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# Introduction to Portfolio Analysis in R

Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.

5 Hours14 Videos57 Exercises

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## Course Description

A golden rule in investing is to always test the portfolio strategy on historical data, and, once you are trading the strategy, to constantly monitor its performance. In this course, you will learn this by critically analyzing portfolio returns using the package PerformanceAnalytics. The course also shows how to estimate the portfolio weights that optimally balance risk and return. This is a data-driven course that combines portfolio theory with the practice in R, illustrated on real-life examples of equity portfolios and asset allocation problems. If you'd like to continue exploring the data after you've finished this course, the data used in the first three chapters can be obtained using the tseries-package.

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1. 1

### The Building Blocks

Free

Asset returns and portfolio weights; those are the building blocks of a portfolio return. This chapter is about computing those portfolio weights and returns in R.

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Welcome to the course
50 xp
Getting a grasp of the basics
50 xp
Get a feel for the data
100 xp
The portfolio weights
50 xp
Calculating portfolio weights when component values are given
100 xp
The weights of an equally weighted portfolio
50 xp
The weights of a market capitalization-weighted portfolio
100 xp
The portfolio return
50 xp
Calculation of portfolio returns
100 xp
From simple to gross and multi-period returns
50 xp
The asymmetric impact of gains and losses
50 xp
PerformanceAnalytics
50 xp
50 xp
The time series of asset returns
100 xp
The time series of portfolio returns
100 xp
The time series of weights
100 xp
2. 2

### Analyzing Performance

The history of portfolio returns reveals valuable information about how much the investor can expect to gain or lose. This chapter introduces the R functionality to analyze the investment performance based on a statistical analysis of the portfolio returns. It includes graphical analysis and the calculation of performance statistics expressing average return, risk, and risk-adjusted return over rolling estimation samples.

3. 3

### Performance Drivers

In addition to studying portfolio performance based on the observed portfolio return series, it is relevant to determine how individual (expected) returns, volatilities, and correlations interact to determine the total portfolio performance.

4. 4

### Optimizing the Portfolio

We have up to now considered the portfolio weights as given. In this chapter, you learn how to determine in R the portfolio weights that are optimal in terms of achieving a target return with minimum variance, while satisfying constraints on the portfolio weights.

### In the following Tracks

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#### Quantitative Analyst with R

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Datasets

Stock prices for Apple and MicrosoftBonds pricesCommodities pricesEquities pricesStock prices for DIJAReal estate pricesDaily prices in S&P 500

Collaborators

Kris Boudt

Professor of Finance and Econometrics at VUB and VUA

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