Después de hacer estos cursos, me siento seguro creando visualizaciones y cuadros de mando profesionales
Shoebur RahmanEspecialista en adquisiciones, Giz Bangladesh
Descripción del curso
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. The code to get them can be found here. The data used in chapter 4 can be downloaded here.
Requisitos previos
No hay requisitos previos para este curso
Programa de formación
Contenido del curso
1
The building blocks
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.
- Welcome To The Course50 XP
- Getting a grasp of the basics50 XP
- Get a feel for the data100 XP
- The Portfolio Weights50 XP
- Calculating portfolio weights when component values are given100 XP
- The weights of an equally weighted portfolio50 XP
- The weights of a market capitalization weighted portfolio100 XP
- The Portfolio Return50 XP
- Calculation of portfolio returns100 XP
- From simple to gross and multi-period returns50 XP
- The asymmetric impact of gains and losses50 XP
- PerformanceAnalytics50 XP
- Buy-and-hold versus (daily) rebalancing50 XP
- The time series of asset returns100 XP
- The time series of portfolio returns100 XP
- The time series of weights100 XP
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 statisical 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
Performance drivers
In addition to studying portfolio performance based on the observed portfolio return series, it is relevant to find out how individual (expected) returns, volatilities and correlations interact to determine the total portfolio performance.
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.
R
Introduction to Portfolio Analysis in R
Curso
completado
