In advance: 2Q23 corporate earnings reports thus far reinforce sentiment for a soft (or no) US economic landing, evidenced in part by outperformance of Small- and Mid-cap factor-based strategies (ref. ETF benchmark proxies: PRFZ +4.4% 1-mo. total return, +17.2% 3-mos., +14.9% YTD23, as of 080423; SMLF +3.0%, +14.7%, +12.7%) relative to higher quality Large- and Mid-cap asset classes (QUAL: +1.5%, +12.0%, +20.7%) at interim-period points of inflection.
Core sectors represent a continuum of investable opportunities, amidst both evolving public policy and technological innovation, even across volatile economic cycles and subcycles. The Energy complex for example, bounded by Oil&Gas (XLE: +6.8%, +12.3%, +1.3%; XOP: +11.8%, +24.9%, +7.7%; OIH: +17.6%, +34.3%, +12.4%) and Clean Tech (PBW: -0.9%, +19.1%, +7.1%), provides structured parameters for complementary niche/thematic/megatrend institutional portfolio strategies.
For depth, relevant subsector ETFs further characterize Clean Tech segments: Solar (TAN: -12.2%, -8.1%, -14.0%), Wind (FAN: -5.7%, -6.6%, -3.9%), Grid (GRID: -3.5%, +6.8%, +17.3%), Lithium (LIT: -4.9%, +7.8%, +8.9%) and Automotive (CARZ: -0.5%, +20.4%, +40.0%).
Adaptive principles of indexation are requisite to improve peer group analytics and valuation during this third iteration of benchmark analysis, an essential means to isolate and capture PBW component member performance dispersion in Alpha-strategies (+62.6%/-81.2% 1-mo., +178.7%/-81.5% 3-mos., +199.5%/-91.9% YTD23, +102.6%/-97.1% 12-mos.).
Proprietary <U/O> Matrix via Applied Indexation, derived from a combined Renewables/Diversified Industrials/Technology sector-themed overlay within PBW, utilizes the modularity of corporate business segment operations embedded in company revenue lines to refine conventionally assigned sector/industry/subindustry nomenclature on a relative portfolio-weighted basis (12 segments, 62 classifications, 256 single and multi-listed component members; n=75).
Effective <U/O> Matrix via Applied Indexation Tier-2: Alpha and Alpha-Beta screens are generated from a comprehensive set of four spreadsheets: 1] Anatomy (component members, data introduction), 2] Iteration (industry sort, computations), 3] Matrix (applied indexation, data analytics) and 4] Summary Template (composite data, portfolio characteristics).
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At Venn’s intersection, sets and subsets of competing interests endure. The dynamic principles of BSOs are three-fold: 1) multinational and Large-cap companies function as benchmark sector/industry/subindustry proxies based on scale (Alpha-Beta), 2) Small- and Mid-cap companies participate as competitive peers (Alpha) and, hence, acquisition candidates and 3) among subsets of 1) and 2) are companies provisioning multiple economic sectors, asset classes and geographies. Successful trading strategies (conventional, systematic, factor-based) and adaptive investable motifs (niche, thematic, megatrend) isolate Value in Growth, and Growth in Value, by aligning the prospective Alpha drivers directly associated with ecosystem composition and supply chain verticals.
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