4QTR21 U/O Matrix via Applied Indexation

 

In advance: 4QTR21 <U/O> Matrix via Applied Indexation is currently available in multi-sheet format illustrating the structured ecosystem composition and supply chain verticals within publicly traded Clean Energy Subindustry Benchmark ETF PBW.

A combined Renewables/Diversified Industrials/Technology sector-themed overlay approach utilizes iterative index applications of peer group analytics and valuation to provide effective Alpha and Alpha-Beta screens. 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, 59 classifications, 76 single and multi-listed component members; n=248).

4Q21 PBW -6.8%, CY21 -29.8%; 12-mos. performance dispersion: +145.5%/-87.7% (011422).

PBW Fwd (adj.) PE=34.4 Beta=1.4 versus 33.2/1.4, 34.1/1.4 and 34.0/1.3 sequentially. SPX 12-month Fwd PE=21.1 v. 20.5/Q3, 21.4/Q2, 21.8/Q1 (FactSet); CAPE 38.5 from 37.9/38.6/37.6, mean 16.9 (Shiller).

Reference the tutorial tab at www.universalorbit.com for a voiceover slide show outlining sample adaptive methodology in tandem with blog post <U/O> Matrix - Establishing Predictive Value exercise. Investable motifs (long/short): conventional, thematic, megatrend, equity/corporates, value/growth and factor-based.

Please message direct with any questions or for product suite access and development considerations.

#Strategy #CleanEnergy #Renewables #CorporateFinance #BSOs #PortfolioManagement #Analytics

www.universalorbit.com

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 and supply chain verticals.

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. No part of this product, related articles, 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 © 2022 and David B. Kleinberg.

U/O Applied Indexation …a brief tutorial.

Topical discussions regarding the nature of performance dispersion among Value and Growth equity indexes and, importantly, their constituents often ignore the inherent commonality of component member business segment operations (BSOs) across both baskets. Proprietary research suggests an approach to portfolio strategies isolating the Venn of capital markets offers an opportunity to exploit standard capital market delineations and enhance absolute return performance against respective benchmarks.

In examining the Clean Energy space for instance, introducing a Renewables/Diversified Industrials/Technology sector-themed overlay begins an iterative process creating a latticed framework to lever a combination of competitive market information (e.g., benchmark ETF - PBW) and applied indexation methodology. Corporate profile BSOs replace broad industry nomenclature assignments at this point, differentiated growth rates are observed and portfolio allocations are rationalized to readily improve peer group analytics and valuation.

For reference, 69 PBW (3QTR21) component members are selected from a of total 71 (21 designated industry groups) to develop effective Tier-2 Alpha/Alpha-Beta screens by populating 201 unique placements along 10 segments and 52 BSOs. To illustrate, simply click thru to Q3 b-platform release and replay of ‘<U/O> Applied Indexation …a brief tutorial.’ voiceover slide show (https://www.universalorbit.com/a-brief-tutorial).

PBW CY21 -18.9%, YTD performance dispersion: +453.5%/-82.4% (102721). 3Q21 -16.8%; capitalization (weight): Small-cap 25.9%, Mid-cap 48.7%, Large-cap 25.3%.

PBW Fwd (adj.) PE=33.2 Beta=1.4 versus 34.1/1.4, 34.0/1.3, 33.4/1.3 and 27.0/1.3 sequentially. SPX 12-month Fwd PE=21.0 v. 20.5/Q3, 21.4/Q2, 21.8/Q1, 18.3/5-yr (FactSet); CAPE 38.8 from 37.9/38.6/37.6/34.9, mean 16.9 (Shiller).

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 and supply chain verticals.

Please message direct for product suite access and development considerations.

#Strategy #PortfolioManagement #CleanEnergy #Renewables #BSOs #CorporateFinance #Analytics

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. No part of this product, related articles, 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 © 2021 and David B. Kleinberg.

U/O Applied Indexation …a brief tutorial.

In advance: ‘<U/O> Applied Indexation …a brief tutorial.’ voiceover slide show is currently posted without restriction (click here) to illustrate benchmark analysis and proprietary Alpha/Alpha-Beta screening via business segment operations, utilizing publicly-sourced Clean Energy Subindustry Benchmark ETF PBW to create a combined Renewables/Diversified Industrials/Technology sector-themed overlay (10 segments, 52 classifications, 66 single and multi-listed component members, 201 placements).

3Q21 PBW -16.8%, CY21 YTD -27.3%; YTD performance dispersion: +247.2%/-79.4% (100821).

