BQuant Optimized Back-testing for Alpha Generation | Bloomberg Professional Services
Webinar

Bquant Optimized Back-Testing for Alpha Generation

Collating ideas, exploring data sets and running backtests are now part of a common process in most research departments, but many approaches fall short in practice. Pitfalls include backtests that look at single exposure, allow unconstrained holdings, and ignore stringent risk rules that exist in the real world.

Join us as we recap our Python backtesting API before showcasing our newly released features, including our state-of-the-art PORT optimizer. We'll also demonstrate realistic implementations of factor strategies—with allocation restraints, turnover rules, and risk metrics adhered to—and highlight how you can maximize targeted factor exposure while ensuring portfolios don't take any "unintended bets".

Speakers

Andrea Zucchelli

BQuant Product Specialist

Bloomberg L.P.

Andrea Zucchelli has been a BQuant Product Specialist for the last 3 years; he has previously worked in the BuySide for nearly 6 years, first in Italy in Arca SGR and then in the UK at Man Group. Andrea graduated cum laude in the MSc Economics of Bocconi University with a merit-only based scholarship, and has successfully completed the Certificate in Quantitative Finance.

Ekaterina Solodkova

Quant Solutions

bloomberg

Ekaterina has been working as an advocate for Bloomberg Quant solutions in the past 3 years across French speaking territories. During the past 6 years at Bloomberg she has previously worked as an account manager for buy-side accounts in Belgium and Luxembourg and as FX and TA specialist in Analytics department. Ekaterina graduated with Honours from Imperial College and LSE.

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