Added test code

value-vs-growth/test-value-vs-growth.R

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+#!/usr/bin/env Rscript
+
+# Load libraries
+library(ggplot2)
+library(stringr)
+library(scales)
+library(ggthemes)
+library(PerformanceAnalytics)
+library(RColorBrewer)
+
+
+# The URL for the data
+url.name     <- "http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp"
+file.name    <- "25_Portfolios_5x5_CSV.zip"
+full.url     <- paste(url.name, file.name, sep="/")
+
+# You can change the ending date of the analysis by changing these variables
+# Beware, however, that the source datafile may only be updated annually
+# and therefore the most recent monthly may not be available
+
+end.year     <- 2017
+end.month    <- 5
+window.width <- 5*12 # The rolling window width. 5 Years in this case
+
+# Download the data and unzip it
+
+temp.file <- tempfile()
+download.file(full.url, temp.file)
+file.list <- unzip(temp.file, list=TRUE)
+
+print(temp.file)
+print(as.character(file.list[1,1]))
+stop("End of script.")
+
+# Parse the data
+french.data   <- read.csv(unzip(temp.file,
+                                files=as.character(file.list[1,1])),
+                          skip=19,
+                          header=TRUE,
+                          stringsAsFactors=FALSE)
+names(french.data)[[1]] <- "DATE"
+
+# Now we want to remove all the data below the end date
+ds.year     <- as.numeric(substr(french.data$DATE[[1]],1,4))
+ds.month    <- as.numeric(substr(french.data$DATE[[1]],5,6))
+num.rows    <- 12*(end.year-ds.year)+(end.month-ds.month)+1
+french.data <- head(french.data,num.rows)
+date.seq    <- as.Date(paste(french.data$DATE,"01",sep=""),"%Y%m%d")
+french.data$DATE <- date.seq
+
+# Transform the data so that the return cells are numeric decimal format
+for (i in 2:ncol(french.data)) french.data[,i] <- as.numeric(str_trim(french.data[,i]))
+for (i in 2:ncol(french.data)) french.data[,i] <- french.data[,i]/100
+
+# Now we calculate the the HML sequence from the factor sequences
+# Column names are: DATE SMALL.LoBM ME1.BM2 SMALL.HiBM BIG.LoBM ME2.BM2 BIG.HiBM
+fd <- french.data
+
+french.data$Hi.Lo <-
+  0.2*( fd$SMALL.HiBM + fd$ME2.BM5 + fd$ME3.BM5 + fd$ME4.BM5 + fd$BIG.HiBM ) -
+  0.2*( fd$SMALL.LoBM + fd$ME2.BM1 + fd$ME3.BM1 + fd$ME4.BM1 + fd$BIG.LoBM )
+
+# Now create a time series of the HML data that we can pass off to apply.rolling
+# and other PerformanceAnalytics functions
+
+ts.data <- data.frame(french.data$Hi.Lo)
+row.names(ts.data) <- date.seq
+
+# Now calculate the a time series of rolling 5-year annualized returns
+z <- apply.rolling(ts.data, width=window.width, FUN = "Return.annualized")
+french.data$Hi.Lo.5YrRolling <- z[[1]]
+
+# Data sets and values used to plot the data
+indexes <- seq(from=window.width,to=length(date.seq),by=7*12)
+breaks  <- c(date.seq[indexes])
+breaks  <- c(breaks,as.Date('2022-01-01'))
+years   <- (indexes-window.width)/12+1931
+years   <- c(years,2022)
+
+dark.blue <- rev( brewer.pal(7,"Blues") )[2]
+colors    <- c('#DD592D','#34BBA7')
+
+# This is the data used to draw the backgrounds
+background <- data.frame( lower = c(-.20,0.0) ,
+                          upper = c(0.0, 0.25),
+                          col = letters[1:2]  )
+
+# Creating PDF for graph
+pdf.filename <- "value-vs-growth.pdf"
+pdf(pdf.filename)
+
+# Plot the data
+g <- ggplot()
+g <- g + geom_line(data = french.data,
+                   aes(x=DATE,y=Hi.Lo.5YrRolling,group=1),
+                   colour=dark.blue)
+
+# Labeling points
+x.point.values <- c('1960-01-01', 
+                    '1969-06-01',
+                    '1980-06-01',
+                    '1991-06-01',
+                    '1999-06-01',
+                    '2010-06-01')
+
+y.point.values <- c(0.025,
+                   -0.025,
+                   0.025,
+                   -0.025,
+                   0.025,
+                   -0.025)
+
+time.period.labels <- c('1960-1966',
+                       '1969-1977',
+                       '1980-1985',
+                       '1991-1996',
+                       '1999-2005',
+                       'Current: 2010-?')
+
+g <- g + geom_point(color='#DD592D',
+                    size=4,
+                    aes(x=as.Date(x.point.values), y=0))
+
+g <- g + geom_label(aes(label=time.period.labels, x=as.Date(x.point.values), y=y.point.values),
+                    size=4,color='#617994')
+
+
+# Creates label to describe significance of other labels 
+g <- g + geom_label(aes(label='A Label Indicates Time Period of Value Recovery', 
+                        x=as.Date('1983-06-01'), ## midpoint of dates on graph 
+                        y=-0.15),
+                    size=4,color='#617994')
+
+# Put a horizontal line at zero for empaphsis
+g <- g + geom_hline(aes(yintercept=0.0),color="black",linetype=2)
+
+# Here we color the background
+g <- g + geom_rect(data = background ,
+                   mapping = aes(
+                     xmin = as.Date('1945-01-01') ,
+                     xmax = as.Date('2022-01-01') ,
+                     ymin = lower ,
+                     ymax = upper ,
+                     fill = col   ) ,
+                   alpha = .1 )
+g <- g + scale_fill_manual( values=colors )
+g <- g + scale_x_date("Year",breaks=breaks,
+                      labels=years,
+                      limits=as.Date(c('1945-01-01','2024-01-01')),
+                      expand=c(0,1) )
+g <- g + scale_y_continuous("Value vs. Growth (Annualized 5-Year Rolling Value Performance)",labels=percent,limits=c(-0.20,0.25),expand=c(0,0))
+
+g <- g + theme_bw() + theme(legend.position="none",
+                            axis.ticks = element_blank(),
+                            panel.background=element_blank() ,
+                            panel.border=element_blank() )
+
+# Creating title and subtitle
+g <- g + labs(title='Growth Has Outperformed Value Six Times Since 1945', 
+              subtitle='Each Time Value Has Had A Significant Recovery')
+# Centering title and subtitle
+g <- g + theme(plot.title = element_text(hjust=0.5), 
+               plot.subtitle = element_text(hjust=0.5))
+
+g
+
+dev.off()
+
+# Opening the png file
+system2('open', args = pdf.filename, wait = FALSE)