Do Alternatives Diversify?
alternatives, correlation, mutual fund

A recent article in The Wall Street Journal discusses how wealth managers are increasingly investing their clients’ money in mutual funds that use hedge-fund strategies. The idea behind these “alternative” investments is a low correlation of their returns to those of the general market, which is supposed to protect portfolios during market downturns. Unfortunately, the price paid for this is a sub-par performance of such investments in normal market conditions.

Let’s take a look at correlations of some of the funds mentioned in the article. Correlation coefficients can be reverse-engineered from data provided by Morningstar:

Fund Ticker Beta Fund StDev Market StDev Correlation
Natixis ASG Global Alternatives GAFYX 0.43 8.30 14.02 0.73
TFS Market Neutral TFSMX 0.33 6.32 14.02 0.73
Highbridge Statistical Market Neutral HSKSX 0.11 3.45 14.02 0.45

The above figures are based on the most recent three-year period. As can be seen, correlations of these funds to the market are quite high.

For further reference, here are average correlations of three types of “traditional” alternative assets, i.e. REITs, commodities, and hedge funds, with stocks and Treasury notes, as calculated by Leuthold Group:

Leuthold Group - Correlations of Alternatives

In the last four years, these correlations were much higher than their long-term historical averages.

Even institutional investors keep pursuing alternatives in the name of diversification. However, true diversification of a portfolio requires not only low correlations but also high returns of assets being added. While it may still turn out that alternative investments provide some degree of portfolio protection during the next market downturn, this assumption is becoming questionable.

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Urban Myths of Mutual Funds
active management, mutual fund

A recent article from MorningstarAdisor discusses an urban myth that mutual funds have hidden fees of 140-200 basis points (bps), which are omitted from expense ratios. In this context, the article provides the following statistics:

Over the trailing 10 years ending March 31, 2013, the average U.S. large-cap equity fund, on an asset-weighted basis, trails the market index by its expense ratio plus about 39 basis points. Over the past five years, this figure shrinks to 25 basis points.

This means that an average large-cap fund not only failed to earn its expenses but also subtracted value on top of them. By how much in total? The Investment Company Institute’s report provides the following asset-weighted statistics of expense ratios for equity funds:

All Funds Actively-Managed Funds Index Funds
2003 100 bps 110 bps 25 bps
2008 83 94 17
2012 77 92 13
10-Year Average 87 98 18
5-Year Average 82 95 15

So, an average large-cap equity fund subtracted about 98 + 39 = 137 bps and 95 + 25 = 120 bps per year in the 10-year and 5-year periods, respectively. The non-asset-weighted statistics of fund expense ratios are even worse (all figures for 2012):

Equity Strategy Median Mean
Aggressive growth 137 bps 147 bps
Growth 124 131
Sector 146 153
Growth and Income 112 118
Income 112 120
International 147 155
Average 133 141

Of note here is the right skew of the expense ratio distribution (in all cases, the mean is greater than the median). This implies that some funds have very high expense ratios. Indeed the 90th percentile of equity funds has an average expense ratio of 216 bps or more, which is over 62% higher than the median of 133 bps.

Apparently, all this was not lost on he California Public Employees’ Retirement System (CalPERS), which this week decided to replace actively-managed strategies with passive ones even for asset classes other than equities:

The $1.64 billion defined-contribution plans, including the $1.1 billion 457 plan, will be adding passively managed U.S. equity, international equity, short-term-bond, intermediate-term-bond and real-asset strategies from State Street Global Advisors.

The investment committee elected to drop actively managed U.S. small- and midcap value and growth strategies managed by The Boston Co. Asset Management LLC, international equity managed by Pyramis Global Advisors, short-term bond managed by Pacific Investment Management Co. LLC, and intermediate and Treasury inflation-protected securities strategies managed in-house.

Fees for the funds will drop to 6 basis points, from 52, because of the change.

Evidently, even with an average expense ratios of 52 bps (which is close to the 10th percentile for actively-managed funds), original strategies failed to earn their keep.

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Battle of the Market Timers
active management

A recent article in The Wall Street Journal explores a hypothetical market-timing performance of various investment newsletters.

To eliminate the effect of individual stock picks, equity positions in each newsletter’s portfolio were virtually substituted with the Vanguard Total Stock Market ETF (ticker VTI) in the the same dollar amount. In periods when the newsletter eliminated equity positions in the portfolio, VTI would be replaced with a typical money market fund. Then the returns and volatility of the virtual portfolio would be compared to those of a fixed portfolio of 100% VTI. Using this methodology, one of the top newsletters would generate almost twice the return with one-third less volatility of VTI in the five-year period through May 2013.