PBW Fwd (adj.) PE=33.2 Beta=1.4 versus 34.1/1.4, 34.0/1.3, 33.4/1.3, and 27.0/1.3 sequentially. SPX 12-month Fwd PE=20.5 v. 21.4/Q2, 21.8/Q1 (FactSet); CAPE 37.9 from 38.6/37.6/34.9/31.7, mean 16.9 (Shiller).

Investable motifs for complementary long/short portfolio strategies: conventional, thematic, megatrend, equity/corporates, value/growth and factor-based.

Please message direct for product suite access and product development considerations.

www.universalorbit.com

___________________________________________________________________

Appendix:

To advance analysis, needed is a reconciliation of specific business segment operations among representative component members apart from the general sector designations presented in standard fund reporting.

At Venn’s intersection, sets and subsets of competing interests endure. Proprietary research suggests its dynamic principle in relation to business segment operations is three-fold: 1) multinational and Large-cap companies function as benchmark sector/industry/subindustry proxies based on scale and business segment operations, 2) Small- and Mid-cap companies compete as peers and are delineated by business segment operations and 3) among subsets of 1) and 2) are vendors provisioning multiple economic sectors, asset classes and geographies. Successful trading strategies (systematic, momentum, thematic) isolate Value in Growth by not overlooking the prospective Alpha drivers directly associated with ecosystem and supply chain verticals or profiles of Small- and Mid-cap companies functioning as competitive peers and, hence, acquisition candidates.

From a portfolio management perspective, designing strategies based on business segment operations lends the advantage of iterative index applications by exploiting the inefficiencies in third party data nomenclature assignments which inevitability skew peer group analytics and valuation. While means and methods vary of course, a latticed framework—gleaned from competitive market information, built by segments/classifications, interpolated for integrity—exhibits the proportionality revealed by business segment operation considerations and distinguishes differentiated growth rates beyond simple revenue line aggregation. Additionally, a developed thesis for security selection in the Energy complex incorporates: 1) a barbell to CAPE as an extrapolation, 2) a barbell of Cleantech to Diversified Industrials as a foundation and 3) a barbell of Value to Growth implicit in corporate anatomy.

Common portfolio position weight allocations (0.5% < x < 5.0%) may be aligned consistent with long/short peak-to-trough cyclical/counter-cyclical exposures and emerging technologies among individual and multi-listed component members. Importantly, often discarded negative PE companies are included to capture points of inflection for cash flow growth and forward earnings momentum. In the end, a structure of analysis in the Energy complex is borne from the examination of business segment operations within diverse companies across economic sectors and asset classes plus, on a standalone basis, competitive peers—by definition, Alpha is singular.

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. No part of this product, related articles, 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 © 2021 and David B. Kleinberg.

U/O Matrix via Applied Indexation – Establishing Predictive Value 2020

Key period takeaways: 1) bounded thematic PBW/PZD composite performance YTD 121120 (+162.4%/+40.2%) is ranged by constituent dispersion of +1,364.5% and -54.3%, 2) tech benchmark QQQ performance (+42.7%) is bested by niche proxies TAN (+172.1%), LIT (+98.7%), FAN (+44.3%) and CARZ (+46.5%), and 3) with the exception of MTUM (+25.8%), SPY (+15.5%) outperformed Smart Beta (PRF, PRFZ, EUSA) and factor-based (LRGF, SMLF, VLUE, QUAL, SIZE, USMV) strategies though trend is reversed on a recent one- and three-month basis (absent USMV).

Alternative Energy Subindustry Benchmark ETFs PBW/PZD are publicly-sourced to create a Renewables/Diversified Industrials/Technology sector-themed overlay based on component member business segment operations (10 segments, 55 classifications, 76 single and multi-listed component members). Proprietary research suggests empirical past-positive forward looking variance inversions of portfolio position weights versus market capitalization indicate directional valuations in select companies.

Please message direct for analytical support/product development or post to open forum in comments section.

www.universalorbit.com

___________________________________________________________________    

Appendix:

To advance analysis, needed is a reconciliation of specific business segment operations among representative component members apart from the general sector designations presented in standard fund reporting.

