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50788-01 - Lecture: Computational Finance & AI 3 CP

Semester spring semester 2024
Course frequency Every spring sem.
Lecturers Dietmar Maringer (dietmar.maringer@unibas.ch, Assessor)
Content Computing is an indispensable part of finance: in pricing financial instruments such as derivatives, managing portfolios and running trading strategies, in risk management and data analysis.

This course introduces students to computational tools and methods used in finance. Topics include:

*) modelling and simulation: efficient implementations of deterministic and non-deterministic models (pricing trees, Monte Carlo methods, artificial markets, agent-based models)

*) trading and portfolios (single and multi period, rebalancing strategies, backtesting)

*) machine learning and AI (algorithmic trading, ML-based asset pricing, learning and self-adaptation)

The course will be hands on, with the better part of lectures dealing with the implementation of techniques and models.
Learning objectives Being able to implement financial models using Python, and being able to solve quantitative problems in finance.
Bibliography There is no designated textbook; useful resources include:

*) M Gilli, D Maringer, E Schumann, Numerical Methods and Optimization in Finance, 2nd edition, Academic Press 2019.

*) A Arratia, Computational Finance: An Introductory Course with R, Atlantis Press 2012.

*) P Brandimarte, Numerical Methods in Economics and Finance, Wiley, 2nd ed, 2006.

*) P Brandimarte, Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics, Wiley 2014.

*) K Cuthbertson and D Nitzsche, Quantitative Financial Economics, Wiley, 2nd ed., 2004.

*) JC Duan, WK Härdle, JE Gentle (eds), Handbook of Computational Finance, Springer 2014.

*) G Fusai, A Roncoroni, Implementing Models in Quantitative Finance: Methods and Cases, Springer 2008.

*) P Glasserman, Monte Carlo Methods in Finance and Engineering, Springer 2003.

Specific recommendations and additional literature to be announced during the course.
Comments *) Throughout the course, we will use Python to implement methods and concepts, and perform experiments. Participants are expected to have at least a basic knowledge of programming as taught in "58989-01 Computing for Business and Economics".
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Admission requirements *) Solid knowledge of financial theory.

*) Solid background in quantitative methods (in particular statistics/econometrics and empirical finance).
Course application Registration: Please enroll in the Online Services (services.unibas.ch);

Eucor-Students and mobility students of other Swiss Universities or the FHNW first have to register at the University of Basel BEFORE the start of the course and receive their login data by post (e-mail address of the University of Basel). Processing time up to a week! Detailed information can be found here: https://www.unibas.ch/de/Studium/Mobilitaet.html
After successful registration you can enroll for the course in the Online Services (services.unibas.ch).

Applies to everyone: Enrolment = Registration for the course and the exam!

A deregistration is possible by email to belegungstorno-wwz-at-unibas.ch by April 24, 2024 at the latest, stating the course number, title and your matriculation number.
Language of instruction English
Use of digital media No specific media used
Course auditors welcome

 

Interval Weekday Time Room
wöchentlich Thursday 14.15-18.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37

Dates

Date Time Room
Thursday 18.04.2024 14.15-18.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Thursday 25.04.2024 14.15-18.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Thursday 02.05.2024 14.15-18.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Thursday 09.05.2024 14.15-18.00 Auffahrt
Thursday 16.05.2024 14.15-18.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Thursday 23.05.2024 14.15-18.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Thursday 30.05.2024 14.15-18.00 Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37
Modules Module: Core Courses in Finance and Money (Master's Studies: Finance and Money)
Module: Field Electives in Economics and Public Policy (Master's Studies: Economics and Public Policy)
Module: Field Electives in Finance and Money (Master's Studies: Finance and Money)
Module: Risk Analysis (Master's Studies: Actuarial Science)
Module: Specific Electives in Data Science and Computational Economics (Master's Studies: Business and Economics)
Module: Specific Electives in Monetary Economics and Financial Markets (Master's Studies: Business and Economics)
Assessment format record of achievement
Assessment details Combination of active participation, assignment(s), and a final written exam.

written exam: 13.06.24; 10:15-11:15.
You can still withdraw from the examination by submitting a completed, signed form to our office from march 26 until april 5 / 12:00 o’clock. The deregistration form and the mail address can be found on the homepage of the Dean of Studies Office: https://wwz.unibas.ch/en/studies/examinations/de-/registration-of-examinations/
Prior to march 25, please deregister only in the Online Services.

Assessment registration/deregistration Reg.: course registr.; dereg.: Office of the Dean of Studies
Repeat examination no repeat examination
Scale 1-6 0,1
Repeated registration as often as necessary
Responsible faculty Faculty of Business and Economics , studiendekanat-wwz@unibas.ch
Offered by Faculty of Business and Economics

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