All Weather Portfolio
alternatives, analysis, asset allocation, hedge fund, portfolio

Today’s post on Yahoo Finance discusses an “all weather” portfolio recommended by one of the most famous hedge fund managers. The portfolio strives to achieve an equal distribution of risk across macro periods of inflation, deflation, high and low economic growth.

The portfolio consists of:

  • 30% stocks
  • 15% intermediate-term government bonds
  • 40% long-term bonds
  • 7.5% gold
  • 7.5% commodities

The portfolio has a large fixed-income component relative to equities to get close to a risk parity (yet, it does not use bond derivatives). The portfolio should be rebalanced at least annually.

Let’s use the Portfolio Service of the Alpholio™ App for Android to analyze this all weather portfolio. To do so, let’s construct a portfolio of ETFs that represent the above asset classes:

These ETFs were selected to have the earliest possible inception dates and lowest sponsor fees (expense ratios). The time span of the analysis is limited by the inception date of DBC. An alternative commodity ETF, the iShares S&P GSCI Commodity-Indexed Trust (GSG), became available about five months after DBC, therefore the latter was chosen. Since about 8% of DBC tracks gold, the weight of IAU is lower than that of DBC by one percentage point (due to the limitation of setting widgets, the app only accepts whole percentage weights).

Here is the setup for the analysis (the Dates, Return Frequency and Rebalance Frequency sections can be expanded by tapping their respective headers):

All Weather Portfolio - Setup

Here are the analysis results for the above portfolio with monthly returns and quarterly rebalancing:

All Weather Portfolio - Quarterly Rebalancing

With semi-annual (i.e. every six months) rebalancing, the all weather portfolio performed slightly better in terms of the higher annualized return and Sharpe ratio as well as smaller maximum drawdown:

All Weather Portfolio - Semi-Annual Rebalancing

Annual rebalancing yielded no further improvement in the annualized return or Sharpe ratio, but reduced the maximum drawdown to 12.1% and lowered the beta to 0.20.

For reference, here are the results for a traditional balanced portfolio, comprised of 60% SPY and 40% of iShares Core U.S. Aggregate Bond ETF (AGG), with monthly returns and semi-annual rebalancing in the same analysis period:

Balanced Portfolio - Semi-Annual Rebalancing

Compared to the traditional balanced portfolio, the all weather portfolio had all the desirable characteristics: a higher annualized return and Sharpe ratio, coupled with a significantly lower beta and maximum drawdown. However, the above analysis covered a prolonged period of decreasing and historically low interest rates that drove the returns of intermediate- and long-term bonds, the dominant positions in the portfolio. In an environment of rising interest rates (generally expected to begin next year) and falling commodity prices (already taking place), a risk-parity oriented portfolio, even with no bond leverage, may suffer.

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Merger Arbitrage Funds as Portfolio Diversifiers
alternatives, analysis, app, asset allocation, correlation, portfolio

A recent article in The Wall Street Journal’s Investing in Funds & ETFs report discusses merger arbitrage mutual funds. According to the article, such funds

…may offer an attractive way to diversify away from the risks of stocks or bonds …[but] can’t replace bonds, because their returns aren’t certain and come mostly through any price appreciation, not yield. But held in tandem with bonds, they can offer a way to hedge against interest-rate risk and might cushion part of a portfolio against stock-market volatility

Let’s take a closer look at these statements with the help of a recently introduced Alpholio™ App for Android, and specifically its Portfolio, Correlation, Total Return and Efficient Frontier services. For the purposes of this analysis, the base portfolio consists of 60% SPDR® S&P 500® ETF (SPY) and 40% of the iShares Core U.S. Aggregate Bond ETF (AGG), i.e. a traditional balanced mix of stocks and bonds. Here is the baseline chart with statistics generated from total monthly returns of both ETFs and quarterly rebalancing of the portfolio:

Portfolio 60% SPY + 40% AGG

The reason why the beta of this portfolio is not exactly 0.6 (i.e. equal to the 60% weight of the SPY) is threefold. Alpholio™ uses a broader definition of “the market” than just the S&P 500® index. Also, the correlation between the market and AGG is not zero. Finally, the portfolio is rebalanced quarterly, not monthly, which can lead to a temporary divergence of SPY/AGG weights from the original 60/40% level.

