The Robust Asset Allocation (RAA) Index

The Robust Asset Allocation (RAA) Index

December 2, 2014 Research Insights, Key Research, Introduction Course, Tactical Asset Allocation Research
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(Last Updated On: May 18, 2017)

Robust: capable of performing without failure under a wide range of conditions

Merriam-Webster Dictionary

Many investors are faced with a fundamental problem: What should I do with my money?

People usually pursue one of four broad solutions to this problem:

  1. Hire an expensive investment advisor that invests in overpriced active management.
  2. Hire an affordable advisor that invests in what amounts to a 60/40-ish portfolio.
  3. Hire a cheap robo-advisor that invests in what amounts to a 60/40-ish portfolio.
  4. Hire an affordable advisor in something different than the 60/40-ish portfolio.

Option #1 is clearly a bad idea, but the options #2, #3, and #4 are all worth consideration.

As far as option #2, there are plenty of affordable, honest, independent advisors who charge reasonable prices for the value they deliver. You’ll probably get a portfolio that essentially mirrors a 60/40-ish portfolio, but you’ll also have access to financial planning, behavioral coaching, and peace of mind (~50-125bps all-in).

Option #3 is interesting as well, and there are plenty of dirt-cheap automated options that may not deliver the peace of mind a human advisor can deliver (at least not yet), but they also don’t charge that much for their 60/40-ish options. (~30-60bps all-in).

Finally, option #4 is also reasonable if the differentiated investment approach is affordable and better at helping an investor achieve an investment goal relative to the 60/40-ish portfolio (~50-200bps all-in).

Options #2 and #3 are probably best for a wide swath of financial consumers, but option #4 is certainly interesting for those with specialized investment goals and sound discipline. Option #4 is the topic of this piece.(1)

Note: For those who want to dive right into the specifics of the Robust Asset Allocation Indexes, information is available below:

A 60/40-ish Portfolio Isn’t Gonna Cut it For My Situation. What Should I do?

First, we recommend all investors trying to tackle the, “What should I do with my money?” question, grab a copy of our book DIY Financial Advisor, which outlines the concepts discussed in this post, but in much greater detail.  The book will prepare you with the knowledge to ask the right questions if you are interviewing financial advisors  and/or it will give you the necessary tools to be a successful Do-It-Yourself investor. (2)

DIY Financial Advisor

Okay, so you’ve powered through the DIY book, or you’ve punted on that option since you’d rather just read this blog post. Either way, you are faced with an investment decision and you consider the following:

Easiest solution:  60% global equity; 40% global bond  (or your own special weights depending on individual circumstances).

  • Cheap. Easy.
  • A reasonable approach. Totally DIYable.
  • This is a personal question, but something one should always consider: Is this portfolio achieving your objectives?

Easy solution:

Meb Faber and Eric Richardson in their book, The Ivy Portfolio, hint at a do-it-yourself model that is a simple portfolio that allocates across US equity, developed equity, REITs, commodities, and US Treasury bonds. These 5 asset classes are commonly referred to as the “IVY 5,” since they form the basic building blocks for the endowments of the ivy league schools and others. This can be a reasonable allocation to achieve some investors goals. We’ll discuss this framework and why it is an interesting starting point for those trying to achieve an objective that may differ from those blindly allocating to a generic 60/40 portfolio.

Robust Asset Allocation (RAA) Index:

The Robust Asset Allocation (RAA) Index is a dynamic algorithm we built with a specific goal: RAA seeks capital appreciation with downside protection. (3)

The tactical objectives of our RAA indexes are as follows:

  • Portfolio growth that keeps up with inflation (principle growth)
  • Downside protection (avoid large drawdowns)
  • Superior tax efficiency (tax-savvy investing)
  • Liquidity (facilitates flexibility)

Different investors have different objectives, but if your goal is to capture global asset returns, but at the same time you’d like to minimize the chance of a complete meltdown, our fully transparent RAA Indexes may be an interesting approach to explore.

There are three flavors of the RAA Index — balanced, moderate, and aggressive.

Let’s get started on understanding the nuts and bolts of our RAA Indexes.

Core Premise: Financial Advice Can be Simple and Effective

Our seed investor, who also happens to be a multi-billionaire and knows a lot more about investing than we could ever hope to achieve, has a great quote:

Wealth is built by concentrated holdings, but wealth is protected by diversification.

In short, if the goal is to get super rich, diversification and risk-management are arguably terrible ideas. A better idea is to concentrate on a single holding (i.e., build a business) and shoot for the stars. Of course, if your goal is to protect your wealth, diversification is a much more prudent approach. But there is no right answer. Goals are dependent on the investor and the specific objectives they want to achieve.

Once goals are established, we need financial advice to identify an investment solution that will achieve our goal. Remarkably, financial advice does not need to be complex to be effective. Our belief is based on a robust view of the evidence and my Marine Corps brainwashing to focus on having “brilliance in the basics.” Complexity is often a smokescreen that hides a conflict of interest. For example, there are known incentives for financial firms to generate complexity in order to justify their existence. There are also well-established dangers associated with data-mining and whipping the data until it says what you want. Good financial advice should minimize both scenarios, if possible.

To summarize, we are biased towards simplicity because it works and also has the following benefits:
  1. Simple processes are less susceptible to data-mining.
  2. Simple processes are harder to disguise as black-box solutions that charge higher fees.
Our beliefs serve as the cornerstone of how we build investment algorithms. We aim to keep things simple and effective.

Three Elements of Simple and Effective Financial Advice

We break our discussion into three sections:

  1. Asset Allocation: Instead of complex asset allocation, use simple allocation.
  2. Security Selection: Instead of story-based stock selection, use evidence-based stock selection.
  3. Risk Management: Instead of buy-and-hold, use a downside-protection system.
Charts presented are for illustrative purposes only. Our downside protection models may not work in all situations and could fail to achieve their objectives.

Each of these elements form the building blocks of the Robust Asset Allocation Index, which we discuss in the following three sections.

#1 Asset Allocation:  Instead of complex asset allocation, use simple allocation.

Charts presented are for illustrative purposes only. Our downside protection models may not work in all situations and could fail to achieve their objectives.

“Of the 14 models we evaluate across seven empirical datasets, none is consistently better than the 1/N rule…”

— DeMiguel, Garlappi and Uppal.

Victor Demiguel and his colleagues have explored many sophisticated methodologies to optimize asset allocation. They have solutions that can possibly beat an equal-weight allocation, but these alternative solutions add a high degree of complexity. Prof. DeMiguel has an outstanding outline of asset allocation research here if you’d like to explore further. We’ve discussed the academic rationale for following a simple asset allocation model in the past, here, and here. An equal-weight portfolio–also suggested by DeMiguel et al.–would seem to fly in the face of modern portfolio management, which in general has suggested that investors rely on mean-variance type allocation, or other highly engineered schemes. However, while mean-variance-analysis has reverse engineered the best historical Sharpe ratio (i.e. the tangency portfolio), this solution relies on a correlation matrix input, which is highly unstable and difficult to estimate. Indeed other approaches have this same weakness.(4)

DeMiguel et al. are not the only researchers suggesting that simplicity often rules the day when it comes to asset allocation. Even the great Harry Markowitz, a Nobel Prize winner and the founder of portfolio management, is quoted as saying:

“I should have computed the historical covariance of the asset classes and drawn an efficient frontier, [but] I split my contributions 50/50 between bonds and equities.”

A few quotes attributed to Einstein sum up the key lessons learned from piles of disinterested research compiled on the subject of asset allocation.

  1. Keep it simple.
  2. Complexity does not imply value.

Robust Asset Allocation_Keep it simple

 

Complexity is Suspect. Is Equal-Weight the Answer?

“Don’t try anything fancy. Stick to a simple diversified portfolio, keep your costs down and rebalance periodically to keep your asset allocations in line with your long-term goals.”

–David Swensen, Yale Endowment CIO.

The point of the DeMiguel et al. research cited above is not to imply that equal-weight allocations are always optimal and/or sensible. For example, if a portfolio consists of two assets — 1) call options on 3x leveraged S&P 500 ETFs and 2) 90-day T-bills — an equal-weight allocation may not make sense because the assets involved have dramatically different risk profiles and the 50% allocation to the call options on 3x levered S&P will obviously dominate all the action in the portfolio. So perhaps 50/50 isn’t the answer, but neither is dynamic risk-parity with machine-learning Q-theory Black-Litterman Whiz-bang mousetrap optimization across these 2 assets. Maybe a static 20/80 allocation will fit the bill? The main point of their research is that the signals generated by whiz-bang asset allocation models typically reflect noise, not actual signal.  And that brings us to the so-called benchmark for asset allocation, which is often considered the 60/40 portfolio, which is 60% allocated to global equities and 40% allocated to global bonds.(5) This portfolio reflects the essence of the advice gleamed from DeMiguel et al.’s work — keep it simple. That said, “experts” will put forth hundreds of arguments for why the 60/40 portfolio is sub-optimal, won’t work, and so forth, but the reality is that the portfolio does follow the FACTS and does provide some reasonable diversification. We can all argue why 60/40 is broken (I’m happy to provide those arguments), but for many investors this is an option worth considering.

So how can we possibly improve upon the baseline 60/40 benchmark without going down the complexity railroad, which often is a bridge to nowhere?

One approach is to look at the 60/40 portfolio as essentially 60% equity and 40% “diversifiers.” Bonds are often dumped in the diversifier bucket because they are relatively easy to understand. But bonds only represent one form of a diversifier — there are many others — but will bonds always be an effective diversifier? We’re not sure. Should we really put all our eggs in the bond diversification bucket? Possibly, but it seems prudent to at least consider a more robustly designed diversifier bucket.