At Venn’s intersection, sets and subsets of competing interests endure. Proprietary research suggests its dynamic principle in relation to business segment operations is three-fold: 1) multinational and Large-cap companies function as benchmark sector/industry/subindustry proxies based on scale and business segment operations, 2) Small- and Mid-cap companies compete as peers and are delineated by business segment operations and 3) among subsets of 1) and 2) are vendors provisioning multiple economic sectors, asset classes and geographies. Successful trading strategies (systematic, momentum, thematic) isolate Value in Growth by not overlooking the prospective Alpha drivers directly associated with ecosystem and supply chain verticals or profiles of Small- and Mid-cap companies functioning as competitive peers and, hence, acquisition candidates.

From a portfolio management perspective, designing strategies based on business segment operations lends the advantage of iterative index applications by exploiting the inefficiencies in third party data nomenclature assignments which inevitability skew peer group analytics and valuation. While means and methods vary of course, a latticed framework—gleaned from competitive market information, built by segments/classifications, interpolated for integrity—exhibits the proportionality revealed by business segment operation considerations and distinguishes differentiated growth rates beyond simple revenue line aggregation. Additionally, a developed thesis for security selection in the Energy complex incorporates: 1) a barbell to CAPE as an extrapolation, 2) a barbell of Cleantech to Diversified Industrials as a foundation and 3) a barbell of Value to Growth implicit in corporate anatomy.

Common portfolio position weight allocations (0.5% < x < 4.0%) may be aligned consistent with long/short peak-to-trough cyclical/counter-cyclical exposures and emerging technologies among individual and multi-listed component members. Importantly, often discarded negative PE companies are included to capture points of inflection for cash flow growth and forward earnings momentum. In the end, a structure of analysis in the Energy complex is borne from the examination of business segment operations within diverse companies across economic sectors and asset classes plus, on a standalone basis, competitive peers—by definition, Alpha is singular.

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. No part of this product, related articles, 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 © 2020 and David B. Kleinberg.

Thematic Alpha-Beta Screening via Applied Indexation

Ahead of Q3 earnings, opportunity presents to review core equity and corporate credit portfolio strategies. Varying cyclically rich versus cyclically advantaged sectors prompt drag-and-drop product development as well and an effort to build a better Beta, both factor- and valuation-based. In a period of divergent views, requisite first and second order investment screens challenge institutional managers to lever the qualitative assessments associated with quantitative analysis, rules-based discretion and the nature of performance dispersion.

Lost in translation perhaps is a thematic multi-factor approach to screening which combines the successful tenets of index-plus methodologies, existing Beta-Beta and Alpha-Beta baskets, in parallel with prospective allocated Alpha capture. Proprietary research realizations identify trading pairs (e.g., momentum + growth / low beta + value) and tactical technical partners against a defined motif to help translate specific factor metrics into preferred fundamental corporate characteristics based on, for example, the business segment operations delineated within a company’s revenue line (dtd 091520).

Given this year’s capital market volatility, investors may question the need for additional analytical tools to isolate Alpha against a dispersed Beta. However, as determined progress matches the uncertainty of COVID-19, newfound catalysts mark investable motifs and build points of inflection into productive Alpha-Beta screens.

Thematically, for instance, independent megatrends endure despite dislocations in present valuations. These transformative movements add breadth to an investment universe, amplifying total return potential relative to performance baselines and institutional benchmarks. Here, niche proxies serve as clarifying portable benchmarks lending context to performance differentials in tandem with conventional indexes.

For example, charted megatrend ETF proxies in the overlay below — Renewables (PBW - Invesco WilderHill Clean Energy), Biotechnology (IDNA - iShares Genomics Immunology and Healthcare), Robotics (BOTZ - Global X Robotics & Artificial Intelligence) — together form the coveted V-shaped performance recovery similarly to technology benchmark Nasdaq-100 (QQQ) as of 063020:

Events may still effect the current steepness of V’s right arm slope to result in an alternate letter or shape (U, W, L, square root, reverse square root or swoosh) and subsequent total return proposition. Irrespective, in addition to the long view, megatrend ETFs frame aggregated portfolio performance in time series and importantly provide an accounting of absolute component member performance dispersion: PBW one-year total return +39.1% (ranged returns of US exchange-listed component members +841.7%, -42.8%), IDNA +41.2% (+798.3%, -59.5%), BOTZ +15.5% (+137.3%, -60.3%) and QQQ +33.7% (+375.3%, -40.2%). Correlated returns reflect common drivers of valuation at the same time persistent performance differentials create opportunities to complement existing Alpha-Beta portfolio strategies.

