Intangible-Aware Factor Model
Adjust factor weights to fit how each industry creates economic value
- Difficulty
- Advanced
- Time to result
- ~months to results
- Steps
- 5
- Confidence
- 97%
The model begins with three factor families—value, quality, and sentiment—and combines multiple measures within each family rather than relying on a single ratio. It then ranks businesses by intangible-capital intensity, distinguishing industries driven by research, software, patents, or intellectual property from those dominated by physical assets. Traditional value measures receive more weight where physical capital remains informative, while sentiment becomes more influential for highly intangible businesses whose economics are poorly represented by book value. Portfolio construction then neutralizes exposures, such as countries and sectors, that are not intended sources of return. The resulting portfolio seeks to make its factor-selection edge—not a macroeconomic or geographic bet—the primary driver of performance.
Origin
Extracted from Masters in Business, describing Bridgeway Capital's original research and peer-reviewed work on intangible-capital intensity.
Core principles
- 01Combine value, quality, and sentiment rather than trusting one factor.
- 02Use multiple measures within each factor to stabilize returns.
- 03Recognize that traditional book value understates intangible assets.
- 04Adjust factor emphasis according to intangible-capital intensity.
- 05Neutralize exposures that are outside the strategy's intended edge.
How to run it
- 1
Build the factor families
Define several defensible measures for value, quality, and sentiment. Combine measures within each family to reduce dependence on any one accounting ratio.
Pro tip Draw measures from both the income statement and balance sheet.
Watch out A single popular ratio can produce unstable returns or systematic blind spots.
- 2
Rank intangible intensity
Estimate how strongly each company or industry depends on research, software, patents, brands, and other intangible assets. Place businesses along a spectrum from physical-capital-heavy to intangible-heavy.
Pro tip Industry-level rankings can provide a practical starting point.
Watch out Reported book assets may severely understate the resources behind intangible businesses.
- 3
Adapt the factor mix
Give traditional value measures more influence where physical assets remain informative. Increase the relative weight of sentiment for intangible-intensive companies while retaining value and quality inputs.
Pro tip Test the relationship using decades of data rather than one market cycle.
Watch out Do not replace the three-factor blend with sentiment alone.
- 4
Neutralize unwanted bets
Constrain country, sector, and other exposures that are not part of the model's intended return source. Balance long and short exposure where the mandate requires market neutrality.
Pro tip Define every neutralization target before portfolio optimization.
Watch out Uncontrolled exposures can make macro conditions look like stock-selection skill.
- 5
Qualify picks and assumptions
Inspect data quality, model assumptions, and market developments behind unusually strong signals. Determine whether regulations or company events invalidate the historical relationships.
Pro tip Document overrides and feed them back into model research.
Watch out Treating model output as automatically correct turns systematic investing into blind automation.
In the wild
A software company and an industrial manufacturer both appear expensive on price-to-book. The model identifies the software company as highly intangible-intensive, gives greater weight to sentiment and quality, and applies traditional value measures more strongly to the manufacturer. It then controls industry exposure so the comparison does not become an unintended technology bet.
→ Each company is assessed using signals suited to how it creates value, while sector risk remains controlled.
Common mistakes
Treating book value as universal
Book value captures physical assets better than intellectual property, software, or research. Applying it uniformly can make intangible-intensive businesses look misleadingly expensive.
Confusing factor returns with macro bets
A portfolio may appear successful because of country or sector exposure rather than stock selection. Neutralize risks that are not part of the intended design.
Trusting unqualified data
Global and small-company data can be noisy or stale. Strong model signals require checks for bad records, regulatory changes, and invalid assumptions.
Is it for you?
Best for
Quantitative equity investors comparing companies across old-economy and intangible-intensive industries.
Not ideal for
Investors without reliable financial, industry, sentiment, and intangible-capital data.
From the transcript
“we believe in value, quality, and sentiment, or the three primary legs of the stool.”
“The high in tangible capital intensity ones don't work real well with the classic measures of value.”
“what we found is that sentiment is a stronger predictor of future returns for those”
From the episode
Factor-based Investing with John Montgomery
John Montgomery