Tactical Asset Allocation for Dummies

Tactical Asset Allocation for Dummies

October 7, 2012 Research Insights, Tactical Asset Allocation Research
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(Last Updated On: March 14, 2017)

I was having lunch the other day with the Turnkey PhD and another business school professor, when the conversation turned to Tactical Asset Allocation (TAA).  At this point, this professor, who also happens to have a PhD from Chicago asked, “What is that?”  I realized then that sometimes even those who are otherwise extremely well-versed in finance can be unfamiliar with the term.  So let me try to break it down Barney-style…

Many people have traditionally felt that if they had their net worth invested in a portfolio consisting of a large number of common stocks, that they were, by definition, diversified.  As the financial crisis that unfolded in 2008 demonstrated, however, there is a significant weakness to this approach, which is that in times of extreme financial distress all the stocks in the portfolio can react in the same way – correlations go to one as they all plummet in value together,  potentially permanently devastating portfolios.  How can an investor protect himself against this kind of financial risk?

The key is to invest in asset classes that have low correlations with one another, so that when a given market condition predominates, some asset classes may shine, even as others come under pressure.  Some asset classes zig, as others zag.  For example, it is thought that investing in periods of deflation and recession, it is bonds that offer investors protection.  By contrast, in inflationary environments, hard assets such as commodities and real estate, theoretically can protect investors against a decline in their purchasing power.  Recently,  investors have increasingly sought out the benefits of being invested in foreign stocks which, while correlated with U.S. stocks, are driven heavily by events that are specific to their local markets, and also provide currency diversification.  Indeed, the endowments of major educational institutions have been successfully refining their asset allocation approach for many years.

Consider the financial challenges faced by the average endowment.  The endowment seeks to grow its asset base over time, but is called upon to  divert a steady, predictable cash flow stream from the portfolio to finance the operations of the institution.   Thus, in addition to its mission of growing its assets, it must also be highly sensitive to the risk of significant capital impairment.   If the portfolio suffers a large drawdown, then it risks putting its operating plans in jeopardy.  The best endowment managers, such as Yale’s David Swenson, manage this balancing act well, consistently growing the asset base, while ensuring that the ongoing cash flow requirements of the  institution can be met without compromising the portfolio, no matter the prevailing market conditions.   This is accomplished by careful  management of the underlying allocations within the portfolio.

“Fine,” you say.  “This all sounds reasonable.  But how am I supposed to determine the appropriate weightings to begin with, and then how do I rebalance these various asset classes going forward?”  Anyone who has sat through the obligatory business school finance classes covering the capital asset pricing model may have some recollections of how one might approach this allocation conundrum, since the theoretical imperative was hammered relentlessly into their heads.  According to most b-school professors, holding the market-weighted portfolio of all assets is the way to go. If you don’t like a ton of risk, simply hold the market portfolio and pair it with some risk-free bond exposure. This all works if you assume investors only care about average returns and standard deviation, you throw in a little Markowitz mean variance mathematics and some assumptions on investor rationality. The tactical asset allocation rule is clear:  investors should seek a value-weighted portfolio of all assets in all markets in the economy.  It is no surprise, therefore, that this is what you hear when you sit in the classroom at business schools today.

Yet is it possible there is another way?  After all, ideally, as financial conditions change, and asset classes within a portfolio fluctuate, investors might hope to tactically reallocate to take advantage of, say, a distressed situation in an asset class that has recently been hammered.  The successful tactical asset allocator might thereby seek to derive a benefit from changes in the underlying market  environment.  But how might you begin to attempt such an outlandish approach that flies in the face of the accepted market orthodoxy?

And that, dear reader, is where Turnkey Analyst comes in, as we have been hard at work researching this very question.  It turns out there has been a sizable body of research over the past several years into how one might hope to make such judgments.  What we are looking for is an approach that will dynamically position us, overweighting us in those asset classes that offer the potential  for significant gain, while simultaneously de-emphasizing those that are likely to generate losses. Is the process perfect? Of course not. Will they definitely work in the future? Who knows. But one thing is certainly clear: holding the “market portfolio” is a sure way to eat 50% drawdowns for breakfast.

