commit 5c772597840b6dd5d1e5c1db49ef3a6d5d5ae21e
parent aa44ef8b19ae8b81060f7e4a02564e91d4b974dc
Author: Erik Loualiche <[email protected]>
Date: Tue, 4 Jun 2019 12:53:04 -0400
plot of prediction
Diffstat:
7 files changed, 97 insertions(+), 9 deletions(-)
diff --git a/log/R-session-info.log.R b/log/R-session-info.log.R
@@ -89,7 +89,7 @@
devtools * 1.13.6 2018-06-27 CRAN (R 3.5.1)
digest 0.6.15 2018-01-28 CRAN (R 3.5.1)
dplyr 0.8.0.9010 2019-03-31 Github (tidyverse/dplyr@6832c62)
- ggplot2 3.1.0.9000 2019-03-31 Github (tidyverse/ggplot2@230e8f7)
+ ggplot2 * 3.1.0.9000 2019-03-31 Github (tidyverse/ggplot2@230e8f7)
glue 1.3.0 2018-07-17 CRAN (R 3.5.1)
graphics * 3.5.1 2018-08-05 local
grDevices * 3.5.1 2018-08-05 local
@@ -124,6 +124,7 @@
tools 3.5.1 2018-08-05 local
utils * 3.5.1 2018-08-05 local
vctrs 0.1.0.9003 2019-05-19 Github (r-lib/vctrs@b1e6b81)
+ wesanderson * 0.3.6 2018-04-20 CRAN (R 3.5.1)
withr 2.1.2 2018-03-15 CRAN (R 3.5.1)
zeallot 0.1.0 2018-01-28 CRAN (R 3.5.1)
zoo * 1.8-3 2018-07-16 CRAN (R 3.5.1)
diff --git a/log/import_predictors.log.R b/log/import_predictors.log.R
@@ -48,7 +48,7 @@ Type 'q()' to quit R.
Log file for code executed at
> message(format(Sys.time(), "%a %b %d %X %Y"))
-Tue Jun 04 12:05:52 2019
+Tue Jun 04 12:51:59 2019
> ##################################################################################
>
>
@@ -237,4 +237,4 @@ Packages ----------------------------------------------------------------------
>
> proc.time()
user system elapsed
- 1.336 0.138 1.783
+ 1.526 0.164 2.142
diff --git a/log/rp_measure.log.R b/log/rp_measure.log.R
@@ -36,7 +36,7 @@ Type 'q()' to quit R.
Log file for code executed at
> message(format(Sys.time(), "%a %b %d %X %Y"))
-Tue Jun 04 12:05:54 2019
+Tue Jun 04 12:52:01 2019
> ##################################################################################
>
>
@@ -44,8 +44,15 @@ Tue Jun 04 12:05:54 2019
> # APPEND REQUIRED PACKAGES
> library(crayon)
> library(devtools)
->
-> # library(ggplot2)
+> library(wesanderson)
+> library(ggplot2)
+
+Attaching package: ‘ggplot2’
+
+The following object is masked from ‘package:crayon’:
+
+ %+%
+
> library(statar)
> library(stringr)
> library(lubridate)
@@ -186,6 +193,49 @@ Notes: ***Significant at the 1 percent level.
