Analysis of John Hancock Multifactor ETFs
analysis, correlation, exchange-traded fund, factor investing, financial adviser, mutual fund

In September 2015, John Hancock Investments launched six strategic (smart) beta John Hancock Multifactor ETFs, with underlying indexes designed by Dimensional Fund Advisors LP (DFA). By now, the product suite has grown to a total of twelve ETFs, three “core” and nine “sector” ones.

Traditionally, DFA mutual funds were available only through advisors operating within the company’s program. With John Hancock Multifactor ETFs, retail investors can access DFA strategies without paying an advisory fee, which is typically 1% of assets under management (AUM). However, since DFA offers a large selection of mutual funds, it is not clear which of them can be replaced by the ETFs.

Let’s start with the John Hancock Multifactor Large Cap ETF (JHML). To identify the best candidates for substitution, we will use the correlation of rolling 52-week returns (conventionally, we would use rolling 36-month returns, but John Hancock ETFs have insufficient history). Although high correlations do not imply product identity, there are a good starting point for further analysis. Here are the correlations of DFA core and large-cap funds with JHML:

Correlations of DFA Large-Cap Funds with John Hancock Multifactor Large Cap ETF (JHML)

Of the candidate funds, the DFA US Large Cap Equity Portfolio (DUSQX) and DFA US Large Company Portfolio (DFUSX) had the highest correlation with JHML. Let’s see what total returns and traditional statistics looked like for the candidate funds and the ETF:

Total Return of DFA Large-Cap Funds and John Hancock Multifactor Large Cap ETF (JHML)

Indeed, the performance of DUSQX and DFUSX was similar to that of JHML, although the volatility of the ETF was slightly lower than that of the funds.

Next, let’s take a look at the John Hancock Multifactor Mid Cap ETF (JHMM). DFA does not offer an explicitly-named mid-cap fund, so we will try the core and small-cap funds. Here are their correlations with JHMM:

Correlations of DFA Core and Small-Cap Funds with John Hancock Multifactor Mid Cap ETF (JHMM)

Based on this criterion, the DFA US Core Equity 1 Portfolio (I) (DFEOX) and DFA US Core Equity 2 Portfolio (I) (DFQTX) were the best candidates for substitution.

Total Return of DFA Core Funds and John Hancock Multifactor Mid Cap ETF (JHMM)

The DFEOX tracked JMHH most closely, although at a lower annualized return and a slightly higher standard deviation.

Finally, let’s analyze the John Hancock Multifactor Developed International ETF (JHMD). This ETF was launched in mid-December 2016 and, as of this writing, does not have 52 weeks of history. Therefore, to determine its correlations with DFA International funds we will use a rolling 26-week period:

Correlations of DFA International Funds with John Hancock Multifactor Developed International ETF (JHMD)

The DFA International Core Equity Portfolio (I) (DFIEX) and DFA International Large Cap Growth Portfolio (DILRX) had the highest correlations with the ETF. The ETF most closely tracked the former fund:

Total Return of DFA International Funds and John Hancock Multifactor Developed International ETF (JHMD)

Although John Hancock Multifactor ETFs have a relatively short history, we have identified specific DFA mutual funds that these ETFs can effectively substitute. However, it should be noted that ETFs trade at market prices and not at net asset values (NAVs) as mutual funds do. Therefore, ETF premiums/discounts and spreads may negatively affect investors’ returns. Nevertheless, these ETFs are worth a consideration by those investors who like DFA’s multifactor strategies but do not want to pay recurring advisory fees to gain access to DFA mutual funds.

To learn more about the performance of John Hancock Multifactor sector ETFs, please register on our website.


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Analysis of Cambria ETFs (Part II)
analysis, exchange-traded fund

The previous post in this two-part series covered the three actively-managed products out of the five Cambria ETFs with a sufficiently long history. This post will focus on the remaining two index ETFs.

Let’s start with the analysis of the Cambria Foreign Shareholder Yield ETF (FYLD). According to the sponsor, the fund follows a proprietary index that

…consists of stocks with high cash distribution characteristics. The initial screening universe for this Index includes stocks in foreign developed countries with marketing capitalizations over $200 million. The Index is comprised of the 100 companies with the best combined rank of dividend payments and net stock buybacks, which are the key components of shareholder yield. The Index also screens for value and quality factors, including low financial leverage.

As in the case of actively-managed Cambria ETFs, the evaluation with begin in the first full calendar month since the fund’s inception and end in July 2016. Here is a chart with related statistics of the cumulative RealAlpha™ for the fund:

Cumulative RealAlpha™ for Cambria Foreign Shareholder Yield ETF (FYLD)

Similarly to its predecessors, the fund failed to outperform its reference ETF portfolio which had a slightly smaller volatility, measured as the standard deviation of monthly returns. The fund’s RealBeta™ was moderately higher than that of a broad-based domestic equity ETF.

The following chart and corresponding statistics show the constant composition of the reference ETF portfolio for the fund over the same period:

Reference Weights for Cambria Foreign Shareholder Yield ETF (FYLD)

The fund had major equivalent positions in the Schwab International Small-Cap Equity ETF (SCHC), WisdomTree International SmallCap Dividend Fund (DLS), First Trust Dow Jones Global Select Dividend Index Fund (FGD), iShares MSCI United Kingdom ETF (EWU), PowerShares DWA Industrials Momentum Portfolio (PRN), and Vanguard FTSE Europe ETF (VGK). The Other component in the chart collectively represents additional five foreign-stock ETFs covering the New Zealand, Japan, Australia, Spain and Mexico markets. The reference weights indicate a significant foreign small-cap equity tilt of the fund.