We need to be careful when we explore a more complex diversifier allocation — the cure may be worse than the disease. When it comes to diversifiers, often labeled “alternatives,” one can go nuts trying to compile unique risk/return premiums. Perhaps this effort is appropriate for some investors with the time, resources, and buying power to create a solution that is in line with the FACTS and achieves their specific objectives. However, for the rest of us (and maybe even the pros), we may be better off trying to replicate what larger more sophisticated investors can achieve, but without all the brain damage and costs. The “IVY 5” portfolio, described by Faber (2007) and then further elaborated by Faber and Richardson (2009), is a great example of this approach. The authors highlight that the largest endowments have highly complex portfolios that extend well beyond the 60/40 benchmark with respect to their levels of complexity. Nonetheless, the performance of a simple endowment replication model, consisting of 5 core asset classes, does a pretty reasonable job at capturing their performance. The 5 core asset classes are as follows:

  • US Stocks= SP500 Total Return Index
  • Int’l Stocks= MSCI EAFE Total Return Index
  • REIT= FTSE NAREIT All Equity REITS Total Return Index
  • Comm.= Goldman Sachs Commodity Index (GSCI) Index
  • Bonds= Merrill Lynch 7-10 year Government Bond Index

With a shift away from equal-weights across the 5 assets, we can augment the IVY 5 concept to create a 60/40 portfolio, where the key difference is the “diversifier” bucket is no longer entirely dependent on bonds, but has a mix of real assets and bonds. We refer to this portfolio as “RAA Simple.” The goal of RAA Simple is to capture expected returns associated with a diversified pool of global assets.

Arguably, this slightly more complex 60/40 allocation is structurally more robust to various economic regimes in the future and doesn’t have all the diversifier eggs in the “bond basket.”

Here are some summary statistics for RAA Simple and the underlying components:(6)

Summary Statistics: Simulated Strategy Performance (1/1995 – 12/2016)
Summary Statistics RAA Simple US Stocks Int’l Stocks REIT Comm. Bonds
CAGR 7.41% 9.76% 4.57% 10.97% 0.41% 6.82%
Sharpe Ratio 0.49 0.54 0.21 0.51 0.02 0.73
Worst Drawdown -43.90% -50.21% -56.68% -68.30% -80.90% -6.40%

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.

RAA Simple achieves its goal of capturing global risk premiums, but without the chaos of any of the individual asset classes. So RAA Simple achieves the goal of capturing global risk premiums in a structurally diverse way. Did RAA Simple do better than a US 60/40? Not by a long shot. But RAA Simple and US 60/40 aren’t built to achieve the same goal. US 60/40 doesn’t achieve the goal of capturing global risk premiums in a structurally robust way. US 60/40 captures US risk premiums with limited asset diversification. If that is your goal, great.

Another thing to point out is that RAA Simple doesn’t really curb your drawdown that much via diversification. -43.90% is a lot better than some of the alternatives, but the 2008 Financial Crisis taught investors that diversification isn’t a silver bullet to prevent permanent loss of capital. Moreover, US 60/40 is also not the sure-fire answer, as the table in our “world’s longest trend following backtest highlights.”  We’ll talk about potential methods to solve the limits of diversification when we talk about risk management, but first let’s move on to security selection.

#2 Security Selection: Instead of story-based stock selection, use evidence-based stock selection

Charts presented are for illustrative purposes only. Our downside protection models may not work in all situations and could fail to achieve their objectives.

RAA Simple deploys passive equity investments in the form of the large-cap domestic equity and large-cap developed equity. This is a fine approach and is easy to understand and implement. However, when it comes to security selection methods, there are arguably ways to potentially improve the overall profile of the investment portfolio, without getting too far out on the complexity curve. In this section we focus entirely on the equity component of the portfolio, however, as discussed in our DIY book and throughout blog, there is research to suggests that one can leverage selection algorithms to differentiate REIT, commodity, and bond exposures. We think the juice generated from the additional complexity may not be worth the squeeze in most cases, but this is certainly something an investor could explore.(7)

In case you haven’t noticed, we have droned on and on over the potential benefits and sustainability of focused value and momentum equity exposures. We’ve even spent the time to write entire books dedicated to both of these subjects, which we encourage you to read. However, the synopsis is simple and will save you a lot of time:

  • Value: Buy cheap stuff everyone hates.
  • Momentum: Buy winners.
  • Have a 10+yr horizon and stick with the strategies through thick and thin.

Here are some key stats related associated with our Quantitative Value and Quantitative Momentum Indexes, relative to passive equity exposures.

First, the US Value/Momentum simulated results:(8)

Summary Statistics: Simulated Strategy Performance

(1/1995 – 12/2016)

Summary Statistics US_Combo SP500
CAGR 13.33% 9.76%
Sharpe Ratio 0.61 0.54
Worst Drawdown -57.35% -50.21%

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.

And here are the International Value/Momentum simulated results:(9)

Summary Statistics: Simulated Strategy Performance

(1/1995 – 12/2016)

Summary Statistics Int’l_Combo EAFE
CAGR 13.87% 4.57%
Sharpe Ratio 0.69 0.21
Worst Drawdown -55.49% -56.68%

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.

We look at the addition of our Quantitative Value and Quantitative Momentum Indexes inside the RAA Index because these indexes are part of the RAA system, however, more statistics on value and momentum are available in the references.(10)

The key thing to consider with any simulated index is that they look good on paper — there was never a backtest published that didn’t look great. But what generated these excess returns? And why can we hypothesize that these excess returns will be captured in the future? This is a debate that still rages on in academic research circles, but essentially excess expected returns are driven by 2 potential sources: 1) additional risk, and/or 2) systematic mispricing. With value and momentum in particular, there is arguably some mispricing built into the premiums, but exploiting these premiums is not a free lunch. An investor will likely be asked to take on more risk, and one can expect to endure epic episodes of relative performance pain (See here on momentum and here on value).

Bottomline: no pain, no gain is a good motto to live by when it comes to setting financial investment expectations for focused factor investments such as our flavor of systematic value and momentum.

So let’s assume that the evidence is compelling enough for our quantitative value and quantitative momentum processes and you are a long-term buyer. Great. But how do these exposures work in the context of our RAA construct?

Here are some summary stats comparing RAA Simple, which allocates to passive equity investment vehicles, with RAA Simple w/ Val/Mom, which replaces the passive equity indexes with our value and momentum indexes:(11)

Summary Statistics: Simulated Strategy Performance

(1/1995 – 12/2016)

Summary Statistics RAA Simple Val/Mom RAA Simple
CAGR 11.42% 7.41%
Sharpe Ratio 0.73 0.49
Worst Drawdown -46.86% -43.90%

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.

Replacing passive equity with our focused value and momentum indexes definitely improves the historical returns and risk-adjusted ratios, but there is also a pickup in the drawdown by a few percent. On the net, the simulated benefits look promising, but there is still that pesky drawdown problem.

#3 Risk Management: instead of no downside protection, use downside protection.

Charts presented are for illustrative purposes only. Our downside protection models may not work in all situations and could fail to achieve their objectives.

As we saw above, diversification is a prudent thing to implement in a portfolio. However, if the goal of your investment program is to capture global risk premiums and minimize permanent loss of capital, diversification isn’t going to cut it when correlations go to 1. Even the RAA Simple portfolio, which diversifies across a broad swath of assets, ate a 40%+ drawdown in 2008. Yikes.

If diversification isn’t going to help some investors achieve their goal of minimizing extreme tail risks, what can an investor do? Unfortunately, we enter a murky world of complexity, which should automatically raise our spidey sense. In fact,  any effort to minimize tail risk almost necessarily requires that the portfolio be 1) diversified and 2) be dynamic.  A 60/40 portfolio or a RAA Simple portfolio are both diversified, but their allocations aren’t dynamic.

Having reviewed and considered an incredible number of dynamic timing systems, the sad truth is it difficult to identify robustness.(12)

However, there are one class of models that are fairly simple and have historically achieved the goal of capturing risk premiums, while simultaneously minimize the risk or large drawdowns. These models generally fall under the category of “trend-following,” and include things like moving averages and channel breakouts.

The application of simple moving average rules has been demonstrated to protect investors from large market drawdowns, which is defined as the peak-to-trough decline experienced by an investor. For example, Jeremy Siegel, in his book, Stocks for the Long Run, explores the effect on performance on the Dow Jones Industrial Average from 1886 to 2006, when applying a 200-day moving average rule. Applying the rule is straightforward. If the market is above the 200-day moving average rule, hold, otherwise go to cash. Siegel found that this simple technical rule outperforms a buy-and-hold approach, both in absolute terms and on a risk-adjusted basis. Meb also highlights similar results in his paper on the subject of long-term moving averages.

We’ve conducted a similar analysis on the US stock market from 1801 to 2015 and found that trend-following rules applied on the generic stock market have been effective at minimizing tail risk events. We’ve extended the analysis to every asset class where we could get our hands on the numbers and investigated the results. Same conclusion: trend-following minimizes tail risk.

Got it. This so-called trend-following aspect helps minimize large drawdowns, but 1) why should I care? and 2) can you explain the voodoo behind it?

Why Tail-Risk Management Matters

For some investors with multi-decade horizons, managing large drawdown risks, especially if it comes at an expense to long-term compounding, may not be a great idea. However, for some investors, who have shorter horizons and/or more immediate liquidity needs, risk-management is really important if they want to achieve their investment goals. The chart below highlights why large drawdowns are hazardous to your wealth.

Charts presented are for illustrative purposes only. Our downside protection models may not work in all situations and could fail to achieve their objectives.

The chart on the left shows what happens to an investment portfolio when it is cut in half. Just to get back to even requires 11 years at a 7% return. Perhaps some people don’t need to tap that capital for 11 years so compounding out of the drawdown isn’t a big deal. But what if the plan was to live off your nest egg? Taking a 4% yield on $100 is one thing — taking a 4% yield on $50 is entirely different and may no longer meet the investor’s needs. The chart on the right shows what happens when there is a less severe drawdown of 15%. This is obviously not the ideal outcome, but if an investor seeks capital appreciation, they must take on risk, which means drawdowns and volatility are inevitable. But a 15% drawdown is much more manageable and only requires 3 years at 7% compounding to get back to even. A lot of investors can wait out 3 years of pain, but few can deal with 11 years of pain.

Roger That — I Get Why I Want to Control My Drawdowns. Can You Explain the Voodoo Magic of Trend-Following?

The depth of research on trend-following is mind-blowing. You can quickly go down the dark rabbit hole of backtesting and generate charts that would make Bernie Madoff blush. Of course, these systems are clearly over-optimized and unlikely to be robust out of sample. Moreover, having reviewed and thought about hundreds of trend-following systems, there is one clear message — nothing works all the time. The goal is to find the simplest and most robust approaches out there and then have the conviction to follow these systems to the grave. The figure below outlines our approach:

Charts presented are for illustrative purposes only. Our downside protection models may not work in all situations and could fail to achieve their objectives.

