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Quantitative Evaluation of ‘Lazy Portfolios'

Quantitative Evaluation of ‘Lazy Portfolios'

by: Geoff Considine posted on: June 26, 2008 | about stocks: AGG / DJP / EEM / EFA / ICF / IDU / IGE / IVV / IWM / TIP    

Lazy Portfolios

I am a fan of what are typically referred to as ‘lazy portfolios,' which are static (or very slowly changing) allocations to a series of funds. These portfolios are ‘lazy' because they are designed to be set up and left alone, aside from periodic rebalancing. There is a wide range of these portfolios (let's call them LPs for short) that have soundly thrashed the S&P500 for long periods of time. Paul Farrell, a champion of this style of investing, periodically reviews the performance of a range of LPs. Here, for example, is a recent update.

It is actually quite simple for a reasonably well-designed LP to beat the S&P500. The main task is simply to diversify beyond the S&P500, allowing the portfolio to generate increased return without increasing risk. In reaping the benefits of diversification across asset classes, you also need to be wary of fund expenses-but low cost solutions abound. There is no magic here, as I discuss in this article called The Humble Arithmetic of Portfolio Management.

Beating the S&P500, while a rare feat for mutual funds, is quite straightforward if you follow a disciplined approach to portfolio management, with low fees and low turnover, as I explained in this article. The punch line of this article is the following:


Any investor, knowing nothing about analyzing stocks, should be able to get more return than the S&P500 for the same level of risk as the S&P500 simply by combining index funds.


Now, this sort of statement will strike many investors as bold, especially given that most mutual funds under-perform their index benchmarks. For the motivation behind this statement, you will need to read the two articles above. If you are willing to bear with me on this point, or if you already understand enough about portfolio theory that this is not contentious, read on.


Lazy ETF Portfolios

There are a number of model portfolios that I have designed that could be classified as LPs, such as this set of ETF portfolios with varying risk levels.

From my perspective in designing these asset allocations, the goal is to maximize the diversification benefits and minimize fees, keeping the number of investments fairly low. I do not consider this type of portfolio the best that can done, but they will out-perform the majority of individual investors (see my Humble Arithmetic article linked above). I designed these portfolios using Quantext Portfolio Planner [QPP], a portfolio management tool that uses Monte Carlo Simulation [MCS]. These portfolios were created with a range of allocations to fixed income. The portfolio with 20% in bonds is called P20, for example, and this may be a reasonable portfolio to compare to an LP with 20% in bonds, etc. I am going to use these simple ETF portfolios as a basis of comparison in examining two of the lazy portfolios that Mr. Farrell's follows.


Comparing Lazy Portfolios

Two people independently contacted me recently to ask if I had ever run some of the better-known LPs through Quantext Portfolio Planner-and both specifically made reference to the articles by Paul Farrell on this topic. This struck me as an interesting idea, not least because Ben Stein and Phil DeMuth did something similar in their recent book called Yes, You Can Supercharge Your Portfolio.

I was particularly motivated to perform this analysis because Mr. Farrell's most recent article specifically discusses the ability of good LPs to weather a prolonged market malaise and high inflation (stagflation).


Case 1: Aronson Lazy Portfolio

The first of the LPs that I examined was the Aronson portfolio (see Mr. Farrell's article for the history of this portfolio). The Aronson portfolio is made up of Vanguard funds, and has produced the most impressive performance of any of the LPs that Mr. Farrell tracks. This portfolio has 20% in bond funds, so I wanted to compare it to my recent model ETF portfolio with 20% in bonds-see P20 in this article.