Below are some backtest performance results achieved by applying different tactical asset allocation models.  As you can see, the choice of model can have a significant influence on the outcome.

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[Click to enlarge] The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.
Source: http://empiritrage.com/wp-content/uploads/2012/07/assetallocation_comparison_v01.pdf

The simple buy-and-hold equal-weight index eats a 47% drawdown. Yuck. Meanwhile, simple risk parity models, minimum variance allocations, or risk parity and momentum combinations drop the drawdown to 30% or less. If one adds a long-term MA rule on there, the results are even better.

As you can see from the data above, it would appear that different approaches to tactical asset allocation can have dramatically different outcomes.  We believe it is possible to use signals supplied to us by the markets to inform our exposures to different asset classes.  If you are curious and want to learn more about some of the cutting edge research exploring these tantalizing areas within finance, then stick with Turnkey Analyst.  We will share all our insights and then you can judge for yourself.

Big question: If this is so “easy,” why isn’t everyone doing it?

A few possibilities:

  • Data-mining–maybe the results were a result of good luck and the next 30 years won’t be so kind to the tactical asset allocation models suggested
  • Institutional Structure–Imagine a manager of a large endowment telling his investment board that he’ll be dropping stock exposure to zero because a long-term MA rule was triggered? Good luck with that.
  • Model Discipline–Most people simply can’t stay discipline to a systematic strategy. Why? Unclear, but my guess is it is the same reason people love eating Bic Macs, skip exercise, and can’t save for retirement.

 

 

 


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Definitions of common statistics used in our analysis are available here (towards the bottom)




About the Author

David Foulke

Mr. Foulke is currently an owner/manager at Tradingfront, Inc., a white-label robo advisor platform. Previously he was a Managing Member of Alpha Architect, a quantitative asset manager. Prior to joining Alpha Architect, he was a Senior Vice President at Pardee Resources Company, a manager of natural resource assets, including investments in mineral rights, timber and renewables. He has also worked in investment banking and capital markets roles within the financial services industry, including at Houlihan Lokey, GE Capital, and Burnham Financial. He also founded two technology companies: E-lingo.com, an internet-based provider of automated translation services, and Stonelocator.com, an online wholesaler of stone and tile. Mr. Foulke received an M.B.A. from The Wharton School of the University of Pennsylvania, and an A.B. from Dartmouth College.


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  • inthewoods

    This is great stuff – and I love the data you’re providing. I think there are multiple issues:

    1. It is tough for the average person to understand any of this – I’ve tried, for example, to explain this kind of thinking to, say, my brother-in-law and all I get back are deer-in-headlights. This is why most people in picking a money manager select the person they think is the smartest – and care little for their actual methodology.

    2. Managing money on a monthly basis takes some skill and time – rebalancing, buying, selling, etc. – especially with the more complicated models involving MAs.

    3. What the market is currently doing intimidates people – if the market has been on an upswing for a while and the model is telling you to get bigger, many people will hesitate – basically your model discipline issue with a bit more specificity. In the same way, if the market if falling, falling, it can be tough to make that buy.

    4. 401ks – a great number of my friends have most of their investments in 401ks – often ones which should have been rolled (but that’s a different story). So they are reduced to the investments available to them (usually a crappy set) – and then there are further restrictions put on them in terms of how often they can switch. I have this issue myself with a Fidelity 401k from my job – the switching costs and timing are very difficult to manage – thus, in that investment vehicle I’ve taken a much, much simpler approach.

    I’ve been looking for a source this kind of a portfolio for a while – thanks for providing.

  • All those ideas make sense. I agree on #4 in particular–I am currently stuck in my retirement plan at Drexel with a small set of crap options.

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