We have a time series, or absolute momentum rule, and we have a long-term moving average rule.

We define each of the rules below:

1. Time Series Momentum Rule (TMOM)

This rule is meant to avoid assets with poor absolute performance.

  • Excess return = total return over past x months less return of T-bill
    • If Excess return >0, go long risky assets. Otherwise, go alternative assets (T-bills or Zero).
    • Popularized by Gary Antonacci and rigorously examined by Moskowitz et al.

2. Simple Moving Average Rule (MA)

This rule is meant to avoid assets with poor trending performance.

  • Moving Average (N) = average N month prices
    • If Current Price – Moving Average (N) > 0, go long risky assets. Otherwise, go alternative assets (T-bills or Zero).

As the equations highlight, MOM and MA rules are tied together: Time-series momentum rules (MOM) are a function of MA rules. And while MOM and MA triggers are highly correlated, there are circumstances where the rules have a difference of opinion.

TMOM and MA rules are actually mathematically related.(13)

However, while these rules are similar, we’ve found evidence that these rules sometimes have a “difference of opinion,” where one rule says “risk” and the other says “no risk.” We also find that spreading our trend-following bet across these two systems is more robust than simply relying on one or the other. (14)

What Does Trend-Following Do For the Model RAA Portfolio?

Step 1 outlined the idea that we don’t need overly complex asset allocation frameworks to capture global risk premiums. Step 2 suggested that we can maximize our chance of the highest expected equity risk premium via focused value and momentum exposures. In step 3 we’ve suggested that trend-following can help minimize the chance of large drawdowns. Let’s see how trend-following affects the RAA system.

First some basics on the test:

  • RAA Moderate Index = 60% equity, volatility weighted across QVAL_INDEX_NET, QMOM_INDEX_NET, IVAL_INDEX_NET, and QMOM_INDEX_NET, annually rebalanced; 10% REIT; 10% GSCI; 20% LTR.
    • RAA Index results are net of 75bps management fee
    • Trend rules are calculated based on underlying passive asset class benchmark (i.e., QVAL_INDEX_NET is based on SP500 TR Index)
  • US_Combo = US Value and Momentum Portfolio, monthly rebalanced
    • 50% Quantitative Value Index, net of 2% fees
    • 50% Quantitative Momentum Index, net of 2% fees
  • Int’l_Combo = Int’l Value and Momentum Portfolio, monthly rebalanced
    • 50% International Quantitative Value Index, net of 2% fees
    • 50% International Quantitative Momentum Index, net of 3% fees
  • RAA Simple Val/Mom = 30% US Combo, 30% Int’l Combo, 10% REIT, 10% Comm, 20% Bonds
  • Total returns, including dividends and distributions

Here are the results comparing RAA Simple (passive IVY5 portfolio), RAA Val/Mom (RAA Simple with value and momentum equity exposures), and RAA Moderate Index, which is RAA Simple Val/Mom, but with the addition of our trend-following rules applied on each asset class.

Summary Statistics: Simulated Strategy Performance

(1/1995 – 12/2016)

Summary Statistics* RAA_MOD_INDEX_NET RAA Simple Val/Mom RAA Simple
CAGR 11.74% 11.42% 7.41%
Sharpe Ratio 1.02 0.73 -0.13
Worst Drawdown -15.41% -46.86% -43.90%

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.

One of these systems doesn’t look like the other. The RAA Moderate Index, which includes the trend-following overlay has a more favorable drawdown profile relative to the other globally diversified portfolio.

Sure sounds great if my goal it to capture global risk premiums while simultaneously looking to minimize the likelihood of eating a major loss along the way. What’s the catch?

First, systems like the RAA index are not going to track standard benchmarks. The chart below maps out the 12-month rolling compound growth rate for the model portfolios in the table above and the US 60/40 portfolio (monthly rebalanced across S&P 500 and 10-Year bonds).

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.

One can expect to underperform (and outperform) the generic 60/40 in any given year or set of years. But that is to be expected because the US 60/40 is a different portfolio with different objectives than the RAA Moderate Index. The RAA Moderate Index is built to capture global risk premiums and minimize the chance of large tail risks. The US 60/40 portfolio is built to capture US risk premiums. Different portfolios will mechanically lead to different outcomes.

Second, the RAA system can’t eliminate volatility and isn’t build to minimize short-run volatility. By construction, RAA will hold risky assets in order to try and capture some returns. Again, the golden rule of investing still applies here: no pain, no gain. So the RAA Index will go up and down and all around. No way around that reality if part of the investment goal is to grow the investment portfolio.

Robust Asset Allocation — Putting It All Together

RAA is our best effort to develop a simple model. Developing a complicated model would have been easier, but simple was a considerably more difficult challenge. We’ve discussed the three building blocks of the RAA Index methodology: simple asset allocation, evidence-based security selection, and a trend-following based downside protection mechanism.

Charts presented are for illustrative purposes only. Our downside protection models may not work in all situations and could fail to achieve their objectives.

Here is a detailed visualization of the RAA Index process (moderate shown).

Charts presented are for illustrative purposes only. Our downside protection models may not work in all situations and could fail to achieve their objectives.

We start with a more robust 60/40 framework that splits the traditional bond-only 40% diversifier bucket across real and bond assets.

Next, we replace passive stock exposures with focused value and momentum exposures.

Then, we calculate trend-following rules for each asset class to determine their respective exposures.

Finally, we implement the model.

Is the RAA Index process a holy grail? Is the RAA Index appropriate for all investors? Highly unlikely.

Here are some reasons why the RAA concept is a bad idea:

  • The RAA multi-asset focus can drag on returns relative to generic 60/40 portfolios
  • Downside protection can drag on returns relative to 60/40 portfolios
  • Value/momentum can drag on returns relative to passive equity portfolios
  • Global equity can drag on returns relative to domestic-centric portfolios

Long story short, RAA will not always work and will often underperform standard benchmarks. But that is baked in the cake. The RAA Index mission is goal-oriented and seeks to provide capital appreciation with downside protection. The RAA Index is not meant to track the 60/40 index or closely track generic benchmarks. The RAA Index is not meant to outperform X, Y, or Z. The systems are simply our best attempt to achieve the goal of capturing global risk premiums, while simultaneously minimizing the chance of a permanent loss of capital. Simple as that.

For those who are interested in exploring our RAA Indexes in greater detail, to include monthly returns, simulated results, and a more details on the process, we provide documentation on our Indexes here. The RAA Index specific information is available via the links below:

We want to emphasize that RAA is merely one solution we have proposed to achieve a specific investment goal.  There are a set of other solutions in the marketplace that seek to do similar thing and we recommend that investors explore all of these options. However, we suggest that investors can narrow their solutions down to those options that are simple, liquid, transparent,  affordable, and tax-efficient (if applicable).

Sounds great — What’s the next step?

Investors have a few options with the RAA Indexes:

  • DIY investor: we provide free tools to help investors facilitate a variety of tactical asset allocation strategies (to include the RAA Indexes).
  • Managed Accounts: We seek to track the performance of our RAA Indexes via managed accounts, which are offered via our automated offering, Alpha Architect Advisor.
  • Sub-Advisory: Are you advisor looking to achieve the RAA Index objectives? We can help facilitate.
  • Ask Your Advisor: Are you currently a client of an advisor and you’d like them to explore our solution? Let us know — we’ll help them get up and running.

As always, feel free to contact us if you have any questions and or thoughts.


Note: This site provides NO information on our value investing ETFs or our momentum investing ETFs. Please refer to this site.


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

References   [ + ]

1. Of course, as the authors of the book, DIY Financial Advisor, we’d be remiss if we failed to mention that another option for investors is to simply Do-It-Yourself. This is a fine option if one has the 1) time, 2) sophistication, and 3) discipline to identify an investment goal, build a portfolio to achieve that goal, and can stick to the program through thick and thin.
2. I have a Google Talk on the book if you want a video version of the DIY philosophy. If this is too much brain damage, simply head over to our active robo advisor and we’ll implement a strategy that attempts to follow the RAA Index most suitable for your investment profile.
3. Past performance is no guarantee of future results. Any historical returns, expected returns, or probability projections may not reflect actual future performance. All securities involve risk and may result in loss. Our downside protection models may not work in all situations and could fail to achieve their objectives.
4. The results below, taken from the DeMiguel et al. paper on asset allocation, highlight the incredible robustness associated with an equal-weight, or 1/N, type of asset allocation regime. (we have our own version of this in “Tactical Asset Allocation: Beware of Geeks Bearing Formulas“)

Robust Asset Allocation_Optimal vs Naive Diversification
Source: DeMiguel, V., L. Garlappi, and R. Uppal, 2009, Optimal Versus Naïve Diversification: How Inefficient is the 1/N Portfolio Strategy? Review of Financial Studies 5, 1915-1953. 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.

The chart above is visualized below. Sharpe ratio is on the X-axis for the various asset allocation systems trading with S&P sectors. Note that the simple 1/N strategy works as well, and often better, than more complex approaches.

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.

5. Why this portfolio structure became the benchmark solution is beyond me and perhaps there is someone who has done the history of how this came to be.
6.

  • RAA Simple = 30% US Stocks, 30% Int’l Stocks, 10% REIT, 10% Comm, 20% Bonds (gross of fees)
  • US Stocks= SP500 Total Return Index
  • Int’l Stocks= MSCI EAFE Total Return Index
  • REIT= FTSE NAREIT All Equity REITS Total Return Index
  • Comm.= Goldman Sachs Commodity Index (GSCI) Index
  • Bonds= Merrill Lynch 7-10 year Government Bond Index
  • All indexes are gross of fees and reflect total returns, including dividends and distributions.
7. The most compelling argument is with respect to the commodity exposure, which we benchmark using the GSCI index, however, there are economic and evidence-based reasons why in practical implementation GSCI may not be the desired vehicle.
8.

  • US_Combo = US Value and Momentum Portfolio, monthly rebalanced
    • 50% Quantitative Value Index, net of 2% fees
    • 50% Quantitative Momentum Index, net of 2% fees
  • SP500 = SP500 Total Return Index, gross of fees
  • Simulated Performance: 1/1/1995 to 12/31/2016
  • Total returns, including dividends and distributions
9.

