Portfolio Selection and Risk Management (Coursera)

Portfolio Selection and Risk Management (Coursera)
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Portfolio Selection and Risk Management (Coursera)
When an investor is faced with a portfolio choice problem, the number of possible assets and the various combinations and proportions in which each can be held can seem overwhelming. In this course, you’ll learn the basic principles underlying optimal portfolio construction, diversification, and risk management. You’ll start by acquiring the tools to characterize an investor’s risk and return trade-off. You will next analyze how a portfolio choice problem can be structured and learn how to solve for and implement the optimal portfolio solution. Finally, you will learn about the main pricing models for equilibrium asset prices.

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Learners will:

• Develop risk and return measures for portfolio of assets

• Understand the main insights from modern portfolio theory based on diversification

• Describe and identify efficient portfolios that manage risk effectively

• Solve for portfolio with the best risk-return trade-offs

• Understand how risk preference drive optimal asset allocation decisions

• Describe and use equilibrium asset pricing models.


Course 2 of 5 in the Investment and Portfolio Management Specialization.


Syllabus


WEEK 1

Introduction & Risk and Return

This module introduces the second course in the Investment and Portfolio Management Specialization. In this module, we discuss one of the main principles of investing: the risk-return trade-off, the idea that in competitive security markets, higher expected returns come only at a price – the need to bear greater risk. We develop statistical measures of risk and expected return and review the historical record on risk-return patterns across various asset classes.


WEEK 2

Portfolio construction and diversification

In this module, we build on the tools from the previous module to develop measure of portfolio risk and return. We define and distinguish between the different sources of risk and discuss the concept of diversification: how and why putting risky assets together in a portfolio eliminates risk that yields a portfolio with less risk than its components. Finally, we review the quantitative tools that help us identify the ‘best’ portfolios with the least risk for a given level of expected return by considering a numerical example using international equity data.


WEEK 3

Mean-variance preferences

In this module, we describe how investors make choices. Specifically, we look at how utility functions are used to express preferences. We review measures to describe investors’ attitude towards risk. Finally, we discuss how we can summarize investors’ preferences using a specific utility function: mean-variance preferences.


WEEK 4

Optimal capital allocation and portfolio choice

In this module, you will learn about mean-variance optimization: how to make optimal capital allocation and portfolio choice decisions when investors have mean-variance preferences. This was one of the ground-breaking ideas in finance. We will formally set up the investor’s portfolio choice problem and learn step-by-step how to solve for the optimal allocation and risky portfolio choice given a set of risky securities. You will also have an opportunity to apply these techniques to a numerical example. This module is slightly more technical than the others. Stick with it… you will not regret it!


WEEK 5

Equilibrium asset pricing models

In this module, we build on the insights obtained from modern portfolio theory to understand how risk and return are related in equilibrium. We first look at the main workhorse model in finance, the Capital Asset Pricing Model and discuss the expected return-beta relationship. We then turn our attention to multi-factor models, such as the Fama-French three-factor model.



MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Course Auditing
41.00 EUR/month

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.