Package 'yfR'

Title: Downloads and Organizes Financial Data from Yahoo Finance
Description: Facilitates download of financial data from Yahoo Finance <https://finance.yahoo.com/>, a vast repository of stock price data across multiple financial exchanges. The package offers a local caching system and support for parallel computation.
Authors: Marcelo Perlin [aut, cre], Nic Crane [rev] (Nic reviewed the package (v. 0.0.5) for rOpenSci, see <https://github.com/ropensci/software-review/issues/523>), Alexander Fischer [rev] (Alexander reviewed the package (v. 0.0.5) for rOpenSci, see <https://github.com/ropensci/software-review/issues/523>)
Maintainer: Marcelo Perlin <[email protected]>
License: MIT + file LICENSE
Version: 1.1.1
Built: 2024-10-22 05:31:32 UTC
Source: https://github.com/ropensci/yfR

Help Index


Returns the default folder for caching

Description

By default, yfR uses a temp dir to store files.

Usage

yf_cachefolder_get()

Value

a path (string)

Examples

print(yf_cachefolder_get())

Downloads a collection of data from Yahoo Finance

Description

This function will use a set collection of YF data, such as index components and will download all data from Yahoo Finance using yf_get.

Usage

yf_collection_get(
  collection,
  first_date = Sys.Date() - 30,
  last_date = Sys.Date(),
  do_parallel = FALSE,
  do_cache = TRUE,
  cache_folder = yf_cachefolder_get(),
  ...
)

Arguments

collection

A collection to fetch data (e.g. "SP500", "IBOV", "FTSE" ). See function yf_get_available_collections for finding all available collections

first_date

The first date of query (Date or character as YYYY-MM-DD)

last_date

The last date of query (Date or character as YYYY-MM-DD)

do_parallel

Flag for using parallel or not (default = FALSE). Before using parallel, make sure you call function future::plan() first. See <https://furrr.futureverse.org/> for more details.

do_cache

Use cache system? (default = TRUE)

cache_folder

Where to save cache files? (default = yfR::yf_cachefolder_get() )

...

Other arguments passed to yf_get

Value

A data frame with financial prices from collection

Examples

df_yf <- yf_collection_get(collection = "IBOV",
                           first_date = Sys.Date() - 30,
                           last_date = Sys.Date()
)

Transforms a long (stacked) data frame into a list of wide data frames

Description

Transforms a long (stacked) data frame into a list of wide data frames

Usage

yf_convert_to_wide(df_in)

Arguments

df_in

dataframe in the long format (probably the output of yf_get())

Value

A list with dataframes in the wide format (each element is a different column)

Examples

my_f <- system.file("extdata/example_data_yfR.rds", package = "yfR")
df_tickers <- readRDS(my_f)

print(df_tickers)

l_wide <- yf_convert_to_wide(df_tickers)
l_wide

Download financial data from Yahoo Finance

Description

Based on a ticker (id of a stock) and time period, this function will download stock price data from Yahoo Finance and organizes it in the long format. Yahoo Finance <https://finance.yahoo.com/> provides a vast repository of stock price data around the globe. It cover a significant number of markets and assets, being used extensively in academic research and teaching. In the website you can lookup the ticker of a company.

Usage

yf_get(
  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_cache = TRUE,
  cache_folder = yf_cachefolder_get(),
  do_parallel = FALSE,
  be_quiet = FALSE
)

Arguments

tickers

A single or vector of tickers. If not sure whether the ticker is available, search for it in YF <https://finance.yahoo.com/>.

first_date

The first date of query (Date or character as YYYY-MM-DD)

last_date

The last date of query (Date or character 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' - arithmetic (default), 'log' - log returns.

freq_data

Frequency of financial data: 'daily' (default), '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. (Default = "last")

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_cache

Use cache system? (default = TRUE)

cache_folder

Where to save cache files? (default = yfR::yf_cachefolder_get() )

do_parallel

Flag for using parallel or not (default = FALSE). Before using parallel, make sure you call function future::plan() first. See <https://furrr.futureverse.org/> for more details.

be_quiet

Flag for not printing statements (default = FALSE)

Value

A dataframe with the financial data for working days, when markets are open. All price data is measured at the unit of the financial exchange. For example, price data for META (NYSE/US) is measures in dollars, while price data for PETR3.SA (B3/BR) is measured in Reais (Brazilian currency).

