In dominant ‘top-down, bottom-up’ approaches, portfolio strategies often meet at eclectic intersections: points joining benchmark indexes, structural nomenclature assignments and company-specific business segment operations. The structural inefficiencies embedded within performance benchmarks at these junctures result in measurable tiering effects on peer group analytics and, subsequently, valuation. The view from the bottom suggests Alpha-Beta single- and multi-factor index applications provide a means to capture capital market dynamics in one construct consistent with existing managed portfolio strategies and the proven empirical data associated with new product implementation.
Determined by the prevalence of allocation-based institutional investment policy guidelines, overall portfolio construction is responsible for approximately 90% of aggregated performance attribution. The absolute range variability of the remainder is driven by differentiated growth rates consistent with secular period economics and discretionary cyclical investing. Ideally static allocations are self-contained within established parameters. More common are commodity, inflation, currency and event hedge combinations with macro, thematic and Beta performance amplifiers completing overall portfolio composition. After anchoring projected benchmark performance of index-plus and active strategies (60-70% of a portfolio), both Beta boosters and Alpha drivers demand attention.
Relative to overall portfolio posture Exchange Traded Funds are increasingly actioned as Smart, Strategic or thematic Beta allocations; over- or underweighting specific sectors or themes such as US Shale, Value, Volatility, LATAM, Renewables and Capital Structure. The anticipated incremental marginal performance of this Beta-centric trade effectively (perhaps even inadvertently) becomes an Alpha driver due to its broad simple, multi-factor tilting or thematic exposure. From inception, many considered the Smart Beta premise a promising long-term alternative to standard benchmark allocations. Few envisioned trading Smart Beta a necessity based on valuation as its pioneers now advise. Pitfalls of this Beta-type ETF investing, the need to distinguish between systemic and situational performance attributes, are a reminder that intended Alpha-Beta roles are often structurally reversed. Tenet deconstruction of an evolved or thematic Beta is useful however, revealing fund component members and the prospects for producing portfolio enhancing Alpha in its base form (Alpha-Alpha).
Overlapping portfolio strategies attempt to capture desired peak-to-trough exposures with predictability based on factors determined by fundamental analysis and relative valuation, though ecosystem verticals and cross-horizontal peer applications are inherently disadvantaged due to broad sector and thematic reporting in conventional structures. Full expression of the interrelationships among corporate profiles within a fund structure necessitates functional process designations among respective component member business segment operations (BSOs). From the revenue line BSOs begin to replace sector/industry nomenclature and propagate descriptive subindustry classifications in a refined iterative structure. These segments/classifications produce richer sets of peer group analytics and valuation (pgav) for further Alpha-specific analysis.
Below, a flow-based abstraction:
At this point the qualitative assessments associated with fundamental research complete an evolving process of corporate profile presentation from general capitalization-weighted index sector designations to an aggregated factor-based thematic approach and, ultimately, to a BSO reconciliation of managed fund or allocated strategies within a latticed structure. Portfolio weights initially hold for relativity then are recalculated in the alternative index format to its newly formed segments and more specific classifications.
In functionality, uniquely derived indicators distinguish between company characteristics in a multi-factor framework and process templates may be systematically replicated throughout an entire investment universe. For instance, Apple's dominance in an Internet of Things themed ETF is mitigated and emerging tech firms are revealed, a Small- or Mid-Cap Oil & Gas recovery play in US Shale is identified per basin and early- versus late-cycle solar investing is contrasted by separating subcycle leaders/laggards as end-product output (commodity bull) or input manufacturing cost (bear) scenarios are posited and scaled.
Applying index methodologies to the active/passive features of Smart Beta and thematic funds creates an effective matrix with similar indicators to those based on single-, multi-factor and thematic characteristics: 1) cyclical, subcyclical or countercyclical, value or growth investing, 2) capitalization attributes (Large, Mid and Small), 3) a neutralized market cap orientation (adjusted by portfolio weight) and 4) discerning momentum measurement (price and/or position build). Differentiated growth rates among BSO-structured parallel indexes isolate areas of opportunity across capitalizations and geography transcending sector, asset class and secular themes.
Even as benchmark indexes reach new highs, the current 'risk-on, risk-off' environment rightly exposes precarious gaps in developed investment theses and portfolio posture. When parameters of valuation breakdown only to have points of inflection again reinforce these gaps, a discerning characterization of capital market participants is essential. Given this protocol, the differentiated growth rates determining actual and projected relative performance are readily illuminated at the BSO level. While means to lever competitive market information vary, the drivers of valuation—cash flow, growth and profitability—are preferably (and rather expeditiously) identified prior to overall company or fund aggregation.
In an effort to generate a more deliberate Alpha, applied indexation offers a fluid structure provisioning management of period economics, sector dynamics and corporate catalysts in an alternative Beta format. Refinement of established investment structures and related third party data sets along sector/subsector proxies and within industry verticals demonstrates the capacity to develop peer group analytical models providing for effective correlations, performance standards and the directional value of securities. Opportunities present for the traditional strengths of investment research and institutional marketing roles to endeavor ever innovative product designs and portfolio strategies, both intuitive and actionable.
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No part of this article, related publications or web-based content may be reproduced in any form or referred to in any other publication without express written permission of Universal Orbit © 2016 and David B. Kleinberg. Forward looking statements, estimates and certain information contained herein are based upon proprietary and non-proprietary research and other sources. Information contained herein has been obtained from sources believed to be reliable but are not assured as to accuracy. Past performance is not indicative of future results. There is neither representation nor warranty as to the current accuracy of, nor liability for, decisions based on such information. This content is distributed for informational purposes only and should not be considered as investing advice or a recommendation of any particular security, strategy or investment product. The author's opinions are subject to change without notice.
Published research serves as both a quantitative reference and instructional resource in addition to a template for client services. Metrics may be modified to accommodate the universe of sector, industry and subindustry research. For assistance implementing the aforementioned concepts within financial/economic models or investment research process, please note three levels of consultation: Qualitative – Support, Quantitative – Directed and Quantitative – Fundamental. For additional articles and quantitative analytics, please visit <U/O> Research.
Published research serves as both a quantitative reference and instructional resource in addition to a template for client services. Metrics may be modified to accommodate the universe of sector, industry and subindustry research. For assistance implementing the aforementioned concepts within financial/economic models or investment research process, please note three levels of consultation: Qualitative – Support, Quantitative – Directed and Quantitative – Fundamental. For additional articles and quantitative analytics, please visit <U/O> Research.
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