  • Int’l_Combo = Int’l Value and Momentum Portfolio, monthly rebalanced
    • 50% International Quantitative Value Index, net of 2% fees
    • 50% International Quantitative Momentum Index, net of 3% fees
  • SP500 = SP500 Total Return Index, gross of fees
  • Simulated Performance: 1/1/1995 to 12/31/2016
  • Total returns, including dividends and distributions
10. Here we present simulated gross of fee performances of these two strategies from 1/1/1963 to 12/31/2015, using publicly available data from Ken French’s website.

First, we examine momentum:

  • MOM_10 = Top Decile Momentum (Data); Momentum has worked!
Robust Asset Allocation figure 3
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.
  • VAL_10 = Top Decile Value (Data); Value has also worked!
Robust Asset Allocation figure 4
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.

11.

  • RAA Simple Val/Mom = 30% US Combo, 30% Int’l Combo, 10% REIT, 10% Comm, 20% Bonds
  • US_Combo = US Value and Momentum Portfolio, monthly rebalanced
    • 50% Quantitative Value Index, net of 2% fees
    • 50% Quantitative Momentum Index, net of 2% fees
  • Int’l_Combo = Int’l Value and Momentum Portfolio, monthly rebalanced
    • 50% International Quantitative Value Index, net of 2% fees
    • 50% International Quantitative Momentum Index, net of 3% fees
  • RAA Simple = 30% US Stocks, 30% Int’l Stocks, 10% REIT, 10% Comm, 20% Bonds
  • Total returns, including dividends and distributions
12. We have examined hundreds of risk-management platforms over the years. You name it–we’ve backtested it, thought about it, and/or considered implementing it. We’ll keep testing new ideas and trying to identify the holy grail, but we haven’t found it yet.

Conclusion: Asset allocation models are 99% noise; 1% signal.

Here is a sampling of the various ideas we have tested:

Macroeconomic Fundamental Indicators

  • Wealth Ratio — Lettau and Ludvigson (2001) , “Consumption, Aggregate Wealth, and Expected Stock Returns”
  • Adaptive Macro Indexes — Bai (2010) ,”Equity Premium Predictions with Adaptive Macro Indexes”
  • Sum of Macro Variables — Ferreira and Santa-Clara (2011),  “Forecasting Stock Market Returns: The Sum of the Parts is More than the Whole”
  • Industrial Mental Return — Jacobsen, Marshall and Visaltanachoti (2013), “Stock Market Predictability and Industrial Metal Returns”
  • Implied Cost of Capital — Li, Ng and Swaminathan (2013), “Predicting Market Returns Using Aggregate Implied Cost of Capital”
  • Oil Factor — Kilian and Park (2007), “The Impact of Oil Price Shocks on the U.S. Stock Market”
  • CAPE — Robert Shiller (2013)

Technical Indicators

  • Historical Data Forecast — Maheu and McCurdy (2006), “How Useful are Historical Data for Forecasting the Long-Run Equity Return Distribution?”
  • Time-Varying Sharpe Ratio — Tang and Whitelaw (2011), “Time-Varying Sharpe Ratios and Market Timing”
  • Return Dispersion — Maio (2012), “Return dispersion and the predictability of stock returns”
  • Mean Reversion Indicator — Huang, Jinag, Tu and Zhou (2012), “Mean Reversion, Momentum and Return Predictability”
  • Cross-sectional Technical Analysis–Han, Yang, Zhou, “A New Anomaly: The Cross-Sectional Profitability of Technical Analysis”
  • Simple MA Rule –Faber (2007), “A Quantitative Approach to Tactical Asset Allocation.”
  • Challenging MA rule #1 –Scholz and Walther (2011), “The trend is not your friend! Why empirical timing success is determined by the underlying’s price characteristics and market efficiency is irrelevant”
  • Challenging MA Rule #2–Zakamulin, “The Real-Life Performance of Market Timing with Moving Average and Time-Series Momentum Rules”
  • Challenging MA Rule #3–Marmi, Pacati, Risso, Reno, “A Quantitative Approach to Faber’s Tactical Asset Allocation”
  • Overview of Technical Analysis — Park and Irwin (2007), “What we know about the profitability of technical analysis?”

Sentiment and Variance Indicators

  • Investor Sentiment — Huang, Tu, Jiang and Zhou (2014), “Investor Sentiment Aligned: A Powerful Predictor of Stock Returns”
  • Cross-Section of Volatility — Ang, Hodrick, Xing and Zhang (2006), “The Cross-Section of Volatility and Expected Returns”
  • Variance Risk Premia — Bollerslev, Tauchen and Zhou (2009), “Expected Stock Returns and Variance Risk Premia”
  • VIX Term Structure — Johnson (2011), “Equity Risk Premia and the VIX Term Structure”
  • Equity Shares — Baker and Wurgler (2000), “The Equity Share in New Issues and Aggregate Stock Returns”
  • Broker-Dealer Leverage — Adrian, Etula and Muir (2013), “Financial Intermediaries and the Cross-Section of Asset Returns”
  • Implied Volatility Spread — Atilgan, Bali and Demirtas (2011),”Implied Volatility Spreads, Skewness and Expected Market Returns”

Comprehensive Summary of Different Predictors

  • Gupta, Modise and Uwilingiye (2012) — “Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors”
  • Welch and Goyal (2008) — “A Comprehensive Look at The Empirical Performance of Equity Premium Prediction”
  • Rapach and Zhou (2011) — “Forecasting Stock Returns”
  • Combo — Neely, Rapach, Tu and Zhou (2011), “Forecasting the Equity Risk Premium: The Role of Technical Indicators”

The sad conclusion is that none of these ideas stand up to intense robustness tests, except for the simplest, technical rules. You just can’t beat them.

13. We have actually identified the mathematical relationship between MOM and MA Rules, outlined in the chart below:

Robust Asset Allocation_Momentum and MA rule

14. Here is an extensive study on these rules and their historical performance on a slew of generic return data series.



About the Author

Wesley R. Gray, Ph.D.

After serving as a Captain in the United States Marine Corps, Dr. Gray earned a PhD, and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management that delivers affordable active exposures for tax-sensitive investors. Dr. Gray has published four books and a number of academic articles. Wes is a regular contributor to multiple industry outlets, to include the following: Wall Street Journal, Forbes, ETF.com, and the CFA Institute. Dr. Gray earned an MBA and a PhD in finance from the University of Chicago and graduated magna cum laude with a BS from The Wharton School of the University of Pennsylvania.


  • Doug

    Great article! How would you change it for tax-deferred accounts (IRAs, non-profits, etc.)? More frequent rebalancing?

  • I wouldn’t change it.

    Perhaps you can think strategically about how you apply the concept across your taxable/non-taxable money. So push the income-producing/tax-inefficient bonds into the non-taxable accounts, and keep the taxable $ for equity (which is easy to tax manage).

    More frequent rebalancing doesn’t improve results in expectation and after costs.

    Just keep it simple.

  • Chris Scott

    Interesting article. I agree data mining is rampant in TAA models/research, most everything I’ve looked at provides no reliable value after transaction costs.

    Can you elaborate on the simulated graphs comparing MOM/MA rules? I can’t figure out what they represent.

    You state that combining MOM and MA gives a more robust result – do you find that you get this increase in robustness over using two MA (or MOM) rules with different lookback periods(N)?

    What lookback period do you use in your strategy backtest? Most MA models seem to use 10 months/200 days which historically gives great results as it is the optimal lookback period for the US stock market. While MA rules in general seem to provide a valid improvement in risk/return, using an optimal lookback period (most likely a data mining artifact) overstates the potential benefit.

  • They represent different scenarios where MOM=MA=0, MOM=MA=1, and MOMMA. Just meant to highlight that there are scenarios where the 2 systems disagree.

    When you dig into the drawdowns across various asset classes you notice that the two systems protect at different times and aren’t the exact same thing. So you get some ‘diversification’ across risk management systems. The effects are somewhat marginal, since MOM and MA are so similar in nature, but there does seem to be some measurable benefit. Again, the trick with TAA is writing a shorter story, not a long one. Anyone can write a long story…

    12 months for MA and MOM. Robust across a range of 8month to 15month, etc.

  • David

    If equities are in taxable space how damaging is that to the returns of the risk managed versions vs buy, hold and rebalance? 50bps doesn’t seem like it would cover tax costs. Presumably you’ve done more detailed (private) analysis for affected clients – any broad conclusions?

  • you need to tax manage the risk-management events–never eat a taxable gain…engineer around it…you can short an S&P 500 future against an equity position to drag its exposure to ~0…do whatever you can to avoid realizing taxes…

  • davidcarris

    Any place here for TIPs? I realize, though, that their short existence defies back-testing but is that any reason to eliminate them going forward? Couldn’t a back-test use a “synthetic” TIP or even just an inflation asset?

  • We’ve looked at it–among other things.
    Summary problems: I think you already have the ‘inflation-protection’ plug filled with the large real-asset exposure. Not sure TIPS add anything but complexity beyond what is already presented above.
    And the income taxation on the ‘inflation-adjustment’ is akin the government digging your heart out with a spoon–first they inflate your dollars away, and then they only really comp you for 50% of the inflation hit after you pay your taxes. Crazy. Throwing TIPs in place of 10-years in an IRA–or splitting them 50/50–might be a reasonable idea, but it will have marginal effects on your long-term risk/reward after-tax after-fee returns.

  • AA

    Hi Dr Gray,

    As always, a superb article.

    My question is: In your RAA solution, why do you not use the Momentum and Value strategies for Real Estate, Commodities and Fixed Income? Are these strategies simply not robust enough for these asset classes during your backtests, or are there other more fundamental reasons?

    Thank you

  • You could certainly do that if you have the means and are willing to work through that additional complexity. Trading underlying equities is typically easier for most investors than trading in commodities and fixed income. Applying value/momentum concepts to REITS is not too challenging.

  • AA

    Thank you Dr Gray.

    One other question is whether you have tested the Kelly Criterion in your asset allocation methodologies above? I understand that further complexities arise because (i) implementation is time dependent compared to a 1/N strategy and (ii) a sufficient knowledge of odds is required a priori, but I’m curious as to what you think of it.

