Insegnamento a.a. 2021-2022

20248 - ASSET MANAGEMENT

Department of Finance

Course taught in English
Go to class group/s: 31
DSBA (6 credits - I sem. - OP  |  SECS-P/11)
Course Director:
DAVIDE MASPERO

Classes: 31 (I sem.)
Instructors:
Class 31: DAVIDE MASPERO


Suggested background knowledge

Even if there is no formal requirements for this course you should be familiar with the basic concepts of theoretical finance such as, for example, Capital Asset Pricing Model and Market Efficiency. Students are expected to be familiar with the fundamentals of statistics and multiple regression analysis. We also take for granted the knowledge of basic calculus and matrix algebra.

Mission & Content Summary

MISSION

This is an intermediate to advanced course in asset management. This course aims at analyzing recent theoretical and empirical developments in portfolio management, putting strong emphasis on strategic asset allocation, risk management of asset management portfolios and the evaluation of investment performance. As relevant topics in the Asset Management industry change and evolve over time, so do course contents. As an example, topics such as factor investing and digital wealth advisory were introduced in the course over the last few years. At the end of the course students should have a comprehensive understanding of the relevant technical aspects of the Asset Management industry.

CONTENT SUMMARY

Among other topics, we shall review recent developments of traditional mean/variance analysis, the role of alternative asset classes in portfolio construction, the technical aspects of long/short investing, factor investing,  risk management techniques designed specifically for asset management portfolios,the impact of digital advisory services and of ESG principles. We cover in detail the main aspects of the active/passive management debate. We devote a relevant portion of our time to the practical implementation of portfolio management strategies. The course includes four info room sessions and three sessions with industry experts.


Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...

Identify and describe theoretical advancements in the following topics:

  • Alternatives to mean-variance asset allocation models.
  • Dynamic asset allocation models.
  • Role of alternative asset classes.
  • Impact of exchange risk hedging.
  • Active vs. passive manaagement
  • Factor models.
  • Style analysis.
  • Risk measurement and management.
  • Performance evaluation.
  • Digital advisory services.
  • ESG investment policies

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Use advanced asset allocation models, build long-short portfolios, measure and manage the risk of asset management portfolios, evaluate the performance of asset managers and discuss relevant current issues in the asset management industry, such as digital advisory, the growth of passive and factor-based products. the emergence of ESG compliant investment policies.

Teaching methods

  • Face-to-face lectures
  • Online lectures
  • Guest speaker's talks (in class or in distance)
  • Exercises (exercises, database, software etc.)
  • Group assignments

DETAILS

  • Guest speakers are portfolio managers operating both in the long-only and in the long-short environments.
  • Exercises are simple problems to be solved at home and discussed in class.
  • The group assignment asks you to apply the course material on real data, using Excel or other software. This assignment should help you better understand how the class material can be applied, as well as prepare you for solving practical investments problems commonly encountered in the world of finance. Groups are made by 5 people.The group assignment is divided into two parts:  a) Style analysis and portfolio positioning vs. efficient frontier and b) Risk management and performance evaluation of asset management portfolios.

Assessment methods

  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
    x
  • Group assignment (report, exercise, presentation, project work etc.)
    x
  • Active class participation (virtual, attendance)
x    

ATTENDING STUDENTS

Your course grade reflects your performance on a final written test and the group assignment, with weights determined as follows:

  • Final online written test: 50%
  • Assignment – part 1: 25%
  • Assignment – part 2: 25%

Both the final test and the assignment are graded out of 30. The assignment is only valid together with the December test (for exchange students leaving Italy in December) and  the two online written tests to be held in January 2022.

A minimum grade of 16/30 in the final written test is required in order to pass the course regardless of the overall average inclusive of the assignment.

The goal of the groupwork is to enable students to put in practice the operational learning outcomes of the course, while the final written test will verify the learning process with respect to the theoretical topics covered in class.

 


NOT ATTENDING STUDENTS

Non attending students are graded exclusively by means of a final online written test including both qualitative and quantitative questions.

Qualitatative questions will be aimed at verifying the understanding of the theoretical topics covered in class, while quantitative questions will veriffy the students' ability to tackle operational tasks.


Teaching materials


ATTENDING AND NOT ATTENDING STUDENTS

There is no textbook for this course. Since the teaching material is revised and updated every year, in line with changes in the syllabus, it consists of a  number of journal articles and  slides. You have to study in depth all compulsory articles. You also receive indications about optional articles and reference books on specific topics. Compulsory articles for the whole course will be posted  on the Blackboard page of the course at the beginning of the course. All the remining teaching materials, including optional articles, slides and the text of Group Assignments will be posted on the Blackboard page of the course approximately one week before the classes.

Last change 24/08/2021 15:06