Premialab Pure Factors®


What They Are

Heatmap of Factor Risk Proportion Premialab
Heatmap of Factor Risk Proportion

Premialab Pure Factors® are proprietary benchmarks on risk premia and factor performances.

They are constructed by harvesting strategy data from Premialab's extensive database to capture the consensus implementation across providers.

Heatmap of Factor Risk Proportion Premialab
Heatmap of Factor Risk Proportion
Principal component analysis Premialab
Principal component analysis

Our methodology to construct an unbiased factor model consists of extracting the maximum amount of market information while eliminating model-specific interference.

The Premialab Pure Factors® framework includes Carry, Low Volatility, Momentum, Quality, Size, Value, and Volatility across five asset classes.


Our platform embodies the general market consensus of risk premia as the common variance across implementations


We synthesize information from the universe of strategies from leading providers into 47 uncorrelated factors across asset classes


We introduce clarity into a highly fragmented market allowing objective comparative analyses across strategies


Our platform is based exclusively on investible strategies representing actual assets under management

Investors can utilize our Premialab Pure Factors® model as an anchor point to navigate between various market offerings and find their portfolio's missing puzzle piece.

The Premialab Pure Factors® model captures the risk profiles associated with key market risk factors from the universe of risk premia strategies.

Minimum Spanning Tree Premialab
Minimum Spanning Tree

Monitor Factor Dynamics

Unparalleled transparency for monitoring cross-asset factor performance trends and changing market dynamics

Reveal Factor Risks

Decomposing any fund or portfolio into independent risk factors will enhance your understanding around the risk and return drivers of your portfolio

Benchmark Performance

We are used as an independent referential to benchmark manager and strategy performance and to measure alpha generation

Control for Style Drift

Rolling regressions against the Premialab Pure Factors® highlight changes in factor exposure across time to better monitor potential style drift