commit 15da1d370f72a234e7f415679b7f1e1a1884d335
Author: Erik Loualiche <[email protected]>
Date: Tue, 4 Jun 2019 12:11:18 -0400
Push most files after run.
Diffstat:
13 files changed, 2523 insertions(+), 0 deletions(-)
diff --git a/.gitignore b/.gitignore
@@ -0,0 +1,12 @@
+# .gitignore file for RiskPremium Repo
+
+
+## STANDARD EXCLUSIONS
+archive
+doc/*.lyx
+tmp
+.Rhistory
+
+# Specific files
+doc/dividendpriceratio.tex
+input/msi.sas7bdat+
\ No newline at end of file
diff --git a/Makefile b/Makefile
@@ -0,0 +1,50 @@
+#
+# Makefile for PREDICTING THE EQUITY RISK PREMIUM
+#
+# Created on June 04th 2019
+# Last modified on April 04th 2019
+# --------------------------------------------------------------------------------------------------------
+
+
+# --------------------------------------------------------------------------------------------------------
+all: output/predict.csv readme.md
+
+## DOWNLOAD THE DATA FROM WRDS
+input/msi.sas7bdat:
+ rsync -aPvzh --stats --human-readable [email protected]:/wrds/crsp/sasdata/a_stock/msi.sas7bdat ./input/
+
+## GENERATE PREDICTORS
+tmp/predict.csv: src/import_predictors.R input/cay_current.csv input/msi.sas7bdat
+ R CMD BATCH $(R_OPTS) src/import_predictors.R log/import_predictors.log.R
+
+## RUN REGRESSIONS
+output/predict.csv: src/rp_measure.R tmp/predict.csv
+ R CMD BATCH $(R_OPTS) src/rp_measure.R log/rp_measure.log.R
+ @echo
+
+## OUTPUT RESULTS
+readme.md: src/readme_in.md
+ cat src/readme_in.md tmp/reg_update.txt > readme.md
+
+
+# --------------------------------------------------------------------------------------------------------
+.PHONY : help
+help : Makefile
+ @sed -n 's/^##//p' $<
+
+## clean
+.PHONY : clean
+clean:
+ rm -rf ./output/*
+ rm -rf ./log/*.log*
+ rm -rf ./tmp/*
+
+
+# --------------------------------------------------------------------------------------------------------
+SHELL := /bin/bash
+R_OPTS := --vanilla
+# DATE := `date '+%Y-%m-%d %H:%M:%S'`
+# --------------------------------------------------------------------------------------------------------
+
+
+
diff --git a/doc/dividendpriceratio.pdf b/doc/dividendpriceratio.pdf
Binary files differ.
diff --git a/input/cay_current.csv b/input/cay_current.csv
@@ -0,0 +1,265 @@
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+201002,10.38306817,12.12679745,10.20189441,-0.004120902
+201003,10.38752014,12.14825147,10.20493464,-0.007853384
+201004,10.39569147,12.18068245,10.20416992,-0.007991569
+201101,10.39901344,12.19114276,10.21122653,-0.01288464
+201102,10.39933665,12.18645873,10.20277696,-0.004873942
+201103,10.40167307,12.14367807,10.20158648,0.010090533
+201104,10.40306707,12.163639,10.19354456,0.012108104
+201201,10.40744238,12.19319683,10.20578649,-0.000895883
+201202,10.40748035,12.19245159,10.20737567,-0.001858043
+201203,10.40814172,12.21732615,10.20503977,-0.006244276
+201204,10.40896328,12.22598983,10.21774391,-0.017425398
+201301,10.41215242,12.26147785,10.18439318,0.001312162
+201302,10.41264013,12.28316096,10.19208326,-0.009971338
+201303,10.41531169,12.31008855,10.19449664,-0.016509419
+201304,10.42169125,12.33817751,10.19550457,-0.018592692
+201401,10.424797,12.34558322,10.20302759,-0.023218232
+201402,10.43160729,12.35979604,10.20844901,-0.024412266
+201403,10.43919365,12.35937058,10.21586838,-0.022332177
+201404,10.44947895,12.38002573,10.22875616,-0.027475502
+201501,10.45684875,12.40146138,10.24015827,-0.034622307
+201502,10.46256543,12.40470186,10.24653883,-0.034629428
+201503,10.46734812,12.38549823,10.24914833,-0.02656083
+201504,10.47190889,12.40427123,10.25976458,-0.035191286
+201601,10.47478362,12.40512783,10.25672492,-0.030247686
+201602,10.48246925,12.40920055,10.26212304,-0.027769407
+201603,10.48743766,12.42801793,10.26372071,-0.029169505
+201604,10.4927175,12.44184314,10.25415362,-0.02042846