> ##################################################################################
>
>
+> ##################################################################################
+> # PLOT
+> dt_plot <- dt_exp_rmrf[, .(date=as.Date(ISOdate(str_sub(dateym,1, 4), str_sub(dateym, 5, 6), 1)),
++ dp, cay, rf, rmrf_y3, exp_rmrf)]
+> dt_plot
+ date dp cay rf rmrf_y3 exp_rmrf
+ 1: 1952-01-01 0.05812871 0.01646544 0.0157 0.17701996 0.201294617
+ 2: 1952-02-01 0.05899675 0.02551783 0.0154 0.19964326 0.222836429
+ 3: 1952-03-01 0.05817138 0.01633620 0.0159 0.18092953 0.200926735
+ 4: 1952-04-01 0.05847809 0.02542006 0.0157 0.21473395 0.220859636
+ 5: 1953-01-01 0.05472504 0.02543387 0.0196 0.21110181 0.206163415
+ ---
+252: 2014-04-01 0.02159773 -0.02747550 0.0003 0.08441447 0.025044998
+253: 2015-01-01 0.02090927 -0.03462231 0.0003 0.12632351 0.008287874
+254: 2015-02-01 0.02098770 -0.03462943 0.0002 0.09072934 0.008601014
+255: 2015-03-01 0.02111608 -0.02656083 0.0003 0.08734601 0.025601134
+256: 2015-04-01 0.02109137 -0.03519129 0.0002 0.08565438 0.007723565
+>
+> p0 <- dt_plot[, .(date, dp, cay, rf, rmrf_y3) ] %>%
++ melt(id.vars="date") %>%
++ ggplot(aes(date, value, colour = variable)) +
++ geom_line(alpha=0.75, size=0.25) + geom_point(shape=1, size = 1, alpha=0.5) +
++ theme_bw()
+> # p0
+>
+> p1 <- dt_plot[, .(date, exp_rmrf, rmrf_y3) ] %>%
++ melt(id.vars="date") %>%
++ ggplot(aes(date, 100*value, colour = variable)) +
++ geom_line(alpha=0.75, size=0.25) + geom_point(shape=1, size = 1, alpha=0.5) +
++ xlab("") + ylab("Returns (percent)") +
++ theme_bw() +
++ theme(legend.position = c(0.3, 0.9)) +
++ scale_colour_manual(name = "",
++ breaks = c("exp_rmrf", "rmrf_y3"),
++ values = c(wes_palette("Zissou1")[1], wes_palette("Zissou1")[5]),
++ labels=c("Expected", "Realized")) +
++ guides(colour = guide_legend(nrow = 1))
+>
+> ggsave("./output/predict.png", p1, width = 8, height=6)
+>
+>
+>
+>
> proc.time()
user system elapsed
- 1.685 0.135 1.793
+ 2.500 0.207 2.776
diff --git a/output/predict.png b/output/predict.png
Binary files differ.
diff --git a/readme.md b/readme.md
@@ -1,5 +1,8 @@
# Measuring the Market Risk Premium
+
+
+
This code updates the measure of equity risk premium from the paper **Buyout Activity: the Impact of Aggregate Discount Rates** in the *Journal of Finance*
Authors: Valentin Haddad, Erik Loualiche & Matthew Plosser.
diff --git a/src/readme_in.md b/src/readme_in.md
@@ -1,5 +1,8 @@
# Measuring the Market Risk Premium
+
+
+
This code updates the measure of equity risk premium from the paper **Buyout Activity: the Impact of Aggregate Discount Rates** in the *Journal of Finance*
Authors: Valentin Haddad, Erik Loualiche & Matthew Plosser.
diff --git a/src/rp_measure.R b/src/rp_measure.R
@@ -22,8 +22,8 @@ message(format(Sys.time(), "%a %b %d %X %Y"))
# APPEND REQUIRED PACKAGES
library(crayon)
library(devtools)
-
-# library(ggplot2)
+library(wesanderson)
+library(ggplot2)
library(statar)
library(stringr)
library(lubridate)
@@ -73,3 +73,34 @@ dt_exp_rmrf <- cbind(dt_predict[!is.na(rmrf_y3), -c("datem")], exp_rmrf = predic
fwrite(dt_exp_rmrf, "./output/predict.csv")
##################################################################################
+
+##################################################################################
+# PLOT
+dt_plot <- dt_exp_rmrf[, .(date=as.Date(ISOdate(str_sub(dateym,1, 4), str_sub(dateym, 5, 6), 1)),
+ dp, cay, rf, rmrf_y3, exp_rmrf)]
+dt_plot
+
+p0 <- dt_plot[, .(date, dp, cay, rf, rmrf_y3) ] %>%
+ melt(id.vars="date") %>%
+ ggplot(aes(date, value, colour = variable)) +
+ geom_line(alpha=0.75, size=0.25) + geom_point(shape=1, size = 1, alpha=0.5) +
+ theme_bw()
+# p0
+
+p1 <- dt_plot[, .(date, exp_rmrf, rmrf_y3) ] %>%
+ melt(id.vars="date") %>%
+ ggplot(aes(date, 100*value, colour = variable)) +
+ geom_line(alpha=0.75, size=0.25) + geom_point(shape=1, size = 1, alpha=0.5) +
+ xlab("") + ylab("Returns (percent)") +
+ theme_bw() +
+ theme(legend.position = c(0.3, 0.9)) +
+ scale_colour_manual(name = "",
+ breaks = c("exp_rmrf", "rmrf_y3"),
+ values = c(wes_palette("Zissou1")[1], wes_palette("Zissou1")[5]),
+ labels=c("Expected", "Realized")) +
+ guides(colour = guide_legend(nrow = 1))
+
+ggsave("./output/predict.png", p1, width = 8, height=6)
+
+
+