Lastly, we will evaluate the Cambria Global Value ETF (GVAL). The issuer states that this product implements a proprietary index which

…consists of stocks with strong value characteristics. The Index begins with a universe of 45 countries located in developed and emerging markets. […] The Index next separates the top 25% of these countries as measured by Cambria’s proprietary long term valuation metrics. The Index then screens stocks with market capitalizations over $200 million. The Index is comprised of approximately 100 companies.

The following chart and associated statistics depict the cumulative RealAlpha™ for the fund:

Cumulative RealAlpha™ for Cambria Global Value ETF (GVAL)

Compared to its reference ETF portfolio, the fund added a modest amount of value (mostly in the last four months of the analysis period), although the portfolio had a slightly lower volatility. The RealBeta™ of the fund was substantially higher than that of a broad-based U.S. stock ETF.

The following chart and statistics demonstrate the fixed membership and weights of the reference ETF portfolio for the fund:

Reference Weights for Cambria Global Value ETF (GVAL)

The fund had main equivalent positions in the iShares MSCI Italy Capped ETF (EWI), WisdomTree Europe SmallCap Dividend Fund (DFE), Guggenheim CurrencyShares® Euro Trust (FXE), iShares MSCI Poland Capped ETF (EPOL), iShares Latin America 40 ETF (ILF), and Global X MSCI Greece ETF (GREK). The remaining six ETFs in the above table, spanning the Spain, Brazil and Germany equities as well as international-corporate and emerging-markets bonds, collectively constitute the Other item in the above chart.

Conclusion

One of our previous posts outlined the benefits of similar analyses of iShares smart beta ETFs, which we will not repeat here for brevity. This evaluation of Cambria ETFs provides investors with similar insights.

Just like any other composite investment vehicles, Cambria ETFs change their holdings over time. Therefore, a question arises about the value of an analysis in which a static ETF portfolio is calculated from long-term data. The answer is to use a more advanced variant of Alpholio™ patented methodology, in which the membership of the reference ETF portfolio is still fixed but weights can fluctuate. Such a dynamic portfolio tends to more accurately track the analyzed fund over time.

For example, here is a chart with accompanying statistics of a reference ETF portfolio determined in that manner for the Cambria Shareholder Yield ETF (SYLD):

Reference Weights for Cambria Shareholder Yield ETF (SYLD) - Fine Fit

This gives a more accurate view of the fund’s recent average exposures.

If you would like to use our ETP Analysis Service to investigate similar products, please register on our website.


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Analysis of Cambria ETFs (Part I)
active management, analysis, exchange-traded fund

Cambria currently offers eight ETFs. Of those, five have a history longer than twelve calendar months, which is a minimum Alpholio™ requires to conduct an initial analysis. Of these remaining five products, three are actively-managed and two follow proprietary Cambria indices. This post, the first in a two-part series, focuses on the actively-managed Cambria ETFs. The second part will cover index-based funds.

We will evaluate each fund from the first full month since its inception through July 2016 using the simplest variant of the Alpholio™ patented methodology. This approach constructs a reference ETF portfolio with both fixed membership and weights that most closely tracks the returns of the analyzed fund. In essence, the reference ETF portfolio embodies average core exposures of the analyzed fund to various factors, indices and strategies over the analysis period. Since it constitutes a potential static substitute for the analyzed fund, i.e. it is an investment alternative, it also serves as a relevant performance benchmark for the fund. (Unlike with pure indices that are not investable, this real benchmark accounts for actual implementation costs.)

Let’s start with the oldest product, the Cambria Shareholder Yield ETF (SYLD). According to the firm, this actively-managed fund

…invests in 100 [U.S. listed] stocks with market caps greater than $200 million that rank among the highest in (a) paying cash dividends, (b) engaging in net share repurchases, and (c) paying down debt on their balance sheets.

Here is the resulting chart with statistics of the cumulative RealAlpha™ for the fund (to learn more about this and other performance measures, please visit our FAQ):

Cumulative RealAlpha™ for Cambria Shareholder Yield ETF (SYLD)

The fund did not not add value when compared to a reference ETF portfolio, which had a slightly lower volatility. The RealBeta™ of the fund was slightly higher than that of a broad-based domestic equity ETF.

The following chart with related statistics shows the constant composition of the reference ETF portfolio for the fund over the same evaluation period:

Reference Weights for Cambria Shareholder Yield ETF (SYLD)

The fund had major equivalent positions in the PowerShares BuyBack Achievers Portfolio (PKW; an index-based ETF), WisdomTree MidCap Dividend Fund (DON), Guggenheim S&P 500® Equal Weight Technology ETF (RYT), FlexShares Quality Dividend Index Fund (QDF), PowerShares Dynamic Market Portfolio (PWC), and First Trust Large Cap Value AlphaDEX® Fund (FTA). The Other component in the chart collectively represents additional six ETFs with smaller weights, listed in the above table.

It should be noted that one of the well-known investment analytics firms classifies SYLD into the mid-cap value category. While this may be based on the assessment of the fund’s individual holdings, our analysis shows that the fund had primarily large-cap exposures. As a matter of fact, the fund’s prospectus states that

Although the Fund generally expects to invest in companies with larger market capitalizations, the Fund may invest in small- and mid-capitalization companies.