  • I think simple is generally better, all else equal. To justify complexity you need some substantive empirical evidence and theoretical justification for the added brain damage.

    I think Victor DeMiguel does a wonderful job discussing the costs/benefits of complexity in the context of asset allocation. He wrote the paper that highlights that complexity hasn’t worked relative to 1/N, but he also has some extraordinary research–that is also highly complex–suggesting that there might be ways to improve upon 1/N. http://faculty.london.edu/avmiguel/papers.html

    Kelly Criterion betting, or any system that identifies the best way to achieve the highest possible long-term geometric mean with the lowest variance possible, is good to go. But you also gotta weigh the brain damage costs against the potential benefits…I have 10 brain cells, so burning a few on Kelly Criterion, only leaves me with 7 or 8…yikes

  • scottsinvest

    Nicely done. Does your RAA backtest require the risk asset to have positive time series momentum AND to be trading above its moving average? Are you using 12 month time frame for both in the tests?

  • Park Research, LLC.

    Dr. Gray,

    I am wondering why you proposed 6 months instead of 12 months Gary has proposed on the momentum area. I would appreciate the explanation.

    Thanks!
    John

  • we use 12 months as well…did I have a typo on that?

  • Park Research, LLC.

    sorry, I misread x to 6 months on your MOM explanation. thanks!

  • ChadBitar

    Curious to know if you have tried to back-test Ray Dalio’s All Weather portfolio?

  • depends what you consider the “All weather” portfolio. But in general, leveraging t-bonds over the past 30 years has been a great trade and would make anyone look like a genius.

  • ChadBitar

    Good point.

  • frankkaeb

    Great article. One more question about the MOM and MA issue. Antonacci (of Dual Momentum fame) on his blog mentions that a 6M MOM is equivalent to a 12M MA (MA length needs to be 2x MOM length). Have you tested this option? Setting MOM=6 and MA=12 as opposed to 12M for both? Thoughts?

  • Thanks for the question.
    We’ve checked robustness across everything. A large swath of options work to a certain extent. We chose 12 months on both because it is simple and straight forward. Over the next 50 years I’m sure 12/12 won’t be the winner, but all the ponies currently in the race seem about the same. You could always tweak it at the margin, but that is up to each investor’s discretion. I don’t have any special insight, so 12/12 seems good enough…
    Also, just to make this clear, the outline above is simply a framework and guideline that we use–it isn’t a panacea by a long shot, nor is it meant to be an end-all, be-all. The mission is to provide a simple and elegant solution for a DIY investor with some motivation to take control of their hard earned wealth.

  • Andrew Spencer

    Excellent article, Dr. Gray- as always!

    Comment: in 4.6 “MAMOM, go 50% long, 0% cash”. Should it be 50% cash?

    Question: you use MOM_10 and VAL_10 for domestic equities. These are the top tenth deciles of the total US market (same, only quintiles, for the International). What are the useful instruments (e.g. ETFs) that reflect this selection? Maybe, not exactly but at least similar and resulting in the same ore similar performance as you’ve tested. The ones that I found, at least for US market, have way too many equities to be a “decile”.

    Thank you

  • Yes Sir. Nice catch.

    Can’t really talk about ETFs on this site or I’m sure a compliance lawyer would fast rope out of a CH-56 and stab me.

    It is a challenge to find high-conviction, focused exposures on value and momentum in the ETF space. Our value proposition outlines a need for this niche in the marketplace: http://www.alphaarchitect.com/blog/2014/09/16/the-alpha-architect-value-proposition/#.VH-rCjHF9MU. We’re working to solve that problem…

    In the meantime, Dorsey Wright has some cool ideas in the momentum space and RAFI has some reasonable value strats. We know of another high-conviction value-based ETF strategy, but I’m not gonna mention it here…I’ll leave that up to your imagination…

    You can also try and create these exposures on your own…

  • timoth3y

    Thank you for taking the time to put this together. It’s a fascinating read. I am a bit unclear on how hedging a LT gain instead of selling it outright would be more tax-efficent. Let’s say the model says SELL SPY, and rather than actually sell it you hedge it (sell futures, short SPY, buy an inverse fund, etc). After nine months the model says BUY and you unwind the hedge.

    I have not done the math, but it seems the ST cap gain you would have to pay on the hedge position would more than offset the LT cap gain savings on the actual position. What am I missing here?

  • Chris Scott

    It’s going to depend upon how large your unrealized gains are relative to the expected decline. If you have a long position that has only appreciated 1%, and on average you expect a 2% decline on a sell signal then it makes more sense to sell than to hedge (pay cap gains tax on 1% rather than 2%). However if you have a long term position that has appreciated significantly, then hedging is going to be more tax efficient. Say you have a position with 200% unrealized gains, and again you expect on average a 2% decline on a sell signal, then hedging the position with a short futures position would be the most tax efficient. Assuming mark-to-market tax treatment of the futures position you would pay 60% long-term, 40% short-term cap gains tax rates on the 2% decline vs. selling the long position and paying long-term cap gains tax on the 200% gain.

  • Chris Scott

    I don’t have any compliance lawyer worries. ETFs that use the top decile:
    US value – QVAL (40 stocks from the top value decile ranked on quality)
    US large cap momentum – PDP (top 100 stocks ranked on relative strength)
    US small cap momentum – DWAS (top 200 stocks ranked on relative strength)
    Intl value – no good ETFs and very difficult to DIY
    Intl momentum – PIZ (top 100 stocks ranked on relative strength)

  • what chris said…

  • Scott Anglin

    Very well done. I’m unclear of how you’d recommend a DIY’er get individual equity exposure in the VAL_10 approach (at least for the U.S. equity sleeve). I have several free screeners that I have access to (none give me all the cateriories I’d like to utilize though) but would be interested in your recommendation on the best approach to identifying the companies that make up the top value decile. Thanks.

  • We’re working on some tools to facilitate, but until then you can try and find val/mom exposures you like in the marketplace that are tax-efficient and affordable.

    The true DIY can do the following (maybe http://finviz.com/ ):

    Value: sort the R1K by P/E or P/B or whatever ‘value’ data point you can access and buy the top 50. Rebalance annually. Tax manage rebalance.

    Mom: sort the R1K on their past 12 month performance and buy the top 50 winners. Rebalance monthly. Tax manage.

    Without a tax wrapper on momentum you’d probably want to run that in an IRA…otherwise the tax will kill you.

    Good luck.

  • timoth3y

    That makes sense, but can we take it a step further? We know the exact type and amount of our unrealized gain, but we cannot predict the future price of the asset. The core-asset asset might increase (SLT on hedge) fall 10% for a nine months (STG) of plunge 50% and not re-enter for 18 months (LTG). We don’t know with certainly what the price will do in the future.

    Given those assumptions, can a useful rule be constructed on when to hedge and when to sell?

    I realize that this is probably a non-trivial question. But as you point out in the article, the effects of tax-management dwarf those of fine-tuning the model, but it does not seem that anyone has addressed this subject.

    Anyway, keep up the good work.

  • Doug01

    Trend following can keep you out of bear markets. However, it may also keep you out of bull markets, and there is the risk of being whip sawed.

    I wonder what would happen if you only used trend following when the market was in the top third of its usual valuation. For example, assume the PE10 of the US stock market is 19 for the last 50 years, and the top third is when PE10 is above 24. Only trend follow when the PE10 is above 24.

    Jeremy Siegel in “Stocks for the Long Run” applies trend following, and uses daily data; there is significant whip sawing. Mebane Faber did something similar, but used monthly data. Why not determine the trend every 2 months? Sometimes bear markets can come on quickly (1987 would be an example), but usually they take some time. With a two month strategy, your drawdowns would be greater, but your costs would be lower and it would be easier to implement.

  • Doug,

    These are some great questions. We thought of these in the past and have posted some of our analysis on the subject.

    http://www.alphaarchitect.com/blog/2014/06/12/can-market-valuations-be-effective-market-timing-signals/#.VIHsmTHF9MU

    http://www.alphaarchitect.com/blog/2014/08/22/tactical-asset-allocation-during-cheap-markets/#.VIHsljHF9MU

    It seems like combining valuation and trend doesn’t seem to work in a robust way. Maybe you can figure it out. If you can–PLEASE SHARE–a trend following model with a macro valuation element would be super intuitive. We just can’t get comfortable with the evidence that is actually works.

    In general, long-term trend following rules work better than short–at least recently. In earlier time periods (<1970) the shorter horizon rules work better. I can go into a long-winded behavioral explanation for why I think long-term trend rules capture bias better, but I'll refrain.

    Here is a post on old school MA:

    http://www.alphaarchitect.com/blog/2014/08/13/old-school-academics-on-moving-average-rules-remarkable/#.VIHttjHF9MU

    And yes, the biggest issue with trend rules is whipsawing. Nothing in life is free.

    Here is a study looking at the dynamics of MA across various data simulations:

    http://www.alphaarchitect.com/blog/2014/07/28/a-simulation-study-on-simple-moving-average-rules/#.VIHt0THF9MU

    I think MA exploits a behavioral flaw because there is no simulated dataset that can generate a benefit to MA–there is something unique about empirical data that can't be modeled. I believe it is the "human element," but that is my own bias speaking. It could just as well be a "lucky" data set…

    Anyway, as is the case with all this asset allocation stuff–BE INSANELY SKEPTICAL. I am only mildly comfortable with simple trend-following rules as a best attempt to time markets. In the end, if you can't live with risk, the safest route is to put your money in bonds/cash. There is no way to guarantee a timing system will work in the future…wish we could find it!!!

  • Park Research, LLC.

    Just wondering if the “Re-allocation” is done at different time such as last trading day of the month vs. the first trading day of the following month, or 10th trading day, 15th trading day, etc…. would impact the return differently.

  • Chris Scott

    “if you can’t live with risk, the safest route is to put your money in bonds/cash” – great point. Or another way to say it, if you don’t believe this timing stuff works, use value/momentum along with enough cash/bonds to bring your risk down to a comfortable level. It’s actually pretty tough to beat the risk reduction of cash. SMA timing has historically been marginally better at reducing risk than cash, but if you don’t believe that will be the case in the future just allocate some to cash.