For reference, in the same time frame a portfolio consisting of just the SPY would have an annualized return of 8.52% with a standard deviation of 14.25%, Sharpe ratio of 0.55 and maximum drawdown of 50.8%. Adding AGG to such an equity-only portfolio decreases its return but reduces its volatility even more, thus improving the Sharpe ratio. The maximum drawdown is also significantly diminished.

The article quotes two merger arbitrage funds with substantial assets: The Merger Fund® (MERFX) and The Arbitrage Fund (ARBFX). To effectively diversify the balanced portfolio, should either fund replace a portion of stocks, a portion of bonds, or a combination of both? What should be the extent of such a replacement?

To answer the first question, let’s take a look at the correlation between SPY, AGG and either fund using the Correlation service of the Alpholio™ app. Here is a chart of the rolling 12-month correlation coefficient for monthly returns of SPY and MERFX:

Correlation SPY - MERFX

The starting date of the chart stems from the earliest availability of AGG whose first full monthly return was in October 2003. The average correlation of 0.56 indicates that MERFX was a marginal diversifier for SPY (generally, a correlation of 0.6 or less is desirable). Here is a similar chart for AGG and MERFX:

Correlation AGG - MERFX

The average correlation of just below zero indicates that MERFX was a much better diversifier for AGG than SPY. Similarly, the average correlation between SPY and ARBFX was about 0.42 and virtually zero between AGG and ARBFX. Therefore, to effectively diversify the base portfolio, it should generally be better to allocate more of SPY rather than AGG to MERFX or ARBFX. However, this would also suppress portfolio returns — as the following total return chart shows, MERFX and ARBFX had steadier but smaller cumulative returns than SPY:

Total Return of SPY, MERFX and ARBFX

To answer the second question: a portfolio with the highest Sharpe ratio (i.e. the tangency portfolio) would be mostly composed of AGG and MERFX. Here is an efficient frontier chart in which the current portfolio, depicted by a standalone marker inside the frontier, had 80% in AGG and 20% in MERFX but no SPY and was very close to the tangency portfolio:

Efficient Frontier 0% SPY + 80% AGG + 20% MERFX

Adding MERFX at the expense of SPY decreased the portfolio volatility and increased its Sharpe ratio, but resulted in lower returns. To illustrate this further, here is a chart and statistics for a portfolio that consisted of 45% SPY, 40% AGG and 15% MERFX, rebalanced quarterly:

Portfolio 45% SPY + 40% AGG + 15% MERFX

Ultimately, it is up to the investor to trade off portfolio returns for risk — some may choose to optimize for the highest return per unit of risk, while others may strive for higher returns at the expense of a sub-optimal Sharpe ratio. The Alpholio™ app for Android provides a set of tools that facilitate the exploration of historical data and construction of desired portfolios, with the usual caveat that the past performance is not a guarantee of future results.

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Alpholio™ App for Android – Efficient Frontier Service

In one of the previous posts, we introduced the Alpholio™ app for Android. This post is the sixth one in a series covering the app’s services in more detail.

The Efficient Frontier service produces efficient frontier charts for a portfolio in the specified time frame. A full explanation of the efficient frontier and modern portfolio theory (MPT) is beyond the scope of this post. Among other places, you can find a good coverage of these concepts here and here.

To access the service, start the app, open the navigation drawer and tap the Efficient Frontier item:

Alpholio™ App for Android - Services

This will open a new screen, on which you can enter inputs for the chart. To expand the Dates and Return Frequency sections, simply tap each section header:

Alpholio™ App for Android - Efficient Frontier Input

The Positions, Dates and Return Frequency sections are identical to their counterparts in the Portfolio service described in the previous post. However, settings for the Efficient Frontier service are separate from those of the Portfolio service.

After you specify all parameters, tap the Get Efficient Frontier button. If any of your inputs are invalid, you will see a brief pop-up warning. If all settings are acceptable, they will be saved on the device for subsequent use. Please note that to generate the chart, your device must be connected to the Internet.

