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The Case for High Multiples



High P/E multiple companies, along with their near cousins N/A and NMF, display the characteristics of mid- to late-cycle reporting periods—increasing trends in cash flow, from negative to positive.  The case for high multiples is initially supported by lofty valuations and low interest rates amid robust earnings in this perhaps peak cycle.  Irrespective of the cycles and subcycles driving profitability, we look forward to more variable less certain comparables among changing industry-specific capital market dynamics.


Consider the spread between Large-Cap Value and Small-Cap Growth total return performance as it remains above 10% YTD in absolute difference (source: Lipper Indexes).  Relative performance is illustrated below by JKF - iShares Morningstar Large-Cap Value ETF and JKK - iShares Morningstar Small-Cap Growth ETF:

The chart is characteristic of normalizing total return expectations demonstrated by changing levels in standard institutional benchmarks of valuation (e.g., Cyclically Adjusted Price Earnings Ratio and P/E ttm).  Coupled with projected S&P 500 aggregated revenue growth and profit splits (4% and 6%, respectively) the relativity of current equity valuations provides defined points of secular inflection.  However the divergence embedded in performance figures reflect a combination of diminished scale for organic growth, latter cycle divestment of early period acquisitions and the effects of inspired share programs in the Large-Cap arena.


Given varied equilibriums among sectors and within verticals, generalized market metric applications are tempered and unable to accurately measure the proportionality of risk-return across corporate capital structures in diverse industries—the differentiated cost of debt and expected price of equity.  Despite the opacity, opportunities persist to identify value in volatile or arguably fairly valued markets. For instance, the disaggregation of business segment operations (BSOs) of publicly traded corporations isolates emerging trends and contrasts varying degrees of internal corporate performance, first by comparative analysis then by peer group analytics and valuation.


A deep dive into a Large-Cap company's financial statements will likely reveal related but distinct BSOs and product divisions, effectively replicating the corporate profiles of its Mid- and Small-Cap competitive peers.  The well-known conglomerate discount illustrated by a sum-of-the-parts valuation method simplifies this proposition.  Contrasting company-specific segment multiples, Betas and relevant metrics characteristic of peer classifications within industry vertical segments produces comparables in a manner profiling growth rates among the determinants of cash flow and profitability driving valuation of individual BSOs.  Capturing these attributes to link BSOs across economic sectors, asset classes and geography requires an alternative (lattice) approach to conventionally structured protocol inherent in traditional index and benchmark ETF nomenclature assignments.


To participate in the innovations at hand and those to be determined (performance Alpha), refined applications of peer group analytics and valuation enable the investor to anticipate company-specific catalysts occurring over a series of time frames ranging from a six month tech cycle to a 25 year period of capital investment.  Few cycles are as clear in recent history as when federal/state/municipal policies are aligned with tax incentives, capital investment and a growing global movement—the evolving Alternative Energy Subindustry is one such trend.


The U.S. Department of Energy's Energy Information Administration Annual Energy Outlook presents an opportunity to audit national energy policy, measure the effects of newly sourced natural resources and progress on carbon emissions reflected in the composition of U.S. domestic electricity generation and energy consumption.  The EIA Office of Energy Analysis provides an interactive modular approach to endeavor the task:

Populating the AEO Integrating Module with representative companies is in itself quite a feat.  Even in the relatively small renewable component of the AEO 'one energy' equation, a combined Alternative Energy ETF benchmark portfolio composed of U.S. domestic and international component members encompasses 18 Industry Groups according to the MSCI and Standard & Poor's Global Industry Classification Standard.  The thematic structure of representative portfolios lends direct exposure to corporate profiles comprising the renewable segment, though fundamentally only in broad measure.  The ETF provider groups component members as most do, in a general sector framework—Information Technology, Industrials, Utilities, Materials, Energy, Consumer Discretionary—without the benefit of more detailed contextual structure to facilitate a rigorous investment research process and actionable capital market transactions.


Refining industry classifications presented in SEC filings, SIC codes and institutionalized norms dictates 1) applying a standard framework for relativity and 2) explicit nomenclature in a defined construct to separate BSOs from their general structural assignment of largest proportionate business segment representation.  The benefit of first stage application is an ability to freely source financial and quantitative data from premier third party vendors (i.e., Morningstar, Bloomberg) utilizing publicly available information and secondly, to develop an effective real-time matrix of component members linked by designated BSO with forward looking indicators to anticipate the equity price performance of the proven former.  BSOs are distinct from generalized third party data vendor industry assignments (e.g., Semiconductor Equipment & Materials, Diversified Industrials, Utilities - Independent Power Producers, Electronic Components, Solar among many others); for example, proprietary methods distillate companies in 40 industries into a matrix consisting of 10 segments, 60 classifications and over 100 multi-listed component members.


Independent study suggests a tandem approach to modularity offers the prospect of relative outperformance by identifying select high P/E (>25), negative and undetermined multiples which routinely outpace growth-oriented benchmarks.  For the nine months ending 093014, 36% of the combined Alternative Energy ETF benchmark portfolio subset noted above (n=33) outperformed the Russell 2000 (represented by all capitalizations: Small-Cap 6, Large-Cap 4 and Mid-Cap 2).  Outperforming corporate profiles include a vertically integrated solar company, a solar power conversion component manufacturer, two hydrogen fuel cell manufactures, an electric car company, a Chinese wind turbine manufacturer, an ultracapacitor power grid supplier and a solar wafer/LCD equipment manufacturer.  Certainly from a capital market perspective elements of the end product are susceptible to overall economic health, the boom-and-bust cycle of commodity pricing (oil, natural gas, coal) and subsidies (renewables) plus permitting along with event risk in advance of its next iteration—the long and short of the matter.


Predictably a portion of Small-Cap innovators, commodity and subsidy umbrella volume operators deteriorate from Small- to Micro-Cap then distressed and ultimately are divested from portfolio holdings.  Conversely, many competitive peers continue to progress along the capitalization strata with a few achieving the rare but universal status of a company that revolutionizes the world.  Occurring simultaneously, proportionality and frequency of either are reflective of concurrent cycles and subcycles.  Below, a wider view of Alpha's effects (JKF versus JKK in red):

Replicating the cyclicalities and interrelationships among sector/industry/subindustry verticals adjoined by tangential business operations depends upon the modularity provided by nomenclature and a construct unconstrained from an environment dependent on passive strategies which mask the Alpha drivers of outperformance.  Assuming all permutations of correlated relationships are known, performance differentials solely depend upon analysis and execution.

Developing a process both systematic and repeatable supports the determination if multiple expansion or compression is based on improving, declining or maturing factors whether mathematical or evolutionary.  Anticipating the directional value of securities is a greater challenge when clarity is obscured by observation, as one micro-niche is supplied by a predominance of mainstream players . . . but therein lies the value of a case yet defined.

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