Schedule

ARF, Spring 2026. Room 2209, Monday & Thursday 16:00 – 17:30. Zoom https://us02web.zoom.us/j/81501793754

Part 1

Session 1. Monday, January 12.

• Reading. Course syllabus (this document).
• Activity. Welcome and introduction to the course.
• Activity. Set up your free DataCamp account. Invitations have been sent to your UDEM student email.
• Activity. Define your team of no more than 4 members.
• Bonus points. Reto grupal. Al menos durante este semestre es necesario que te suscribas al canal de YouTube ahyaentendi. Si todo el grupo lo hace, entonces asigno +5 a todos mis alumnos de este grupo.

Session 2. Thursday, January 15.

• Reading. Course syllabus (this document).
• Activity. How DataCamp and DataLab works.
• Bonus points. Reto colectivo. Tengo aproximadamente 90 alumnos este semestre, y todos tienen que ver los siguientes tres videos: Primavera 2026. Si todos mis alumnos lo hacen, equivale a 180 horas de reproducción. En caso de que al jueves 15 de enero a las 7:00pm se alcance esa meta, entonces asigno +10 a todos mis alumnos.

Session 3. Monday, January 19.

• Topic 1/3: Risk management.
• Obligatorio. Acepta las normativas del curso: Formulario.
• Reading. Hull (2018), chapter 1, section 1.1: Risk vs. return for investors.
• Reading. Hull (2018), chapter 1, section 1.2: The efficient frontier.
• Complementary material. PowerPoint slides: John C. Hull.
• Complementary material. Drake and Fabozzi (2010), chapter 16: The theory of portfolio selection.
• Complementary material. Brealey et al. (2020), chapter 8: Portfolio theory and the capital asset pricing model.
• Complementary material. Ruppert and Matteson (2011), chapter 16: Portfolio selection.
• Complementary material. Lozano (2024b), chapter 2: Prices and returns.
• Complementary material. Lozano (2024b), chapter 4: Asset allocation.

Session 4. Thursday, January 22.

• Video. Carteras de inversión | Diseño y análisis.
• Video. Cartera óptima con rendimiento objetivo.
• Reading. Hull (2018), chapter 1, section 1.3: The capital asset pricing model.
• Reading. Hull (2018), chapter 1, section 1.4: Arbitrage pricing theory.
• Complementary material. Lozano (2024b), chapter 3: Asset pricing.

Session 5. Monday, January 26.

• Reading. Hull (2018), chapter 1, section 1.5: Risk vs. return for companies.
• Reading. Hull (2018), chapter 1, section 1.6: Risk management by financial institutions.
• Complementary material. Crouhy, Galai, and Mark (2014), video 1 The building blocks of risk management.
• Complementary material. Crouhy, Galai, and Mark (2014), video 2 Risk management: A helicopter view.
• Complementary material. Crouhy, Galai, and Mark (2014), video 3 Corporate risk management: A primer.

Session 6, . Thursday, January 29.

• Reading. Hull (2018), chapter 1, section 1.7: Credit ratings.
• Reading. Hull (2022), chapter 24, section 24.1: Credit ratings.
• Reading. Hull (2022), chapter 24, section 24.2: Historical default probabilities.
• Reading. Hull (2022), chapter 24, section 24.3: Recovery rates.
• Complementary material. Fictional video (warning, it has offensive language): FrontPoint partners confronts Morgan Stanley risk assessors and S&P.

Holiday. Monday, February 2.

Session 7. Thursday, February 5.

• Reading. Hull (2022), chapter 10, section 10.1: Types of options.
• Reading. Hull (2022), chapter 10, section 10.2: Option positions.
• Video. Estrategias de cobertura y especulación usando opciones financieras.
• Reading. Lozano (2024c), chapter 1: Payoff functions.

Session 8. Monday, February 9.