The asset allocations in P20 are given below:

Quantitative Evaluation of Lazy Portfolios


I analyzed both the Aronson portfolio and my P20 ETF portfolio using all default settings in QPP and using the standard three years of trailing history (through May 2008) to initialize the model. The results are summarized below:

Quantitative Evaluation of Lazy Portfolios

Historical and Projected Risk and Return for Aronson Lazy Portfolio compared to P20 ETF Portfolio (SD is annualized standard deviation in return, a measure of risk)

Several things are worth noting here. First, over the past three years, the Aronson portfolio has soundly beaten my P20 ETF portfolio-to the tune of almost 3% per year. Not also that the historical standard deviation in return [SD] for the Aronson portfolio is substantially higher than the ETF portfolio. Even correcting for the differences in risk, however, the Aronson portfolio has out-performed the ETF portfolio. When we look at the projected future performance from QPP, however, things look somewhat more complex. QPP's projected returns strongly discount recent performance in order to mitigate the influence of a single historical period in impacting asset allocation. QPP's projected returns suggest that the ETF portfolio will outperform the Aronson portfolio going forward, and the ETF portfolio is projected to be less risky. As an additional point, note that the Aronson portfolio has a value of Beta (with respect to the S&P500) of 88% vs. 63% for the ETF portfolio. QPP's projections suggest that a substantial portion of the Aronson portfolio's out-performance will not persist---so let's explore this more deeply.


What is most striking to me about the Aronson portfolio is that the single largest allocation in the portfolio is to emerging markets, with 20% of the portfolio in VEIEX. That has been a very good place to have a substantial concentration in recent years, of course, but QPP is suggesting that emerging markets are due for a ‘reversion to the mean.' QPP may or may not be correct on this-time will tell. It is inarguable that this portfolio's future performance is a significant bet on emerging markets, with a 93% correlation between the monthly returns on VEIEX and the returns on the total portfolio. This portfolio's returns have also exhibited a 93% correlation to EFA (which tracks the EAFE index) and an 85% correlation to VFINX (which tracks the S&P500).


The maximum correlation between the returns on the P20 portfolio is 80% (with EFA). P20 exhibits a 78% correlation to EEM (the emerging markets ETF) and a 77% correlation to IVV (the S&P500 index ETF). QPP projects that the P20 portfolio is simply somewhat better diversified than the Aronson portfolio-and this is illustrated by the lower correlations of the portfolio returns to the major indices. These lower correlations are largely due to the allocations to utilities (IDU), energy (IGE) and commodities (IGE). These asset classes reduce the correlation of the portfolio to the major market-cap weighted equity indices (like the S&P500 and EAFE). The P20 portfolio has a 53% correlation to the Dow Jones AIG Commodity Index (i.e. DJP), while the Aronson portfolio has a 31% correlation to this index, which shows that P20 is more driven by commodities.

If the commodities bull market collapses, this will have more impact on P20 than on the Aronson portfolio. On the other hand, if we see a period of high inflation, P20 will tend to keep up better.

When I look at the portfolio holdings in Aronson vs. P20, I believe that P20 is better positioned to ride out a period of stagflation than Aronson's portfolio. Asset classes like REITs, energy, commodities, and utilities are emphasized in the P20 portfolio but are represented primarily via market cap weights in the Aronson portfolio. These asset classes are precisely those that have the best odds of performing well in an inflationary environment. Further, the lower Beta of P20 suggests that less of its performance depends on a rising S&P500.


Case 2: Lazy Portfolio

The second lazy portfolio from Paul Farrell's article that I analyzed was developed by, and the rationales for its allocations are provided there. This portfolio has 40% bonds, so I compared it to an ETF portfolio with 40% bonds that I laid out in the article cited earlier. This portfolio, called P40, is shown below:

Quantitative Evaluation of Lazy Portfolios

Note: the original article has two portfolios with 40% in bonds. This is P40-2, and I chose it for the comparison case because its historical risk was most similar to the portfolio. The comparison of the P40 ETF portfolio with the portfolio is provided below:

Historical and Projected Risk and Return for Lazy Portfolio compared to P40 ETF Portfolio (SD is annualized standard deviation in return, a measure of risk)

