Portfolio Optimization
Chapter 2 - Financial Data: Stylized Facts

R code

R code examples for Chapter 2 of the book:

Daniel P. Palomar (2024). Portfolio Optimization: Theory and Application. Cambridge University Press.

Loading packages

The following packages are used in the examples:

# basic finance
library(xts)                    # to manipulate time series of stock data
library(quantmod)               # to download stock data
library(pob)                    # book package with financial data
                                # install with: devtools::install_github("dppalomar/pob")
library(stochvol)               # to compute volatility envelope

# plotting
library(ggplot2)                # for nice plots
library(patchwork)              # for combining plots
library(viridisLite)            # for nice colors
library(reshape2)               # to reshape data

Prices and returns

Price time series of S&P 500:

# get data from Yahoo!Finance
library(quantmod)
sp500_prices  <- Ad(getSymbols("^GSPC", from = "2007-01-01", to = "2022-11-04", auto.assign = FALSE))

ggplot(fortify(sp500_prices, melt = TRUE), aes(x = Index, y = Value)) +
  geom_line(linewidth = 0.8, color = "blue", show.legend = FALSE) +
  scale_x_date(date_breaks = "1 year", date_labels = "%Y", date_minor_breaks = "1 month") +
  scale_y_log10() +
  xlab(element_blank()) + ylab(element_blank()) + ggtitle("S&P 500 price")