• Video. Estrategias de cobertura y especulación usando opciones financieras.
• Complementary material. Riesgo financiero. Spotify . Hablemos de economía y política. Asociación para la Conciencia Económica y Política (ACEyP). Noviembre 2024.
• Activity. \(H_1\) review.

Session 9. Thursday, February 12.

• Graded. Complete \(H_1\) before 10:00 a.m.
• Activity. \(H_1\) presentations 1/2.
• No conozco la fecha límite, pero deben completar la encuesta avanza 180 por favor.

Session 10. Monday, February 16.

• Activity. \(H_1\) presentations 2/2.

Session 11. Thursday, February 19.

• Activity. \(E_1\) review.

Session 12, . Monday, February 23.

• Graded. \(E_1\) Instructions in Blackboard.
• The link to complete \(H_1\) and \(E_1\) co-evaluation will be available on Blackboard right after the exam.

Part 2

Session 13. Thursday, February 26.

• Activity. Discuss \(E_1\) answers.
• Bonus points. The wheel of fortune 1/3. This is a class activity.
• Graded. Submit \(H_1\) and \(E_1\) co-evaluation before 10:00 a.m. Instructions in Blackboard.
• Bonus points. Data Analyst in R. Complete DataCamp assignment before 10:00 a.m. It is not required to send evidence of having completed because the system automatically records if it was completed on time.
• Non graded. Mention DataCamp in social media if possible. Instructions.

Session 14. Monday, March 2.

• Activity. \(H_2\) review.

Session 15. Thursday, March 5.

• Graded. Complete \(H_2\) before 10:00 a.m.
• Activity. \(H_2\) presentations 1/2.

Session 16. Monday, March 9.

• Activity. \(H_2\) presentations 2/2.

Session 17. Thursday, March 12.

• Activity. \(E_2\) review.

Holiday. Monday, March 16.

Session 18, . Thursday, March 19.

• Graded. \(E_2\) Instructions in Blackboard.
• The link to complete \(H_2\) and \(E_2\) co-evaluation will be available on Blackboard right after the exam.

Part 3

Session 19, . Monday, March 23.

• Activity. Discuss \(E_2\) answers.
• Bonus points. The wheel of fortune 2/3. This is a class activity.
• Graded. Submit \(H_2\) and \(E_2\) co-evaluation before 10:00 a.m. Instructions in Blackboard.

Session 20, . Thursday, March 26.

• Topic 2/3: Credit default prediction using statistical and machine learning techniques.
• Reading. Lozano (2024a), chapter 1, section 1.1: Explore the database.
• Complementary material. Retos y oportunidades en el aprendizaje de ciencia de datos en las escuelas de negocios. Available at: Spotify ; YouTube ; LinkedIn . Café de Datos, Datlas. Temporada 9, capítulo 132. Diciembre 2023.
• Bonus points. Associate Data Analyst in SQL. Complete DataCamp assignment before 10:00 a.m. It is not required to send evidence of having completed because the system automatically records if it was completed on time.

Holiday. Monday, March 30.

Holiday. Thursday, April 2.

Session 21. Monday, April 6.

• Reading. Lozano (2024a), chapter 1, section 1.2: Logistic models.
• Complementary material. Hanck et al. (2020), chapter 11: Regression with a binary dependent variable.
• Complementary material. Hull (2020), chapter 3: Supervised learning: linear regression.

Session 22. Thursday, April 9.

• Reading. Lozano (2024a), chapter 1, section 1.3: Prediction and model evaluation.

Session 23. Monday, April 13.

• Reading. Lozano (2024a), chapter 1, section 1.3: Prediction and model evaluation.
• Complementary material. Alonso and Carbó Martínez (2021): Understanding the performance of machine learning models to predict credit default: a novel approach for supervisory evaluation.

Session 24. Thursday, April 16.

• Reading. Lozano (2024a), chapter 1, section 1.4: The bank strategy.

Session 25, . Monday, April 20.

