This lack of tailoring of investment plans is unfortunate. Still, moving from generic to tailored solutions is a measure of maturity of most areas of commerce. In the fifteenth century, there were just a couple of shoe sizes and left and right shoes were identical. Thankfully, our shoes are now matched far more closely to the shapes of individual feet and (hopefully) asset allocation will follow suit.
Case Study: Jane Doe
Because of the differences between specific individuals, we are writing some case studies to explore real asset allocation problems for specific individuals. We are going to look at asset allocation using a very simple universe of iShares ETF’s and develop portfolios for specific individuals. For our first case in this series, we are choosing Jane Doe. Jane is 40 years old and plans to retire at age 65:
Jane Doe's Profile
Jane has $120,000 in her retirement portfolio and plans to contribute $15,000 per year (adjusted up each year to match inflation) to her 401(k) each year, including her employer match. When Jane retires, she plans to draw $75,000 per year (in 2005 dollars) from her portfolio. She will adjust that upwards each year to account for inflation. Jane is saving fairly aggressively at this stage in her life by comparison to most Americans of the same age. We are going to look at two allocations and how they might work for Jane.
A Simplified Universe of Investments
In a paper from December of 2005, we looked at a wide range of iShares ETF’s and at the range of performance variables of different members of this fund family. Based upon that analysis, we have identified a small group of ten ETF’s that have a long history (by ETF standards) and provide the ability to create a wide range of low-cost portfolios with nicely optimized risk-return balances:
Simplified universe of investments using iShares ETF’s
If you are interested in building a portfolio that exploits strategic diversification effects but you do not want to invest the time to investigate individuals companies or stocks, you could do a lot worse than starting with this small selection of investment options.
Rather than looking at recent historical values for risk and return, we project forward using the Quantext Portfolio Planner (QPP), a Monte Carlo simulation tool. QPP takes both fairly recent market history (three years in this case), combined with the long-term balance of risk and return in the stock and bond markets and the assumed future performance of the S&P500 as a whole, and generates projections for risk and return. QPP includes fund fees and assumes reinvestment of all dividends. For more information on how the model simulates future risk and return and why we believe the numbers, visit our website at http://www.quantext.com. When we calculate projected future values for these ETF’s using QPP we obtain the following:
Projection Using Trailing 3-Year Results
These projections are generated by the Monte Carlo portfolio simulation, assuming that the future average return on the S&P500 is 8.3% per year, with a standard deviation (SD) of 15.07%.
Portfolio 1: Buy Some of Everything
For our first sample portfolio for Jane, we have chosen a mix of these ETF’s that is simply an equal mix of all ten of these ETF’s. This portfolio has previously been discussed in a recent paper:
Equal allocation in 10 ETF’s
This portfolio has a projected future return of 9.83% per year, with a standard deviation of 12.68% per year. This means that this portfolio is projected to have less future volatility than the S&P500 (recall that this is projected at 15.07%) and a higher return. This portfolio has performed very well over the past three years (shown above—Historical Data), but note that we are projecting a future annual return that is less than half of this level (9.83% vs. 19.59%). This portfolio, while it can be improved, looks pretty good. This is not accidental and you would not get portfolio diversification effects nearly this good if you start with just any random selection of ETF’s. To get a better understanding of why we feel that this is a good ‘small universe’ to start from, read the previous paper cited above.
Now, even though this portfolio takes good advantage of diversification effects, is it right for Jane? This is where the issue of personalization comes in. What does a standard deviation of 12.68% per year, with average return of 9.8% per year mean for Jane? We can be pretty happy with the projected average return, but is this risk level a lot or a little. An easy way to examine this is to look at short and medium term projections for the portfolio—these make a portfolio feel much more concrete. QPP allows the user to specify a time horizon and then look at the probability of sustaining a certain level of loss. We took a look at a 90 (calendar) day projection and got the following:
90-Day projected returns for Portfolio 1
This table, a standard output in QPP, shows the probability of certain returns for a portfolio. In this case, Jane has a 5% chance of losing at least 8% of her portfolio over any 90-day period (the 5th percentile above). She has a 35% chance of have a return of zero or less than zero over any given 90-day period (see above). If Jane looks at this number and feels that she can’t deal with losing money in roughly 1/3 of all quarters (as above), she may want a less aggressive portfolio.