+201701,10.49589657,12.45703895,10.25927611,-0.0252966
+201702,10.50230614,12.47080687,10.26441263,-0.026553501
+201703,10.50568767,12.48331976,10.26573817,-0.027606225+
\ No newline at end of file
diff --git a/log/R-session-info.log.R b/log/R-session-info.log.R
@@ -0,0 +1,129 @@
+
+
+# -----
+# Session info for import_predictors
+
+ setting value
+ version R version 3.5.1 (2018-07-02)
+ system x86_64, darwin15.6.0
+ ui X11
+ language (EN)
+ collate en_US.UTF-8
+ tz America/New_York
+ date 2019-06-04
+
+ package * version date source
+ alfred * 0.1.6 2018-04-06 CRAN (R 3.5.1)
+ assertthat 0.2.0 2017-04-11 CRAN (R 3.5.1)
+ backports 1.1.2 2017-12-13 CRAN (R 3.5.1)
+ base * 3.5.1 2018-08-05 local
+ colorspace 1.3-2 2016-12-14 CRAN (R 3.5.1)
+ compiler 3.5.1 2018-08-05 local
+ crayon * 1.3.4 2019-05-19 Github (gaborcsardi/crayon@84be620)
+ data.table * 1.12.3 2019-06-03 local
+ datasets * 3.5.1 2018-08-05 local
+ 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)
+ forcats 0.3.0 2018-02-19 CRAN (R 3.5.1)
+ 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
+ grid 3.5.1 2018-08-05 local
+ gtable 0.2.0 2016-02-26 CRAN (R 3.5.1)
+ haven * 1.1.2 2018-06-27 CRAN (R 3.5.1)
+ hms 0.4.2 2018-03-10 CRAN (R 3.5.1)
+ jsonlite 1.5 2017-06-01 CRAN (R 3.5.0)
+ lazyeval 0.2.1 2017-10-29 CRAN (R 3.5.1)
+ lubridate * 1.7.4 2018-04-11 CRAN (R 3.5.1)
+ magrittr 1.5 2014-11-22 CRAN (R 3.5.1)
+ matrixStats 0.54.0 2018-07-23 CRAN (R 3.5.1)
+ memoise 1.1.0 2017-04-21 CRAN (R 3.5.1)
+ methods * 3.5.1 2018-08-05 local
+ munsell 0.5.0 2018-06-12 CRAN (R 3.5.1)
+ parallel 3.5.1 2018-08-05 local
+ pillar 1.4.0.9002 2019-05-19 Github (r-lib/pillar@5ded57f)
+ pkgconfig 2.0.2 2019-05-19 Github (r-lib/pkgconfig@5453f79)
+ purrr 0.2.5 2018-05-29 CRAN (R 3.5.1)
+ R6 2.2.2 2017-06-17 CRAN (R 3.5.0)
+ Rcpp 1.0.1.3 2019-05-19 Github (RcppCore/Rcpp@6062d56)
+ RcppRoll * 0.3.0 2018-06-05 CRAN (R 3.5.1)
+ rlang 0.3.4.9003 2019-05-19 Github (r-lib/rlang@6a232c0)
+ scales 1.0.0.9000 2019-03-31 Github (r-lib/scales@c374014)
+ statar * 0.6.5 2017-07-06 CRAN (R 3.5.1)
+ stats * 3.5.1 2018-08-05 local
+ stringi 1.2.4 2018-07-20 CRAN (R 3.5.1)
+ stringr * 1.3.1 2018-05-10 CRAN (R 3.5.1)
+ tibble 2.1.1.9000 2019-05-19 Github (tidyverse/tibble@71b8ff6)
+ tidyr 0.8.3.9000 2019-05-19 Github (tidyverse/tidyr@b6ec78b)
+ tidyselect 0.2.5.9000 2019-05-19 Github (tidyverse/tidyselect@19150c0)
+ 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)
+ withr 2.1.2 2018-03-15 CRAN (R 3.5.1)
+ zeallot 0.1.0 2018-01-28 CRAN (R 3.5.1)
+
+
+# -----
+# Session info for rp_measure.csv
+
+ setting value
+ version R version 3.5.1 (2018-07-02)
+ system x86_64, darwin15.6.0
+ ui X11
+ language (EN)
+ collate en_US.UTF-8
+ tz America/New_York
+ date 2019-06-04
+
+ package * version date source
+ assertthat 0.2.0 2017-04-11 CRAN (R 3.5.1)
+ backports 1.1.2 2017-12-13 CRAN (R 3.5.1)
+ base * 3.5.1 2018-08-05 local
+ colorspace 1.3-2 2016-12-14 CRAN (R 3.5.1)
+ compiler 3.5.1 2018-08-05 local
+ crayon * 1.3.4 2019-05-19 Github (gaborcsardi/crayon@84be620)
+ data.table * 1.12.3 2019-06-03 local
+ datasets * 3.5.1 2018-08-05 local
+ 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)
+ 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
+ grid 3.5.1 2018-08-05 local
+ gtable 0.2.0 2016-02-26 CRAN (R 3.5.1)
+ lattice 0.20-35 2017-03-25 CRAN (R 3.5.1)
+ lazyeval 0.2.1 2017-10-29 CRAN (R 3.5.1)
+ lmtest * 0.9-36 2018-04-04 CRAN (R 3.5.1)
+ lubridate * 1.7.4 2018-04-11 CRAN (R 3.5.1)
+ magrittr 1.5 2014-11-22 CRAN (R 3.5.1)
+ matrixStats 0.54.0 2018-07-23 CRAN (R 3.5.1)
+ memoise 1.1.0 2017-04-21 CRAN (R 3.5.1)
+ methods * 3.5.1 2018-08-05 local
+ munsell 0.5.0 2018-06-12 CRAN (R 3.5.1)
+ parallel 3.5.1 2018-08-05 local
+ pillar 1.4.0.9002 2019-05-19 Github (r-lib/pillar@5ded57f)