Unfortunately, such market timing does not generate RealAlpha™. The article underscores that

“It also is worth noting that the best-performing timers primarily focus on market trends of several months’ duration or longer, not trying to profit from shorter-term market gyrations.”

As discussed in the FAQ, this is a classic situation where one fixed benchmark, or even a combination of two fixed benchmarks, is not appropriate. In this case, a fixed 100% VTI benchmark is not applicable to prolonged (multiple-month) periods in which the hypothetical portfolio was invested in a money market fund with practically zero volatility.

A benchmark composed of VTI and a reference money market in fixed proportions in the entire evaluation period is better in that it attempts to match the overall risk of the hypothetical portfolio. For example, if over a five-year period the portfolio held VTI roughly two-thirds of the time and a money market one-third of the time, then a composite benchmark with such weights might be used. (Incidentally, this is similar to devising a proper benchmark for target date funds that consist of multiple types of assets, whose weights change over time.) However, this fixed dual-asset benchmark is also imperfect — at any given time, one part of that benchmark is not applicable to what the “binary” portfolio holds.

In the Alpholio™ approach, the benchmark would dynamically adapt to the holdings of the analyzed portfolio in each multiple-month sub-period. This is necessary for a true risk adjustment of the portfolio. Unfortunately, this would also result in little to no credit given for market timing.

Finally, the article only covers a five-year period starting right after the trough of the recent major downturn, i.e. a rebound portion of the market cycle. A longer period encompassing the entire cycle should have been used to assess market timing strategies.

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Easy to Be a Value Investor
analysis, mutual fund, value investing

A recent post on Barron’s reports on statements made by Bill Nygren at the Morningstar Investment Conference. Mr. Nygren, manager of Oakmark Fund (ticker OAKMX), claims that it is easier to be a value manager today than it was 20 to 30 years ago because:

  • The analysts his firm hires now are “definitely” smarter than those it was hiring when he started out
  • His firm’s investment horizon for a security is five to seven years, as opposed to, say, only a couple of quarters for other investors.

So, let’s see how this is reflected in the historical performance of the above fund. First, as indicated in the most recent SEC filing, the annual turnover rate of the fund was 27% during the most recent fiscal year (18% and 24% in the two prior years, respectively). For simplicity, let’s assume an average turnover rate of approximately 23% and that a different part of the portfolio is replaced each year. Then it would take a little over four years to replace all holdings. This implies that an average security persists for only about two years in the portfolio. Even if this is not entirely accurate due to simplifying assumptions, that period is a far cry from the much longer investment horizon mentioned above. So much for the buy-and-hold philosophy.

Second, the Alpholio™ analysis of the fund shows that in the past eight years, it practically generated no alpha for its shareholders, when fully adjusted for the ever-changing risk of its positions:

Cumulative RealAlpha™ for OAKMX

In other words, instead of investing in carefully-analyzed individual stocks, the fund would do a comparable job investing in a reference portfolio of exchange-traded products (ETPs). In addition, this reference portfolio would have a smaller volatility of returns. (Alpholio™ calculates such reference portfolios for all US mutual funds on an ongoing basis.)

Therefore, while it may be true that today’s analysts are smarter than those hired in the past, it is definitely not any easier to be a value investor with a self-proclaimed long-term horizon.


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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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Boring Is Better
exchange-traded fund

A recent post from Barron’s attempts to compare the performance of PowerShares S&P 500® Low Volatility Portfolio (ticker SPLV) to that of PowerShares S&P 500® High Beta Portfolio (SPHB). In doing so, the post uses charts of price returns of these exchange-traded funds (ETFs).

First, given that both ETFs had dividend distributions and at disparate levels (12-month yield of 2.76% for SPLV and 0.75% for SPHB, according to Morningstar), a comparison of total instead of price returns would be more appropriate.

Second, the comparison does not take into account the volatility of either ETF. The simplest approach to do that would be to use a Sharpe Ratio (SR) for both funds. Unfortunately, since these funds have been in existence for only a little more than two years, the SR and standard deviation (SD) figures are not yet available (typically, they are only calculated for funds older than three years). So, here are the results derived from the available monthly return data since May 2011:

SPLV SPHB SPY
SR vs. TB 0.44 0.07 0.27
SR vs. SPY 0.02 -0.13 0.00
SD 8.73% 25.94% 13.28%

Traditionally, SR is calculated using a risk-free rate; in the above table, TB stands for the 4-week Treasury Bill, the interest rate of which is appropriate because monthly returns of ETFs are used. However, an ex-post SR can also be calculated using an arbitrary benchmark; in this case, returns of the SPDR® S&P 500® ETF (SPY) were used.