Jane is a long-term investor, however, and she grasps that short-term risk is only part of the story. Often, more short-term risk makes a portfolio less risky in the long-term:
Retirement at 65 with $75K in income per year (2005 dollars, inflated each year)
When Jane looks at the Monte Carlo simulation output to see how well her portfolio will support her future planned income, she sees that we has a 20% chance of running out of money by age 85 (see above). Is she willing to take a 1-in-5 risk of totally depleting her portfolio by age 85? This is where risk, return, and desired income levels become very concrete.
Jane is projected to have a median portfolio of $3.1 Million at retirement. Her planned draw of $75,000 per year in 2005 dollars means that she will be drawing around $155,000 when she retires at age 65. Such is the power of inflation.
Portfolio 2: No Bonds
We now consider another portfolio for Jane and we have specifically set out to ignore bonds as an asset class:
Jane’s 100% equity portfolio
This portfolio is 100% in stock ETF’s, with concentrations in U.S. utilities and U.S. healthcare because these sectors, as we always point out, have low Betas and thus have the ability to create good portfolio effects. We have also decreased the allocation to large firms and increased the allocation to small value stocks via IWN. By the standards of normal financial advising, this is a far more aggressive portfolio.
Projected and historical performance of Jane’s 100% equity portfolio
The portfolio invested without bonds has markedly higher volatility (as measured by standard deviation in return) on an historical and projected basis. The projected standard deviation in annual return is 15.71% (see above) as compared with the projected future standard deviation in the S&P500 of 15.07%. That said, the Beta of this portfolio is 98% (see above), so this portfolio is not getting its return by ‘leveraging’ against gains in the S&P500. With the higher volatility, the portfolio is projected to get Jane an extra 2% per year in average return. So, how does this portfolio behave in the short-term?
90-day projected returns for all-equity portfolio (Portfolio 2)
The 5th percentile outcome over 90 days for Portfolio 1 was a loss of 8%. The 5th percentile outcome over 90 days for the all-equity portfolio is a loss of 10% (see above). This means than in the worst 1-in-20 quarters, you should expect to lose 10% or more. This portfolio is certainly more volatile in the short term than Portfolio 1, but what does it look like on the long-term?
Retirement at 65 with $75K in income per year (2005 dollars, inflated each year)
If Jane invests in this portfolio, her projected future outcomes (from the Monte Carlo model) are improved—she has less chance of running out of funds in retirement at every percentile but the 10th (above), but this percentile is no worse than the portfolio including bonds.
For Jane to consider either of these portfolios, she must first think hard about what she is trying to do, her own risk tolerance, and why she would invest in bonds in the first place. It is also important to think about the fundamentals. Bonds make sense for investors with very limited tolerance for volatility. For an investor like Jane, with lots of time until retirement, my opinion is that bonds do not really add value—but this is based on my particular perspective. Jeremy Siegel, a professor at Wharton and well-known author in investing, makes the case for stocks vs. bonds in a recent article on Yahoo! Finance.
This article is an excellent articulation of the key issues that drive my belief that stocks are the asset class of choice and that bonds are a ‘defense’ asset when you need to manage portfolio volatility down to a low level. I believe that many investors invest in bonds simply because they do not really understand how to use strategic asset allocation.
The above notwithstanding, Jane may decide that she prefers the portfolio that contains bonds. Jane might, in fact, want a more conservative portfolio than Portfolio 1 simply so she can sleep better at night. Given Jane’s goals and current situation, I would prefer Portfolio 2. I simply do not see the case for bonds in this situation and the additional growth looks very attractive. With an assumed future rate of inflation at 3% (the long-term average), an extra 2% in expected return is very valuable. This is another case in which a portfolio with more short-term risk (as measured by Beta and standard deviation) actually makes Jane’s future prospects look less risky. This is a function of Jane’s specific situation—age, wealth, and future plans. As Jane examines her portfolio each year, she will likely find that her ideal allocation changes. This is part of the process of portfolio management.
On a personal note, I own no bonds for all the reasons discussed here. I have been adding only individual stocks to my portfolio for the past 4+ years (no funds), and I have some legacy allocation in S&P500 index funds. I tend to choose my asset allocation carefully to manage total volatility and portfolio Beta, with the goal being to maximize my probability of meeting long-term income goals. I re-balance my portfolio only by adding new money to my portfolio. I believe that this is the best approach for younger investors, but only if you have the interest and dedication to analyze individual stocks. If not, a limited basket of ETF’s (as we have shown here) is a good option.
More information on Quantext Monte Carlo planning tools.
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