+ pkgconfig 2.0.2 2019-05-19 Github (r-lib/pkgconfig@5453f79)
+ purrr 0.2.5 2018-05-29 CRAN (R 3.5.1)
+ R6 2.2.2 2017-06-17 CRAN (R 3.5.0)
+ Rcpp 1.0.1.3 2019-05-19 Github (RcppCore/Rcpp@6062d56)
+ rlang 0.3.4.9003 2019-05-19 Github (r-lib/rlang@6a232c0)
+ sandwich * 2.4-0 2017-07-26 CRAN (R 3.5.1)
+ scales 1.0.0.9000 2019-03-31 Github (r-lib/scales@c374014)
+ stargazer * 5.2.2 2018-05-30 CRAN (R 3.5.1)
+ statar * 0.6.5 2017-07-06 CRAN (R 3.5.1)
+ stats * 3.5.1 2018-08-05 local
+ stringi 1.2.4 2018-07-20 CRAN (R 3.5.1)
+ stringr * 1.3.1 2018-05-10 CRAN (R 3.5.1)
+ tibble 2.1.1.9000 2019-05-19 Github (tidyverse/tibble@71b8ff6)
+ tidyr 0.8.3.9000 2019-05-19 Github (tidyverse/tidyr@b6ec78b)
+ tidyselect 0.2.5.9000 2019-05-19 Github (tidyverse/tidyselect@19150c0)
+ 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)
+ 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
@@ -0,0 +1,240 @@
+
+R version 3.5.1 (2018-07-02) -- "Feather Spray"
+Copyright (C) 2018 The R Foundation for Statistical Computing
+Platform: x86_64-apple-darwin15.6.0 (64-bit)
+
+R is free software and comes with ABSOLUTELY NO WARRANTY.
+You are welcome to redistribute it under certain conditions.
+Type 'license()' or 'licence()' for distribution details.
+
+ Natural language support but running in an English locale
+
+R is a collaborative project with many contributors.
+Type 'contributors()' for more information and
+'citation()' on how to cite R or R packages in publications.
+
+Type 'demo()' for some demos, 'help()' for on-line help, or
+'help.start()' for an HTML browser interface to help.
+Type 'q()' to quit R.
+
+> #!/usr/bin/env Rscript
+> #
+> # import_predictors.R
+> #
+> # This code creates or imports the predictors of aggregate equity returns
+> # There are three parts for T-bill, D/P ratio and cay
+> #
+> # 1. T-bill comes from the H15 release of the FRB
+> # we downloaded it directly from FRED at https://fred.stlouisfed.org/series/TB3MS
+> #
+> # 2. cay comes from Martin Lettau's website at http://faculty.haas.berkeley.edu/lettau/data_cay.html
+> #
+> # 3. D-P ratio is estimated from the MSI CRSP Files
+> # We use a method of continuously reinvested dividends
+> # See attached LaTeX file for explanations of the procedure
+> # Data is from CRSP and available at /wrds/crsp/sasdata/a_stock/msi.sas7bdat
+> #
+> # 4. Estimate future excess returns: we use a horizon of three years in the paper
+> #
+> # (c) Valentin Haddad, Erik Loualiche & Matthew Plosser
+> #
+> # Last updated on June 4th 2019
+> #
+> ##################################################################################
+>
+>
+> ##################################################################################
+> message("Log file for code executed at\n")
+Log file for code executed at
+
+> message(format(Sys.time(), "%a %b %d %X %Y"))
+Tue Jun 04 12:05:52 2019
+> ##################################################################################
+>
+>
+> ##################################################################################
+> # APPEND REQUIRED PACKAGES
+> library(crayon)
+> library(devtools)
+>
+> library(alfred)
+> library(haven)
+> library(dplyr)
+
+Attaching package: ‘dplyr’
+
+The following objects are masked from ‘package:stats’:
+
+ filter, lag
+
+The following objects are masked from ‘package:base’:
+
+ intersect, setdiff, setequal, union
+
+> library(stringr)
+> library(lubridate)
+
+Attaching package: ‘lubridate’
+
+The following object is masked from ‘package:base’:
+
+ date
+
+> library(RcppRoll)
+> library(statar)
+> library(data.table)
+
+Attaching package: ‘data.table’
+
+The following objects are masked from ‘package:lubridate’:
+
+ hour, isoweek, mday, minute, month, quarter, second, wday, week,
+ yday, year
+
+The following objects are masked from ‘package:dplyr’:
