Data
The datasets will be available soon.
Project
Crypto Asset markets differ fundamentally from traditional equity markets. Thousands of digital assets trade across numerous exchanges, market structures evolve rapidly, and differences in data providers, filtering rules, portfolio construction, weighting schemes, and factor definitions can substantially influence empirical results. These methodological choices often make it difficult to compare findings across studies or reproduce published research.
OSCAP addresses these challenges by providing a standardized, transparent, and reproducible framework for cryptocurrency asset pricing research. The platform combines rigorous data curation, automated data processing, comprehensive documentation, and latest computational methods to generate reliable factor datasets across multiple research designs. Rather than presenting a single definition of each factor, OSCAP enables users to understand how alternative methodological choices affect empirical results and factor predictability.
The platform supports a broad community of users. Researchers can download standardized datasets and replicate existing studies or develop new methodologies. Students and educators can access transparent educational resources and real-world datasets. Practitioners can evaluate factor investing strategies and risk management approaches, while policymakers benefit from reliable evidence that contributes to greater transparency and understanding of digital asset markets.
As an open research initiative, OSCAP promotes transparency, collaboration, and reproducibility. All datasets, factor definitions, and documentation are made publicly available to facilitate cumulative scientific progress and encourage innovation in cryptocurrency asset pricing. The platform is continuously expanded as new research findings, methodologies, and datasets become available.
Technical note
The technical note will be available soon.
Contributors
- Dr. Juliane Proelss
Investigator – Infrastructure and Funding
John Molson School of Business, Concordia University
More info - Dr. Denis Schweizer
Investigator – Research Framework and Outreach
John Molson School of Business, Concordia University
More info - Dr. Christian Fieberg
Investigator – Econometrics & Machine Learning
Hochschule Bremen
More info - Dr. Gerrit Liedtke
Investigator – Data Architecture & Computational Methods
University of Bremen
More info