Clearly portfolio strategies in active markets are tactically enhanced by Beta-boosters and informed factor tilts. Unfortunately though, despite incremental gains, oblique broad market assumptions often mask Alpha-specific drivers due to a predominantly lagged approach. Contrasting unique company characteristics consistent with elements of the traditional nine-grid style box (Large-, Mid-, Small-cap; Growth, Value, Blend) to principles of Smart Beta and factor investing (growth, value, quality, size, momentum, volatility, equal weighting, rebalancing) recognizes an inherent cyclicality, and subcyclicality, to requisite modeled corporate valuations and relative value assessments. Proprietary research suggests the Alpha-Beta trade-off is best mitigated from the bottom-up.

Conceptually, reconstructing megatrend ETFs and benchmark proxies via Applied Indexation starts at the revenue line by delineating differentiated growth rates of respective business segment operations. Alpha-capturing exercises link ETF component member corporate business profiles tangentially to form distinctive peer groups based on refined sector/industry/subindustry nomenclature assignments. Comparatively, the resultant variances of component member portfolio position weight classifications versus market capitalized position weights reveal meaningful performance causality between structurally embedded ETF research (security selection, size) and implicit tenets of Smart Beta and factor strategies.

The empirical premise of designing portfolio management strategies based on business segment operations lends advantage to index applications by limiting inefficiencies in third party data that predictably skew peer group analytics and valuation. Properties of business segment operations presentation are three-fold: 1) multinational and Large-cap companies function as benchmark proxies based on scale, 2) Small- and Mid-cap companies compete as peers by defined business segment operations and 3) subsets of 1) and 2) provision multiple economic sectors, asset classes and geographies.

To illustrate, Top/Bottom-5 component member equity performers of Renewables megatrend (PBW) are exhibited in the proceeding table listed with their corresponding prior five-period data set of past-positive forward looking inverse indicators (variance of portfolio weight to market capitalization per position per classification). Observable are the quarterly variances derived from business segment operations which produce directional valuation trends in both long and short positions:

The prevalence and depth of Top/Bottom-5 negative differentials are representative of position weighted trends, effectively profiling relative strength indicators with sufficient specificity to portend and attribute performance. Small-cap companies generally display the greatest sensitivity to price and demand changes, hence the absolute range of outperformance/underperformance. Large-caps maintain positive indicators reflecting the dominance of capitalization within a classification, Mid-caps alternately lead and lag. Applied Indexation offers a capability to accommodate component member corporate actions, the fluidity of new segment or classification introductions, portfolio management and research evolutions.

For reference, performance dispersion in the (A) Automotive segment is evident above in review of Top/Bottom-5 listed (A) Automotive classifications: (A) Manufactures, (A) Fuel Cells – Lithium, (A) Fuel Cells – Hydrogen, (A) Components – Composites, (A) Components – Conversion and (A) Interiors. Tesla’s performance exemplifies the dynamic of innovation and scope of global operations. Interestingly, a competitive peer in classification — (A) Automotive (A) Manufactures — Workhorse Group (then a Small-cap) outperforms by demonstrating more immediate exposure to demand-driven scaling of electric commercial delivery trucks. SpaceX notably represents yet another prevailing megatrend although its motif is beyond the parameters of Renewables megatrend (PBW) construct and, separately, also excluded from Tesla’s currently filed SEC documents.

Successful trading strategies — thematic, systematic, momentum — isolate Value in Growth (and Growth in Value) by incorporating prospective Alpha drivers directly associated with ecosystem and supply chain verticals. Predictive value in tiered portfolios is established only by the degree objective research measures increase total return performance above a designated benchmark (i.e., Alpha equals excess return). Standard benchmark analysis begins an iterative process to include computed variances as a means to articulate relationships among investment themes, portfolio structure and security selection. Borne from a fundamental posture, derivative analytics via Applied Indexation help manage the complexity and nuance in barbell portfolio strategies—a bridge from allocated Beta to Alpha capture.



www.universalorbit.com






<U/O> Universal Orbit © 2020

U/O Matrix via Applied Indexation – Establishing Predictive Value 2019

U/O Matrix via Applied Indexation – Establishing Predictive Value 2019 exercise demonstrates the capability to confer the directional value of select securities utilizing benchmark applications of peer group analytics and valuation.

Exhibited in this Establishing Predictive Value series is 1) the importance of both standardized specific and descriptive nomenclature in fundamental benchmark index component member assignments, 2) period outperformance based on differentiated growth rates delineated by business segment operations (BSOs) within proprietary segment verticals (primary/secondary/tertiary classifications as determined), 3) capacity to profile M&A employing common BSOs and 4) development of portfolio strategies including clinical applications for long/short active/passive managers.

