The project objectives are (1) to analyze and determine the parameters impacting the quality of synthetic investment portfolios using fundamental algorithms from Mathematical Finance (MathFinance) and Machine Learning and (2) to learn and develop by ourselves platform-based AI agents for portfolio creation and performance forecasting.
In particular we construct synthetic investment portfolios whose rating mechanisms are learned by Machine Learning algorithms. By combining methods from the theory of MathFinance and Data Science, we apply Monte Carlo simulations for portfolio loss distribution that enable estimates of future portfolio performance and investment recommendations. We then aim to bake these these insights into an automatized web-based AI agent using popular Agent-as-a-Service (AaaS) platforms like e.g. n8n.
Target audience: BW/IM/IWI/Erasmus
Course language: English
Credit Points: 4 SWS | 5 ECTS
Proof of performance: (Team-)Presentation + written exposition
Course day: Project Jour Fixe Mondays 2pm - 5pm
Registration: Email to jianing.zhang@tha.de until October 5th
- Dozent/in: Jianing Zhang