Next, we will analyze the Cambria Global Momentum ETF (GMOM). According to its issuer, the fund

…intends to target investing in the top 33% of a target universe of approximately 50 ETFs based on measures of trailing momentum and trend. The portfolio begins with a universe of assets consisting of domestic and foreign stocks, bonds, real estate, commodities and currencies.

The following chart with corresponding statistics illustrates the cumulative RealAlpha™ for the fund:

Cumulative RealAlpha™ for Cambria Global Momentum ETF (GMOM)

This fund also failed to add value compared to its reference ETF portfolio of a somewhat lower volatility. However, its RealBeta™ was only about one-third that of the broad-based stock market.

The following chart with associated statistics depicts the fixed composition of the reference ETF portfolio for the fund over the same analysis period:

Reference Weights for Cambria Global Momentum ETF (GMOM)

The fund had major equivalent positions in the PowerShares Build America Bond Portfolio (BAB; an index-based ETF), SPDR® Nuveen S&P High Yield Municipal Bond ETF (HYMB), iShares Edge MSCI USA Quality Factor ETF (QUAL), iShares U.S. Utilities ETF (IDU), PowerShares Dynamic Food & Beverage Portfolio (PBJ), and iShares Global Healthcare ETF (IXJ). As in the previous analysis, the Other item in the chart collectively represents additional six ETFs with smaller weights, listed in the above table.

Finally, we will examine the Cambria Global Asset Allocation ETF (GAA). According to its issuer, the fund

…targets investing in approximately 29 ETFs that reflect the global universe of assets consisting of domestic and foreign stocks, bonds, real estate, commodities and currencies.

The following chart with accompanying statistics demonstrates the cumulative RealAlpha™ for the fund:

Cumulative RealAlpha™ for Cambria Global Asset Allocation ETF (GAA)

The fund moderately underperformed its reference ETF portfolio that had a slightly smaller standard deviation. The RealBeta™ of the fund was approximately the same as that of a traditional 60% stock / 40% bonds balanced portfolio.

The following chart and statistics show the composition of the reference ETF portfolio for the fund over the same period:

Reference Weights for Cambria Global Asset Allocation ETF (GAA)

The fund had major equivalent positions in the iShares MSCI Kokusai ETF (TOK), PowerShares DB Commodity Index Tracking Fund (DBC), FlexShares iBoxx 5-Year Target Duration TIPS Index Fund (TDTF), iShares U.S. Real Estate ETF (IYR), VanEck Vectors Emerging Markets High Yield Bond ETF (HYEM), and SPDR® Barclays Investment Grade Floating Rate ETF (FLRN). The remaining ETFs in the above table constitute the Other element in the chart.

It has to be noted that GMOM and GAA are relatively new products with only about 18 months of available history as of this writing. Typically, Alpholio™ uses at least 36 months of data for a more accurate analysis, which was the case with SYLD.

The second part of this series will review the Cambria Foreign Shareholder Yield ETF (FYLD) and the Cambria Global Value ETF (GVAL).

If you would like to use our ETP Analysis Service to examine similar products, please register on our website.


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Do iShares Smart Beta ETFs Outperform? (Part II)
analysis, exchange-traded fund, factor investing

In the first part of this post, we analyzed a couple of iShares smart beta ETFs, the iShares Edge MSCI USA Size Factor ETF (SIZE) and the iShares Edge MSCI USA Value Factor ETF (VLUE).

Let’s start the second part with the evaluation of the iShares Edge MSCI USA Momentum Factor ETF (MTUM). Its issuer states that this ETF generates

Exposure to large- and mid-cap U.S. stocks exhibiting relatively higher price momentum

As before, the analysis will start in the first full month of the ETF’s existence and end in July 2016. Here is the cumulative RealAlpha™ chart with related statistics for the ETF:

Cumulative RealAlpha™ for iShares Edge MSCI USA Momentum Factor ETF (MTUM)

The ETF produced a return comparable to that of its reference portfolio, which had a lower volatility. The RealBeta™ of the ETF was considerably below than that of a broad-based equity market ETF.

The following chart and associated statistics show the constant composition of the reference ETF portfolio for the iShares Edge MSCI USA Momentum Factor ETF:

Reference Weights for iShares Edge MSCI USA Momentum Factor ETF (MTUM)

The ETF had major equivalent positions in the Consumer Staples Select Sector SPDR® Fund (XLP), First Trust Large Cap Growth AlphaDEX® Fund (FTC), Health Care Select Sector SPDR® Fund (XLV), PowerShares Dynamic Large Cap Growth Portfolio (PWB), First Trust Dow Jones Internet Index Fund (FDN), and PowerShares NASDAQ Internet Portfolio (PNQI). (The Other component in the chart collectively represents additional two ETFs with smaller weights.)

Not surpringly, the ETF had a strong tilt toward large-cap growth stocks, especially in the consumer staples and healthcare sectors, as well as the Internet industry. Unlike with the previous iShares smart beta ETFs, no single position was clearly dominant in its reference portfolio. It can also be reasonably expected that in the future, the ETF’s exposure to specific sectors and industries will change along with price momentum shifts. Therefore, for a further performance comparison, a similar smart beta equivalent position should be chosen.