In a combined Renewables/Diversified Industrials/Technology sector-themed overlay based on publicly-sourced Alternative Energy Subindustry Benchmark ETFs PBW/PZD, aggregated are top and bottom constituent equity performers (YTD as of 112919) displayed by refined sector/industry/subindustry nomenclature (BSOs) in tandem with a five-period sequential quarterly data set of forward-looking inverse indicators derived from variances between respective market capitalization and position weightings across proprietary segments (Wind, Solar, Fuel Cells, Smart Grid, Water, LED, Biofuel, Automotive, Natural Gas) and within segment verticals (53 classifications, including 184 single and multi-listed component members).

Interesting to note during general examination of niche ETF strategies (thematic, Smart Beta and factor-based) against conventional benchmarks, actual historic performance suggests only an intermittency of outperformance amidst observed economic cycles and subcycles. However thematic capture, coupled with a fundamental bias towards Smart Beta and factor-based attributes (plus period recognition), lends opportunity as a tactical and strategic complement to equity and corporate credit portfolio strategies (Alpha, Alpha-Beta). The robustness of generated data patterns below corresponds to absolute performance dispersion, arithmetic to mean proxy total returns (scroll down and right to center).


Please message direct (here) for product suite access and development considerations.

      #AppliedIndexation  #ETFs  #BSOs
       ___________________________________________________________________     


Appendix:

To advance analysis, needed is a reconciliation of specific business segment operations among representative component members apart from the general sector designations presented in standard fund reporting.

At Venn’s intersection, sets and subsets of competing interests endure. Proprietary research suggests its dynamic principle in relation to business segment operations is three-fold: 1) multinational and Large-cap companies function as benchmark sector/industry/subindustry proxies based on scale and business segment operations, 2) Small- and Mid-cap companies compete as peers and are delineated by business segment operations and 3) among subsets of 1) and 2) are vendors provisioning multiple economic sectors, asset classes and geographies. Successful trading strategies (systematic, momentum, thematic) isolate Value in Growth by not overlooking the prospective Alpha drivers directly associated with ecosystem and supply chain verticals or profiles of Small- and Mid-cap companies functioning as competitive peers and, hence, acquisition candidates.

From a portfolio management perspective, designing strategies based on business segment operations lends the advantage of iterative index applications by exploiting the inefficiencies in third party data nomenclature assignments which inevitability skew peer group analytics and valuation. While means and methods vary of course, a latticed framework—gleaned from competitive market information, built by segments/classifications, interpolated for integrity—exhibits the proportionality revealed by business segment operation considerations and distinguishes differentiated growth rates beyond simple revenue line aggregation. Additionally, a developed thesis for security selection in the Energy complex incorporates: 1) a barbell to CAPE as an extrapolation, 2) a barbell of Cleantech to Diversified Industrials as a foundation and 3) a barbell of Value to Growth implicit in corporate anatomy.

Common portfolio position weight allocations (0.5% < x < 4.0%) may be aligned consistent with long/short peak-to-trough cyclical/counter-cyclical exposures and emerging technologies among individual and multi-listed component members. Importantly, often discarded negative PE companies are included to capture points of inflection for cash flow growth and forward earnings momentum. In the end, a structure of analysis in the Energy complex is borne from the examination of business segment operations within diverse companies across economic sectors and asset classes plus, on a standalone basis, competitive peers—by definition, Alpha is singular.

​

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. No part of this product, related articles, 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 © 2019 and David B. Kleinberg.

U/O Matrix - Establishing Predictive Value (113018)

Both Alpha and Beta portfolio strategies endeavored for outperformance may be readily accomplished by the development of unconstrained Alpha-Beta quantitative screens via competitive peer group business segment operations (BSOs) based on public policy, capital investment, innovation and scale.

Here's just one example how demonstrated in the recent <U/O> Matrix - Establishing Predictive Value exercise as cross-sector/industry/asset class equity exposure to BSOs of standalone Renewables, Diversified Industrials and Technology companies contrast Alternative Energy benchmark proxy ETFs and conventional performance standards.

Please note range variability of returns (message direct for model construction considerations):

         #renewableenergy  #analytics  #ETFs  #BSOs

        www.universalorbit.com/contact-us

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. No part of this product, related articles, 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 © 2018 and David B. Kleinberg.