Alternatives vs. Bonds
alternatives, correlation

In light of a recent downturn in bonds caused by a perception of the Fed’s upcoming actions, a Barron’s blog post and a Morningstar article explore alternative investments with “bond-like” returns. However, it turns out that these alternatives behave mostly like stocks with poor return-to-risk characteristics, and thus do not provide diversification to a broader portfolio.

To illustrate, here are correlations to stocks and Sharpe Ratios derived from Morningstar’s statistics for mutual funds and ETFs mentioned in the post and article:

Fund Ticker Category Beta StDev Correlation Sharpe Ratio
S&P 500® SPX Stock Index 1.00 13.56 1.00 1.32
IQ Merger Arbitrage ETF MNA Market Neutral 0.26 5.08 0.69 0.37
Merger MERFX Market Neutral 0.12 2.63 0.62 1.07
Robeco Boston Partners L/S Rsrch BPRRX Long/Short N/A N/A N/A N/A
IQ Alpha Hedge Strategy IQHOX Multialternative 0.31 6.54 0.64 0.36

These three-year statistics indicate a high positive correlation to stocks coupled with sub-par risk-adjusted returns. This observation is corroborated by a new study from the Leuthold Group cited in The Wall Street Journal article that states:

“From 1994 through May, it found that hedge-fund correlations have slowly been inching up to 0.75, almost 36% higher than earlier levels. Since a measure of 1.00 represents lock-step movements, hedge fund returns are generally following the tendencies of stocks about three-quarters of the time… Funds with correlations to stocks of 0.6 or less are prized by investors since they can significantly reduce portfolio volatility and limit risks over full-market cycles.”

In the past month or so, these alternative funds held their value well relative to bond investments. This is supported by their negative or low positive three-year correlations to iShares Core Total U.S. Bond Market ETF (AGG), as estimated by Alpholio™:

Fund Ticker Correlation
IQ Merger Arbitrage ETF MNA -0.30
Merger MERFX -0.24
IQ Alpha Hedge Strategy IQHOX 0.27

For reference, the correlation of SPDR® S&P 500® ETF (SPY) to AGG over the same period is -0.33. Therefore, these alternatives do not provide a significant amount of diversification to a balanced equity-and-bond portfolio, but could be marginally helpful if the portfolio contains only bonds. However, even in the latter case they could be a drag on the risk-adjusted performance of the portfolio: at 1.31, the Sharpe Ratio of SPY is higher than that of any of the above funds.

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Risk Disparity
correlation, risk parity

A couple of articles in InvestmentNews and The Wall Street Journal discuss the recent underperformance of risk parity funds. To recap what such funds do:

“Risk parity funds operate under the notion that the majority of risk in a portfolio comes from stocks. So instead of investing 60% of a portfolio in stocks, the funds lower the stock allocation and use leverage to boost the returns of the safer side of portfolio, e.g. bonds, to achieve the same returns with less risk.”

“Risk-parity funds use leverage to try to increase returns on bond investments so they more closely resemble returns of stocks. The basic idea of the strategy is that by equally distributing risks among stocks, bonds and commodities, the portfolio can weather huge price swings without sacrificing returns.”

The benchmark for these funds is typically a classic balanced portfolio of 60% stocks (e.g. represented by the S&P 500® index) and bonds (e.g. Barclays Capital Aggregate Bond Index). As indicated by a performance chart for one of the funds mentioned in the articles, AQR Risk Parity Fund (AQRIX), it is not easy to beat that benchmark even over a period of several years:

AQRIX Performance

Lately, risk-parity strategies underperformed:

“That is mostly because stocks have tumbled along with bonds after the Federal Reserve hinted at a reduction in its stimulus program last month. Making things worse, commodities and inflation-protected securities, which are widely used by risk-parity managers as a hedge against inflation, also suffered heavy losses because of receding inflationary expectations.”

To see why, let’s consider the long-term and short-term correlation coefficients between returns of stocks, bonds and commodities, represented by SPDR® S&P 500® ETF (SPY), iShares Core Total U.S. Bond Market ETF (AGG), and PowerShares DB Commodity Index Tracking Fund (DBC), and iShares TIPS Bond ETF (TIP):

Correlation 7 Years (Monthly) 1 Month (Daily)
SPY – AGG 0.09 0.63
SPY – DBC 0.60 0.66
AGG – DBC 0.04 0.48
SPY – TIP 0.21 0.45
AGG – TIP 0.75 0.89
DBC – TIP 0.38 0.32

The above figures clearly illustrate a significant increase in correlations between SPY and AGG, AGG and DBC, SPY and TIP, and AGG and TIP, in the last month. This explains losses suffered by risk parity strategies: stocks, bonds, and commodities all moved down in unison, and leverage exacerbated the bond downfall caused by rising interest rates. Thus, the basic premise of equalizing the risk contributed by uncorrelated components was broken, and risk parity turned to “risk disparity.”

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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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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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Musings on 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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