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.
Applied quantitative finance in Python
| 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. |
Anotace
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.
Povinná literatura
Doporučená literatura
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. ISBN 978-1-119-52681-0.
UNPINGCO, José. Python programming for data analysis. Cham, Switzerland: Springer, 2021. ISBN 978-3-030-68951-3.
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. ISBN 978-1-119-52681-0.
UNPINGCO, José. Python programming for data analysis. Cham, Switzerland: Springer, 2021. ISBN 978-3-030-68951-3.