When the app obtains and processes the data, you should see the following screen:

Alpholio™ App for Android - Efficient Frontier Output

The first thing you may notice is that the chart begins in October 2003 and not January 2000 that was specified as the From date. That is because the inception date of AGG was in September 2003 and the first full month of returns for this ETF was the following month. The app automatically selected the largest possible date range for the analysis.

The efficient frontier (EF) is plotted in two sections: a small red one below the minimum-variance portfolio (MVP) and a large blue one above it. The capital allocation line (CAL) touches the upper EF section at the tangency portfolio (TP) point. Finally, the current portfolio (CP) is shown as a point inside the EF.

To zoom in on a portion of the chart, tap the + button or use a spread gesture. To scroll a zoomed-in chart horizontally or vertically, use a corresponding swipe gesture. To zoom out, tap the button or use a pinch gesture. To immediately restore the chart to its original view, tap the 1:1 button.

Below the chart, there is a Statistics section that can be collapsed and expanded by tapping its header. The section contains precise expected-return / standard-deviation coordinates for the MVP, TP and CP. It also provides the risk-free rate and the maximum Sharpe ratio (that of the TP).

Press or tap the Back button on the device to change the weights of positions in the portfolio and see how the CP location changes with respect to the efficient frontier. Give the app a try today:

Get It on Google Play

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Alpholio™ App for Android – Portfolio Service

In one of the previous posts, we introduced the Alpholio™ app for Android. This post is the fifth one in a series covering the app’s services in more detail.

The Portfolio service produces charts of total returns for portfolios composed of multiple securities and rebalanced with a specified frequency. (To better understand the importance of using total returns as opposed to price returns, please refer to the description of the app’s Total Return service.)

To access the service, start the app, open the navigation drawer and tap the Portfolio item:

Alpholio™ App for Android - Services

This will open a new screen, on which you can enter inputs for the chart. To expand the Dates, Return Frequency and Rebalance Frequency sections, simply tap each section header:

Alpholio™ App for Android - Portfolio Input

You can enter up to 20 portfolio positions by specifying a ticker and percentage weight for each. The weight determines the value of the position relative to the total value of the portfolio. For example, if the portfolio is worth $10,000 and a position has a weight of 25%, then the position’s value is $2,500. Position weights in a portfolio always add up to 100%.

The default positions are VTI (Vanguard Total Stock Market ETF) at 40%, EFA (iShares MSCI EAFE ETF) at 20%, and AGG (iShares Core U.S. Aggregate Bond ETF) at 40%. This is effectively a balanced 60/40 portfolio with one-third (i.e. 20% out of 60%) of the equity part in foreign securities.

To change a position’s ticker, tap the corresponding field and use the pop-up keyboard to edit it. (If you need to find the ticker based on other information, use the Security Lookup service of the app.)

To change a position weight, tap and drag the thumb of the corresponding seek bar until you see the desired percentage displayed above the bar. When you finish, weights of all other positions in the portfolio will automatically recalculate to add up to 100% (due to the seek bar resolution, there may be a rounding error of up to 1%). If you do not want the weight of a particular position to change, tap a corresponding Fix check box. If only one position remains unfixed, its weight cannot be changed.

To delete a position, tap its Del button; you will not be able to remove the last remaining position. When a position with non-zero weight is removed, its weight is distributed among the remaining positions according to their weights. To add a position, tap the Add Position button at the bottom of the list, then enter the new position’s ticker and set its weight.

To modify either the From or To date, tap its corresponding button. This will pop up a standard date selection dialog. The From date must chronologically precede the To date.

To select a different return frequency, tap the corresponding radio button. Generally, monthly returns will provide a smoother return plot than weekly or daily ones.

To choose a rebalance frequency, expand the Rebalance Frequency section and tap the corresponding radio button:

Alpholio™ App for Android - Portfolio Input - Rebalance Frequency

Portfolio rebalancing involves adjusting positions to bring their weights to their original specification. The service assumes that trading costs are negligibly small compared to the position value. This is, for example, the case with no-transaction-fee ETFs at discount brokerages.

The frequency of rebalancing cannot be higher than the frequency of returns. For example, with monthly returns, portfolio can be rebalanced monthly, quarterly or semi-annually (i.e. every six months), but not daily or weekly. If you make both frequencies the same then the portfolio weights will effectively be kept constant (disregarding weight fluctuations in between rebalancing events).