+
+ between, first, last
+
+>
+> check_file = file.exists("log/R-session-info.log.R")
+> sink("log/R-session-info.log.R", append=check_file)
+> cat(bold("\n\n# -----\n# Session info for import_predictors\n\n"))
+> session_info()
+Session info ------------------------------------------------------------------
+Packages ----------------------------------------------------------------------
+> sink()
+> ##################################################################################
+>
+>
+> ##################################################################################
+> # 1. TREASURIES
+> dt_tbill <- get_fred_series("TB3MS", "rf", observation_start = "1950-01-01", observation_end = "2019-05-31") %>% data.table
+> dt_tbill <- dt_tbill[, .(dateym=year(date)*100+month(date), rf=rf/100)]
+> # fwrite(dt_tbill, "./input/tbill.csv")
+> ##################################################################################
+>
+>
+> ##################################################################################
+> # 2. CAY
+> dt_cay <- fread("./input/cay_current.csv", skip=1, header=T)
+> dt_cay <- dt_cay[, .(dateym=as.integer(str_sub(date, 1, 6)), cay=cay) ]
+> dt_cay
+ dateym cay
+ 1: 195201 0.01646544
+ 2: 195202 0.02551783
+ 3: 195203 0.01633620
+ 4: 195204 0.02542006
+ 5: 195301 0.02543387
+ ---
+259: 201603 -0.02916950
+260: 201604 -0.02042846
+261: 201701 -0.02529660
+262: 201702 -0.02655350
+263: 201703 -0.02760623
+> ##################################################################################
+>
+>
+> ##################################################################################
+> # 3. Dividend-Price RATIO
+> dt_msi <- read_sas("./input/msi.sas7bdat") %>% data.table
+> dt_msi <- dt_msi[, .(date=DATE, vwretd, vwretx) ]
+> fwrite(dt_msi, "./output/msi.csv") # SAVED HERE IF YOU NEED IT
+>
+> # ESTIMATE THE DP RATIO
+> dt_dp <- dt_msi[, .(date, vwretx, vwretd, vwrx=1+vwretx, vwrd=1+vwretd) ]
+> dt_dp[, `:=`(vwrx=1+vwretx, vwrd=1+vwretd) ]
+> dt_dp[, `:=`(dpvw = 100 * (vwretd-vwretx) / (1+vwretx) ) ]
+> dt_dp[, `:=`(retd_retx = (1+vwretd) / (1+vwretx) ) ]
+> dt_dp[, `:=`(datem = as.monthly(date)) ]
+> dt_dp[, dp := 0 ]
+> for (i in seq(11,0)){
++ dt_dp[, dp := (dp*tlag(retd_retx, i, time=datem) + tlag(dpvw, i, time=datem)) ]
++ }
+> dt_dp <- dt_dp[, .(dateym=year(datem)*100+month(datem), dp=dp/100)]
+> dt_dp[]
+ dateym dp
+ 1: 192512 NA
+ 2: 192601 NA
+ 3: 192602 NA
+ 4: 192603 NA
+ 5: 192604 NA
+ ---
+1113: 201808 0.02033382
+1114: 201809 0.02040150
+1115: 201810 0.02047582
+1116: 201811 0.02050859
+1117: 201812 0.02114445
+> ##################################################################################
+>
+>
+> ##################################################################################
+> # ESTIMATE FUTURE EXCESS RETURNS
+> dt_rmrf <- fread("./output/msi.csv") %>% data.table
+> dt_rmrf <- dt_rmrf[, .(dateym=year(date)*100+month(date), retm=vwretd) ]
+> dt_rmrf <- merge(dt_rmrf, dt_tbill, by = "dateym")
+>
+> dt_rmrf[, lead1_retm := shift(retm, 1, type="lead") ]
+> dt_rmrf[, retm_y := exp( roll_sum(log(1+lead1_retm), n=12, align="left", fill=NA) ) - 1 ]
+> dt_rmrf[, rf_y := (1+rf)^(1/4) * (1+shift(rf, 3, type="lead"))^(1/4) *
++ (1+shift(rf, 6, type="lead"))^(1/4) * (1+shift(rf, 9, type="lead"))^(1/4) - 1 ]
+> dt_rmrf[, rmrf_y3 := 1 * (
++ ( (1+retm_y) * (1 + shift(retm_y, 12, type="lead")) * (1 + shift(retm_y, 24, type="lead")) )^(1/3) -
++ ( ((1+rf_y) * (1 + shift(rf_y, 12, type="lead")) * (1 + shift(rf_y, 24, type="lead")) )^(1/3) - 1) -1) ]
+>
+> dt_rmrf <- dt_rmrf[, .(dateym, rmrf_y3) ]
+> dt_rmrf[ !is.na(rmrf_y3) ]
+ dateym rmrf_y3
+ 1: 195001 0.19164596
+ 2: 195002 0.18441326
+ 3: 195003 0.17389623
+ 4: 195004 0.14728401
+ 5: 195005 0.13288460
+ ---
+788: 201508 0.13987039
