Data Refinement: Business Segment Operations (BSOs)  092223

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In advance: Refinement of data inputs intuitively improves peer group analytics and valuation, even within a finite investment universe (index, proxy, asset class). Stochastic opportunities persist in Tier 2: Alpha and Alpha-Beta screens to exploit capital market inefficiencies (e.g. sector/industry/subindustry nomenclature) patterned sequentially at distinct points of inflection.

 

Asserting the premise, thematically, of a Clean Tech motif derived from a combined Renewables/Diversified Industrials/Technology sector-themed overlay requires only a small allowance. In our example, we assign Invesco’s WilderHill Clean Energy ETF as the benchmark proxy/index to demonstrate an actively managed absolute return portfolio strategy borne from levering a prevalent niche benchmark construct against unconstrained ranged performance dispersion among differentiated growth rates—individually and collectively.

 

Separately, in suggested independent parallel research, note common limitations in conventional fund reporting (six sector structure) and third-party data presentation (i.e. lithium recycling as Waste Management, etc.).

 

To begin an iterative process:

 

1) Revisit tenets of Venn in tandem with adaptive cross-asset multi-factor portfolio strategies: a) multinational and Large-cap companies function as benchmark sector/industry/subindustry proxies based on scale (Alpha-Beta), b) Small- and Mid-cap companies participate as competitive peers (Alpha) and, hence, acquisition candidates and c) among subsets of a) and b) are companies provisioning multiple economic sectors, asset classes and geographies.

 

2) Deconstruct company revenue lines of component members into business segment operations (BSOs) in order to more descriptively characterize ecosystem composition and supply chain vertical dynamics; link BSOs in <U/O> Matrix via Applied Indexation format.

 

3) Compute variances of component member market capitalization relative to respective portfolio position weight per segment/classification based on BSOs; chart, ladder in time series.

 

4) Rerun traditional screens, rank.

 

5) Complete Tier 3: Fundamental Analysis to assess company-specific performance (cash flow, growth, profitability) and relative value.

 

PBW total return: 2023YTD -14.3%, 3-mos. -16.3%, 12-mos. -39.2%; YTD performance dispersion +194.7%/-80.1% (092223 am).

 

<U/O> Matrix via Applied Indexation segments include Wind, Solar, Fuel Cells, Smart Grid, Water, LED, Biofuel, Automotive, Natural Gas, Storage and Aviation plus further classifications detailing component member assignments based on corporate business segment operations (12 segments, 62 classifications, 256 single and multi-listed component members; n=75 as of 063023); next scheduled update 101023.

 

For additional background, reference slideshow tutorial <U/O> Matrix - Establishing Predictive Value: Applied Indexation, Hierarchical Data Sets and Competitive Market Information along with related tabs online; composite spreadsheets downloadable thru Access link.

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#EnergyComplex #CleanEnergy #Renewables #Strategy #PortfolioManagement #PortfolioStrategies #CorporateFinance #BSOs #Analytics #BenchmarkAnalysis #AppliedIndexation

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