Over the same analysis period, MTUM outperformed FTC and PWB in terms of the annualized return and Sortino ratio, and had an equal or higher Sharpe ratio:

Total Return of iShares Edge MSCI USA Momentum Factor ETF (MTUM), First Trust Large Cap Growth AlphaDEX® Fund (FTC) and PowerShares Dynamic Large Cap Growth Portfolio (PWB)

At 0.15%, the expense ratio of MTUM was much lower than the 0.62% of FTC and 0.57% of PWB, which improved relative returns of MTUM. The average correlation between rolling 24-month returns was 0.95 and 0.96 for MTUM with FTC and MTUM with PWB, respectively.

Finally, we will evaluate the iShares Edge MSCI USA Quality Factor ETF (QUAL). According to the issuer, this ETF produces

Exposure to large- and mid-cap U.S. stocks exhibiting positive fundamentals (high return on equity, stable year-over-year earnings growth and low financial leverage)

Since QUAL’s inception date was in July 2013, the analysis begins in August 2013. Here is a chart with accompanying statistics of the cumulative RealAlpha™ for the ETF:

Cumulative RealAlpha™ for iShares Edge MSCI USA Quality Factor ETF (QUAL)

The ETF moderately outperformed its reference portfolio, which had a slightly higher volatility. The ETF’s RealBeta™ was lower than that of a broad-based equity market ETF.

The following chart with accompanying statistics depicts the composition of the reference portfolio for the iShares Edge MSCI USA Quality Factor ETF:

Reference Weights for iShares Edge MSCI USA Quality Factor ETF (QUAL)

The ETF had major equivalent positions in the iShares Russell Top 200 Growth ETF (IWY), SPDR® Dow Jones® Industrial Average ETF (DIA), PowerShares S&P 500 Quality Portfolio (SPHQ), Vanguard Dividend Appreciation ETF (VIG), PowerShares NASDAQ Internet Portfolio (PNQI), and iShares U.S. Energy ETF (IYE). Clearly, this ETF had a strong tilt toward mega-cap stocks, especially of the growth classification.

Over the same analysis period, QUAL had a significantly lower return as well as slightly smaller Sharpe and Sortino ratios than those of IWY:

Total Return of iShares Edge MSCI USA Quality Factor ETF (QUAL) and iShares Russell Top 200 Growth ETF (IWY)

The average correlation between rolling 24-month returns of the two ETFs was 0.98.

Conclusion

The above analyses uncovered reference portfolios for select iShares smart beta ETFs. While a wholesale substitution of an ETF with its multi-member reference portfolio may not always be practical, each of these portfolios

  • Built a foundation for assessment of the true risk-adjusted performance of a smart beta ETF.
  • Captured exposures of a smart beta ETF to various stock market styles, sectors and industries (paradoxically, these are exposures of the analyzed factor ETF to various other factors). This may help investors avoid an undesirable overlap with other positions in their overall investment portfolios.
  • Identified a predominant exposure of a smart beta ETF to a single factor. This may help investors substitute a smart beta ETF with another product that implements a traditional market-cap index or with a similar strategic beta strategy.

If you would like to use the ETP Analysis Service to examine other smart beta products, please register on our website.


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Do iShares Smart Beta ETFs Outperform? (Part I)
analysis, exchange-traded fund, factor investing

To better demonstrate the new Alpholio™ ETP Analysis Service in action, let’s analyze several of the iShares smart beta ETFs. The oldest of these products were introduced in mid-April 2013, so by now more than three years of performance data are available. According to their issuer

Smart beta ETFs can help investors achieve goals like reducing risk, generating income, or potentially enhancing returns. These funds primarily focus on factors – broad, persistent drivers of returns across equities and other asset classes. New technologies have made it easier to target factor exposures, which investors can access with iShares Edge ETFs.

Due to the scope of analysis, this post will be divided into two parts. We will start with the iShares Edge MSCI USA Size Factor ETF (SIZE). According to its issuer, this ETF provides

Exposure to large- and mid-cap U.S. stocks with a tilt towards the smaller, lower risk stocks within that universe

Here is a chart with related statistics of the cumulative RealAlpha™ for this ETF from May 2013 (the first full month of returns since its inception) through July 2016:

Cumulative RealAlpha™ for iShares Edge MSCI USA Size Factor ETF (SIZE)

The ETF returned effectively as much as its reference ETF portfolio that had a slightly lower volatility. The ETF’s RealBeta™, measured against a broad-based US equity index ETF, was close to one.

The following chart shows the constant composition of the reference ETF portfolio for the iShares Edge MSCI USA Size Factor ETF:

Reference Weights for iShares Edge MSCI USA Size Factor ETF (SIZE)

The ETF had equivalent positions in the SPDR Russell 3000® ETF (THRK), SPDR® Dow Jones® REIT ETF (RWR), SPDR® S&P® Insurance ETF (KIE), iShares U.S. Medical Devices ETF (IHI), IQ Hedge Multi-Strategy Tracker ETF (QAI), and Utilities Select Sector SPDR® Fund (XLU).

Over the same analysis period, SIZE outperformed THRK, the dominant position in its reference portfolio, in terms of a slightly larger annualized return, as well as higher Sharpe and Sortino ratios:

Total Return of iShares Edge MSCI USA Size Factor ETF (SIZE) and SPDR Russell 3000® ETF (THRK)

The average correlation between rolling 24-month returns of the two ETFs was 0.96.