+789: 201509 0.15268617
+790: 201510 0.09634409
+791: 201511 0.10151984
+792: 201512 0.07465740
+> ##################################################################################
+>
+>
+> ##################################################################################
+> # MERGE THE PREDICTORS
+> dt_predict <- merge(dt_dp, dt_tbill, by = c("dateym"))
+> dt_predict <- merge(dt_predict, dt_rmrf, by = c("dateym"), all.x = T)
+> dt_predict <- merge(dt_predict, dt_cay, by = c("dateym"), all.x = T)
+> dt_predict <- dt_predict[ !is.na(rmrf_y3) & !is.na(cay) ]
+> dt_predict[]
+ dateym dp rf rmrf_y3 cay
+ 1: 195201 0.05812871 0.0157 0.17701996 0.01646544
+ 2: 195202 0.05899675 0.0154 0.19964326 0.02551783
+ 3: 195203 0.05817138 0.0159 0.18092953 0.01633620
+ 4: 195204 0.05847809 0.0157 0.21473395 0.02542006
+ 5: 195301 0.05472504 0.0196 0.21110181 0.02543387
+ ---
+252: 201404 0.02159773 0.0003 0.08441447 -0.02747550
+253: 201501 0.02090927 0.0003 0.12632351 -0.03462231
+254: 201502 0.02098770 0.0002 0.09072934 -0.03462943
+255: 201503 0.02111608 0.0003 0.08734601 -0.02656083
+256: 201504 0.02109137 0.0002 0.08565438 -0.03519129
+>
+> fwrite(dt_predict, "./tmp/predict.csv")
+> ##################################################################################
+>
+>
+>
+>
+>
+>
+>
+>
+>
+>
+>
+>
+>
+>
+>
+> proc.time()
+ user system elapsed
+ 1.336 0.138 1.783
diff --git a/log/rp_measure.log.R b/log/rp_measure.log.R
@@ -0,0 +1,191 @@
+
+R version 3.5.1 (2018-07-02) -- "Feather Spray"
+Copyright (C) 2018 The R Foundation for Statistical Computing
+Platform: x86_64-apple-darwin15.6.0 (64-bit)
+
+R is free software and comes with ABSOLUTELY NO WARRANTY.
+You are welcome to redistribute it under certain conditions.
+Type 'license()' or 'licence()' for distribution details.
+
+ Natural language support but running in an English locale
+
+R is a collaborative project with many contributors.
+Type 'contributors()' for more information and
+'citation()' on how to cite R or R packages in publications.
+
+Type 'demo()' for some demos, 'help()' for on-line help, or
+'help.start()' for an HTML browser interface to help.
+Type 'q()' to quit R.
+
+> #!/usr/bin/env Rscript
+> #
+> # rp_measure.R
+> #
+> # This code runs the predictive regression
+> # We save in output the expected excess return estimate
+> #
+> #
+> # (c) Valentin Haddad, Erik Loualiche & Matthew Plosser
+> #
+> # Last updated on June 4th 2019
+> #
+> ##################################################################################
+>
+> ##################################################################################
+> message("Log file for code executed at\n")
+Log file for code executed at
+
+> message(format(Sys.time(), "%a %b %d %X %Y"))
+Tue Jun 04 12:05:54 2019
+> ##################################################################################
+>
+>
+> ##################################################################################
+> # APPEND REQUIRED PACKAGES
+> library(crayon)
+> library(devtools)
+>
+> # library(ggplot2)
+> library(statar)
+> library(stringr)
+> library(lubridate)
+
+Attaching package: ‘lubridate’
+
+The following object is masked from ‘package:base’:
+
+ date
+
+> library(data.table)
+
+Attaching package: ‘data.table’
+
+The following objects are masked from ‘package:lubridate’:
+
+ hour, isoweek, mday, minute, month, quarter, second, wday, week,
+ yday, year
+
+> library(lmtest)
+Loading required package: zoo
+
+Attaching package: ‘zoo’
+
+The following objects are masked from ‘package:base’:
+
+ as.Date, as.Date.numeric
+
+
+Attaching package: ‘lmtest’
+
+The following object is masked from ‘package:crayon’:
+
+ reset
+
+> library(sandwich)
+> library(stargazer)
+
+Please cite as:
+
+ Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.
