Title: Downloads and Organizes Financial Data for Multiple Tickers
Version: 2.6.4
Description: Makes it easy to download financial data from Yahoo Finance https://finance.yahoo.com/.
Depends: R (≥ 3.4.0), rvest, dplyr
Imports: stringr, curl, quantmod, XML, tidyr, lubridate, scales, furrr, purrr, future, tibble, zoo, crayon, cli, lifecycle
License: GPL-2
RoxygenNote: 7.1.2
Suggests: knitr, rmarkdown, testthat, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-05-01 14:53:53 UTC; msperlin
Author: Marcelo Perlin [aut, cre]
Maintainer: Marcelo Perlin <marceloperlin@gmail.com>
Repository: CRAN
Date/Publication: 2022-05-01 15:40:11 UTC

Function to download financial data

Description

This function downloads financial data from Yahoo Finance using getSymbols. Based on a set of tickers and a time period, the function will download the data for each ticker and return a report of the process, along with the actual data in the long dataframe format. The main advantage of the function is that it automatically recognizes the source of the dataset from the ticker and structures the resulting data from different sources in the long format. A caching system is also available, making it very fast.

Usage

BatchGetSymbols(
  tickers,
  first.date = Sys.Date() - 30,
  last.date = Sys.Date(),
  thresh.bad.data = 0.75,
  bench.ticker = "^GSPC",
  type.return = "arit",
  freq.data = "daily",
  how.to.aggregate = "last",
  do.complete.data = FALSE,
  do.fill.missing.prices = TRUE,
  do.cache = TRUE,
  cache.folder = file.path(tempdir(), "BGS_Cache"),
  do.parallel = FALSE,
  be.quiet = FALSE
)

Arguments

tickers

A vector of tickers. If not sure whether the ticker is available, check the websites of google and yahoo finance. The source for downloading the data can either be Google or Yahoo. The function automatically selects the source webpage based on the input ticker.

first.date

The first date to download data (date or char as YYYY-MM-DD)

last.date

The last date to download data (date or char as YYYY-MM-DD)

thresh.bad.data

A percentage threshold for defining bad data. The dates of the benchmark ticker are compared to each asset. If the percentage of non-missing dates with respect to the benchmark ticker is lower than thresh.bad.data, the function will ignore the asset (default = 0.75)

bench.ticker

The ticker of the benchmark asset used to compare dates. My suggestion is to use the main stock index of the market from where the data is coming from (default = ^GSPC (SP500, US market))

type.return

Type of price return to calculate: 'arit' (default) - aritmetic, 'log' - log returns.

freq.data

Frequency of financial data ('daily', 'weekly', 'monthly', 'yearly')

how.to.aggregate

Defines whether to aggregate the data using the first observations of the aggregating period or last ('first', 'last'). For example, if freq.data = 'yearly' and how.to.aggregate = 'last', the last available day of the year will be used for all aggregated values such as price.adjusted.

do.complete.data

Return a complete/balanced dataset? If TRUE, all missing pairs of ticker-date will be replaced by NA or closest price (see input do.fill.missing.prices). Default = FALSE.

do.fill.missing.prices

Finds all missing prices and replaces them by their closest price with preference for the previous price. This ensures a balanced dataset for all assets, without any NA. Default = TRUE.

do.cache

Use cache system? (default = TRUE)

cache.folder

Where to save cache files? (default = file.path(tempdir(), 'BGS_Cache') )

do.parallel

Flag for using parallel or not (default = FALSE). Before using parallel, make sure you call function future::plan() first.

be.quiet

Logical for printing statements (default = FALSE)

Value

A list with the following items:

df.control

A dataframe containing the results of the download process for each asset

df.tickers

A dataframe with the financial data for all valid tickers

Warning

Do notice that since 2019, adjusted prices are no longer available from google finance. When using this source, the function will output NA values for this column.

Also, be aware that when using cache system in a local folder (and not the default tempdir()), the aggregate prices series might not match if a split or dividends event happens in between cache files.

See Also

getSymbols

Examples

tickers <- c('FB','MMM')

first.date <- Sys.Date()-30
last.date <- Sys.Date()

l.out <- BatchGetSymbols(tickers = tickers,
                         first.date = first.date,
                        last.date = last.date, do.cache=FALSE)

print(l.out$df.control)
print(l.out$df.tickers)

Function to download the current components of the FTSE100 index from Wikipedia

Description

This function scrapes the stocks that constitute the FTSE100 index from the wikipedia page at <https://en.wikipedia.org/wiki/FTSE_100_Index#List_of_FTSE_100_companies>.

Usage

GetFTSE100Stocks(
  do.cache = TRUE,
  cache.folder = file.path(tempdir(), "BGS_Cache")
)

Arguments

do.cache

Use cache system? (default = TRUE)

cache.folder

Where to save cache files? (default = file.path(tempdir(), 'BGS_Cache') )

Value

A dataframe that includes a column with the list of tickers of companies that belong to the FTSE100 index

Examples

## Not run: 
df.FTSE100 <- GetFTSE100Stocks()
print(df.FTSE100$tickers)

## End(Not run)

Function to download the current components of the Ibovespa index from Bovespa website

Description

This function scrapes the stocks that constitute the Ibovespa index from the wikipedia page at http://bvmf.bmfbovespa.com.br/indices/ResumoCarteiraTeorica.aspx?Indice=IBOV&idioma=pt-br.

