The Robust Asset Allocation (RAA) Solution

The Robust Asset Allocation (RAA) Solution

December 2, 2014 Research Insights, Key Research, Introduction Course, Tactical Asset Allocation Research
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(Last Updated On: March 14, 2017)

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–each has costs and benefits:

  1. Hire an expensive investment advisor that offers a limited value proposition. (generally a bad idea, although quite common)
  2. Hire an affordable advisor that delivers a strong value proposition.  (reasonable idea)
  3. Hire a cheap robo-advisor that will deliver a generic, but reasonable value proposition.  (reasonable idea)
  4. Do-it-yourself asset allocation. (reasonable idea)

We think educated investors can successfully move down the “do-it-yourself” path when equipped with the tools and knowledge to move forward. There are a few critical areas to get familiar with, but once that’s complete, DIY is perfectly viable for many. For those who are not comfortable with the DIY approach, we recommend approach 2 or 3, depending on personal preferences and circumstances.

I want to be a DIY investor, so what do I do next?

First, grab a copy of DIY Financial Advisor, which outlines the specifics discussed in this post, but in much greater detail. Or listen to my Google Talk if you want a walk through on the DIY philosophy. If this is too much brain damage, simply head over to our active robo advisor and we’ll do all the work.

Next, consider the following:

Easiest solution: 50% BND; 50% VTI (or your own special weights depending on your risk tolerance, individual circumstances).

  • Insanely cheap; insanely easy; throw away the key. Not an unreasonable approach.

More complex solution:

Meb Faber and Eric Richardson in their book, “The Ivy Portfolio,” hint at a do-it-yourself model that utilizes a simple 10-month trend-following rule  to run a risk-managed portfolio allocated 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 is a reasonable solution for a DIY investor, but the live performance of a related strategy has been underwhelming the past few years.

However, not all is lost–simple still is the key to success, we just need a few tweaks…

We explore a more robust asset allocation solution that improves upon the IVY 5 model in three ways:

  1. We introduce security selection (value and momentum).
  2. We improve upon the IVY 5 risk-management system.
  3. We focus on fee and tax-management.

The outcome of our solution highlights what we call Robust Asset Allocation (RAA).

Robustness: Strong and effective in all or most situations and conditions.

RAA Mission: A low-cost, low-complexity, high-liquidity, diversified, tax-efficient, risk-managed retirement portfolio.

RAA Goal: A One-Stop Retirement Solution.

Let’s get started…

1. What is Your Portfolio’s Mission?

1.1 The Purpose-Driven Portfolio

Wealth is often built by concentrated holdings, but wealth is protected by diversification. Most people accumulate wealth by working, which is a concentrated position, as this usually requires time and effort.

Having a clear purpose is the premise of portfolio investment.

Example:

  • Purpose of the portfolio: Preserve and compound wealth to assure financial security.
  • Return objective: RF (10Yr) + 400bps, AFTER TAX.
  • Risk appetite: As low as practical to achieve objective.
  • Taxes:  Can be huge drag on returns for private individuals –> minimize damage.
  • Human capital: Don’t confuse frenetic human activity, or a large staff, with higher risk-adjusted return potential.

1.2 Strategy Assessment: Stick to FACTS

“Get your facts first, then you can distort ‘em as you please.”

— Attributed to Mark Twain

While there is no “one-size fits all” strategy assessment and allocation model, a systematic framework for decision-making can help simplify the process and maximize returns. For every allocation contemplated, and each strategy that needs to be critically assessed, the FACTS framework (consisting of Fees, Access, Complexity, Taxes and Search) can be employed to clarify important considerations for the prospective investor. 

Robust Asset Allocation solution stop retirement plan
Click to read our white paper: Stick to the FACTS

A in-depth look at the FACTS framework is here.

The high level summary is as follows: Create a portfolio that minimizes fees, increases access to your own capital (e.g., liquid investments), is easy to understand (low complexity), minimizes taxes, and minimizes manager search costs. Our goal is to propose a portfolio that optimizes across all 5 key points.

2. Does Complexity Enhance Asset Allocation?

2.1 Do Fancy Models Work? Not Exactly…

“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 rational for following a simple asset allocation model in the past, here, and here. An equal-weight portfolio–also promoted 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. 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.

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.

