Applied quantitative finance in Python

Applied quantitative finance in Python
154-0571/01
angličtina

Summary

The course is aimed at expanding students' ability to formulate, solve and subsequently interpret practical problems in the field of quantitative finance with the support of the Python programming language. Attention is paid especially to practical applications of individual models and approaches, in which students are expected to have at least basic theoretical knowledge and orientation.

Literature

BRUGIÈRE, Pierre. Quantitative portfolio management: with applications in Python. Cham, Switzerland: Springer, 2020. Springer texts in business and economics. ISBN 978-3-030-37739-7.
HILPISCH, Yves J. Financial theory with Python: a gentle introduction. Sebastopol, CA: O'Reilly, 2021. ISBN 978-1-098-10435-1.
HILPISCH, Yves J. Python for finance: mastering data-driven finance. Second edition. Sebastopol, CA: O'Reilly, 2018. ISBN 978-1-492-02433-0.

Advised literature

HILPISCH, Yves J. Python for algorithmic trading: from idea to cloud deployment. Sebastopol, CA: O'Reilly, 2020. ISBN 978-1-492-05335-4.
LAROSE, Chantal D. and Daniel T. LAROSE. Data science using Python and R. Hoboken: Wiley, 2019. Wiley series on methods and applications in data mining. .
UNPINGCO, José. Python programming for data analysis. Cham, Switzerland: Springer, 2021. ISBN 978-3-030-68951-3.

back to search page

Language of instruction	angličtina
Code	154-0571
Abbreviation	AQFP
Course title	Applied quantitative finance in Python
Coordinating department	Department of Finance
Course coordinator	doc. Ing. Aleš Kresta, Ph.D.