• Topic 3/3: Estimating firm default risk using the Merton structural model.
• Reading. Hull (2022), chapter 24, section 24.6: Using equity prices to estimate default probabilities.
• Complementary material. Video: Ethics and trust in the investment profession.

Session 26. Thursday, April 23.

• Reading. Hull (2022), chapter 24, section 24.6: Using equity prices to estimate default probabilities.
• Reading. Lozano (2024a), chapter 2, section 2.2: The estimation.
• Complementary material. Brealey et al. (2020), chapter 23 Credit risk and the value of corporate debt.
• No conozco la fecha límite, pero deben completar la encuesta avanza 360 por favor.

Session 27. Monday, April 27.

• Reading. Hull (2022), chapter 24, section 24.6: Using equity prices to estimate default probabilities.
• Reading. Lozano (2024a), chapter 2, section 2.3: Inside view of the Merton’s model.
• Complementary material. Video: FRM: How \(d_2\) in Black-Scholes becomes PD in Merton model.

Session 28. Thursday, April 30.

• Reading. Hull (2022), chapter 24, section 24.6: Using equity prices to estimate default probabilities.
• Reading. Lozano (2024a), chapter 2, section2.4: The probability of default as a function of some parameters.
• Complementary material. Video: Measuring credit risk.

Session 29. Monday, May 4.

• Reading. Hull (2022), chapter 24, section 24.6: Using equity prices to estimate default probabilities.
• Reading. Lozano (2024a), chapter 2, section 2.5: GoT: capital structure.
• Complementary material. The Plastic Recycling Myth.

Session 30, . Thursday, May 7.

• Activity. \(E_F\) review.
• Bonus points. The wheel of fortune 3/3. This is a class activity.
• Bonus points. Data Analyst Certification. Complete DataCamp assignment before 10:00 a.m. It is not required to send evidence of having completed because the system automatically records if it was completed on time.
• Farewell .

The end

Final exam, . Thursday, May 14, 16:00 – 18:00.

• Graded. \(E_F\) Instructions in Blackboard.

Alonso, Andrés, and José Manuel Carbó Martínez. 2021. “Understanding the Performance of Machine Learning Models to Predict Credit Default: A Novel Approach for Supervisory Evaluation.” Documentos de Trabajo/Banco de España, 2105. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3774075.

Brealey, Richard A, Stewart C Myers, Franklin Allen, and Pitabas Mohanty. 2020. Principles of Corporate Finance. 13th ed. McGraw-Hill Education.

Crouhy, Michel, Dan Galai, and Robert Mark. 2014. The Essentials of Risk Management. 2nd ed. McGraw-Hill.

Drake, Pamela Peterson, and Frank J Fabozzi. 2010. The Basics of Finance: An Introduction to Financial Markets, Business Finance, and Portfolio Management. Vol. 192. John Wiley & Sons.

Hanck, Christoph, Martin Arnold, Alexander Gerber, and Martin Schmelzer. 2020. Introduction to Econometrics with R. Essen: University of Duisburg-Essen. https://www.econometrics-with-r.org/.

Hull, John C. 2018. Risk Management and Financial Institutions. 5th ed. Prentice Hall.

———. 2020. Machine Learning in Business: An Introduction to the World of Data Science. Amazon Distribution.

———. 2022. Options, Futures, and Other Derivatives. 11th ed. Prentice Hall.

Lozano, Martín. 2024a. Credit Risk with R. GitHub Pages. https://mlozanoqf.github.io/tutorial_arf/.

———. 2024b. Financial Modeling in R. GitHub Pages. https://mlozanoqf.github.io/tutorial_pmf/.

———. 2024c. Options and VaR with R. GitHub Pages. https://mlozanoqf.github.io/tutorial_if/.

Ruppert, David, and David S Matteson. 2011. Statistics and Data Analysis for Financial Engineering with R Examples. Vol. 13. Springer. https://github.com/mlozanoqf/Statistical-Computing .