Software written by our Faculty
We write industry-leading software
Our students will have the opportunity to contribute to production-grade software developed by our Faculty and gain visibility on GitHub as software developers
Module 1: Python for Finance
The lingua franca of data science, machine learning, and finance
- tcapy by Saeed Amen and Cuemacro – FX TCA/transaction cost analysis Python library
- finmarketpy by Saeed Amen and Cuemacro – open source Python library for backtesting
- finaddpy by Saeed Amen and Cuemacro – proprietary Python library to cache market data
- Saeed Amen’s blogpost: Learn how our software reduces trading costs and improve alpha!
- thalesians.adiutor by Paul Bilokon, Abir Sridi, Thalesians Ltd, and Thalesians Marine Ltd
- The rest of our numerous software projects are not in public domain and may be protected by NDAs, contracts, and/or other legal documents
Module 2: Databases in finance – Kdb+/q
An unrivaled tool for big data and high-frequency data
- quantQ by Jan Novotny, Paul Bilokon, Aris Galiotos, and Frédéric Délèze
Module 3: C++ fundamentals with use cases from finance
Performance, production stability, and portability
- A Monte Carlo VaR framework by Ivan Zhdankin
Module 4: Data Structures and Algorithms in C++
The core of computing
- A Monte Carlo VaR framework by Ivan Zhdankin
- Semi-Static conditions framework by Paul Bilokon, Max Lucuta, and Erez Shermer
Module 5: Designing algorithmic trading applications
State-of-the-art content
- Semi-Static conditions framework by Paul Bilokon, Max Lucuta, and Erez Shermer
- HFT design patterns by Paul Bilokon and Burak Gunduz
- HFT design patterns by Paul Bilokon and Gordon Lee
- CUDA in computational finance by Paul Bilokon, Sergei Kucherenko, and Casey Williams
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