The second smart beta ETF we will evaluate is the iShares Edge MSCI USA Value Factor ETF (VLUE). According to the issuer, this ETF supplies

Exposure to large- and mid-cap U.S. stocks with lower valuations based on fundamentals

Here is a chart with related statistics of the cumulative RealAlpha™ for this ETF:

Cumulative RealAlpha™ for iShares Edge MSCI USA Value Factor ETF (VLUE)

Since late 2014, the ETF failed to add value over its reference portfolio that had a slightly lower volatility. The ETF’s RealBeta™ was higher than that of a broad-based stock market ETF.

The following chart shows the fixed reference ETF portfolio for the iShares Edge MSCI USA Value Factor ETF:

Reference Weights for iShares Edge MSCI USA Value Factor ETF (VLUE)

The ETF had major equivalent positions in the SPDR® S&P® 500 Value ETF (SPYV), SPDR® Morgan Stanley Technology ETF (MTK), iShares U.S. Broker-Dealers & Securities Exchanges ETF (IAI), First Trust Large Cap Value AlphaDEX® Fund (FTA), iShares U.S. Healthcare Providers ETF (IHF), and iShares Transportation Average ETF (IYT). The Other component in the chart collectively represents two additional ETFs with smaller weights.

Although VLUE had a slightly higher annualized return than SPYV (the prevailing ETF in its reference portfolio), it underperformed SPYV in terms of both Sharpe and Sortino ratios:

Total Return of iShares Edge MSCI USA Value Factor ETF (VLUE) and SPDR® S&P® 500 Value ETF (SPYV)

The average correlation between rolling 24-month returns of the two ETFs was 0.98.

The second part of this post will cover two other iShares smart beta ETFs, the iShares Edge MSCI USA Momentum Factor ETF (MTUM) and iShares Edge MSCI USA Quality Factor ETF (QUAL).


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Introducing ETP Analysis Service
active management, analysis, exchange-traded fund, exchange-traded product, portfolio

Alpholio™ has recently added the ETP Analysis Service to its platform. The exchange-traded product (ETP) is an exchange-traded fund (ETF), exchange-traded note (ETN), NextShares ETMF®, or other exchange-traded financial instrument.

The main motivation behind the new service is the availability of ETPs that do not track market-cap weighted indices. In particular, this includes “smart beta” (a.k.a. “strategic beta“) strategies that blend active and passive management. Due to the former aspect, smart-beta ETPs resemble traditional actively-managed mutual funds. Consequently, they can be analyzed with Alpholio™’s patented methodology, which constructs a custom reference portfolio of ETFs for each analyzed fund.

This leads to an apparent paradox: an analyzed ETP (which may be an ETF) is to be replicated by a portfolio of ETFs. Why do this at all? Just as with a traditional mutual fund, for several main reasons:

  • To determine whether active management aspect of the ETP adds value on a truly risk-adjusted basis
  • To understand the exposure of the analyzed ETP to various factors. This helps eliminate excessive exposures in the overall investment portfolio.
  • To replicate the ETP’s performance with other ETFs that may have preferable characteristics, such as lower fees, smaller trading premia or spreads, accessibility, etc. Conversely, to simplify a portfolio by substituting multiple ETFs with a single ETP.
  • To discern periods of underperformance and outperformance of the ETP after adjustment for its exposures.

Let’s demonstrate the new ETP Analysis Service in action. First, we will analyze the PowerShares FTSE RAFI US 1000 Portfolio (PRF). This ETP tracks the FTSE RAFI US 1000 Index, which

…is designed to track the performance of the largest US equities, selected based on the following four fundamental measures of firm size: book value, cash flow, sales and dividends. The 1,000 equities with the highest fundamental strength are weighted by their fundamental scores.

To conduct the analysis, we will use the simplest variant of Alpholio™’s methodology, which builds a reference ETF portfolio with both fixed membership and weights. The following chart and related statistics show the cumulative RealAlpha™ for the ETP (to learn more about this and other performance measures, please visit our FAQ):

Cumulative RealAlpha™ for PowerShares FTSE RAFI US 1000 Portfolio (PRF)

Over the five years through July 2016, the ETP added a small amount of value vs. its reference ETF portfolio of comparable volatility. The RealBeta™ of the ETF was the same as that of a broad-based equity market ETF.

The following chart with accompanying statistics presents the fixed composition of the reference ETF portfolio for the analyzed ETP:

Reference Weights for PowerShares FTSE RAFI US 1000 Portfolio (PRF)

The ETP had major equivalent positions in the iShares Russell 1000 Value ETF (IWD), Vanguard Value ETF (VTV), iShares Core S&P Total U.S. Stock Market ETF (ITOT), SPDR® S&P® 500 Value ETF (SPYV), PowerShares BuyBack Achievers Portfolio (PKW), and Guggenheim S&P 500® Pure Value ETF (RPV). Clearly, this ETP had a very strong exposure to the large-cap value factors represented by reference ETFs. (The Other component in the chart collectively depicts additional six ETFs with smaller weights, some of which were effectively zero.)

In the second example, let’s analyze the Guggenheim S&P 500® Equal Weight ETF (RSP). This ETP

Seeks to replicate as closely as possible the performance of the S&P 500 Equal Weight Index, before fees and expenses, on a daily basis.

