Advanced Asset Management

It is an advanced course in asset management (theory and applications). The course is given at the University of Evry/Paris-Saclay.

Description

• Portfolio Optimization
• Risk Budgeting
• Smart Beta, Factor Investing and Alternative Risk Premia
• Green and Sustainable Finance, ESG Investing and Climate Risk
• Machine Learning in Asset Management

Materials

• Textbook: Roncalli, T. (2013), Introduction to Risk Parity and Budgeting, Chapman & Hall/CRC Financial Mathematics Series

• Download the Presentation Slides on Asset Management

• Download the presentation slides
  1. Lecture 1 (Portfolio Optimization)
  2. Lecture 2 (Risk Budgeting)
  3. Lecture 3 (Smart Beta, Factor Investing and Alternative Risk Premia)
  4. Lecture 4 (Green and Sustainable Finance, ESG Investing and Climate Risk)
  5. Lecture 5 (Machine Learning in Asset Management)
• Download the Merged PDF File of the 5 lectures
• Download the TeX Source of the slides

• Download examination 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023.

References

1. Portfolio optimization
   • Bourgeron, T., Lezmi, E., and Roncalli, T. (2018), Robust Asset Allocation for Robo-Advisors, arXiv, arxiv.org/abs/1902.07449
   • Roncalli, T. (2013), Introduction to Risk Parity and Budgeting, Chapman & Hall/CRC Financial Mathematics Series
2. Risk Budgeting
   • Jurczenko, E. (2015), Risk-Based and Factor Investing, ISTE Press - Elsevier
   • Roncalli, T. (2013), Introduction to Risk Parity and Budgeting, Chapman & Hall/CRC Financial Mathematics Series
   • Roncalli, T. (2015), Introducing Expected Returns into Risk Parity Portfolios: A New Framework for Asset Allocation, Bankers, Markets & Investors, 138, www.ssrn.com/abstract=2321309
3. Smart Beta, Factor Investing and Alternative Risk Premia
   • Ang, A. (2014), Asset Management - A Systematic Approach to Factor Investing, Oxford University Press
   • Fama, E.F., and French, K.R. (1992), The Cross-Section of Expected Stock Returns, Journal of Finance, 47(2), pp. 427-465.
   • Hamdan, R., Pavlowsky F., Roncalli, T., and Zheng, B. (2016), A Primer on Alternative Risk Premia, SSRN, www.ssrn.com/abstract=2766850
   • Jusselin, P., Lezmi, E., Malongo, H., Masselin, C, Roncalli, T., and Dao, T-L. (2017), Understanding the Momentum Risk Premium: An In-Depth Journey Through Trend-Following Strategies, SSRN, www.ssrn.com/abstract=3083921
   • Koijen, R.S.J., Moskowitz, T.J., Pedersen, L.H., and Vrugt, E.B. (2018), Carry, Journal of Financial Economics, 127(2), pp. 197-225, NBER version
   • Roncalli, T. (2013), Introduction to Risk Parity and Budgeting, Chapman & Hall/CRC Financial Mathematics Series
   • Roncalli, T. (2017), Alternative Risk Premia: What Do We Know?, Chapter 10 of the book Factor Investing: From Traditional to Alternative Risk Premia, www.ssrn.com/abstract=2868425
4. Green and Sustainable Finance, ESG Investing and Climate Risk
   • Bennani, L., Le Guenedal, T, Lepetit, F., Ly, L., Mortier, V., Roncalli, T., and Sekine T. (2018), How ESG Investing Has Impacted the Asset Pricing in the Equity Market, SSRN, www.ssrn.com/abstract=3316862
   • Ben Slimane, M., Brard, E., Le Guenedal, T, Roncalli, T., and Sekine T. (2020), ESG Investing in Fixed Income: It's Time To Cross the Rubicon, SSRN, www.ssrn.com/abstract=3683477
   • Drei, A., Le Guenedal, T, Lepetit, F., Mortier, V., Roncalli, T., and Sekine T. (2020), ESG Investing in Recent Years: New Insights from Old Challenges, SSRN, www.ssrn.com/abstract=3683469
   • Eurosif (2019), European SRI Study 2018, http://www.eurosif.org
   • Le Guenedal, T. (2019), Economic Modeling of Climate Risks, SSRN, www.ssrn.com/abstract=3693661
   • Roncalli, T., Le Guenedal, T., Lepetit, F., Roncalli, T., and Sekine, T. (2020), Measuring and Managing Carbon Risk in Investment Portfolios, SSRN, www.ssrn.com/abstract=3681266
5. Machine Learning in Asset Management
   • Beck, A. (2017), First-Order Methods in Optimization, MOS-SIAM Series on Optimization, 25, SIAM
   • Boyd, S., Parikh, N., Chu, E., Peleato, B., and Eckstein, J. (2011), Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers, Foundations and Trends in Machine Learning, stanford.edu/~boyd
   • Chen, Y. (2018), Large-Scale Optimization for Data Science, Lecture Notes, www.princeton.edu/~yc5/ele538_optimization
   • Coqueret, G., and Guida, T. (2020), Machine Learning for Factor Investing, Chapman and Hall/CRC Financial Mathematics Series, www.mlfactor.com
   • Parikh, N., and Boyd, S. (2014), Proximal Algorithms, Foundations and Trends in Machine Learning, stanford.edu/~boyd
   • Perrin, S., and Roncalli, T. (2020), Machine Learning Optimization Algorithms & Portfolio Allocation, Chapter 8 of the book Machine Learning and Asset Management, arxiv.org/abs/1909.10233

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