  • Chris, I think we need to have you start writing on this blog. You keep saying the exact same thing I would have said. LOL

  • Doug01

    About managing risk, a well known way is to value invest.

    http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2470935

    Look at Exhibits 6 and 7 in the above link. They relate drawdown risk of national stock markets to CAPE.

    http://vpcenter.ust.hk/public/files/Performance%20of%20Value%20Investing%20Strategies%20JP_2013-07-05.pdf

    Value stock investing during the Japanese secular bear market starting 1990 was profitable, despite the overall market decline.

    So there is data that value investing, at the level of individual stocks or individual stock markets, can help to manage risk. I haven’t seen any data at the sector level.

  • Larry

    Very well written article. Thanks for sharing as always Wesley and also to the very insightful questions raised as well.
    Cheers from Singapore.

    Larry

  • BG

    Thank you very much for you insightful article, Dr. Gray. I’m not sure if this is a naive question, but… How do the summary statistics for RAA compare to stats for strategies which are identical to RAA but do not apply the risk management rules (i.e., are not tactical)?

  • Hi Bill,
    Traveling at the moment so don’t have stats on hand, but without risk-management overlays you are going to 2x drawdowns. But, you do lower complexity and tax-management gets a lot easier. If you have long-horizon and a strong preference for simplicity that is a viable option.

  • BG

    Thank you!

    What is the best source(s) for screens on TEV, EBIT, etc.? For example, FactSet, Bloomberg, Capital IQ, etc. Or is it necessary to extract and compute the ratios from the original financial statements?

    By the way, for data analysis do you tend to rely mainly on spreadsheets or other software, like R, Python, etc.?

  • bloomberg is good. All of the services you mentioned are good. We typically build the variable up using the individual components.

    re software: depends on mission. We use a mix of vba/excel, SAS, python, etc.

  • marcus

    Hi Dr Gray… do you have a link to the description of MOM amd MA scoring system you briefly describe here. (TMOM=0, MA=0, TMOM=1 MA=0, MOM=0, MA=1) I think I’ve seen it before on your site.. but can’t seem to locate it now. thanks!

  • Jack Vogel, PhD

    We have a post coming out in the next few weeks which will give a simple example for everyone to follow.

  • Golgo13

    Hello gentlemen,

    I recently came across an article that calls into question the value of momentum based on 300 years of data. If you could take a look at this article, and offer a few thoughts, it would be greatly appreciated.

    Apparently the Ivy portfolio, and the traditional 60/40 allocation, performed well over the last 100 years, but over 300 … faltered.

    Harry Brown’s Portfolio did well, however.

    Your thoughts?

    http://www.nasdaq.com/article/the-most-rewarding-portfolio-construction-techniques-an-unbiased-evaluation-cm279719

    (my apologies for the handle, apparently the internet has a memory)

  • JBRUE

    Hello :

    Has there been any discussion or work on turnover or trade count of this system in the backtesting ? I believe you mentioned monthly review of strategy, but has backtesting demonstrated a high trade count or low trade count, say over a 12 – 24 month period ? Thx – great stuff !

  • We confirm their general thesis in the following article, but also highlight that bootstrapping using blocks of historical return data highlights that simulations can never fully replicate the true structure of live returns.
    http://www.alphaarchitect.com/blog/2014/07/28/a-simulation-study-on-simple-moving-average-rules/#.VSaelPnF9MU

    We believe the “unexplained” difference between modeled/simulated studies and simulations from actual return periods is due to the psychology component of actual market prices. Another argument is data-mining/in-sample luck. We happen to believe in the “behavioral” hypothesis.

  • the trades are usually “lumpy” in the sense they come in batches, but typically you get, on average, 1 trigger every 2 years. So over a 30 year horizon you’ll end up with ~15 triggers, or 30 total trades (in and out). However, you don’t actually get 1 trigger every 2 years, you usually end up with 3 triggers in a year, then none for a few years, etc.

  • BG

    Uncle Stock (http://www.unclestock.com) appears to allow screening and sorting by TEV/EBIT.

  • thanks for sharing

  • Bill Grant

    How do you determine which future to use to hedge an exposure like REITs or international momentum?

  • reits are tough to tax manage because of their high distributions–good for qualified money. for international equity–val or mom–eafe futures are cheapest/deep.

  • Fabian

    Hello Wesley,

    I wonder a bit, how you see your RAA approach compared to the Style
    Investing approach of Asness/AQR.

    As I understand it, Asness says a bit similar as in RAA model that
    investing in styles reduces overall correlation and results therefore
    in ‘alpha’. Though he is not limiting it to Value and Momentum, but
    includes Carry and Defensive (low beta) as well.

    In addition, the style system is not limited to stocks, but includes further
    assets like bonds and currencies. He applies a market weighting based
    on liquidity and scales the resulting portfolio to 10% annual
    volatility.

    To achieve a complete style approach leverage, derivatives and shorting
    is needed. He argues, that a long/short portfolio can diversify away
    market beta as well.

    To this I have a few questions:

    1) I do not see an advantage to have ‘fancy’ tools like leverage,
    derivatives + shorting and wonder, if you took a look at this as well
    and what your view about the long/short approach is?

    2) What do you think about the style strategy? I personally see it (at
    least the long-only variant) as a reasonable enhancement to RAA as it
    combines further styles.

    3) Do you have experience with scaling the portfolio to certain
    volatility levels?

    4) How would you apply value and momentum to other assets?

    The main drawback I see, is that it might not be possible to handle as
    a private investor and the effort to administrate (with focus on tax,fees) the assets and
    styles looks huge (and should be seen in the fees).

    Best Regards Fabian

  • Hey Fabian,

    Some quick comments for you:

    1. In general, complexity is something you want to avoid. Shorting is a very tough business–if not impossible– for professionals and even tougher for semi-pros or individuals. I’ve tried in the past on numerous occasions and I always end up with the same answer: expected (gain) < expected (costs)

    2. AQR does great work and I know a lot of their researchers. I really admire the firm and their intellectually heft. They make reasonable products. However, when it comes to product decisions it all boils down to the FACTS: http://blog.alphaarchitect.com/2014/09/16/white-paper-stick-facts/. You'll have to weigh the costs and benefits.

    3. Sure, we do research on these concepts all the time. Scaling to vol levels typically involves leverage. Leverage isn't a bad word, but it does have costs/benefits. You can scale systems like RAA, IVY 5, Dual Mom, etc.

    4. For equity, highly active non-closet indexing value and momentum seem like a no-brainer. For other asset classes the evidence is less convincing in my mind. I'm sure you are aware of the "value and momentum everywhere" paper by Asness et al….they have some simple techniques to do val/mom across all assets.

    There are 100's of really cool ideas out in the world and 1000's of cool products. As a private investor, fees AND TAXES, define the decision and allow an investor to quickly scale the opportunity set from 1000's to 10-20. Focus on deferral; focus on long-term gains; focus on minimal turnover/activity; and consider the fees. Investing really isn't that tough–compound after-tax, after-fee for a long time–but it isn't that easy, either.

  • Fabian

    Thanks for sharing your view on this!
    Best Regards
    Fabian

  • Mark

    Thanks for the post… just a quick question about asset class. I think the fundamental reason to create multi-asset portfolio is to achieve diversification. However, as the correlation between domestic equity& international equity increases, does that still make sense to treat international equity as another separate asset class?

    Do you have thoughts or references about how we should about asset class ? Thanks

  • Mark,
    equity is equity–big small global domestic, etc. When the world blows up, all equity is losing money. That said, at the margin, there are benefits to diversifying across the world when the fees, liquidity, taxes, etc make sense. So to answer your question, there are really 3 core asset classes: equity, real assets (reit/comm), fixed income.

  • BG

    Do you have the new RAA weights at

    http://tools.alphaarchitect.com/tools/diy

    for November?

  • updated

  • Daniel Speer

    For those of us who are only interested in maximizing our terminal values and not concerned with volatility, is the best course of action to just choose QVAL or QMOM and not consider the robust allocation models?

  • Hey Dan, we can’t comment on ETFs here, sorry about that.

    In general, punting on “diversifiers” and going all-in on riskier assets will maximize your terminal value in expectation. Of course, the other key is to maximize tax-deferral and minimize fees along the way.

  • Mark

    Hello, I implemented a version of this strategy in Quantopian (with some simplifications). It seems to do quite well over the backtest period (06/01/2006 – 12/31/2015). the backtest can be found here,

    https://www.quantopian.com/posts/an-implementation-of-the-robust-asset-allocation-strategy-from-alpha-architects

    One small adjustment to the strategy I would suggest is to test the robust allocation weights monthly for the Value strategy and come out of cash early if the robust system recommends it. Since the value strategy rebalances yearly it can stay in cash too long after a rally has begun.

  • Mark, thanks for sharing. Great to see others replicating and extending the analysis. We don’t claim ownership on the best approach/ideas, but our hope is the frameworks and concepts outlined in the discussion inspire folks to build interesting and useful investment algorithms that are relatively simple, transparent, robust, and effective.
    Regards,
    Wes

  • Mark

    Thanks Wes,

    I tried implementing the Frog in the Pan strategy with less compelling results. I’ll clean up my code and post my results on the FIP post.

    Regards,
    Mark

  • Alex Baranosky

    Maybe I missed it in the article, but I would think that this strategy gets killed in taxable accounts — whenever you need to switch out of an asset into cash there is going to be a taxable event.

    1) Is that correct, that this only really works will in tax-advantaged accounts?
    2) Do you have any tricks to ameliorate the tax hit in taxable?

    Thanks for the great articles!

  • Great questions:

    1. No, you can deploy the system across a taxable and non-taxable complex (we do that for $1mm+ managed accounts). If you don’t have scale and only non-taxable money we have a robo-advisor that implements the program (also can do DIY).
    2. Yes, the main “trick’ is the use of futures to hedge beta risks on low-basis assets and to deploy the system in a smart way across your taxable/non-taxable

  • Alex Baranosky

    Hi Wesley,

    Thanks for the response. I didn’t actually expect one 🙂

    I have less than a million. About 20% tax-advantaged and 80% taxable.

    I guess I should do some reading on futures, which I’ve never purchases before.

  • No problem and happy to help.

    Futures are Sec 1256 contracts and have a unique tax treatment.