Here is the chart with related statistics of the cumulative RealAlpha™ for this ETP:

Cumulative RealAlpha™ for Guggenheim S&P 500® Equal Weight ETF (RSP)

Over the five years through July 2016, this ETP also added little value vs. its reference ETF portfolio. Its RealBeta™ was above that of a broad-based stock market ETF.

The final chart and statistics show the static composition of the reference ETF portfolio for the ETP:

Reference Weights for Guggenheim S&P 500® Equal Weight ETF (RSP)

The ETP had major equivalent positions in the First Trust Large Cap Core AlphaDEX® Fund (FEX), iShares Russell Mid-Cap Value ETF (IWS), PowerShares S&P 500 Quality Portfolio (SPHQ), PowerShares S&P 500® High Beta Portfolio (SPHB), iShares Russell Mid-Cap Growth ETF (IWP), and Consumer Discretionary Select Sector SPDR® Fund (XLY). The Other component in the chart collectively represents additional six ETFs with smaller constant weights, one of which was effectively zero.

As could be expected, due to equal-weighting of its positions this large-cap ETP had a significant tilt toward mid-cap stocks, especially of value characteristics. In addition, the ETP had considerable exposure to economic sectors such as consumer discretionary, financials, technology, and industrials.

If you would like to take advantage of the new ETP Analysis Service, please register on our website.


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Substituting Liquid Alternative Funds
alternatives, analysis, asset allocation, exchange-traded fund, hedge fund, mutual fund, portfolio

A recent cover story in Barron’s features liquid alternative funds from AQR. According to the article

The liquid-alt pitch is that individuals can access the same types of investments as university endowments and other big institutions, to diversify equity-heavy portfolios, typically with a 10% to 20% allocation to liquid alts… The advantage of the [AQR Managed Futures] strategy […] is that it is uncorrelated with other asset classes, and “has the most consistently strong performance in equity bear markets.” That is when diversification matters most, as was the case in the third quarter of last year and the early part of this year.

Ideally, returns of a liquid-alt fund should not only be uncorrelated with those of both stocks and bonds but also significantly positive over a long evaluation period. Let’s take a look at the performance of three AQR funds with a sufficiently long history.

The following chart shows rolling return correlation of the AQR Managed Futures Strategy Fund (AQMIX) with the Vanguard Total Stock Market ETF (VTI) and the Vanguard Total Bond Market ETF (BND):

Correlation of Rolling 36 Monthly Returns for VTI and BND with AQMIX

Please note that AQMIX had the first full month of returns in February 2010. Consequently, the first rolling 36-month return became available at the end of January 2013. As could be expected, the fund had lower correlation to stocks than to fixed income, although both coefficients were quite low (generally, correlation below 0.6 provides diversification benefits).

Here is a similar chart with related statistics for the AQR Multi-Strategy Alternative Fund (ASAIX):

Correlation of Rolling 36 Monthly Returns for VTI and BND with ASAIX

Compared to AQMIX, this strategy had a higher correlation to bonds.

Here is a similar chart with statistics for the AQR Diversified Arbitrage Fund (ADAIX):

Correlation of Rolling 36 Monthly Returns for VTI and BND with ADAIX

In contrast to AQMIX and ASAIX, this strategy had a higher correlation to equities than bonds; however, both coefficients were still pretty low.

The problem with any of these strategies is the lack of accessibility for most individual investors:

AQR’s approach can be hard to understand. Because of this—and to deter hot money—the firm sells its liquid-alt funds almost entirely through financial advisors. Retail buyers can access the funds directly through fund supermarkets like Fidelity, but direct investments involve a minimum of $1 million. Investments through advisors and 401(k) plans have no minimum.

Is there a way to substitute these liquid-alt funds with readily available ETFs? Let’s explore this possibility using Alpholio™’s patent-based analysis service for mutual funds. One variant of this methodology constructs a reference portfolio of ETFs with fixed both membership and weights. Here is the resulting cumulative RealAlpha™ chart for the AQR Managed Futures Strategy Fund (to learn more about this and other performance measures, please visit our FAQ):

Cumulative RealAlpha™ and Statistics for AQR Managed Futures Strategy Fund (AQMIX)

As the statistics section below the chart shows, since its inception the fund had a smaller return and a much higher volatility (measured by standard deviation) than those of the reference portfolio. The following chart illustrates the constant composition of the reference ETF portfolio in this analysis:

Reference Weights for AQR Managed Futures Strategy Fund (AQMIX)

The major positions in the reference portfolio were the PowerShares DB US Dollar Index Bullish Fund (UUP; fixed weight of 38.1%), iShares 20+ Year Treasury Bond ETF (TLT; 22.9%), iShares MSCI Netherlands ETF (EWN; 9.3%), Guggenheim CurrencyShares® Swiss Franc Trust (FXF; 6.0%), Consumer Staples Select Sector SPDR® Fund (XLP; 5.5%), and Utilities Select Sector SPDR® Fund (XLU; 4.7%). The Other component in the chart collectively represents addition five ETFs with smaller fixed weights.

The return correlation of the reference ETF portfolio over the entire evaluation period was 0.16 with VTI and 0.58 with BND. Given that these figures for AQMIX were approximately -0.07 and 0.21, respectively, the reference portfolio was not as good a diversifier for stocks and bonds as the fund was. However, the reference portfolio only had long positions in non-leveraged ETFs. It also returned about 8% more than the fund on a cumulative basis and with a 59% lower volatility. Similar analyses can be conducted for ASAIX and ADAIX. In the end, it is up to the investor to weigh the pros and cons of using reference ETF portfolios as substitutes for these funds in the context of the overall portfolio.

