## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup, eval=TRUE, echo=FALSE, warning=FALSE, message=FALSE---------------
library(FFdownload)
library(dplyr)
library(ggplot2)
library(tidyr)
outd    <- paste0(tempdir(),"/",format(Sys.time(), "%F_%H-%M"))
outfile <- paste0(outd,"FFData_tbl.RData")

## ----setup2, eval=FALSE, echo=TRUE--------------------------------------------
# library(FFdownload)
# library(tidyverse)
# outd    <- paste0("data/", format(Sys.time(), "%F_%H-%M"))
# outfile <- paste0(outd, "FFData_tbl.RData")

## ----tbl_ffget, eval=FALSE----------------------------------------------------
# # Monthly FF 3-factor data as a tibble, NAs handled automatically
# ff3 <- FFget("F-F_Research_Data_Factors", subtable = "Temp2")
# head(ff3)
# #> # A tibble: 6 × 5
# #>   date      Mkt.RF   SMB   HML    RF
# #>   <yearmon>  <dbl> <dbl> <dbl> <dbl>
# #> 1 Jul 1926    2.89 -2.55 -2.39  0.22
# #> ...

## ----tbl_ffget_all, eval=FALSE------------------------------------------------
# # All sub-tables for the monthly frequency
# ff3_monthly <- FFget("F-F_Research_Data_Factors", subtable = NULL)
# names(ff3_monthly)   # e.g. "Temp2"
# 
# # Annual data as xts
# ff3_ann_xts <- FFget("F-F_Research_Data_Factors", frequency = "annual", format = "xts")

## ----tbl_fflist, eval=FALSE---------------------------------------------------
# fl <- FFlist()
# nrow(fl)         # 100+ non-daily datasets
# fl |> filter(grepl("5_Factors|Momentum", name))

## ----tbl_ffmatch, eval=FALSE--------------------------------------------------
# FFmatch(c("Research_Data_Factors", "Momentum_Factor"))
# #> # A tibble: 2 × 4
# #>   requested             matched                    edit_distance similarity
# #>   <chr>                 <chr>                              <int>      <dbl>
# #> 1 Research_Data_Factors F-F_Research_Data_Factors              3      0.87
# #> 2 Momentum_Factor       F-F_Momentum_Factor                    4      0.78

## ----tbl_all------------------------------------------------------------------
inputlist <- c("F-F_Research_Data_Factors_CSV","F-F_Momentum_Factor_CSV")
FFdownload(exclude_daily=TRUE, tempd=outd, download=TRUE, download_only=FALSE,
           inputlist=inputlist, output_file=outfile, format="tibble")

## ----tbl_na_values, eval=FALSE------------------------------------------------
# FFdownload(exclude_daily=TRUE, tempd=outd, download=TRUE, download_only=FALSE,
#            inputlist=inputlist, output_file=outfile, format="tibble",
#            na_values=c(-99, -999, -99.99))

## ----tbl_return_data, eval=FALSE----------------------------------------------
# FFdata <- FFdownload(exclude_daily=TRUE, tempd=outd, download=TRUE,
#                      download_only=FALSE, inputlist=inputlist,
#                      output_file=outfile, format="tibble",
#                      return_data=TRUE)

## ----tbl_load-----------------------------------------------------------------
load(outfile)
ls.str(FFdata)

## ----tbl_check----------------------------------------------------------------
str(FFdata$`x_F-F_Research_Data_Factors`$monthly$Temp2)

## ----tbl_merge----------------------------------------------------------------
FFfour <- FFdata$`x_F-F_Research_Data_Factors`$monthly$Temp2 %>%
  left_join(FFdata$`x_F-F_Momentum_Factor`$monthly$Temp2, by="date")
FFfour %>% head()

## ----FFFourPic, out.width="100%", fig.width=8, fig.height=4-------------------
FFfour %>%
  pivot_longer(Mkt.RF:Mom, names_to="FFVar", values_to="FFret") %>%
  mutate(FFret=FFret/100, date=as.Date(date)) %>%
  filter(date>="1960-01-01", !FFVar=="RF") %>%
  group_by(FFVar) %>% arrange(FFVar, date) %>%
  mutate(FFret=ifelse(date=="1960-01-01",1,FFret), FFretv=cumprod(1+FFret)-1) %>%
  ggplot(aes(x=date, y=FFretv, col=FFVar, type=FFVar)) + geom_line(lwd=1.2) +
  scale_y_log10() +
  labs(title="FF4 Factors", subtitle="Cumulative wealth plots", ylab="cum. returns") +
  scale_colour_viridis_d("FFvar") +
  theme_bw() + theme(legend.position="bottom")