After you specify all parameters, tap the Analyze Portfolio button. If any of your inputs are invalid, you will see a brief pop-up warning. If all settings are acceptable, they will be saved on the device for subsequent use. Please note that to generate the chart, your device must be connected to the Internet.

When the app obtains and processes the data, you should see the following screen:

Alpholio™ App for Android - Portfolio Output

The first thing you may notice is that the chart begins in October 2003 and not January 2000 that was specified as the From date. That is because the inception date of AGG was in September 2003 and the first full month of returns for this ETF was the following month. The app automatically selected the largest possible date range for the analysis.

To zoom in on a portion of the chart, tap the + button or use a spread gesture. To scroll a zoomed-in chart horizontally or vertically, use a corresponding swipe gesture. To zoom out, tap the button or use a pinch gesture. To immediately restore the chart to its original view, tap the 1:1 button.

Below the chart, there is a Statistics section that can be collapsed and expanded by tapping its header. You can see that the portfolio had an annualized return of about 7.4% with an annualized standard deviation or returns of about 9.6%. The portfolio generated a modest amount of alpha but its beta was significantly lower than that of the market (by definition, equal to one). The Sharpe ratio of the portfolio was 0.64 and the maximum drawdown from the peak in October 2007 to the trough in March 2008 was about 34%.

Press or tap the Back button on your device and change some position weights or rebalancing frequency to see how that affects portfolio statistics. Give the app a try today:

Get It on Google Play

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Analysis of Fidelity OTC Portfolio
analysis, mutual fund

A recent mutual fund story in Barron’s covers the Fidelity OTC Portfolio (FOCPX). This $11 billion fund sports a relatively low 0.76% expense ratio but has a high 102% turnover. According to the fund’s profile, its strategy is based on

Normally investing at least 80% of assets in securities principally traded on NASDAQ or an over-the-counter [OTC] market, which has more small and medium-sized companies than other markets. Investing more than 25% of total assets in the technology sector.

Although the article quotes a five-year annualized return of the fund, it is worth noting that that current manager has headed the fund only since July 1, 2009 (just under five years ago, as of this writing). Therefore, all further analyses will use that shorter timeframe. (It could also be argued that an even shorter observation period should be applied because the new manager likely did not change the inherited portfolio of the fund overnight.)

The fund’s prospectus benchmark is the NASDAQ Composite® index, whose practical implementation is the Fidelity NASDAQ Composite ETF (ONEQ). Alpholio™ calculated that since the current manager took over, on average the fund returned 1.94% more than the ETF in each of the rolling 12-month periods. However, the median difference was 3.35%, which indicates that the majority of differences were much smaller (i.e. a left skew of the distribution). The fund’s rolling returns beat those of the ETF about two-thirds of the time.

Alpholio™’s calculations also indicate that the fund’s returns were quite volatile. Since the new manager took the helm in mid-2009, the fund’s annualized standard deviation of 18.3% was higher than 16.1% for the ETF. As a result, at 1.12 the fund’s Sharpe ratio (a simplest measure of risk-adjusted returns) was smaller than 1.20 for the ETF in the same period.

Let’s take a further look at Fidelity OTC Portfolio from Alpholio™’s perspective. Here is the cumulative RealAlpha™ chart for the fund during the current manager’s tenure:

Cumulative RealAlpha™ for FOCPX

The fund’s cumulative RealAlpha™ was unremarkable except for a brief and rapid rise in mid-2013. Overall, the annualized discounted RealAlpha™ of the fund was about 2% on a regular and about 1% on a lag basis (to learn about the difference between these two measures, please visit the FAQ). The lag RealAlpha™ curve was below its regular counterpart, which means that not all new investment ideas worked out as well as expected. The volatility of the reference ETF portfolio was lower than that of the fund by about 1.5%.

The following chart depicts ETF weights in Fidelity OTC Portfolio’s reference portfolio in the same analysis period:

Reference Weights for FOCPX

As expected based on the fund’s declared strategy, the PowerShares QQQ™ ETF (QQQ) was the largest equivalent position with an average weight of 44.2%, followed by the Vanguard Small-Cap Growth ETF (VBK; 22.1%), iShares Russell 2000 Growth ETF (IWO; 7.6%), SPDR® Morgan Stanley Technology ETF (MTK; 7.6%), iShares Nasdaq Biotechnology ETF (IBB; 5.8%), and iShares North American Tech-Multimedia Networking ETF (IGN; 5.5%). The Other component in the chart represents two more ETFs will smaller average weights.