We hope that our Investment Toolkit™ will provide useful services for investors who want to construct well-diversified portfolios. If you would like to use it, please register on our website.


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Equal-Weighting S&P 500
app, asset allocation, exchange-traded fund, market, portfolio

The popular market-proxy S&P 500® index is market-cap weighted. This is one of the factors that helps reduce the turnover of ETFs tracking this index. For example, the iShares Core S&P 500 ETF (IVV) has a turnover rate of only 4%. The following chart, produced by the Alpholio™ App for Android, shows the characteristics of a portfolio composed solely of this ETF:

Portfolio 100% iShares Core S&P 500 ETF (IVV)

(Note that Alpholio™ uses a broader ETF as a representation of “the market”; hence, the beta of IVV is different from the conventional one and alpha from zero.)

However, market-cap weighting implies that the largest companies’ stocks have the highest impact on the index. While returns of mega-caps in the index tend to be less volatile, they are usually lower than those of their smaller-cap peers. To overcome this limitation, other ETFs weight equities in the index differently. For example, the Guggenheim S&P 500™ Equal Weight ETF (RSP) assigns each of the 500 stocks a 0.2% weight. This tilts RSP toward smaller-cap equities in the index and results in a 18% turnover. Over the same analysis period, RSP produced markedly higher returns than IVV but at the expense of an elevated volatility and a slightly lower Sharpe ratio:

Portfolio 100% Guggenheim S&P 500® Equal Weight ETF (RSP)

In addition to overweighting of mega-caps, some economic sectors in the index dominate others, as shown in the latest edition of S&P Capital IQ The Outlook:

Sector Weight %
Consumer Discretionary 12.7
Consumer Staples 9.4
Energy 7.8
Financials 16.5
Health Care 15.3
Industrials 10.2
Information Technology 19.9
Materials 3.2
Telecommunication Services 2.2
Utilities 2.9

To counteract this, the ALPS Equal Sector Weight ETF (EQL) applies the same weight to nine sectors (with telecommunication services considered part of information technology). Here are the characteristics of a portfolio consisting solely of this ETF over the identical analysis period:

Portfolio 100% ALPS Equal Sector Weight ETF (EQL)

While the annualized return of EQL was lower than than of IVV or RSP, it was more than adequately offset by a decrease in volatility, which resulted in an improved Sharpe ratio and maximum drawdown.

What if the investor wanted to equal-weight all ten sectors instead of just nine, i.e. keep telecoms separate from IT? To do so, the investor could construct a portfolio of Vanguard sector ETFs, excluding the Vanguard REIT ETF (VNQ). That is because real estate stocks are currently part of the financials sector and not expected to become a separate asset class until mid-2016. Here is how such a portfolio, rebalanced quarterly (just like EQL), performed over the same analysis period:

Portfolio Vanguard Sector (VCR, VDC, VDE, VFH, VHT, VIS, VGT, VAW, VOX, VPU)

The Vanguard sector portfolio had the second highest alpha and Sharpe ratio as well as the second lowest standard deviation (a measure of volatility of returns).

The above analysis period was dictated by the inception date of the EQL, the youngest of all the ETFs used. Arguably, this approximately six-year period may be considered too short and not representative of performance over a full economic cycle. However, it was interesting to see that while equal-weighting the index on a security level produced highest absolute returns, equal-weighting on a sector-level delivered the highest risk-adjusted returns.

To conduct your own analyses of various ETF portfolios, download the Alpholio™ app from

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Growth vs. Value
analysis, app, asset allocation, exchange-traded fund, factor investing

In one of the previous posts, Alpholio™ made the case for increasing the mid-cap stock holdings in the portfolio. As promised, in this follow-on post, we will examine the performance of growth vs. value equities.

A recent article on this topic in The Wall Street Journal states that

Over the past year, the average U.S. large-cap growth fund has risen 18.2%, while the average U.S. large-cap value fund is up 10.4%… from 2003 through 2013, the average gap between the two styles of stock-picking for large-cap stocks was 0.75 percentage point… it’s a similar story among small-company stocks, where growth-stock funds […] are up 16% over the past year. Funds investing in small-cap value stocks […] are up 7.7%.

The trend of growth equities outperforming value equities is hardly a past-year phenomenon. Contrary to what might be expected, this trend is also not confined to the last seven years since the market’s trough during the financial crisis. The trend is best examined using specific ETFs as opposed to hypothetical and unspecified “average U.S. [mutual] funds.”

To start with, let’s use the Total Return service of the Alpholio™ App for Android to review the long-term performance of a couple of long-lived large-cap ETFs, the iShares S&P 500 Growth ETF (IVW) and iShares S&P 500 Value ETF (IVE), from their inception through March 2015, using monthly total returns:

Total Return of iShares S&P 500 Growth ETF (IVW) and iShares S&P 500 Value ETF (IVE) from 2000 to 2015

In that period, the large-cap value ETF handily outperformed its growth counterpart, albeit with a slightly higher standard deviation (a measure of volatility of returns). However, this only paints a part of the picture: in 2000, growth stocks significantly underperformed, following the deflation of the dot-com bubble. If the start of the analysis period is advanced to the beginning of 2001, growth slightly outperformed value:

Total Return of iShares S&P 500 Growth ETF (IVW) and iShares S&P 500 Value ETF (IVE) from 2001 to 2015

Through the market peak in October 2007, growth stocks did not advance as much as value ones did, but they suffered a much smaller drawdown (45.4% for growth vs. 56.7% for value, as calculated by the Portfolio service).