DeMiguel et al. are not the only researchers pointing towards the 1/n solution. Even the great Harry Morkowitz, 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…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

2.2 Simplify the Allocation Problem: Simplify; Simplify; Simplify

“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 “IVY 5” portfolio, described by Faber (2007) and then further elaborated by Faber and Richardson (2009), includes 5 asset classes:

  • SP500 = SP500 Total Return Index
  • EAFE = MSCI EAFE Total Return Index
  • REIT = FTSE NAREIT All Equity REITS Total Return Index
  • GSCI = GSCI Index
  • LTR = Merrill Lynch 7-10 year Government Bond Index
Robust Asset Allocation_IVY5
Click to enlarge.

At a high level, one can think of the IVY 5 portfolio as a 40% equity, 40% real asset, and 20% fixed income portfolio. I consider it a goldilocks portfolio: Not too simple; not too complex; just right.

2.3 Simplify Risk-Management

In general, while efforts to time the market should be viewed with skepticism, certain systematic timing strategies that have been explored in academia appear to reduce risk, without significantly impacting long-run returns. In particular, 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. 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.

The simple moving average trading rule can be used across asset classes and is suggested in the Faber/Richardson Ivy Portfolio book. Below I outline how this rule might look over the past few years on the S&P 500 (12-month SMA depicted).

Robust Asset Allocation_Moving average
Click to enlarge

Below is a diagram of how the IVY 5 with a moving average rule might look in practice.

Robust Asset Allocation_IVY5 Moving average example
Click to enlarge.

The IVY 5 with moving average model sounds good in theory, but what does this portfolio look like historically?

3. Exploring a Simple IVY5 Model

3.1 Simulation Background:

Simulated Historical Performance: 1/1/1979 to 12/31/2015

Results are gross of management fee and transaction costs for illustrative purposes only. These are simulated performance results and do not reflect the returns an investor would actually achieve. All returns are total returns and include the reinvestment of distributions (e.g., dividends). Data is from Bloomberg and publicly available sources. Portfolios are annually rebalanced.

The following 5 asset classes are used in the back-test (referred to as the “IVY 5”):

  • SP500 = SP500 Total Return Index
  • EAFE = MSCI EAFE Total Return Index
  • REIT = FTSE NAREIT All Equity REITS Total Return Index
  • GSCI = GSCI Index
  • LTR = Merrill Lynch 7-10 year Government Bond Index (prior to 6/1982, Amit Goyal Data)

3.2 Benchmark Summary Statistics

10-Year Bonds and US Equity have performed the best over the past 30+ years. No wonder everyone is so enamored with the 60/40 S&P 500/10-year portfolio…

Robust Asset Allocation figure 1
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.

3.3 Strategy Summary Statistics

Below we depict the simple IVY 5 portfolio, the IVY 5 portfolio with a moving average rule applied, a 60/40 SP500/LTR portfolio, and a SP500 portfolio.

  • IVY5_MA: 5 assets, equal-weight, annual-rebalance, MA rule –> Tough to beat.
  • 60/40: 60% SP500; 40% LTR, annual-rebalance –> Tough to beat.
Robust Asset Allocation figure 2
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.

4. The Robust Asset Allocation Solution (RAA)

Unfortunately, we can’t buy IVY5 index returns, but can only run a backtest on the IVY5 portfolio. Investment vehicles cost money in the real world, so we need to choose wisely. To replicate the IVY5 we could do the following with iShares products, which happen to have an ETF for all of the IVY 5 exposures:

  • IVV (7bps): iShares Core S&P 500
  • EFA (34bps): iShares MSCI EAFE Total Return Index
  • IYR (46bps): iShares US Real Estate
  • GSG (75bps): iShares S&P GSCI Commodity-Indexed Trust
  • IEF (15bps): iShares 7-10 Year Treasury Bond

In our backtests above, we looked at gross of fee performance, but we clearly can’t invest in an index for free. Using iShares, the ETF fee costs are 35.4bps, on average, plus transaction costs and RIA fees (As of December 2015).

All that said, one could certainly implement the IVY 5 portfolio with moving average strategy with minimal brain damage. For example, Yahoo Finance charts allows one to run a monthly 12-month moving average test for each asset class, and with a yearly rebalance across asset classes, you would be in DIY heaven.

But can we do better?

4.1 Three Simple, but Important, Improvements Over IVY5

4.1.1 We believe value and momentum can work.
  • How do we get access to these exposures without buying the asset manager a new yacht each year?
    • Focus on affordable exposures that take active bets (not closet index) on value and momentum.

