanced Dividend Yield strategy basically takes cheap market leading stocks and ranks them by dividend yield. An investors buys the top stocks from this ranked list and holds them for one year. Rinse and repeat. For details of the implementation of the strategy see my earlier post. Lets look at the recent performance of the strategy. The table below shows the performance of the Enhanced Dividend Yield strategy from the beginning of 1999 through Oct 19, 2014. I also list several other metrics which I’ll discuss below.

Enhanced Div Yield 1999 to Oct 2014

The strategy returned 17.4% a year over the last 15 years and 10 months. That compares to the 4.6% a year for the SP500 over the same time period. Not bad. As the dividend yield column shows the starting yield of the portfolio varies quite a bit every year. This is really a value strategy first, then a dividend strategy. The potential dividend income from the portfolio rises at 15.5% a year as well. An investor who is trying to build an income stream as retirement approaches would have been well served with such an approach. But what about a retiree? A retiree would maybe like to spend the dividends instead of re-investing them in the portfolio. The table below shows that analysis along side the previous one.

Enhanced Div Yield for retirees 1999 to Oct 2014

For a retiree, who is not re-investing the dividends into the portfolio the results of the Enhanced Dividend Yield strategy are quite impressive as well. Without re-invested dividends the portfolio grows at 9.9% a year plus the dividend income stream grows at 8.6% a year. That’s still a lot better than the SP500 and the income stream handily trounces inflation as well. Sounds like a great strategy to consider for a retirement portfolio. It is one of the core strategies I use in mine. But it’s not all roses. There are two negatives. One, is the strategy does not limit drawdowns. This is typical of all quant value strategies. You get higher returns in the long run but still suffer large drawdowns. The Consumer Staples and Utilities Value strategies do a better job of limiting drawdowns while still providing some level of income, all be it lower. The other downside, in particular for retirees, is the fluctuating level of dividend income from year to year. As the last column in the table shows, from year to year the level of dividends can decrease quite a bit, even though it is rises quite strongly over the long run. A retiree using this strategy could apply a smoothing approach to the income stream over a 3-5 year period to avoid this downside. Also, an allocation to bonds in an overall portfolio can accomplish the same thing.

Finally, what is the Enhanced Dividend Yield strategy telling us today. I ran the screen this weekend and the top 15 stocks are shown below.

Enhanced Div Yield Screen as of Oct 18 2014

The portfolio above yields 5% as of last Friday. That’s on the low end of the yield range for the last 15 years (compare to the first table in the post) which is to be expected in the current valuation environment but still a robust yield. We’ll see how it does over the next year compared to the market. I have a tracking portfolio set up in FINVIZ to monitor its progress.

In summary, the Enhanced Dividend Yield quant strategy is a great strategy for investors in the wealth building part of their lives and for retirees in the withdrawal phase. The high level of dividends not only enhances returns but also makes it easier to stick with the portfolio during rough times knowing that at least that income stream is there.

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Future returns and their impact on SWRs

Today I wanted to talk about the forecasting of future returns and more importantly what implications future returns have for SWRs (Safe Withdrawal Rates). As I showed in my last post, the first 10 year period real return in retirement is the best predictor of SWRs for 30 year retirement periods. Thus by creating a model for returns for the next 10 years based on where assets are priced today we can get a better idea as to the applicability of the traditional 4% SWR for future retirees.

There’s a been lot of discussion over the last couple of years in the financial blogosphere about future equity returns. Most of the that discussion is centered around US equity markets being over valued and therefore leading to very poor returns going forward, for anywhere from the next 5 years to the next 20 years. The analysis goes something like this; you take historical valuation figures based on different parameters such as Shiller PE, MarketCap to GDP, Q ratio and see what the historical forward returns where for different levels of starting valuation. Then you compare that history to today’s valuation level and make a statistical forecast for future returns. It’s more complicated than it sounds but that is essence of what the process is to arrive at return forecasts. The best summary of these types of analyses I’ve found anywhere is this post from GestaltU. There is a lot of gory detail (or awesome detail for folks like me) in the post and associated caveats but here is the punch line that we need to consider.

