Markets, Trading and Technology

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The course is suitable for PhD students but most of its content is
absolutely accessible to undergraduate
students of the scientific area. There are no prerequisites except an active interest in the subject. An introductory knowledge of notions of quantitative finance, although not necessary, can make the course easier to use.


- An introduction to equities, options, futures and other financial products

- Index funds, exchange traded funds, passive vs active investing, smart beta

- Volatility and options trading

- valuation, trend following and technical analysis

- Algorithmic Trading

- High Frequency Trading and Statistical Arbitrage

- Reinforcement and Machine Learning for trading
- Centralized and Decentralized Exchanges

- Seminar on blockchain e decentralized exchanges
- Seminar on NLP and financial trading
- possible seminar on NFTs and art investing

Educational aims

The goal of the course is to provide students with an overview of the structure of financial markets and of trading and investment methodologies

Bibliographical references

Hull Options, Futures and other Derivatives
Marco Avellaneda and Jeong-Hyun Lee, Statistical Arbitrage in the U.S. Equities Market, Quantitative Finance
Lehar, A and Parlour CA. Decentralized exchanges, working paper, University of Calgary and University of California, Berkeley (2021)
Barbon, A, Ranaldo, A. On The Quality Of Cryptocurrency Markets: Centralized Versus Decentralized Exchanges, arXiv:2112.07386 (2021)Ben Hambly, Renyuan Xu, Huining Yang,  Recent advances in reinforcement learning in finance, Mathematical Finance (2023)
Other papers and material will be provided during the course.