Founded in 1991, we are a global quantitative and systematic asset management firm applying a scientific approach to finance to develop alternative investment strategies that create value for our clients.
We value innovation, dedication, collaboration, and the ability to make an impact. Together, we create a stimulating environment for talented and passionate experts in research, technology, and business to explore new ideas and challenge existing assumptions.

Internship – Quantitative Investment Strategies Replication and Learning

Objective

Quantitative Investment Strategies are rules-based and systematically executed indices created by banks and index providers.​ They harvest well-documented risk premia/factors and trading signals on all financial instruments (stocks, futures, options) e.g. carry, momentum, value, short-term reversal. Over the last 10 years, assets managed under those strategies have grown significantly. The goal of the internship is to study how the growing demand for those indexes are driving instrument performances.

Scope of the work

The intern will engage in the following activities:

• Replicating and simulating synthetic QIS on stocks and futures using internal datasets.
• Benchmarking replications against open and internal sources.
• Testing for commonalities between strategies and identifying a sparser set of relevant ones.
• Using replicated signals and returns in event studies and as inputs of ML based forecasting models.

Required skills and qualifications

• Pursuing a degree in Finance, Economics, Data Science or a related field;
• Familiarity with econometric analysis and financial markets;
• Experience with Python (and relevant statistical libraries: statsmodels, scikit-learn).

References

Berkin, A. L., Swedroe, L. E, 016, Your Complete Guide to Factor-Based Investing: The Way Smart Money Invests Today, ed. BAM Alliance Press.

O'Doherty, M. S., Wang, F.  and Yan, S, 2025, On the Macroeconomic Foundations of the Anomaly Zoo, https://ssrn.com/abstract=5395852 or http://dx.doi.org/10.2139/ssrn.5395852.

Feng, G., Giglio, S. and Xiu D., 2020, Taming the Factor Zoo: A test of New Factors, Journal of Finance, p. 1327-1370.

Illmanen, A., 2011, Expected Returns: An Investor's Guide to Harvesting Market Rewards, ed. Willey Finance

Profile description:

Required skills and qualifications

• Pursuing a degree in Finance, Economics, Data Science or a related field;
• Familiarity with econometric analysis and financial markets;
• Experience with Python (and relevant statistical libraries: statsmodels, scikit-learn).

We are continuously striving to be an equal opportunity employer and we prohibit any discrimination based on sex, disability, origin, sexual orientation, gender identity, age, race, or religion. We believe that our diversity, breadth of experience, and multiple points of view are among the leading factors in our success.
CFM is a signatory of the Women Empowerment Principles.
 

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