    The main idea is that if you have a $1 basis in a $10 position and a risk-mgmt rule hits …you don’t want to sell…but you don’t want market beta…selling a future can help alleviate this problem by essentially creating a market neutral exposure…http://blog.alphaarchitect.com/2014/12/15/an-affordable-tax-efficient-longshort-hedge-fund-solution/ has some more background.

    Dig around. Futures are an interesting instrument…

  • Alex Baranosky

    Interesting, I’ll have to dig deeper into the hedging w/ futures concept detailed in the article you linked to.

    My money is almost all in a Vanguard brokerage account, and they don’t trade futures there. They do trade options. On a quick googling it seems like I might be able to use options to hedge as well:
    http://www.investopedia.com/articles/trading/09/offset-risk-options-futures-hedge-funds.asp

    Do you think options can be used similarly?

  • Mark

    What are the diversification benefits of making distinct allocations between US and World –ex US asset allocations? Looking at the top holding of the IVV and EFA etfs I can see large allocations to multinationals that derive much of their earnings outside of their domestic borders, it seems the diversification benefits of holding Exxon and Procter and Gamble in IVV while simultaneously holding BP and Unilever in EFA would be minimal. Have you considered a simpler asset allocation model that does not distinguish between US and non-US companies and applies a value and momentum filter to a universe of stocks from a basket of markets?

    Similarly with respect to the suggested allocation to Real Estate, do the desired diversification benefits hold if the proxy for real estate is IYR which invests in a particular set of publicly traded companies that as far as I can tell are as volatile as any other industry sector?

    As always, I sincerely appreciate your insightful responses,

    Mark

  • Hey Mark,

    Great question and I’m rushing to a dinner so I’ll be quick…excuse any typos.

    At some level, equity is equity –emerging, dev, dom, val, mom, low vol, growth, tech, sunspot, frontier, Ouija board, etc — it will all blow up in a major crash. So the diversification benefits –when it matters — are somewhat muted off the bat. That said, to optimize the diversification within equity, the evidence suggests one focus on value and momentum exposures (they are natural yin/yang type strategies). Roger that…

    So why do we recommend a 50/50 split? Well, that approximates the market cap between US and ex US, it’s simple, and, at the margin, there are some diversification benefits to having exposure outside of your own country with unique laws, FX risks, etc. — even if the businesses aren’t that much different.

    We have looked at doing a straight up global val and mom, irrespective of country, and the results aren’t that much different than the 50/50. Intellectually that isn’t a bad idea.

    Real estate is essentially a quasi bond/equity like asset that also has an element of “real asset” attached to it. So I think it has some aspects of a reasonable diversifier, that will help a portfolio manage volatility. That said, if the world blows up, real estate will probably blow up as well, so the doomsday diversification benefits are not the same as you’d get with a mgd futures program or 10yr treasury bonds. The other thing to consider on bonds is they are relatively tax inefficient because of the income distributions. This concern can be minimized in a sheltered account, but if you are mainly taxable money, the decision to include REIT exposure becomes a bit more complex.

  • Mark

    Thanks Wes,

    You guys are great.

  • Greg

    Hi Dr. Gray,

    I just finished your recent book DIY Financial Advisor and thoroughly enjoyed it. I’m also enjoying with the Alpha Architect website and am very impressed with all of the posts, contributors and commenters.

    I’ve been a lifelong buy and hold index investor but I am intrigued by the RAA approach. In particular, the model-driven concepts and the tactical risk management timing techniques (SMA and TMOM) are very interesting. Even if over the long term the expected RAA returns aren’t significantly different from B&H, the idea of blunting the super big gut wrenching declines and drawdowns is very attractive.

    I’m thinking about the possibility of SMA and TMOM but it appears that one of the biggest psychological/behavioral risks for someone adopting the strategy is that in some situations, such as when there is volatility and the recent downturn, RAA may not track the broader market very closely – switching out after rapid declines and back in after quickly following rapid rises. I am curious about your thoughts on transitioning from B&H to RAA in the current market conditions and in the context of scenarios where RAA may not do well.

    Regarding specific asset classes, the majority of my assets are in an employer 401(k) which only offers mutual funds. There are fairly good options for tilt towards value strategies but not for momentum. There are however funds concentrating on small and even small value. What are your thoughts on combing value and small cap strategies for equity tilt?

    Thanks in advance for any thoughts or responses!

    Greg

  • You may want to consider a 50/50 type structure. So 50% dedicated to B&H and 50% dedicated to a trend-following based system. We run a robo advisor that implements the trend-following version: http://www.alphaarchitect.com/robo or you can try and DIY via our tools http://www.alphaarchitect.com/tools

    This may give you a better shot at sticking with the program. As you mention, these systems aren’t challenging or overly complex, but they require extraordinary discipline. And the threat of whipsaws are simply the cost of doing business if you want to try and prevent major drawdowns. There is no way to avoid this problem or you’d be fooling yourself.

    I think the combination of value alongside momentum is by far the most valuable combination. See the Asness et al paper “Value and Momentum Everywhere” for a good overview of the evidence. The size aspect is interesting, but if you already have global value and momentum in your equity book I don’t think you gain that much by adding in size…you just get less liquidity, more volatility, and there isn’t a great diversification benefit…and these exposures are typically expensive…

  • Mark

    Hi Wes,

    I’ve been spending a little time testing the value strategy in Quantopian. It seems that the month chosen to rebalance the strategy can have significant effect on returns. I’m wondering if you’re aware of any seasonality effects on value strategies similar to what you’ve reported for momentum? If you adjust the strategy to buy a few value stocks each month then hold for a year, that seems to smooth out the seasonality effects, since you are buying and selling a few stocks every month.

    Also, it seems the momentum strategy benefits from the ROBUST rule significantly more than the value strategy based on my testing for an admittedly short time frame (2007-2015). Value without ROBUST has a much higher total return with a correspondingly much higher max drawdown, yielding similar risk adjusted return metrics. While Momentum with ROBUST significantly outperforms Momentum without ROBUST on total return, max drawdown and a risk adjusted basis. I’m wondering if you’ve noticed this phenomenon in your more expansive testing and whether there is a better rule specifically for value?

  • We have done extensive studies on value seasonality under a variety of conditions and extending the analysis back to 1963. We can’t find strong evidence that it matters (save January, especially for small caps), whereas, with momentum, seasonality clearly matters. But we are always open to new ideas and evidence. There would also need to be an associated behavioral theory or institutional theory as to why we saw value seasonality…otherwise, there is a high risk that the finding might be related to data mining…so we are talking about the “art” of quant here and less about the “science”. http://blog.alphaarchitect.com/2015/08/17/the-sustainable-active-investing-framework-simple-but-not-easy/

    Yep, we use ROBUST rules on the underlying index BTW, not on the value or mom strategies. These systems are trying to capture market-wide psychology issues and the broad, market-wide benchmarks are much better at picking up “fear/panic” than niche/concentrated value or mom strategies.

    great work — keep it up!

  • Mark

    Thanks Wes,

    Sincerely appreciate your feedback as always. Just to be clear my results are based on an implementation of the strategy described in the DIY book (I use the Magic Formula as an approximation to your Quantitative Value strategy). The ROBUST rule in my strategy is also applied against the underlying market index (the SPY etf to be specific).

  • Mark

    Hi Wes,

    I continue to explore the DIY strategy, in a previous response to me you noted that a managed futures strategy offers potentially better diversification benefits than REITs. I wanted to take a closer look at that so I implemented the 50 Day Breakout strategy discussed in Andreas Clenow’s ‘Following the Trend’ book and integrated it with my implementation of the DIY strategy in Q. The period tested was 2007-2015 and the results look quite compelling, results can be found here

    https://www.quantopian.com/posts/value-momentum-and-trend-following

    At least a small allocation to managed futures does what it is supposed to do, reduce volatility and increase risk adjusted returns. I’m curious if you have any thoughts with respect to making managed futures part of the DIY strategy? Are there issues that I am overlooking?

    Regards,
    Mark

  • GM

    Hi Dr. Gray,

    Thanks so much for the insightful blog post and all that you do. I have read Quantitative Value and DIY Financial Advisor and consider them among the best and most impactful investing books I have read – thank you.

    I too am reluctant to override models for reasons when known and proven; however with regard to the asset classes I have a couple of queries which I was hoping to get your insight; apologies if my questions are simplistic and perhaps a bit daft. Please let me frame my mindset before asking the questions as I believe this will affect your response – In general I do not equate risk and volatility; to me risk is the permanent loss of capital, not market fluctuations. That said, I would certainly use MA and MOM to manage drawdown risk (yes, contradictory; human fallibility!)

    Bonds – I understand they are for diversification and considered a ‘flight to safety’ asset. However, if they fall in value as interest rates rise, and interest rates are near 0 currently what realistic upside is there to this asset class? I understand they appreciated in the 2008/09 crisis, however, I also understand that at times they have been correlated with equities and have fallen along with them. In essence my reservation with regard to bonds was captured in “Dual Momentum Investing” in Chapter 5 under the section on ‘We Don’t Need No Stinkin’ Bonds’. I haven’t finished the book so perhaps my question is premature.

    Commodities – the argument against this was addressed in Chapter 5 of “Dual Momentum Investing” also. Basically, I struggle to understand the diversification benefit and see them more in light of a term I first heard from you “di-worse-ificaton”. What am I missing here?

    REITs – I literally know nothing about these so think I should read “Investing in REITs: Real Estate Investment Trusts” unless you have a better book recommendation.

    From a DIY perspective, to me, it makes more sense to have a pure equity portfolio (statistically highest CAGR) with capital not required for say 5 to 10 year and savings to live from on the side. For a commodities play I would look at market conditions for a particular commodity and invest in companies involved in that sector on the basis of mean reversion.

    Please set me straight on this as I am very aware of the risks of overriding models, especially those crafted by you with a lot of awesome research and evidence backing them.

    Kind regards,
    G

  • G,
    I think you are outlining the challenges of the current environment. Essentially we are looking at a low nominal return world and is hard to know what the heck is going to happen. Diversification will be important. Eventually downside protection will be important, but sticking to the program will be difficult.

