Course 2019-2020 a.y.

After going over `The introduction to the course’ lecture, we address the following:

• Basic knowledge in finance, statistics, probability.
• Introduction to programming.
• Returns: definitions, interpretation; measurement; data collection; analysis.
• Modeling and Simulating Returns.
• Estimating Linear Models of Returns.
• Interpreting Regression Results.
• TBA.
• High-order risk sources.

The objective of this course is to introduce the main econometric methods and techniques used in empirical finance. This is an ambitious task that brings together different type of knowledge: finance theory, statistics, programming. You learn how to use software, to specify, estimate and simulate model of financial data to be used for asset allocation, risk measurement and risk management. The course is designed to give opportunities. The decision of how many opportunities to take and how to take them is left to course participants. 

• Apply econometric techniques to assset allocation and risk measurement.

• Face-to-face lectures
• Exercises (exercises, database, software etc.)

The main inputs provided to the students are references, slides, notes, draft R codes and exercises designed to provide challenges that stimulate learning. The empirical applications are based on databases freely available on the web.

The final grade depends on the individual performance of each student in all of the course related examinations (final exam, individual quizzes,...). The grading weights are detailed in class. With the purpose of measuring the acquisition of the above-mentioned learning outcomes, the students’ assessment is based on the following components:

• In-class participation aimed to test the students’ ability to interact in a constructive way and to think critically.
• On-line quizzes. These quizzes are aimed to assess on a regular basis the full understanding of the main contents addressed in class. These quizzes guide the students to better review the topics addressed during our lectures.
• Homework(s). These homeworks are designed to help students use appropriate software in order to specify, estimate, and simulate models of financial data. These models  are used for asset allocation, risk measurement, and risk management.
• Written exam. The written exam consists of exercises and open questions aimed at assessing students’ ability to: 
  • Apply the analytical tools illustrated during the course.
  • Discuss finance theory and statistics.
  • Solve problems related to asset allocation, risk measurement, and risk management. 
• Students are expected to take a written in-class quiz and a written exam at the end of the course. If a student cannot take the in-class quiz, the weight assigned to the in-class quiz is shifted to the final exam.

• J. COCHRANE, Asset pricing. Revised Edition.
• TBA, communicated by July.