Quantitative Finance

Course: Quantitative Finance
Workload: 30h
Prerequisite: Quantitative Finance requires Probability, Statistics, and Investments. The course also requires familiarity with calculus's basic tools and with a software package that can be used for numerical computation (such as Excel, Matlab, R, and Python).
Professor: Marcelo Verdini Maia

Introduction. Asset Allocation. Options Strategies. Swaps, Forwards, and Futures Strategies. Fixed Income Portfolio Management. Equity Portfolio Management. Risk Management.

Mandatory Bibliography:
1. Ali Hirsa e Salih Nefcti. An Introduction of the Mathematics of Financial Derivatives.
Academic Press, 3rd edition, 2013.
2. Andrew Pole. Statistical Arbitrage: Algorithmic Trading Insights and Techniques.
3. Aurelien Gueron. Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow:
Concepts, Tools, and Techniques to Build Intelligent Systems. Third Edition, 2023, O’Reilly
4. Bodie, Kane e Marcus. Investments. McGraw-Hill
5. Bruce Tuckman and Angel Serrat. Fixed Income Securities: Tools for Today's Markets
6. C. Bishop, Pattern Recognition and Machine Learning, 2006, Springer
7. Damiano Brigo and Fabio Mercurio, Interest Rate Models - Theory and Practice, 2nd edition, Springer, 2006
8. Darrel Duffie. Dynamic Asset Pricing Theory.
9. Das, Satyiajit. Traders, Guns & Money, 3rd ed. Financial Times/Prentice Hall 2006.
10. J. Gregory, The xVA Challenge: Counterparty Credit Risk, Funding, Collateral and Capital, third edition, 2015, Wiley
11. John C. Hull. Options, Futures, and Other Derivatives, 11th edition, Pearson, 2021.
12. Lawrence McMillan. Options as a Strategic Investment. Prentice Hall Press, 5th edition, 2012.
13. M. Kuhn and K. Johnson, Applied Predictive Analytics, 2013, Springer
14. M. Lopez de Prado, Advances in Financial Machine Learning, 2018, Wiley
15. Martelini, Priaulet, Priaulet. Fixed Income Securities: Valuation, Risk Management and Portfolio Strategies.
16. Paul Wilmott, Machine Learning: An Applied Mathematics Introduction, 2019, Wiley
17. Paul Willmott. Paul Wilmott Introduces Quantitative Finance, second edition, 2007, John Wiley.
18. Paul Wilmott, Sam Howison, and Jeff Dewynne. The Mathematics of Financial Derivatives: A Student Introduction.
19. Riccardo Rebonato, Volatility and Correlation, 2nd edition, Wiley, 2004.
20. Richard C. Grinold and Ronald N. Kahn Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk.
21. Sheldon Natenberg. Option Volatility and Pricing: Advanced Trading Strategies and Techniques.
22. T. Hastie et al., The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2009 (2nd edition), Springer
23. Veronesi, Pietro. Fixed Income Securities: Valuation, Risk, and Risk management, Wiley 2010
24. Yves Hilpisch, Artificial Intelligence in Finance, 2020, O’Reilly
25. Yves Hilpisch, Python for Finance, 2019, O′Reilly