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  3. Intermediate Portfolio Analysis in R
  • 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.

  • 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.

  • 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.

  • 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.

Initializing

Exercise

Optimization with custom objective function

This exercise builds on the previous exercise and we will run the optimization with the custom objective function that computes portfolio annualized standard deviation. Because an objective function can be any valid R function, we add a risk objective for the pasd() function. The set.portfolio.moments() function will not recognize the pasd() objective name, so we need to create a custom moment function to calculate the second moment, sigma. We will solve the problem using random portfolios as the optimization method.

Instructions

100 XP
  • Add the custom objective function you created in the previous exercise to the portfolio specification object.
  • Print the portfolio specification object to see the constraints and objective.
  • Run the optimization. The name of the custom moment function is set_sigma.
  • Print the results of the optimization.