The final chart shows a hypothetical buy-sell signal for the fund derived from the smoothed cumulative RealAlpha™ presented above:

Buy-Sell Signal for FOCPX

An investor following this signal would have avoided a period of fund’s relative underperformance from late 2011 through early 2013, while capturing the aforementioned strong rebound in mid-2013.

This analysis demonstrated the importance of focusing on a shorter tenure of the current manager instead of assessing a full historical performance of a fund. On a truly risk-adjusted basis, Fidelity OTC Portfolio generated a modest amount of RealAlpha™ most of which accrued during six months in mid-2013. Since then, the fund’s cumulative RealAlpha™ has been largely flat. Therefore, there is currently no indication that the fund will significantly outperform its reference ETF portfolio in the near future.

To learn more about the Fidelity OTC Portfolio and other mutual funds, please register on our website.

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Finding Star Fund Managers
active management, active share, correlation, performance persistence

With the new Fund Manager of the Year awards from Morningstar, a question of future performance of star fund managers inevitably arises. Apparently, the awards carry little short-term predictive value:

While our Fund Manager of the Year awards are recognition of past contributions rather than predictions of future results, we’re confident in each one’s long-term prospects because of their deep research resources and willingness to stick with their discipline in good times and bad. We wouldn’t expect repeat performances in 2014, as our winners and their rivals will wrestle with lofty equity valuations, policy-related volatility, a still-recovering economy, and the specter of rising rates.

Indeed, statistics on award winners presented by an article in The Wall Street Journal are not too encouraging:

Subsequent Period Beating the Benchmark
1 year 58%
3 years 45%
5 years 56%
10 years 65%

Generally, the best long-term predictors of fund outperformance remain a low expense ratio (fees), minimal portfolio turnover (a proxy for trading costs), and divergence from benchmark index weightings. The latter measure, known as active share should be high:

Prof. Cremers says the best funds tend to have active-shares percentages that are at least 60%. Large-stock managers should ideally have an active share above 70%. Midcap managers should have active share above 85% and small-cap managers should exceed 90%, he says.

Unfortunately, the proportion of funds with such big active shares has been falling over the years, which gave rise to “closet indexing,” as a chart from a Lazard Research study demonstrates:

Rise in Closet Indexing

The active share in the aggregate portfolio of actively-managed U.S. stock funds has been also declining:

Active Share in Aggregate Portfolio of Active U.S. Stock Funds

However, active is not always a guarantee of strong performance, as shown in an earlier Alpholio™ post.

As for fund fees, an article in The New York Times points out that

The average total expense ratio, which encompasses management fees and operating expenses but not brokerage commissions and other trading costs, is 1.33 percent of assets a year for domestic stock funds and 0.97 percent for domestic bond funds, according to Morningstar.

Over time, these fees add up. According to a paper by William Sharpe, which estimated an average expense ratio of stock funds at 1.12% compared to 0.06% (now 0.05%) for the Vanguard Total Stock Market Index Fund (VTSAX, Admiral Shares):

Whether one is investing a lump-sum amount or a series of periodic amounts, the arithmetic of investment expenses is compelling… Under plausible conditions, a person saving for retirement who chooses low-cost investments could have a standard of living throughout retirement more than 20% higher than that of a comparable investor in high-cost investments.

However, as a Gerstein Fisher study found, the cheapest funds may not always provide the highest returns:

We found that the best performing quintile of funds was the second most expensive quintile (i.e., the 21-40% highest-cost ones), whether we equally weighted funds or asset-weighted them. The consistent results of the study: the cheapest quintile of funds was not the best performing, but the most expensive funds were the worst performing.