The above results clearly demonstrate that over the most recent two-year period, SPLV exhibited a return/risk performance superior to that of either SPHB or SPY. However, only time will tell if this outperformance persists in the future.

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Old-School Stock Picking vs. Index Craze
analysis, mutual fund

A recent article from The Wall Street Journal describes how a long-time stock picker in charge of his namesake Weitz Value (ticker WVALX) mutual fund increasingly loses the assets under management (AUM) battle to index funds. According to the article:

“Over three years, his Weitz Value mutual fund has outperformed the Standard & Poor’s 500-stock index by an average of about one percentage point a year and beat about 90% of similar stock funds.

Investors aren’t impressed. In that time, they pulled about $400 million more out of the fund than they put in.”

Why would that be — don’t investors want to make more money? The Alpholio™ analysis of the fund shows that investors are not irrational after all. After a full adjustment for risk taken on by the fund, it turns out that in the past eight years it hardly generated any RealAlpha™:

Cumulative RealAlpha™ for WVALX

This is further illustrated by the Alpholio™ statistics for the fund:

WVALX Statistics

The above chart and figures clearly explain why the fund has been losing AUM. While the volatility of the fund’s returns was comparable to that of its S&P 500® benchmark (also see Morningstar figures), the volatility of its reference exchange-traded product (ETP) portfolio was about 1% lower. At the same time, the reference ETP portfolio generated higher returns. In other words, this elaborate stock-picking was all for naught — the manager would have generated much more value for the fund’s shareholders if he just traded a small number of ETPs. Investors are right to vote with their wallets.


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Funds Whose Managers Eat Their Own Cooking
mutual fund

A recent article published by Morningstar makes the following statement:

“What do you look for in a fund with a relatively new manager?

The first thing is a track record at other funds that indicates the manager has skill. Next, you want other key fundamentals like low costs, high manager investment, a good strategy, and a good fund company.”

The articles goes on to focus on those managers who have at least $1 million invested in their current funds and who had a good track record in managing previous funds. Unfortunately, despite the author’s efforts, the thesis of the article is not supported even by Morningstar’s own ratings of previous funds, let alone by Alpholio™’s RealAlpha™ measure of the current or previous funds:

Current Fund Rating Previous Fund Rating Real-Alpha™
Fidelity Small Cap Stock (FSLCX) * * Fidelity Small Cap Growth (FCPGX) * * * -0.81%
Fidelity Equity Dividend Income (FEQTX) * * Fidelity Value Discovery (FVDFX) * * * -0.49%
Fidelity Magellan (FMAGX) * Fidelity Trend (FTRNX) * * * * 1.02%
Fidelity Municipal Income 2015 (FMLCX) NR NA NA 0.29%
GoodHaven (GOODX) NA Fairholme (FAIRX) * * * 0.09%
Ariel Discovery (ARDFX) NR NA NA -6.05%
Royce Special Equity Multi-Cap (RSEMX) NR NA NA -1.47%
PIMCO EqS Pathfinder (PTHDX) * * Mutual Global Discovery (TEDIX) * * * * * 3.14%
Fairholme Focused Income (FOCIX) * * * Fairholme (FAIRX) * * * 0.09%
Akre Focus Retail (AKREX) * * * * * FBR Focus (NA) NA 2.8%

In the above table, the RealAlpha™ figure pertains to the previous fund, if available, or to the current fund, otherwise. For the most part, the previous fund ratings (or the current fund RealAlpha™ measures) do not support the thesis that the current funds will do well, even in the presence of a substantial investment by their own managers.

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Overpaying for Money Management
active management

A recent article on MarketWatch refers to the op-ed in The Wall Street Journal to make a point about the hidden cost of money management. While the op-ed promotes index-fund over actively-managed mutual fund investing, the article correctly states that even in the latter most investors overpay for financial advice which typically costs about 1% on top of the expense ratios of passive vehicles.

However, the article then makes a mistake that is common in the financial press: it tries to directly compare the returns of one sample mutual fund (Alger Capital Appreciation, ticker ALVOX) to that of a single index (S&P 500® represented by the Vanguard 500 Index Fund, ticker VFINX) to make a statement about fund performance.

