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Can Smart Beta think?

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The concept of Smart Beta introduced by the principles of Fundamental Indexation (Arnott, Hsu and More 2005) provides for a state of Nirvana, greater performance with less risk.  Given the historic price action of equities in the Value and Small Cap asset classes, the extent to which Fundamental indexes are skewed to risk and outperformance relative to its market capitalization weighted CAPM Beta master is mathematical.  Similarly, the degree of associated short-term volatility is predictable. 

 

If Smart Beta could think would it anticipate macro/sector/industry drivers, corporate actions, Fed Policy or externalities?  Would Smart Beta apply the Free Cash Flow theory to evaluate dividend policy, the absence thereof or share repurchase programs and amend its ethos?

 

The long-term benefit of actively defined parameters in passive capital market Smart Beta constructed products is supported by over 40 years of data, illustrated in the 5-year period chart below.  Displayed are Smart Beta standard-bearers PowerShares FTSE RAFI US 1500 Small-Mid Portfolio (PRFZ) and PowerShares FTSE RAFI US 1000 Portfolio (PRF) against the performance of market weighted peer benchmarks iShares Russell 1000 Value ETF (IWD), iShares Russell 2000 Growth ETF (IWO) and iShares Russell 1000 ETF (IWB).  Empirically the Fundamental indexes provide superior returns relative to market capitalization weighted composite benchmark portfolios and on a standalone basis.

In shorter periods of performance measurement, divergence among benchmarks is evident as embedded Alpha across portfolios accounts for the variability relative to the benchmarks PRFZ and PRF.

Within the Fundamental indexes matrix, variability in near- and intermediate-term performance suggests Smart Beta’s equally weighted parameters—book value, cash flow, sales, dividends—mask Alpha drivers when aggregated, unable to detect relevant points of inflection beyond contrasting the price change of respective Smart Beta indexes and their corresponding mean-variances.  In this context Smart Beta may offer excess market or asset class returns though does not offer Alpha generation, per se, but rather enhanced Beta long-term outperformance representing more of a paradigm shift in theoretical Beta—CAPM 2.0.

 

The comparative 6-month chart below displays both Alpha and negative Alpha.  Demonstrated by the inclusion of PowerShares WilderHill Clean Energy Portfolio (PBW), relative out(under)performance of Smart Beta is exaggerated by further skewing capitalization bias and combining the additional risks of thematic investing.

Contrasting performance differentials is a productive exercise as thematic investing is excluded from Smart Beta due to the inconsistency of data relative to its thesis.  Expectedly, causality ranges among many factors; more importantly, one can anticipate the persistent lead and lag effects characteristic among asset classes across capitalizations and within verticals in diverse economic sectors.

 

In this context, corporate performance (Alpha) is best analyzed during a one- to three-year operating environment and three- to five-year business cycle (cyclical and secular).  The sensitivity of these companies to microeconomic and product sub-cycles within greater cyclicalities often provide the quantifiable points of inflection the value bias in Smart Beta ignores.  Due to the finite nature of Fundamental Indexation, Smart Beta asset class benchmarks exclude complete measurement of growth companies engaged in emerging technologies based on its own metrics.

 

For example, the simple presence of a dividend policy infers the inability of a company to develop new projects or products with an internal rate of return greater than its hurdle rate thereby necessitating the return of excess cash to shareholders (as does a share repurchase program).  Growing companies may in fact have negative retained earnings and deteriorating book value with negative cash flow all the while realizing accelerating sales, an increasing market capitalization and lofty valuation multiples (albeit with negative P/E ratios).

 

Intuitively, the general composition profile and even the broad 10 sectors detailed in the Smart Beta construct are comparatively inadequate.  The added capability to assess economic behavior and market risk by aligning the business segment operations of companies separate from the permutations of sector/industry/subindustry classifications and array of proprietary indexes, asset classes and geography produces Alpha.  Standardization of assigned nomenclature is complementary to the proven financial metrics provided by Smart Beta strategies.

 

This reconciliation readily identifies the common tangential profiles of multinational corporations, regional players and new entrants plus captures determinants of valuation.  For with all the Smart Beta packaging derived from Town Hall convention against the purposefully obfuscated complexity of Wall Street (together with its new arbiters), Main Street is not likely to think much of regression analysis or a state of contango but if someone called a cat a truck and said all dogs were the same they would surely take issue.

 

The fundamental parameters defined in Smart Beta may indeed refine Modern Portfolio Theory (Markowitz 1952, 2009) and arguably establish a more efficient frontier.  However, the qualitative assessments associated with quantitative analysis dictate that optimal excess return relative to a benchmark requires both performance attribution and an extrapolation of Alpha to include corporate business planning and strategy independent of the characteristics of the portfolio as a whole.  In its current state, Smart Beta appears to be more of a Beta booster than an Alpha driver though does advance the continued evolution from Fundamental indexes to Applied Indexation.

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