+ R package version 5.2.2. https://CRAN.R-project.org/package=stargazer
+
+>
+> check_file = file.exists("log/R-session-info.log.R")
+> sink("log/R-session-info.log.R", append=check_file)
+> cat(bold("\n\n# -----\n# Session info for rp_measure.csv\n\n"))
+> session_info()
+Session info ------------------------------------------------------------------
+Packages ----------------------------------------------------------------------
+> sink()
+> ##################################################################################
+>
+>
+> ##################################################################################
+> dt_predict <- fread("./tmp/predict.csv")
+> dt_predict[, datem := as.monthly(ISOdate(str_sub(dateym, 1, 4), str_sub(dateym, 5, 6), 1)) ]
+> ##################################################################################
+>
+>
+> ##################################################################################
+> r1_3 = lm(rmrf_y3 ~ dp + cay + rf, data = dt_predict[ year(datem) < 2011])
+> nw_r1_3 = coeftest(r1_3, df = Inf, vcov = NeweyWest(r1_3, lag = 12, prewhite = FALSE) )
+> r2_3 = lm(rmrf_y3 ~ dp + cay + rf, data = dt_predict)
+> nw_r2_3 = coeftest(r2_3, df = Inf, vcov = NeweyWest(r2_3, lag = 12, prewhite = FALSE) )
+>
+> stargazer(r1_3, nw_r1_3, r2_3, nw_r2_3, type="text")
+
+===========================================================================================
+ Dependent variable:
+ -----------------------------------------------------------------------
+ rmrf_y3 rmrf_y3
+ OLS coefficient OLS coefficient
+ test test
+ (1) (2) (3) (4)
+-------------------------------------------------------------------------------------------
+dp 2.932*** 2.932*** 2.788*** 2.788***
+ (0.411) (1.022) (0.411) (1.077)
+
+cay 2.363*** 2.363*** 2.076*** 2.076***
+ (0.244) (0.545) (0.234) (0.568)
+
+rf -0.852*** -0.852** -1.093*** -1.093***
+ (0.161) (0.353) (0.151) (0.376)
+
+Constant 0.001 0.001 0.022* 0.022
+ (0.014) (0.036) (0.013) (0.036)
+
+-------------------------------------------------------------------------------------------
+Observations 236 256
+R2 0.438 0.400
+Adjusted R2 0.431 0.393
+Residual Std. Error 0.070 (df = 232) 0.070 (df = 252)
+F Statistic 60.270*** (df = 3; 232) 56.022*** (df = 3; 252)
+===========================================================================================
+Note: *p<0.1; **p<0.05; ***p<0.01
+>
+> # --- output for the readme
+> star = stargazer(r2_3, type="text", style = "aer",
++ covariate.labels = c("D/P ratio", "cay", "T-bill (three-month)"),
++ dep.var.labels = "Future Excess Returns",
++ omit.stat = c("ser", "adj.rsq") )
+
+===========================================================
+ Future Excess Returns
+-----------------------------------------------------------
+D/P ratio 2.788***
+ (0.411)
+
+cay 2.076***
+ (0.234)
+
+T-bill (three-month) -1.093***
+ (0.151)
+
+Constant 0.022*
+ (0.013)
+
+Observations 256
+R2 0.400
+F Statistic 56.022*** (df = 3; 252)
+-----------------------------------------------------------
+Notes: ***Significant at the 1 percent level.
+ **Significant at the 5 percent level.
+ *Significant at the 10 percent level.
+>
+> star[1] = "~~~R"
+> star[length(star)+1] = "~~~"
+> cat(star, sep = '\n', file = './tmp/reg_update.txt')
+> ##################################################################################
+>
+>
+> ##################################################################################
+> # OUTPUT PREDICTED VALUE
+> dt_exp_rmrf <- cbind(dt_predict[!is.na(rmrf_y3), -c("datem")], exp_rmrf = predict(r2_3))
+>
+> fwrite(dt_exp_rmrf, "./output/predict.csv")
+> ##################################################################################
+>
+>
+> proc.time()
+ user system elapsed
+ 1.685 0.135 1.793
diff --git a/output/msi.csv b/output/msi.csv
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diff --git a/output/predict.csv b/output/predict.csv
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diff --git a/readme.md b/readme.md
@@ -0,0 +1,37 @@
+# Measuring the Risk Premium
+
+1. Measuring Dividend Price ratio uses CRSP Monthly Index files available on [WRDS](https://wrds-web.wharton.upenn.edu/wrds/ds/crsp/stock_a/stkmktix.cfm)
+ - `msi.sas7bdat` downloaded from `/wrds/crsp/sasdata/a_stock/msi.sas7bdat`
+ - See our [note](./doc/dividendpriceratio.pdf) on how to account for reinvested dividends
+2. Measuring the risk-free rate from H15 release available on [FRED](https://fred.stlouisfed.org/series/TB3MS
+)
+3. Measuring cay from Lettau's [website](http://faculty.haas.berkeley.edu/lettau/data_cay.html). *Last downloaded on May 29 2019*
+
+
+## Latest estimates
+
+
+~~~R
+===========================================================
+ Future Excess Returns
+-----------------------------------------------------------
+D/P ratio 2.788***
+ (0.411)
+
+cay 2.076***
+ (0.234)
+
+T-bill (three-month) -1.093***
+ (0.151)
+
+Constant 0.022*
+ (0.013)
+
+Observations 256
+R2 0.400
+F Statistic 56.022*** (df = 3; 252)
+-----------------------------------------------------------
+Notes: ***Significant at the 1 percent level.