Similarly to a low correlation, a factor that is often quoted to aid stock pickers is a high degree of dispersion (measure of spreading) of stock returns. At first blush, it would seem that, just as with active share, an increased dispersion is beneficial. However, all it does is to enlarge the dispersion of active fund returns, without necessarily moving the average, as another article in The Wall Street Journal indicates:

A bigger spread between the best and worst stocks hasn’t helped active funds as a group, but it does tend to make good funds better—and bad funds worse… To put it another way: Markets that aren’t moving in lock step give active managers more rope with which to climb above the pack or to hang themselves.

While a low cost and small turnover coupled with a significant active share are generally good screening criteria, funds clearly have trouble with performance persistence. As our analyses have repeatedly demonstrated, even the star fund managers stumble, so outperformance is fleeting. This is where the Alpholio™ methodology helps by showing momentum in the smoothed cumulative RealAlpha™ for each analyzed fund, from which buy/sell signals can be derived. To learn more, please visit our FAQ.

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Asset Allocation in Retirement Portfolio
asset allocation, equity risk premium

A study by Pfau and Kitces in the Journal of Financial Planning gives a counter-intuitive guidance on asset allocation in a retirement portfolio. Instead of a traditional glide path that decreases the equity portion of the portfolio with the retiree’s age, the authors found that a rising allocation is optimal for retirement success, i.e. not running out of money.

The authors conducted 10,000 Monte Carlo simulations with three different sets of assumptions about stock and bond returns, equity risk premia as well as inflation rates, 121 lifetime asset allocation glide paths, annual withdrawal rates of 4% and 5%, and time horizons of 20, 30 and 40 years. The conclusions were:

Accordingly, for those households looking to maximize their level of sustainable retirement income, and/or to reduce the potential magnitude of any shortfalls in adverse scenarios, portfolios that start off in the vicinity of 20 percent to 40 percent in equities and rise to the level of 60 percent to 80 percent in equities generally perform better than static rebalanced portfolios or declining equity glide paths. The results hold even in situations where the final equity exposure is no higher than what the client’s static portfolio allocation may have been in the first place.

The results also reveal that in particular scenarios where the equity risk premium is depressed, the optimal glide path includes less equity overall. In scenarios where the goal is to withdraw at a level that stresses the portfolio [5%] and its expected growth rate, higher overall levels of equity are necessary (with such high-risk goals, having a relatively high-risk portfolio, even with the danger this approach entails, is still the optimal solution).

The key reason for starting with the initial lower allocation to stocks is that

…in the case of a 30-year time horizon, the outcome of a withdrawal scenario is dictated almost entirely by the real returns of the portfolio for the first 15 years. If the returns are good, the retiree is so far ahead relative to the original goal that a subsequent bear market in the second half of retirement has little impact. Although it is true that final wealth may be highly volatile in the end, the initial spending goal will not be threatened. By contrast, if the returns are bad in the first half of retirement, the portfolio is so stressed that the good returns that follow are absolutely crucial to carry the portfolio through to the end.

This is supported by Vanguard portfolio allocation models that range from 100% bond to 100% stock allocations and are analyzed in the 87 years from 1926 through 2012. As can be expected, the average annual return of a portfolio increases with allocation to equities, but generally so does the number of down years as well as the maximum annual loss. So, is there an optimal allocation that would maximize the average annual return while minimizing the probability of a loss year? To determine that, Alpholio™ compiled the following chart:

Average Return / Probability of Loss Year

The ratio peaks for a portfolio with 20% stocks and 80% bonds, which is consistent with the findings of the study.

The main problem with this and similar studies is that they assume a mechanical annual adjustment of withdrawals based on the prior year’s inflation rate. This is done to maintain the purchasing power of withdrawals. However, in reality expenses fall with age during retirement, as an article in The Wall Street Journal indicates:

“Pretty much every paper you read about retirement assumes that spending increases every year by [the rate of] inflation,” Mr. Blanchett says. But when he analyzed government retiree-spending data, he found otherwise: Between the ages of 65 and 90, spending decreased in inflation-adjusted terms.
Most models would assume that someone spending $50,000 the first year of retirement would need $51,500 the second year (if the inflation rate were 3%). But Mr. Blanchett found that the increase is closer to 1%, which has big implications over decades, “because these changes become cumulative over time,” he says.