Usage

GetIbovStocks(
  do.cache = TRUE,
  cache.folder = file.path(tempdir(), "BGS_Cache"),
  max.tries = 10
)

Arguments

do.cache

Use cache system? (default = TRUE)

cache.folder

Where to save cache files? (default = file.path(tempdir(), 'BGS_Cache') )

max.tries

Maximum number of attempts to download the data

Value

A dataframe that includes a column with the list of tickers of companies that belong to the Ibovespa index

Examples

## Not run: 
df.ibov <- GetIbovStocks()
print(df.ibov$tickers)

## End(Not run)

Function to download the current components of the SP500 index from Wikipedia

Description

This function scrapes the stocks that constitute the SP500 index from the wikipedia page at https://en.wikipedia.org/wiki/List_of_S

Usage

GetSP500Stocks(
  do.cache = TRUE,
  cache.folder = file.path(tempdir(), "BGS_Cache")
)

Arguments

do.cache

Use cache system? (default = TRUE)

cache.folder

Where to save cache files? (default = file.path(tempdir(), 'BGS_Cache') )

Value

A dataframe that includes a column with the list of tickers of companies that belong to the SP500 index

Examples

## Not run: 
df.SP500 <- GetSP500Stocks()
print(df.SP500$tickers)

## End(Not run)

Function to calculate returns from a price and ticker vector

Description

Created so that a return column is added to a dataframe with prices in the long (tidy) format.

Usage

calc.ret(P, tickers = rep("ticker", length(P)), type.return = "arit")

Arguments

P

Price vector

tickers

Ticker of symbols (usefull if working with long dataframe)

type.return

Type of price return to calculate: 'arit' (default) - aritmetic, 'log' - log returns.

Value

A vector of returns

Examples

P <- c(1,2,3)
R <- calc.ret(P)

Replaces NA values in dataframe for closest price

Description

Helper function for BatchGetSymbols. Replaces NA values and returns fixed dataframe.

Usage

df.fill.na(df.in)

Arguments

df.in

DAtaframe to be fixed

Value

A fixed dataframe.

Examples


df <- data.frame(price.adjusted = c(NA, 10, 11, NA, 12, 12.5, NA ), volume = c(1,10, 0, 2, 0, 1, 5))

df.fixed.na <- df.fill.na(df)

Fix name of ticker

Description

Removes bad symbols from names of tickers. This is useful for naming files with cache system.

Usage

fix.ticker.name(ticker.in)

Arguments

ticker.in

A bad ticker name

Value

A good ticker name

Examples

bad.ticker <- '^GSPC'
good.ticker <- fix.ticker.name(bad.ticker)
good.ticker

Get clean data from yahoo/google

Description

Get clean data from yahoo/google

Usage

get.clean.data(tickers, src = "yahoo", first.date, last.date)

Arguments

tickers

A vector of tickers. If not sure whether the ticker is available, check the websites of google and yahoo finance. The source for downloading the data can either be Google or Yahoo. The function automatically selects the source webpage based on the input ticker.

src

Source of data (yahoo or google)

first.date

The first date to download data (date or char as YYYY-MM-DD)

last.date

The last date to download data (date or char as YYYY-MM-DD)

Value

A dataframe with the cleaned data

Examples

df.sp500 <- get.clean.data('^GSPC',
                           first.date = as.Date('2010-01-01'),
                           last.date = as.Date('2010-02-01'))

An improved version of function getSymbols from quantmod

Description

This is a helper function to BatchGetSymbols and it should normaly not be called directly. The purpose of this function is to download financial data based on a ticker and a time period. The main difference from getSymbols is that it imports the data as a dataframe with proper named columns and saves data locally with the caching system.

Usage

myGetSymbols(
  ticker,
  i.ticker,
  length.tickers,
  src = "yahoo",
  first.date,
  last.date,
  do.cache = TRUE,
  cache.folder = file.path(tempdir(), "BGS_Cache"),
  df.bench = NULL,
  be.quiet = FALSE,
  thresh.bad.data
)

Arguments

ticker

A single ticker to download data

i.ticker

A index for the stock that is downloading (for cat() purposes)

length.tickers

total number of stocks being downloaded (also for cat() purposes)

src

The source of the data ('google' or'yahoo')

first.date

The first date to download data (date or char as YYYY-MM-DD)

last.date

The last date to download data (date or char as YYYY-MM-DD)

do.cache

Use cache system? (default = TRUE)

cache.folder

Where to save cache files? (default = file.path(tempdir(), 'BGS_Cache') )

df.bench

Data for bechmark ticker

be.quiet

Logical for printing statements (default = FALSE)

thresh.bad.data

A percentage threshold for defining bad data. The dates of the benchmark ticker are compared to each asset. If the percentage of non-missing dates with respect to the benchmark ticker is lower than thresh.bad.data, the function will ignore the asset (default = 0.75)

Value

A dataframe with the financial data

See Also

getSymbols for the base function

Examples

ticker <- 'FB'

first.date <- Sys.Date()-30
last.date <- Sys.Date()

## Not run: 
df.ticker <- myGetSymbols(ticker,
                          first.date = first.date,
                          last.date = last.date)

## End(Not run)

Transforms a dataframe in the long format to a list of dataframes in the wide format

Description

Transforms a dataframe in the long format to a list of dataframes in the wide format

Usage

reshape.wide(df.tickers)

Arguments

df.tickers

Dataframe in the long format

Value

A list with dataframes in the wide format

Examples


my.f <- system.file( 'extdata/ExampleData.rds', package = 'BatchGetSymbols' )
df.tickers <- readRDS(my.f)
l.wide <- reshape.wide(df.tickers)
l.wide