+ **Significant at the 5 percent level.
+ *Significant at the 10 percent level.
+~~~
diff --git a/src/import_predictors.R b/src/import_predictors.R
@@ -0,0 +1,134 @@
+#!/usr/bin/env Rscript
+#
+# import_predictors.R
+#
+# This code creates or imports the predictors of aggregate equity returns
+# There are three parts for T-bill, D/P ratio and cay
+#
+# 1. T-bill comes from the H15 release of the FRB
+# we downloaded it directly from FRED at https://fred.stlouisfed.org/series/TB3MS
+#
+# 2. cay comes from Martin Lettau's website at http://faculty.haas.berkeley.edu/lettau/data_cay.html
+#
+# 3. D-P ratio is estimated from the MSI CRSP Files
+# We use a method of continuously reinvested dividends
+# See attached LaTeX file for explanations of the procedure
+# Data is from CRSP and available at /wrds/crsp/sasdata/a_stock/msi.sas7bdat
+#
+# 4. Estimate future excess returns: we use a horizon of three years in the paper
+#
+# (c) Valentin Haddad, Erik Loualiche & Matthew Plosser
+#
+# Last updated on June 4th 2019
+#
+##################################################################################
+
+
+##################################################################################
+message("Log file for code executed at\n")
+message(format(Sys.time(), "%a %b %d %X %Y"))
+##################################################################################
+
+
+##################################################################################
+# APPEND REQUIRED PACKAGES
+library(crayon)
+library(devtools)
+
+library(alfred)
+library(haven)
+library(dplyr)
+library(stringr)
+library(lubridate)
+library(RcppRoll)
+library(statar)
+library(data.table)
+
+check_file = file.exists("log/R-session-info.log.R")
+sink("log/R-session-info.log.R", append=check_file)
+cat(bold("\n\n# -----\n# Session info for import_predictors\n\n"))
+session_info()
+sink()
+##################################################################################
+
+
+##################################################################################
+# 1. TREASURIES
+dt_tbill <- get_fred_series("TB3MS", "rf", observation_start = "1950-01-01", observation_end = "2019-05-31") %>% data.table
+dt_tbill <- dt_tbill[, .(dateym=year(date)*100+month(date), rf=rf/100)]
+# fwrite(dt_tbill, "./input/tbill.csv")
+##################################################################################
+
+
+##################################################################################
+# 2. CAY
+dt_cay <- fread("./input/cay_current.csv", skip=1, header=T)
+dt_cay <- dt_cay[, .(dateym=as.integer(str_sub(date, 1, 6)), cay=cay) ]
+dt_cay
+##################################################################################
+
+
+##################################################################################
+# 3. Dividend-Price RATIO
+dt_msi <- read_sas("./input/msi.sas7bdat") %>% data.table
+dt_msi <- dt_msi[, .(date=DATE, vwretd, vwretx) ]
+fwrite(dt_msi, "./output/msi.csv") # SAVED HERE IF YOU NEED IT
+
+# ESTIMATE THE DP RATIO
+dt_dp <- dt_msi[, .(date, vwretx, vwretd, vwrx=1+vwretx, vwrd=1+vwretd) ]
+dt_dp[, `:=`(vwrx=1+vwretx, vwrd=1+vwretd) ]
+dt_dp[, `:=`(dpvw = 100 * (vwretd-vwretx) / (1+vwretx) ) ]
+dt_dp[, `:=`(retd_retx = (1+vwretd) / (1+vwretx) ) ]
+dt_dp[, `:=`(datem = as.monthly(date)) ]
+dt_dp[, dp := 0 ]
+for (i in seq(11,0)){
+ dt_dp[, dp := (dp*tlag(retd_retx, i, time=datem) + tlag(dpvw, i, time=datem)) ]
+}
+dt_dp <- dt_dp[, .(dateym=year(datem)*100+month(datem), dp=dp/100)]
+dt_dp[]
+##################################################################################
+
+
+##################################################################################
+# ESTIMATE FUTURE EXCESS RETURNS
+dt_rmrf <- fread("./output/msi.csv") %>% data.table
+dt_rmrf <- dt_rmrf[, .(dateym=year(date)*100+month(date), retm=vwretd) ]
+dt_rmrf <- merge(dt_rmrf, dt_tbill, by = "dateym")
+
+dt_rmrf[, lead1_retm := shift(retm, 1, type="lead") ]
+dt_rmrf[, retm_y := exp( roll_sum(log(1+lead1_retm), n=12, align="left", fill=NA) ) - 1 ]
+dt_rmrf[, rf_y := (1+rf)^(1/4) * (1+shift(rf, 3, type="lead"))^(1/4) *
+ (1+shift(rf, 6, type="lead"))^(1/4) * (1+shift(rf, 9, type="lead"))^(1/4) - 1 ]
+dt_rmrf[, rmrf_y3 := 1 * (
+ ( (1+retm_y) * (1 + shift(retm_y, 12, type="lead")) * (1 + shift(retm_y, 24, type="lead")) )^(1/3) -
