The aim of the course is to provide a detailed overview of various financial instruments; to provide insight into the relationship between risk and return; to provide insight into the use of asset pricing theory. nother goal is to equip students with a solid background in the different investment strategies in the derivatives markets and arbitrage opportunities

Knowledge and understanding: By the end of the course, students should be able to: • understand risk-return relationship, market efficiency, investment strategies derivatives; fund management, asset price dynamics; • collect, analyse, model and critically interpret investments related to business; • use the software Matlab/Python for investment analysis. Applying knowledge and understanding: Upon completing the study program, students will be able to: • use asset pricing models; • use financial thinking to formalise complex problems and apply analytical tools to solve them; • develop investment decisions; • coding. Making judgements: Upon completing the study program, students will be able to: • face complex problems and apply analytical tools in an independent way; • give original interpretations to the results obtained from the data analysis; • these are requirements that students develop during the weekly problem sets. Communications Skills: Upon completing the study program, students will be able to: • develop the ability to communicate in written form through completing weekly assignments and participating to class discussions; • communicate in financial language; • communicate in software language. Learning skills: Upon completing the study program, students will be able to: • analyse risk-return, market efficiency, arbitrage opportunities; • autonomously understand and interpret new more advanced techniques and adapt them to the specific reference context; • problem solving; • decision making; • use the acquired knowledge to access to prominent job positions within hedge funds, investment banking, consulting companies and institutions and/or to access to further advanced learning programs such as PhD or Master’s in Finance or Management.

The course will treat the following topics: • Efficient and inefficient markets • risk-return • CAPM • Active investment • Equity strategies • Macro strategies • Fixed-income arbitrage • Derivatives The extended program provided below is meant to be flexible and adapted to the course dynamics and students’ interest.

- Lasse Heje Pedersen. Efficiently Inefficient. How Smart Money are Invested and Market Prices are Determined. Princeton University Press. Short: P - John C. Hull. Options, Futures and Other Derivatives, Pearson (9thEdition). Short. H - Y. Hilpisch. Python for Finance: Mastering Data-Driven Finance, O'Reilly, 2nd edition (suggested) Other references: - Y. Hilpsch, Derivatives Analytics with Python: Data Analysis, Models, Simulation, O'Reilly - Bodie, Kande & Marcus – Investments -10th edition. McGraw Hill Please note that additional readings might be required during the course.

Frontal lectures will be complemented by practical exercises, both individual and group works, that will require the use of a software. Solutions will be discussed in class. Students’ participation during lectures is essential.

Class participation (15%), weekly problem sets (55%), final exam (30%). There will be weekly assignments that students will solve in groups of at most three, due one week later the assignment date. Together with class participation, they will contribute to 70% of the final grade. The assignments require using Matlab/Python to be completed. The final exam will be in written form. Further details will be given in due course. There will be no midterm exam.

Full course marks and personal judgment

no