According to Alpholio™ calculations, since early 2005 the annualized standard deviation of returns of these funds was as follows:

Fund Volatility
ALVOX 18.25%
VFINX 15.61%

As can be seen, the volatility of ALVOX was about 16.9% higher than that of VFINX in this analysis period.

In addition, Morningstar currently provides the following standard deviations and categories of these funds:

Fund 3-Year SD 5-Year SD 10-Year SD 15-Year SD Category
ALVOX 16.07 20.84 17.43 21.67 US OE Large Growth
VFINX 14.02 18.84 14.56 16.17 US OE Large Blend

Again, the volatility of ALVOX was anywhere from 10.6% to 34.0% higher than that of VFINX in the respective analysis periods, which is also supported by the different classification of these funds. Therefore, comparing ALVOX to VFINX is highly misleading.

Both the article and op-ed seem to justify management fees if the financial planner “adds value” by adjusting asset allocation, i.e. periodically modifies the weights of index vehicles in the portfolio. In Alpholio™’s view, this type of adjustment does not add any RealAlpha™ because it only changes the risk profile of the portfolio, as reflected by its RealBeta™. A reference portfolio of exchange-traded products (ETPs) calculated by Alpholio™ will simply catch up to any such changes to match the risk of the managed portfolio. For a detailed description of the Alpholio™ methodology, please refer to the FAQ.

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Musings on Correlation
correlation

A recent article from Morningstar states that

“Correlation is bound between negative 1.0 and 1.0. A correlation of 1.0 indicates perfect positive correlation, meaning that as one investment rises (falls), the other rises (falls) at the same rate.”

And, in email correspondence with Alpholio™, a prominent blogger for one of the well-known financial publications (who shall remain anonymous) stated that

“If you’re then going to hang your hat on the distinction between equity and high-yield bonds, I’d point you to the correlation of JNK and HYG to the stock market – about 85% with the financial sector the last three years. Your bond-equity distinction here just doesn’t hold.”

Well, these statements create a good opportunity to explain what correlation really means. First, the correlation in question is a Pearson correlation coefficient between two time series of periodic returns within an analysis interval. In most of practical calculations, the return period is chosen to be one month (daily or weekly returns are considered too “noisy”) and the analysis interval to be three years. In addition, either linear or logarithmic returns are used (the latter to account for continuous compounding).

Second, a high correlation does not imply causation. The fact that two entities are strongly correlated does not imply that one makes the other happen.

Third, and most importantly in the context of this discussion, a high correlation does not imply identity. The fact that two entities are generally moving in the same direction in each period does not mean that they are identical. That is because the magnitude of each respective move can be very different.

To illustrate this, let’s take a look at correlations and returns of the following indexes and securities in the most recent three-year and five-year intervals:

It turns out that the differences between linear and logarithmic return correlations are very small in this case (0.001). The following table shows the latter ones:

Interval S&P 500 SPY SSO
3 Years 1.000 0.998 0.998
5 Years 1.000 0.998 0.996

In both analysis intervals, correlations of both SPY and SOO to the S&P 500® were virtually equal to one (correlation of the S&P 500® with itself equals one by definition).

The following table shows correlations between HYG and VFH:

Interval VFH HYG
3 Years 1.000 0.769
5 Years 1.000 0.669

In neither analysis interval was the correlation close to 0.85 mentioned above.

Now, let’s look at cumulative returns. In the simplest approach, price returns can be used:

Interval S&P 500® SPY SSO VFH HYG
3 Years 59.9% 60.1% 151.6% 45.1% 10.7%
5 Years 28.8% 29.1% 31.5% 7.7% 0.0%

The SPY did a pretty good job tracking its underlying S&P 500® index — its price returns were actually slightly higher than those of the index in both analysis intervals.

However, to make things equal (with the exception of the index), total returns, which factor in the reinvestment of respective dividends, should be used. The following table shows the results:

Interval S&P 500® SPY SSO VFH HYG
3 Years N/A 69.6% 155.1% 52.8% 35.9%
5 Years N/A 43.1% 36.3% 19.0% 50.0%

The above data clearly demonstrate that even when correlations are close to one, as is the case with SPY and SSO to the S&P 500, returns of securities can be very different. Moreover, there the returns of HYG and VFH were quite different in both intervals. Hence, high correlations do not imply that “investments rise and fall at the same rate” or that they are “indistinguishable.”

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