Value and Momentum strategies have been shown to outperform, historically.  Luck for investors, there are a variety of value investing etfs and momentum investing etfs offered in the market. Since they are far and away the strongest anomalies explored in academic research, they are probably worth getting exposure to, but we want to confirm this.

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.

The implication is that we should look at replacing our market-weight passive exposures with high-conviction value and momentum strategies–but only if we can access these exposures in an affordable, tax-efficient, and transparent way. Otherwise, much of the purported “edge” will go to the croupiers and Uncle Sam.

4.1.2 We believe we can deliver a simple and effective risk management system.

We have examined hundreds of risk-management platforms over the past 5 years. You name it–we’ve backtested it, thought about it, or implemented it.

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.

It’s kind of crazy when you think about it.

We had hoped that having tested every model and approach under the sun that we would be able to triumphantly announce that we had identified a way to reliably predict the market using fancy algorithms derived from 100’s of academic researchers. But it just wasn’t the case. We’ve built these complex models: They aren’t reliable; they aren’t robust; and they are littered with data-mining. A large swath of the financial services industry would love to have you believe in their magic. I’m here to tell you that it probably doesn’t exist and I say that as someone who is conflicted and wants nothing more than to devise a secret sauce asset allocation technique that we could market to the world! Our problem is we have a pesky belief in evidence-based investing, not story-based investing.

But after all the years of research and analysis, what have we concluded when it comes to tactical asset allocation?

Is market timing all for nothing? Perhaps…but…

We’ve boiled robust market-timing mechanisms down to two rules that are the best of a bad bunch:

1. Time Series Momentum Rule (MOM)

  • 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)

  • 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).

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

Robust Asset Allocation_Momentum and MA rule

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.

It turns out that this “difference of opinion,” where one zigs when the other zags, adds some robustness to a comprehensive risk-management system. Here is an extensive study on these rules and their historical performance on a slew of generic return data series.

4.1.3. We believe we can minimize taxes.
  • Annually rebalance taxable accounts.
  • Systematically harvest losses (book short-term losses to offset gains in other parts of the portfolio).
  • Tax manage risk management events (i.e., MA rule triggers a move to cash).

Uncle Sam is increasing tax rates year by year. For individual investors, taxes are extremely important–much more important than asset allocation or so-called “alpha.” This important reality is often overlooked by consumers of Wall Street products. Nobody can withstand Uncle Sam’s 50%+ carried interest program, also known as tax rates. Only the most sophisticated and intelligent proprietary traders can earn such a performance. Uncle Sam makes hedge fund fees look cheap with his 50%+ performance fee hurdle. But our goal is to minimize Uncle Sam’s fees. We can do this by minimizing capital gains, maximizing short-term capital losses, and deferring taxes as far out into the future as possible.

Robust Asset Allocation_Tax issues

An example workflow for tax management is outlined in the figure below:

Robust Asset Allocation_Tax Management

Taxes are everything for taxable investors. A failure to plan for taxes is to fail as an investor.

ETF structures are also a valid options for the reasons discussed here and here.

4.2 Three (3) RAA concepts (Choose from our options or create your own weights)

In general, thinking outside of a model is hazardous to one’s wealth. But every investor is different. The three options below are meant to suffice for a wide swath of investors whose primary goal is to protect against inflation, preserve capital, and grow their real wealth by 3-4% a year, if they’re lucky.

But perhaps you are an investor with an extremely bearish view on bonds; or perhaps you are extremely bullish on equities; or maybe you think the value anomaly is a fraud. As someone who has earned their hard-earned wealth, you also maintain the right to allocate as you see fit. Go for it. We merely present the three options below as a reasonable starting point.

4.3 Details of the RAA Process (Moderate Version)

Keep things as simple as possible, but no simpler.