The portfolio has 6% in REITs [VGSIX] vs. 10% in REITs (ICF) in the P40 ETF portfolio. The portfolio has 8% in TIPS [VIPSX] vs. 35% in TIPS (via TIP) in the P40 ETF portfolio. Aside from the bonds and the REITs, the portfolio is invested entirely in broad equity indices. By contrast, the P40 ETF portfolio has concentrated sector exposure to commodities (5% in DJP), energy (5% in IGE), and utilities (10% in IDU). These serve to substantially shift the equity portion of P40 away from financials. QPP has been in favor of this type of portfolio tilt since well before the collapse in financials.

As in the previous case, QPP suggests that much of the out-performance of the portfolio will not be a persistent phenomenon. The QPP projected return of the portfolio is about the same as a generic 60/40 portfolio of stocks (S&P500 and Russell 2000) and bonds (AGG)-albeit with the having 10% less risk than the generic 60/40.

The portfolio's returns have a 92% correlation to Vanguard International Value Index [VTRIX] and a 92% correlation to Vanguard Developed Markets Index [VDMIX]. This portfolio also has an 86% correlation to the returns on the S&P500. These results demonstrate Rob Arnott's point that a simple mix of market-cap weighted equity indices and bonds results in a portfolio that is still highly correlated to the S&P500.

Arnott also cites this result in his book called The Fundamental Index (P. 32), although he claims that the generic 60/40 portfolio has a 99% correlation to the returns on the S&P500, while I get about 92%--but I include reinvested dividends.

The P40 ETF portfolio has a 76% correlation to the S&P500 (via (IVV), a 79% correlation to the EAFE index (EFA) and an 80% correlation to the MSCI emerging markets index (EEM). By investing beyond market-cap weighted equity indices, the P40 portfolio is better diversified.

The 5% allocation to energy (IGE) in P40 provides a boost to trailing performance in much the same way that the 6% allocation to emerging markets [VEIEX] boosts These recent periods of out-performance are automatically discounted in QPP. With these effects taken into account, QPP projects that P40 will meaningfully out-perform the portfolio in the future. The higher projected returns from P40 are due to more effective use of low-correlation assets that also serve to move the portfolio away from market-cap weighting, which inherently over-weights the most over-valued asset classes in the index.



My purpose in writing this article has been to show how a portfolio analysis tool like QPP can provide new perspectives in evaluating portfolios. I reiterate that the two lazy portfolios from Mr. Farrell's article are substantially better than the portfolios of many (if not most) retail investors. Paul Merriman (founder of and Ted Aronson are both very savvy investors. I have approached the problem of evaluating the lazy portfolios developed by these gentlemen from the perspective of portfolio theory-specifically using Quantext Portfolio Planner [QPP]. QPP suggests that both of the lazy portfolios analyzed here could be improved by adding more assets that provide diversification benefits relative to market-cap weighted equity indices. In particular, this can be achieved by adding allocations to commodities, utilities, energy, and REITs.

QPP also favors heavier allocation to TIPS than either of the lazy portfolios from Mr. Farrell's article. These asset classes also serve to provide protection from periods of elevated inflation, as well as having the potential to deliver higher returns that are not as dependent on the direction of the broad equity indices (as exhibited by lower Beta). These are highly desirable features during a period of ‘stagflation.'

As a final note, I do not believe that the QPP ETF portfolios presented here are the best that can be done. There are additional nuances that can be considered, not least of these being additional information in the form of fundamental measures. Further, I believe that portfolios must be re-evaluated regularly. I believe that the model ETF portfolios have staying power, but there are circumstances in which I would alter the portfolios. When I see a portfolio or sector for which the trailing returns are substantially higher than the projected returns, this is a signal of the potential for substantial correction (i.e. reversion to the mean).

If commodities continue to skyrocket, there may come a point when QPP will suggest lighter allocations going forward, for example. The price at which you buy does make a difference.


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