The growth outperformance becomes even more pronounced when the beginning of the analysis is moved to April 2005 for a 10-year evaluation period:

Total Return of iShares S&P 500 Growth ETF (IVW) and iShares S&P 500 Value ETF (IVE) from 2005 to 2015

Large-cap growth stocks returned about 2% more than their value counterparts, and did so with much smaller volatility. As shown by the Rolling Returns service, in the same period growth outperformed value in about 90% of all rolling 36-month intervals, 67% of 24-month intervals, and 63% of 12-month intervals:

Rolling Returns of iShares S&P 500 Growth ETF (IVW) and iShares S&P 500 Value ETF (IVE) from 2005 to 2015

The median difference of rolling 12-month returns over the last 10 years was over 2.6% in favor of growth.

For mid-cap stocks, let’s use the iShares S&P Mid-Cap 400 Growth ETF (IJK) and iShares S&P Mid-Cap 400 Value ETF (IJJ). As with large-caps, the 10-year performance of growth mid-caps was better than that of their value peers:

Total Return of iShares S&P Mid-Cap 400 Growth ETF (IJK) and iShares S&P Mid-Cap 400 Value ETF (IJJ) from 2005 to 2015

Finally, a similar chart for the iShares S&P Small-Cap 600 Growth ETF (IJT) and iShares S&P Small-Cap 600 Value ETF (IJS) also demonstrates the growth superiority over value:

Total Return of iShares S&P Small-Cap 600 Growth ETF (IJT) and iShares S&P Small-Cap 600 Value ETF (IJS) from 2005 to 2015

It is worth noting that the outperformance of growth stocks over value ones in this analysis period appears to directly contradict the value effect in the classic three-factor model. However, the latest research from Fama-French indicates that this factor is less important in the presence of the beta, size, profitability and investment factors.

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© 2015 Envarix Systems Inc. All Rights Reserved.

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A Case for Mid-Cap Stocks
analysis, asset allocation, exchange-traded fund, portfolio

In a traditional portfolio, mid-cap and small-cap equities receive much smaller weights than large-caps. For example, the most recent moderate asset allocation model portfolio recommended by the S&P Capital IQ Investment Policy Committee (see in the November 24, 2014 edition of the S&P The Outlook), consists of the following allocations:

  • 50% to U.S. equities
  • 15% to foreign equities
  • 25% to bonds
  • 10% to cash

To achieve the model allocation, the committee recommends specific ETFs for the 50% U.S. equity part of the portfolio:

Therefore, the mid-cap and small-cap stocks collectively account for only 20% of domestic equities in the portfolio. Is such a low allocation justified by historical performance of these asset classes? Let’s take a look using the Portfolio Service of the Alpholio™ App for Android.

The longest analysis time frame is determined by the existence of IJR, whose first full monthly return was in June 2000 (SPY’s first monthly return was in February 1993, and MDY’s in June 1995). Here are the statistics of a portfolio solely composed of SPY in a period from that month through 2014:

SPY Performance from 2000 to 2014

Similarly, for MDY:

MDY Performance from 2000 to 2014

And for IJR:

IJR Performance from 2000 to 2014

The mid-cap (MDY) and small-cap (IJR) ETFs had annualized returns more than twice that of the large-cap ETF (SPY). The Sharpe ratios of MDY and IJR were also approximately twice that of SPY. While IJR outperformed MDY in terms of the annualized return, alpha and Sharpe ratio (just slightly), it also had the highest standard deviation (volatility), maximum drawdown and beta of all three ETFs. Therefore, the mid-cap ETF appears to be a decent compromise between risk and reward.

For the 10-year period through 2014, the statistics are as follows:

ETF Annualized Return Standard Deviation Alpha* Beta* Sharpe Ratio Max. Drawdown
SPY 7.61% 14.66% -0.02% 0.96 0.48 50.8%
MDY 9.42% 17.66% 0.05% 1.12 0.52 49.7%
IJR 8.96% 18.91% -0.01% 1.16 0.48 51.8%

* In this analysis period, alpha and beta are measured against a broader market index, represented by the Vanguard Total Stock Market ETF (VTI).

In the evaluation period, MDY clearly outperformed its peers by generating the highest annualized return, alpha and Sharpe ratio, while having the lowest maximum drawdown.

Another service offered by the Alpholio™ App for Android is the Rolling Returns analysis. In the 10-year period through 2014, SPY returned more than VTI in about 9.4% of all rolling 36-month periods (a rolling period of 36 months aims to approximate the average holding time of the ETF in an investment portfolio):

SPY vs. VTI Rolling Returns from 2005 to 2014

However, in the same period, MDY outperformed VTI in about 75.3% and IJR in 70.6% of all rolling 36-month periods. Based on this simple measure (it does not take risk into account), MDY again demonstrated a superior performance.

While past performance is not a guarantee of future results, this analysis indicates that mid-cap equities may deserve a higher allocation even in a moderate-risk portfolio. A follow-on post will examine the characteristics of growth vs. value equities, also using services of the Alpholio™ App for Android. The app is available at:

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