The Four Dimensions of Productivity
Each factor examines a distinct aspect of how companies operate. Together, they form an integrated analytical framework.
Resilience Productivity
How companies adapt to changing conditions and maintain operating performance under pressure.
Resilience
Productivity
Resource Productivity
How effectively companies use energy, materials, and other resources to generate economic output.
Resource
Productivity
Process Productivity
How efficiently companies organize and run their business operations.
Process
Productivity
Asset Productivity
How effectively companies use capital and technology to generate economic output.
Asset Productivity
Multi Factor
After calculating each score, a multi-step procedure is applied to identify and select the best performing companies in terms of innovation-productivity, process-productivity, and resiliency. Step 2 builds on Step 1 by selecting the TOP 50 process-efficient companies from the TOP 100 innovation-efficient companies. In step 3 the TOP 20 performing resilient companies are matched with the TOP 50 of the identified companies after step 2. The remaining “spaces” are filled with the TOP 50 companies after step 2. This procedure ensures that the final selection embodies the best performing firms. This approach prevents over-reliance on any single factor while combining the benefits of growth, profitability, and stability.
Multi Factor
Size
Smaller, high-growth companies
Quality
Financially healthy companies
Momentum
Stocks with upward pricetrends
Carry
Income incentive to hold
riskier securities
Value
Stocks discounted relative
to their fundamentals
Minimum volatility
Stable, lower-risk
stocks
Quality
Financially healthy companies
Momentum
Stocks with upward pricetrends
Size
Smaller, high-growth companies
Productivity Adds a Complementary View to Traditional Factors
Averdas makes productivity measurable as an investment factor: how effectively companies turn capital, processes, and resources into economic output. Productivity complements traditional factor analysis; it does not replace it.
How the Framework Works
Averdas analyzes productivity as a structural characteristic of companies. Our framework examines how efficiently companies use capital, technology, processes, and resources and how they maintain operating performance under changing conditions.
The four productivity dimensions support a structured and quantitative analysis of companies across defined investment universes.
Data-driven analysis
Averdas uses defined company data and additional approved data sources to analyse productivity-related characteristics. Historical data and any forward-looking information are treated separately and clearly identified.
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Productivity
frontiers
A productivity frontier describes the relationship between defined inputs and outputs within a specified peer group. Averdas uses this concept to assess how companies compare with their relevant peers across each of the four dimensions.
Quantitative
methodology
Quantitative models support the analysis of inputs, outputs, and relative productivity. The framework is designed to identify differences in how companies convert defined inputs into economic outputs.
Universe-specific application
The productivity framework is applied within a defined investment universe. The applicable index or product methodology specifies the eligible companies, selection rules, and construction approach.
Multi-Factor Approach
The Averdas multi-factor approach combines the four productivity dimensions in a structured, rules-based selection process. Each step builds on the previous one, applying defined criteria to identify companies that demonstrate productivity across multiple dimensions. The specific selection rules, thresholds, and weightings are set out in the applicable index or product methodology.
Factor Framework by Investment Universe
The tables below show selected return and risk characteristics for the Averdas productivity framework applied to different investment universes. Each universe has its own eligible companies, selection rules, and data history. The figures are based on the data sources and methodology specified for each universe and should be read in conjunction with the applicable index or product documentation.
The Averdas Factor Framework by Investment Universe
Return and risk figures are shown for reference purposes. Past performance and modelled results are not a reliable indicator of future performance. Figures may include periods of backtested or simulated performance; please refer to the applicable methodology for details on the calculation basis, time period, and currency.
The Averdas Factor Framework by Investment Universe
Return and risk figures are shown for reference purposes. Past performance and modelled results are not a reliable indicator of future performance. Figures may include periods of backtested or simulated performance; please refer to the applicable methodology for details on the calculation basis, time period, and currency.
Averdas Productivity Indices – Market Commentary 10/2026
A monthly overview of market conditions across the investment universes covered by the Averdas Productivity Indices.
US : The Productivity Leaders US 500 saw a 2.96% uptick in October, while the US 1500 fell 1.98%. The US 500 result is notable against a Nasdaq 100 drop of over 5% for the month. The Fed held at 3.75–4.00%, but the decision was split, with two members voting for a hike. Sticky inflation (3.6% headline, 3.1% core for September's PCE) and firm growth (3.4% Q3 annualised GDP) keep markets pricing a possible December increase. Early-month AI/semiconductor optimism reversed as Alphabet, Amazon, and Intel results dampened concerns over AI spending.
EU: The Productivity Funds—European leaders returned +4.7% in October (EUR-I; CHF-I +1.6%), the strongest result in the set and well ahead of its benchmark (+2.2%). This outcome materialized despite the ECB's decision to maintain the deposit rate at 2.50% on 29 October, despite market expectations of a rate increase in December. Euro-area inflation rose to 3.8% in September, driven by energy, while Q3 GDP grew 0.4% compared to the previous quarter.
Asia: The Asia productivity leader's product fell 7.8% in October, the weakest result. Emerging market equities fell sharply in the same period, led by technology-heavy markets such as Korea due to concerns over datacentre center spending and Chinese competition. Year-to-date, it remains the strongest at +33.6%.
Emerging markets ex-Asia: The region saw a 4.3% decrease, maintaining its position as the most volatile product in the set. Brazilian equities experienced significant pressure around the presidential runoff, and Brent crude rose by approximately 14% amid attacks on Gulf energy infrastructure and shipping, exerting further pressure on energy importers.
Overall: October saw a sharp sell-off in technology and emerging markets, with Europe leading. AI capex and Chinese competition concerns impacted Asia and EM, while higher oil prices, rising inflation and the prospect of tighter monetary policy added to the pressure. Asia remains the top performer for productivity-based selection across all products.
Source: Averdas Ag. Data as of 31. October 2026. Calculation: Total return.
Currency: (EUR/(USD)
Understanding the Full Scope of Productivity Factors
Asset Factor
Process Factor
Resilience Factor
Resource Factor
Multi-Factor
US
Asset Factor
US
Process Factor US
Resilience Factor US
Resource Factor US
Multi-Factor
US
Europe
Asset Factor Europe
Process Factor Europe
Resilience Factor Europe
Resource Factor Europe
Multi-Factor Europe
Global
Asset Factor Global
Process Factor Global
Resilience Factor Global
Resource Factor Global
Multi-Factor Global
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