    The RAA framework is really a bit fancier 60/40. Let’s say you are in the moderate version (60% equity). The 40% is really just split between fixed income and “real assets”. This is meant to make sure the 40% diversifier bucket isn’t only relying on fixed income to provide that benefit. What if we become Zimbabwe for example? Unlikely, but who knows. So real estate and commodity type exposures help defend against that. We also add a trend overlay to avoid massive drawdowns, but this comes with complications on tax-management, tracking-error, and some other things that some people can’t handle.

    re Bonds. I agree they aren’t the silver bullet, but they seem to be a relatively effective “insurance” asset in a lot of scenarios. As a wise person once told me, “There is only one asset that can take $1Trillion–in a day–during chaos. The US Treasury Bond.” So I think in the current environment the flight to quality aspect of US TBonds is reasonably in tact. But who knows…

    re Commodities. They can provide some diversification benefits, but you only really want to mess with commodity futures if you can capture their premiums in the form of term structure and momentum. B&H is probably not a great approach. http://blog.alphaarchitect.com/2015/10/07/commodity-investing-101-basic-insights-most-advisors-dont-know/. Commodity futures are also tax-inefficient relative to equity (sec 1256 vs deferred equity capital gains in an ETF structure). Bottomline: I do think they provide diversification if they are implemented correctly and in an inflationary environment where they can theoretically provide some protection. The summer haven dynamic commodity index is a reasonable approach — check it out — there are some products based on it. We run some commodity programs internally but they are definitely not “DIYable.”

    re REITs. These are really a real asset/bond hybrid at some level. A diversifier with an ability to protect real wealth in a super inflationary environment. The passive options out there are good enough. The downside is the distribution is taxable and large…

    Okay, great. But what’s the point of diversifiers? Diversifiers are really only included in a portfolio to “smooth” the path for those who need liquidity at unknown times. A pure/heavy equity portfolio is a reasonable decision from an after-tax, absolute performance perspective, but they can drawdown at the exact time you need liquidity (trend following can help). But if you have 10yr+ money and limited liquidity needs, the benefit of diversifiers is less clear and all they are going to do is drag down your expected compound cagr…the tax considerations are also really important (most diversifiers have crappy tax statuses).

    Takeway: The approach you mentioned is reasonable–especially for some tax situations and when considering the limited brain damage costs of implementation — but you may also want to consider the portfolio performance as a whole. For example, let’s say you have $1,000,000. You put 70% in equity, 30% in cash to burn on living expenses. For argument’s sake, let’s say you could put 60% in equity and 40% in the diversifier bucket, annually reblanace, and generate a portfolio with a higher risk-adjusted return — so same expected return, but less risk. Perhaps you’d want to run this diversified portfolio and harvest it as a portfolio, as opposed to doing a 70/30 approach where you harvest down cash from the 30%. You may be better off running your money via this approach. This is essentially what endowments do — harvest at the portfolio level and not at the asset level. This “portfolio harvesting” approach gives you the best shot of capturing portfolio diversification benefits. Also, the RAA-like portfolio will maintain a similar risk profile over time, whereas the 70/30 will slowly become more and more “risky” in the sense it will systematically shift from 70/30 to 80/20, 90/10, etc. But, as I mentioned, taxes are typically the biggest issue…so any portfolio benefits might get drowned in tax leakage.

    Anyway, that is a lot to think about, but your approach is great if you have high “brain damage” costs and serious tax considerations. My personal $ is run akin to your approach. I’m pretty much all-in on leveraged active value and momentum with limited “diversifiers.” My limited income covers my limited expenses and I try to follow my own financial planning advice: spend less than you make. LOL.

  • GM

    Hi Dr. Gray (Wes if you prefer),

    I am awestruck by your response! Thank you so much! It is one thing for a firm to have a mission, it is quite another to delivery on it!

    I guess returns need to consider price, so if prices drop then the returns will look better relative to the price paid unless I have misunderstood your comment or future expectations.

    I am actually a ‘foreign’ investor; a ‘non-resident alien’ (think Roger from American Dad) so my tax implications are a bit different.

    I have done my best to find out as much as possible following your post with regard to the fixed income “diversifiers” and taxation:

    • Bonds – Yes, you’re right I am thinking in terms of current market conditions, and also I am limited by my knowledge on the bonds and their relationship to the macroeconomic environment – I think I’ll read “The Bond Book, Third Edition: Everything Investors Need to Know About Treasuries” to better understand this asset class. The coupon payments which are negligible at present will have 30% withholding tax applied. Would it make any sense to invest in Singapore or Australian government bonds where I have better tax status? I say that because if the US ‘sneezes we all catch the cold’ anyway. In this case I would assume would see the flight to safety towards the most stable government bonds.

    • US REIT’s – I would incur 30% withholding tax on distributions which are mandated at 90% of earnings – ouch! Would investing in REIT’s where I am a tax resident (Singapore) provide an adequate substitute to US REIT’s as here I won’t incur much tax, if any, on those distributions? It will create re-balancing challenges with FX rates but better that that getting smashed on tax.

    • Commodities – does investing in USCI as an ETF alleviate the tax issues of futures (I don’t think it does for US investors) – I contacted multiple sources with regard to non-resident alien tax on this product but couldn’t get a definitive or consistent answer – if you happen to know I would really appreciate the insight. Thanks for the links to the blog posts – I’ve read them once and will read them again to better consolidate my understanding.

    Awesome advice with regard to ‘harvest at the portfolio level and not at the asset level’ and the tax considerations – thank you so much. The tax implications will guide my choice as to whether I use “diversifiers” or not; or alternatively, if it isn’t an insane idea, I could invest in those “diversifiers” where I incur the least taxation (I would love your thoughts on this).

    It is a fine line between ‘brain damage’ and ‘flow’ created by cognitive strain, however, I think the benefits of ‘optimizing’ far outweigh the brain damage in the long run. That said, futures, with the negative roll yield, contango, backwardation etc. are certainly hitting brain damage territory for me!

    When you say you ‘leverage’ is that to say you trade on margin? I am glad to know you do what I was thinking of doing, it makes me feel a lot more comfortable about my thought process.

    Kind regards,
    G

  • Hey G,

    Yes, there is generally an inverse relationship between price paid and returns. As prices move up, expected returns go down; as prices move down, expected returns go up. Of course, many investors think the opposite and this was highlighted in surveys in the late 1990’s bull market where people thought equities would earn 20%+ a year after they were selling at 50 p/e. And then when you hit the trough of 2008 surveys suggest investors think equities will earn 5% returns. This is probably due to a wiring issue in the brain. Not sure.

    re REITs. You may want to just punt or find an alternative to be honest. They have arguable diversification benefits, but not if you eat major tax drag.

    re commodities. Nope. the 1256 MTM nature flows through. ETNs can deal with that problem but they have their own issues (counterparty risk, bank decides to end contract risk, etc). There will be limited tax deferral opportunity on futures exposures unless you use other structures in insurance wraps, etc. But that is probably beyond your situation.

    re diversifiers. They are usually tax-inefficient (ie, they aren’t equities) so you want to dump them in tax sheltered vehicles, if possible. And if you want some diversifiers and you have massive tax issues you want to focus on those with the most after-tax bang for their diversifier buck.

    re commodities. These aren’t for everyone, but they can be great portfolio components.

    yes, margin leverage.

  • GM

    Hi Wes,

    I watched your google talk – I was wondering why I missed it when I first read this great post – then I realized the talk came much after the original publication of the article. For anyone who hasn’t seen it, it is highly recommended! The extensive Q & A was excellent and I learned a whole lot more from it – thank you so much.

    In relation to the use of diversifies you mentioned a few times in the talk that if you have 30+ year money the need for “diversifiers” diminishes – based on your research what is the minimum time horizon an investor should allow for before they could start harvesting from a portfolio all in on value and momentum equities (i.e. much like your portfolio?).

    To frame the question better let’s assume 500k investable capital and 50k p.a. living expenses. For how many years would you want to leave the 500k global value/ global momemtum portfolio alone to compound (hopefully) before drawing the first 50k from it? I know its a hard question with no truly correct answer, just a probabilistic view based on market history.

    Kind regards,
    G

  • Hey GM,

    This is a tricky question. In theory, one wants to maximize their risk-adjusted return and then leverage the portfolio to meet a given return/risk. In reality, it never happens like that. So if you want to hit a higher expected return target — and you have the horizon to deal with the bumps along the way — going strong on equity is the only way to achieve your goal. Equity is also way more tax-efficient, typically. Adding diversifiers will simply smooth out your path to a lower expected return when leverage isn’t a possibility.

    Honestly, hard to say what you should do, because there are so many factors that go into the decision. If you are using history as your guide and you have a long horizon, then going long and strong global value and momentum would be a good idea. But, of course, past returns may not reflect future returns and you could lose your a$$ as well.

  • Citi

    Hello, there’s a paper called “Minimizing Timing Luck with Portfolio Tranching”:
    https://www.thinknewfound.com/wp-content/uploads/2014/11/Minimizing-Timing-Luck-with-Portfolio-Tranching.pdf
    Which says the fallowing:
    “We demonstrate that from the period of 1950-2014, the tactical trading methodology proposed by Faber (2013) may
    overstate its total return profile from the true expected strategy return by 1800 percentage points, simply due to its choice of end-of-month rebalancing.”

    Would you agree with that and how sensible returns of moving average strategies are to the change of the rebalancing day from the last day of the month to some other time based on your research ?

  • Agree with their work.

    We’ve conducted robustness on just about everything you can imagine when it comes to trend-following type strategies. The general takeaway is to follow some sort of long-term trend rule, assessed monthly, and stick with it. That general class of rule helps shift the extreme left tail to the right. Some versions do that worse and some do that better, in sample. Out of sample, the rule one picks will almost certainly not be the “best” rule. But the “best” rule is the one you stick with and follow. We don’t believe there is a way to ex-ante predict which version of trend-following will the winner out of sample, so we decided to stick with 2 simple rules: 12-month MA, and 12-month time series.

  • Sharat

    Wow!!! This is really amazing break down in a way easily understood. THanks a lot Dr Gray. You truly are contributing to investor knowledge and awareness!!.

  • Sharat

    Just want to add that I finished reading the QMOM and QVAL books. Looks like I need to buy the DIY as well. All worth the time, effort and investment for educating oneself.

  • Sharat,
    Glad this was helpful. If anything is unclear, please let us know and we will update. We seek to be fully transparent so investors know what is going on at all times.

  • Enjoy!