In the above example, the terminal annual withdrawal after 25 years would be $104,689 with a 3% annual increase vs. only $64,122 with a 1% increase. This significant difference would certainly change the outcome of simulations with the rising equity glide paths. Most likely, either a flatter (less risky) path would suffice for a given success rate, or a success rate would increase for a given glide path.

To determine the optimal asset allocation in retirement, it is also useful to see the spending distribution among major expense categories:

Where the Money Goes

Not surprisingly, in a typical retirement period healthcare and charity expenditures grow, while insurance/pensions, transportation and clothing expenditures shrink as a percentage of the overall budget. A recent slowdown in medical-price inflation, which historically outpaced the overall inflation, is likely a result of passing on more costs to consumers (as well as a temporary effect of the Great Recession). Therefore, it seems reasonable to keep a sizable exposure to equities even late into retirement, while minimizing the risk in early years. This is what a U-shaped glide path strives to accomplish.

For most of current retirees, Social Security is a major source of income:

Keep It Coming

However, with the ongoing shift from the defined-benefit to defined-contribution plans, careful (and individualized) planning of retirement asset allocation in employer-sponsored plans and IRAs as well as other personal investments is evermore important.

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REIT Correlations with Stocks
alternatives, analysis, correlation, portfolio

Traditionally, real-estate investment trusts (REITs) provided a good diversification to other stocks in a portfolio. However, in the last several years, REIT returns have become highly correlated with returns of other equities. One theory, outlined in a Morningstar article, is that over the years REITs evolved from a small, illiquid and neglected to a mainstream and easility accessible asset class.

As an article in The Wall Street Journal indicates

From 1980 through 2006, stock performance of REITs moved in tandem with the broader market only 47% of the time, according to an analysis for The Wall Street Journal by Citi Private Bank in New York… Since then, as the bank’s research shows, REIT correlations have jumped to nearly 80%, erasing more than a quarter of a century in decoupling.

To illustrate that, Alpholio™ compiled the following chart of correlation between returns of the SPDR® S&P 500® ETF (SPY) and iShares U.S. Real Estate ETF (IYR):

SPY-IYR Correlation 3-4 Years

The chart shows rolling correlations in trailing three- and four-year periods using total monthly returns of both ETFs since mid-2000. (As expected, thanks to a larger number of data points the latter curve is a bit smoother but lags the former one.) Either curve is characterized by four distinct phases:

  • Through 2006, the correlation was indeed in the mid-40%
  • From 2007 through 2008, the correlation gradually increased to about 70% and abruptly jumped to over 80% at the onset of the financial crisis
  • From 2009 through mid-2013, the correlation stayed at about 85%
  • Afterwards, the correlation decreased started to decrease.

The last two phases were caused, at least in part, by the Federal Reserve’s interest rate policy: a strong coupling of rising returns stimulated by low rates, followed by an indication of decoupling when rates rose. A better economic outlook is also a factor:

Improving conditions in the broader economy usually lead to lower real-estate correlations… In fact, correlations between the S&P 500 and REITs have dropped by about 10% since late last year.

Let’s take a look at the last phase in more detail, this time using trailing 18- and 24-month returns:

SPY-IYR Correlation 18-24 Months

Here, thanks to shorter time windows the degree of decoupling in the last phase is more evident: the correlation reverted to about 50%. This would suggest that REITs might once again help with portfolio diversification. However, as the next chart shows, REIT returns are currently negatively correlated with the interest rate on a 10-year Treasury note:

IYR - 10-Year T-Note Rate Correlation

With the prospect of rising interest rates this year, REIT returns are likely to continue to be depressed. At the same time, many analysts forecast 5-10% returns of the overall equity market (for example, S&P just increased its 12-month target for the S&P 500® index from 1895 to 1940, which implies an approx. 7% total return). Therefore, until interest rates stabilize, it may be too early to declare a structural decrease in correlation of REIT returns to those of other stocks. A permanent return to pre-2007 correlation levels would certainly help with portfolio construction.