+ ( ((1+rf_y) * (1 + shift(rf_y, 12, type="lead")) * (1 + shift(rf_y, 24, type="lead")) )^(1/3) - 1) -1) ]
+
+dt_rmrf <- dt_rmrf[, .(dateym, rmrf_y3) ]
+dt_rmrf[ !is.na(rmrf_y3) ]
+##################################################################################
+
+
+##################################################################################
+# MERGE THE PREDICTORS
+dt_predict <- merge(dt_dp, dt_tbill, by = c("dateym"))
+dt_predict <- merge(dt_predict, dt_rmrf, by = c("dateym"), all.x = T)
+dt_predict <- merge(dt_predict, dt_cay, by = c("dateym"), all.x = T)
+dt_predict <- dt_predict[ !is.na(rmrf_y3) & !is.na(cay) ]
+dt_predict[]
+
+fwrite(dt_predict, "./tmp/predict.csv")
+##################################################################################
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/src/readme_in.md b/src/readme_in.md
@@ -0,0 +1,13 @@
+# Measuring the Risk Premium
+
+1. Measuring Dividend Price ratio uses CRSP Monthly Index files available on [WRDS](https://wrds-web.wharton.upenn.edu/wrds/ds/crsp/stock_a/stkmktix.cfm)
+ - `msi.sas7bdat` downloaded from `/wrds/crsp/sasdata/a_stock/msi.sas7bdat`
+ - See our [note](./doc/dividendpriceratio.pdf) on how to account for reinvested dividends
+2. Measuring the risk-free rate from H15 release available on [FRED](https://fred.stlouisfed.org/series/TB3MS
+)
+3. Measuring cay from Lettau's [website](http://faculty.haas.berkeley.edu/lettau/data_cay.html). *Last downloaded on May 29 2019*
+
+
+## Latest estimates
+
+
diff --git a/src/rp_measure.R b/src/rp_measure.R
@@ -0,0 +1,75 @@
+#!/usr/bin/env Rscript
+#
+# rp_measure.R
+#
+# This code runs the predictive regression
+# We save in output the expected excess return estimate
+#
+#
+# (c) Valentin Haddad, Erik Loualiche & Matthew Plosser
+#
+# Last updated on June 4th 2019
+#
+##################################################################################
+
+##################################################################################
+message("Log file for code executed at\n")
+message(format(Sys.time(), "%a %b %d %X %Y"))
+##################################################################################
+
+
+##################################################################################
+# APPEND REQUIRED PACKAGES
+library(crayon)
+library(devtools)
+
+# library(ggplot2)
+library(statar)
+library(stringr)
+library(lubridate)
+library(data.table)
+library(lmtest)
+library(sandwich)
+library(stargazer)
+
+check_file = file.exists("log/R-session-info.log.R")
+sink("log/R-session-info.log.R", append=check_file)
+cat(bold("\n\n# -----\n# Session info for rp_measure.csv\n\n"))
+session_info()
+sink()
+##################################################################################
+
+
+##################################################################################
+dt_predict <- fread("./tmp/predict.csv")
+dt_predict[, datem := as.monthly(ISOdate(str_sub(dateym, 1, 4), str_sub(dateym, 5, 6), 1)) ]
+##################################################################################
+
+
+##################################################################################
+r1_3 = lm(rmrf_y3 ~ dp + cay + rf, data = dt_predict[ year(datem) < 2011])
+nw_r1_3 = coeftest(r1_3, df = Inf, vcov = NeweyWest(r1_3, lag = 12, prewhite = FALSE) )
+r2_3 = lm(rmrf_y3 ~ dp + cay + rf, data = dt_predict)
+nw_r2_3 = coeftest(r2_3, df = Inf, vcov = NeweyWest(r2_3, lag = 12, prewhite = FALSE) )
+
+stargazer(r1_3, nw_r1_3, r2_3, nw_r2_3, type="text")
+
+# --- output for the readme
+star = stargazer(r2_3, type="text", style = "aer",
+ covariate.labels = c("D/P ratio", "cay", "T-bill (three-month)"),
+ dep.var.labels = "Future Excess Returns",
+ omit.stat = c("ser", "adj.rsq") )
+
+star[1] = "~~~R"
+star[length(star)+1] = "~~~"
+cat(star, sep = '\n', file = './tmp/reg_update.txt')
+##################################################################################
+
+
+##################################################################################
+# OUTPUT PREDICTED VALUE
+dt_exp_rmrf <- cbind(dt_predict[!is.na(rmrf_y3), -c("datem")], exp_rmrf = predict(r2_3))
+
+fwrite(dt_exp_rmrf, "./output/predict.csv")
+##################################################################################
+