  • Step 1 in the RAA process is to replace generic passive allocations to domestic and international equity with affordable high-conviction tax-efficient value and momentum alternatives. As we mentioned earlier, there are value investing etfs and momentum investing etfs offered in the marketplace.
  • Step 2 in the process is to calculate MA and MOM risk-management calculations on each “line” of the system (e.g., REITs, Domestic Value, etc.). If MA=MOM = 1 , 100% long; if MA=MOM = 0, 100% cash; otherwise, if MA<>MOM, go 50% long, 50% cash.
  • Step 3 in the process involves the implementation of tax-management techniques: harvest short-term losers; tax-manage hedging events; and annually rebalance such that one maximizes long-term capital gain and minimizes short-term capital gains. If an investor is running this system across qualified and non-qualified accounts, concentrate taxable dollars in tax-efficient equity exposures; concentrate non-taxable dollars in tax-inefficient fixed income and real asset exposures.

raa moderate version

4.4 Simulation Background for the Robust Asset Allocation Solution

Simulated Historical Performance: 1/1/1992 to 12/31/2015 (limited due to international momentum data limitations).

Benchmark results (4.8) are gross of management fee and transaction costs for illustrative purposes only.

Strategy results (4.9) are net of 50bps management fee and 50bps transaction costs (1% total annual costs). These are simulated performance results and do not reflect the returns an investor would actually achieve. All returns are total returns and include the reinvestment of distributions (e.g., dividends). Data is from Bloomberg and publicly available sources. Portfolios are annually rebalanced. MA and MOM risk-management rules applied on a monthly basis.

The following 9 asset classes are used in the studies that follow:

  • SP500 = SP500 Total Return Index
  • EAFE = MSCI EAFE Total Return Index
  • REIT = FTSE NAREIT All Equity REITS Total Return Index
  • GSCI = GSCI Index
  • LTR = Merrill Lynch 7-10 year Government Bond Index (prior to 6/1982, Amit Goyal Data)
  • MOM_10 = U.S.Top Decile value-weight Momentum (Data)
  • VAL_10 = U.S. Top Decile value-weight Value (Data)
  • IMOM_5 = International Top Quintile Momentum (Average Top 3 market cap value-weight quintiles, Data)
  • IVAL_5 = International Top Quintile Value (Average Top 3 market cap value-weight quintiles, Data)

4.4.1 Benchmark Summary Statistics

  • Domestic value and momentum outperform the buy & hold index.
  • International value and momentum outperform the buy & hold index.
  • Bonds outperform real assets.
Robust Asset Allocation figure 5
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.

4.4.2 Strategy Summary Statistics

The results for the three permutations of the robust asset allocation solution are presented below.

  • RAA_BAL = 40% Equity; 40% Real; 20% Bonds. Equity split between value and momentum. Risk-Managed.
  • RAA_MOD = 60% Equity; 20% Real; 20% Bonds. Equity split between value and momentum. Risk-Managed.
  • RAA_AGG = 80% Equity; 10% Real; 10% Bonds. Equity split between value and momentum. Risk-Managed.
  • IVY5_MA = 40% Equity; 40% Real; 20% Bonds. Moving average rule applied.
  • 60/40 = 60% Equity; 40% Bonds.

RAA has historically outperformed the IVY 5 with MA system by 100-200bps–without excessive complication!

Robust Asset Allocation figure 6
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. Conclusion

Robust asset allocation solutions should be relatively simple, minimize complexity, and be robust across different market regimes. Simultaneous to these requirements, the solution must be affordable, liquid, simple, tax-efficient, and transparent, otherwise, many of the benefits of the solution will flow to the croupiers and Uncle Sam.

We recommend that investors explore our robust asset allocation framework and go for the do-it-yourself solution. You’ll be paying yourself 1%+ a year via saved RIA fees.

Is this the only solution? No. But any solution must be robust, simple, tax-manageable, and low-cost. This is our best effort to develop a simple model. Developing a complicated model is easy; simple is difficult.

We even provide some  tools to facilitate (we’ll be improving these over the next few months–stay tuned).

We are implementing a version of the robust asset allocation model with our new automated advisor offering, Alpha Architect Advisor.

As always, feel free to contact us if you are interested.


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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About the Author

Wesley R. Gray, Ph.D.

After serving as a Captain in the United States Marine Corps, Dr. Gray received a PhD, and was a finance professor at Drexel University. Dr. Gray’s interest in entrepreneurship and behavioral finance led him to found Alpha Architect. Dr. Gray has published three books: EMBEDDED: A Marine Corps Adviser Inside the Iraqi Army, QUANTITATIVE VALUE: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors, and DIY FINANCIAL ADVISOR: A Simple Solution to Build and Protect Your Wealth. His numerous published works has been highlighted on CBNC, CNN, NPR, Motley Fool, WSJ Market Watch, CFA Institute, Institutional Investor, and CBS News. 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.