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Rebalancing Act
asset allocation, foreign equity, market, mutual fund, valuation

As the end of the year approaches, the investment industry is gearing up for the annual portfolio rebalancing act. An article in InvestmentNews gives the following example:

Still, advisers’ plan to stick to their long-term asset allocation was likely thrown out of whack this year by the divergence of stocks and bonds. For example, a client who started the year with a simple 60/40 portfolio comprised of the $287 billion Vanguard Total Stock Market Fund (VTSMX) and the $247 billion Pimco Total Return Fund (PTTAX), the two largest mutual funds in the world, would now have 66.3% invested in stocks and just 33.7% invested in bonds, pushing beyond the typical 5% leeway most advisers give their asset allocation.

To illustrate the divergence from asset allocation historical averages, here is a chart from a Vanguard blog post:

Mutual Fund and ETF Assets under Management

While the collective allocation of mutual funds and ETFs to equities has recently reached 57%, the biggest divergence from the historical median is in international equities. Allocation to bonds is also relatively high, while the proportion in domestic equities is close to the 20-year median.

The higher allocations to international equities and bonds are at the expense of cash. Assets in money market funds are at a historical minimum of about 18% in the observation period. This has undoubtedly been caused by the low interest rate policy of the Fed, which depressed returns of such funds. The danger is that when interest rates eventually rise, bond prices will suffer:

So in an intermediate-term bond fund, with an average duration of four to five years, the loss would be about 4% to 5%.

This means that it may actually be prudent for an average investor to shorten the duration by moving a part of investment in bonds to money market funds.

Historically, the proportion of international equities in the total equity allocation has been about 19%; currently, it is about 27%. The argument for keeping it high is a relatively low valuation of foreign stocks compared to domestic ones:

Stock Valuation per Market Region

When rebalancing portfolios, it is also important that investors understand the true exposure of their mutual fund holdings to various asset classes. The recurring problem, which Alpholio™ addressed in several prior posts, is that managers in some equity funds (especially value strategies) hold a large percentage of assets in cash. As a result, asset allocation in the overall portfolio can be distorted unbeknownst to the investor.

Alpholio™ provides current information on the exposure of mutual funds to various asset classes. This information is not obtained from the regulatory filings or selective disclosures of fund holdings, which suffer from a number of problems.

In sum, when rebalancing a portfolio either on a fixed schedule or as a result of divergence from prior allocations, investors should take into account a broader market and interest rate context, rather than just follow rigid rules.

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How Much to Invest Abroad
asset allocation, correlation, foreign equity, portfolio

A recent article in the Wealth Management Report of The Wall Street Journal provides recommendations from industry experts on what portion of the portfolio an individual investor should invest in foreign securities. The expert opinions focus on equity, rather than bond or currency, allocation in the portfolio. Although the sample of just seven experts is small, statistics show that opinions do not vary a lot:

Statistic Value
Mean 27.5%
Median 30.0%
Standard Deviation 6.9%

So, is a foreign equity allocation in the high 20s percent points appropriate? It depends on whether this brings the benefit of high and uncorrelated returns to the rest of the portfolio. In his bestselling book, David Swensen recommends the following asset allocation as the starting point for individual customization:

Asset Class Policy Target
Domestic Equity 30%
Foreign Developed Equity 15%
Emerging Market Equity 5%
Real Estate 20%
U.S. Treasury Bonds 15%
U.S. Treasury Inflation-Protected Securities 15%

This implies an explicit foreign equity exposure of 20% of the total portfolio and about 28.6% of its equity portion (20% in a portfolio with 70% of “assets that promise equity-like returns”). Swensen also discusses currency exposure that stems from foreign investments:

“Fortunately, finance theorists conclude that some measure of foreign exchange exposure adds to portfolio diversification. Unless foreign currency positions constitute more than roughly one-quarter of portfolio assets, currency exposure serves to reduce the overall portfolio risk. Beyond a quarter of portfolio assets, the currency exposure constitutes a source of unwanted risk.”

Unfortunately, the diversification provided by foreign equities tends to fail when it is needed most. Since the most recent financial crisis, correlations between foreign and domestic equity returns shot up. Vanguard reports that from October 2007 through February 2009, that correlation was 0.93 for developed international markets and about 0.83 for emerging markets.

At the same time, even a domestic equity portfolio has an implicit exposure to foreign markets. That is because about 46% of revenue of companies in the S&P 500® index has been historically obtained abroad. In sum, an explicit allocation of close to 30% of the equity portfolio to foreign securities, which on average experts recommended, may be on the high side.

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