The return dataframe contains the following columns:

ticker

The requested tickers (ids of stocks)

ref_date

The reference day (this can also be year/month/week when using argument freq_data)

price_open

The opening price of the day/period

price_high

The highest price of the day/period

price_close

The close/last price of the day/period

volume

The financial volume of the day/period

price_adjusted

The stock price adjusted for corporate events such as splits, dividends and others – this is usually what you want/need for studying stocks as it represents the actual financial performance of stockholders

ret_adjusted_prices

The arithmetic or log return (see input type_return) for the adjusted stock prices

ret_adjusted_prices

The arithmetic or log return (see input type_return) for the closing stock prices

cumret_adjusted_prices

The accumulated arithmetic/log return for the period (starts at 100%)

The cache system

The yfR's cache system is basically a bunch of rds files that are saved every time data is imported from YF. It indexes all data by ticker and time period. Whenever a user asks for a dataset, it first checks if the ticker/time period exists in cache and, if it does, loads the data from the rds file.

By default, a temporary folder is used (see function yf_cachefolder_get, which means that all cache files are session-persistent. In practice, whenever you restart your R/RStudio session, all cache files are lost. This is a choice I've made due to the fact that merging adjusted stock price data after corporate events (dividends/splits) is a mess and prone to errors. This only happens for stock price data, and not indices data.

If you really need a persistent cache folder, which is Ok for indices data, simply set a path with argument cache_folder (see warning section).

Warning

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.

Examples

tickers <- c("TSLA", "MMM")

first_date <- Sys.Date() - 30
last_date <- Sys.Date()

df_yf <- yf_get(
  tickers = tickers,
  first_date = first_date,
  last_date = last_date
)

print(df_yf)

Returns available collections

Description

Returns available collections

Usage

yf_get_available_collections(print_description = FALSE)

Arguments

print_description

Logical (TRUE/FALSE) - flag for printing description of available indices/collections

Value

A string vector with available collections

Examples

print(yf_get_available_collections())

Get Yahoo Finance Dividends from a single stock

Description

This function will use the json api to retrieve dividends from Yahoo finance.

Usage

yf_get_dividends(ticker, first_date = Sys.Date() - 365, last_date = Sys.Date())

Arguments

ticker

a single ticker symbol

first_date

The first date of query (Date or character as YYYY-MM-DD)

last_date

The last date of query (Date or character as YYYY-MM-DD)

Value

a tibble with dividends

Examples

yf_get_dividends(ticker = "PETR4.SA")

Get current composition of stock indices

Description

Get current composition of stock indices

Usage

yf_index_composition(
  mkt_index,
  do_cache = TRUE,
  cache_folder = yf_cachefolder_get(),
  force_fallback = FALSE
)

Arguments

mkt_index

the index (e.g. IBOV, SP500, FTSE)

do_cache

Use cache system? (default = TRUE)

cache_folder

Where to save cache files? (default = yfR::yf_cachefolder_get() )

force_fallback

Logical (TRUE/FALSE). Forces the function to use the fallback system

Value

A dataframe with the index composition (column might vary)

Examples

df_sp500 <- yf_index_composition("SP500")

Get available indices in package

Description

This function will return all available market indices that are registered in the package.

Usage

yf_index_list(print_description = FALSE)

Arguments

print_description

Logical (TRUE/FALSE) - flag for printing description of available indices/collections

Value

A vector of mkt indices

Examples

indices <- yf_index_list()
indices

Yahoo Finance Live Prices

Description

This function will use the json api to retrieve live prices from Yahoo finance.

Usage

yf_live_prices(ticker)

Arguments

ticker

a single ticker symbol

Value

a tibble with live prices

Examples

yfR::yf_live_prices("PETR4.SA")