Butler forecasted returns oct 2014

Not so pretty right? The most probable compounded US equity returns for the next 10 years is about -1%. This could imply a rethinking of the 4% SWR. This being a statistical analysis there is a potential range of outcomes. I wanted to get a feel for what those range of outcomes were in the past with specific years attached to it – after all, this is based on historical data anyway. Sometimes the human brain needs context and a story behind the data to derive a better understanding. I went to my handy dandy data base of historical stock returns that I use for my SWR analyses and added the Shiller PE (CAPE) data to it, as well as bond returns, 60/40 portfolio returns and inflation. At the end of the day we care about total portfolio returns, not just equity returns. I then sorted all 10 year period returns starting in 1929 by CAPE range. Below is the summary. Highlighted is the CAPE range of the US equity market today, greater than 25.

Ten year historical returns by CAPE range oct 2014

The data in the table pretty much agrees with the GestaltU data. Forward stock returns from high valuation markets are low. Stock returns pretty much go up with decreasing starting valuation as expected. A couple of interesting things to note in the table are that bonds returns are highest at both high starting equity valuations and low starting equity valuations. Also, inflation increases as starting equity valuation decreases. This is not the place to delve into the reasons why but the important point is that these effects are all important to and affect what we care about which is total real portfolio return. The portfolio returns also decrease directly with increasing equity valuation but note that the absolute numbers are not as bad. A 2.85% avg portfolio real return from the highest valuation tier is a lot better than a -1% stock only return that starts freaking investors out. Now recall that the first 10 yr period return for the worst case retiree in history, which defined the 4% SWR rule, was -1.26% real per year for a 60/40 portfolio. So, this simple look into the details tells me that the 4% SWR rule is probably still OK. But could some of the future periods be worse than any other period in history? Yes. I think for more insight here we need to look into even more detail at the historical data. Below I break out all the 10 year periods with CAPE ratios greater than 20. The table is sorted by CAPE ratio from highest (most expensive) to lowest (cheapest).

Detailed Ten year historical returns by CAPE oct 2014

Along with CAPE I also added the yield of the 10 year note at the start of the period. For example, in the begging of 2000 the CAPE ratio was over 42 and the 10 yr yield was 5.11%. Note that indeed the 10 year period starting 1966 started from a high valuation, although not in the top tier, and produces almost the lowest total portfolio return with both negative real stock returns and bond returns! Now, could it be worse than 1966 in the future thereby forcing a lowering of the 4% SWR? To look at that I highlighted all the past years in yellow that could be called similar to today, with high equity valuations and low bond yields. Looking at the data and thinking about the story behind those periods makes me think that 1937 could be a similar parallel for today. Beginning of 1937 was about 8 years after the Great Depression. Today we stand at close to 7 years after the Great Recession. Maybe? Who knows but worth a think. The data is the data though – high equity valuations and low bond yields is what we face.

You could even say that there is no precedent for where we are today with CAPE ratios of over 25 and bond yields below 2.5%. And that could imply that the 4% rule may fail going forward. Definitely a possibility. But I think the important point is that it would take more than weak first 10 year equity returns to kill the 4% SWR. It would take a similar but even worse brew than the 1966 period which combined high starting equity valuations, with rising bond yields, and rapidly rising inflation.

If that was where we ended it would indeed be a worrying picture. And then maybe the best recommendation would be to reset expectations to a lower SWR. But the problem with the all the above is that we have taken a very narrow view of the brave new investing world we live in. The entire discussion above and in most of the blogosphere is solely focused on US equity markets. There are other markets out there with better valuations. Most of the discussion around the potential failure of the 4% SWR assumes a US large cap stock and US intermediate government bond only allocation. There are better asset allocation methods out there. There are portfolio strategies that seek to enhance return and minimize risk which also help maintain SWRs. There are better retirement withdrawal and spending models that help combat poor early returns in retirement. Before we go off concluding that a 4% SWR won’t cut it anymore we need to look at all of these and what impact they have on SWR. I’ve done that in many previous posts but I plan to recap and summarize most of that work in future posts.

In summary, future US equity returns are probably going to be lower than in the past due to today’s high valuations. But that is only part of the story when it comes to determining SWRs. Despite these headwinds I think that with the combination of better asset allocations, better portfolio strategies, and better spending and withdrawal models the 4% SWR can continue to serve retirees well into the future.

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