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Intermediate Portfolio Analysis in R

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

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Course Description

This course builds on the fundamental concepts from Introduction to Portfolio Analysis in R and explores advanced concepts in the portfolio optimization process. It is critical for an analyst or portfolio manager to understand all aspects of the portfolio optimization problem to make informed decisions. In this course, you will learn a quantitative approach to apply the principles of modern portfolio theory to specify a portfolio, define constraints and objectives, solve the problem, and analyze the results. This course will use the R package PortfolioAnalytics to solve portfolio optimization problems with complex constraints and objectives that mirror real world problems.
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In the following Tracks

Finance Fundamentals in R

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Quantitative Analyst in R

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  1. 1

    Introduction and Portfolio Theory

    Free

    This chapter will give you a brief review of Modern Portfolio Theory and introduce you to the PortfolioAnalytics package by solving a couple portfolio optimization problems.

    Play Chapter Now
    Welcome to the course!
    50 xp
    Load the PortfolioAnalytics package
    100 xp
    Solve a simple portfolio optimization problem
    100 xp
    Visualize results
    100 xp
    Modern Portfolio Theory objective
    50 xp
    Defining risk
    50 xp
    Challenges of portfolio optimization
    50 xp
    Quadratic utility
    50 xp
    Maximize quadratic utility function
    100 xp
    Introduction to PortfolioAnalytics
    50 xp
    Key design goals
    50 xp
  2. 2

    Portfolio Optimization Workflow

    The focus of this chapter is a detailed overview of the recommended workflow for solving portfolio optimization problems with PortfolioAnalytics. You will learn how to create a portfolio specification, add constraints, objectives, run the optimization, and analyze the results of the optimization output.

    Play Chapter Now
    Portfolio specification, constraints, and objectives
    50 xp
    Create a portfolio specification
    100 xp
    Add constraints
    100 xp
    Add objectives
    100 xp
    Running optimizations
    50 xp
    Single-Period optimization
    100 xp
    Optimization with periodic rebalancing
    100 xp
    Global solvers
    50 xp
    Analyzing optimization results
    50 xp
    Objective measure values
    100 xp
    Optimal weights
    100 xp
  3. 3

    Objective Functions and Moment Estimation

    In this chapter, you will learn about estimating moments, characteristics of the distribution of asset returns, as well as custom objective functions.

    Play Chapter Now
    Introduction to moments
    50 xp
    Sample moment estimates
    100 xp
    Advanced moment estimates
    100 xp
    Method for estimating moments
    50 xp
    Custom moment functions
    50 xp
    Define a custom moment function
    100 xp
    Optimization with custom moment function
    100 xp
    Objective functions
    50 xp
    Custom objective function
    100 xp
    Optimization with custom objective function
    100 xp
  4. 4

    Application

    In the final chapter of the course, you will solve a portfolio optimization problem that mimics a real world real world example of constructing a portfolio of hedge fund strategy with different style definitions.

    Play Chapter Now
    Application
    50 xp
    Compute benchmark returns
    100 xp
    Define the portfolio optimization problem
    100 xp
    Benchmark
    50 xp
    Optimization backtest
    50 xp
    Backtest with periodic rebalancing
    100 xp
    Refine constraints and objectives
    100 xp
    Do improved estimates lead to improved performance?
    100 xp
    Analyze results and compare to benchmark
    100 xp
    Congratulations!
    50 xp
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In the following Tracks

Finance Fundamentals in R

Go To Track

Quantitative Analyst in R

Go To Track

datasets

Portfolio specifications object IPortfolio specifications object IISet of random portfolios ISet of random portfolios II

collaborators

Collaborator's avatar
Lore Dirick
Collaborator's avatar
Davis Vaughan

prerequisites

Introduction to Portfolio Analysis in R
Ross Bennett HeadshotRoss Bennett

Co-author of PortfolioAnalytics R package

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