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README.md

alphavantager

https://travis-ci.org/business-science/alphavantager.svg?branch=master codecov CRAN_Status_Badge

A lightweight R interface to the Alpha Vantage API

Alpha Vantage

Alpha Vantage is a free service that enables users to get real-time and historical financial data. New users will need to visit Alpha Vantage and obtain an API key.

R Interface: Getting Started

The alphavantager package provides a convenient and lightweight interface to the Alpha Vantage API.

To get started, install the package from CRAN or from GitHub:

install.packages("alphavantager")
# Or
devtools::install_github("business-science/alphavantager")

Load the package.

library(alphavantager)

Set your API key (get one from Alpha Vantage if you don’t already have one… it’s free).

av_api_key("YOUR_API_KEY")
print(av_api_key())
#> [1] "YOUR_API_KEY"

Getting Financial Data from Alpha Vantage

Now, you’re ready to get financial data via av_get(), which accepts the same1 arguments as the API Documentation parameters. The function is setup with two primary arguments, symbol and av_fun, which accepts an equity and one of the API “function” parameters. You can pass additional API parameters via the ....

# Function is streamlined and user adds additional parameters via ...
args(av_get)
#> function (symbol, av_fun, ...)
#> NULL

Here are a few examples of retrieving real-time and historical financial data!

Time Series Data

av_get(symbol     = "MSFT",
       av_fun     = "TIME_SERIES_INTRADAY",
       interval   = "15min",
       outputsize = "full")
#> # A tibble: 780 x 6
#>    timestamp            open  high   low close  volume
#>    <dttm>              <dbl> <dbl> <dbl> <dbl>   <dbl>
#>  1 2020-01-16 09:45:00  164.  165.  164.  164. 1462062
#>  2 2020-01-16 10:00:00  164.  165.  164.  165.  848193
#>  3 2020-01-16 10:15:00  165.  165.  165.  165.  871392
#>  4 2020-01-16 10:30:00  165.  165.  165.  165.  581252
#>  5 2020-01-16 10:45:00  165.  165.  165.  165.  573179
#>  6 2020-01-16 11:00:00  165.  165.  165.  165.  603171
#>  7 2020-01-16 11:15:00  165.  165.  165.  165.  561376
#>  8 2020-01-16 11:30:00  165.  165.  165.  165.  392252
#>  9 2020-01-16 11:45:00  165.  165.  165.  165.  382030
#> 10 2020-01-16 12:00:00  165.  165.  165.  165.  365478
#> # … with 770 more rows

ForEx

# REAL-TIME QUOTE
av_get("EUR/USD", av_fun = "CURRENCY_EXCHANGE_RATE")
#> # A tibble: 1 x 9
#>   from_currency_c… from_currency_n… to_currency_code to_currency_name
#>   <chr>            <chr>            <chr>            <chr>
#> 1 EUR              Euro             USD              United States D…
#> # … with 5 more variables: exchange_rate <dbl>, last_refreshed <dttm>,
#> #   time_zone <chr>, bid_price <dbl>, ask_price <dbl>
# TIME SERIES
av_get("EUR/USD", av_fun = "FX_DAILY", outputsize = "full")
#> # A tibble: 5,000 x 5
#>    timestamp   open  high   low close
#>    <date>     <dbl> <dbl> <dbl> <dbl>
#>  1 2002-02-12 0.876 0.880 0.874 0.876
#>  2 2002-02-13 0.876 0.877 0.87  0.871
#>  3 2002-02-14 0.871 0.874 0.868 0.874
#>  4 2002-02-15 0.874 0.875 0.869 0.872
#>  5 2002-02-18 0.873 0.874 0.870 0.870
#>  6 2002-02-19 0.871 0.878 0.866 0.876
#>  7 2002-02-20 0.876 0.878 0.870 0.870
#>  8 2002-02-21 0.87  0.872 0.868 0.869
#>  9 2002-02-22 0.868 0.878 0.868 0.876
#> 10 2002-02-25 0.875 0.876 0.868 0.869
#> # … with 4,990 more rows

Technical Indicators

av_get(symbol      = "MSFT",
       av_fun      = "AROON",
       interval    = "monthly",
       time_period = 60,
       outputsize  = "full")
#> # A tibble: 180 x 3
#>    time       aroon_down aroon_up
#>    <date>          <dbl>    <dbl>
#>  1 2020-02-28       10      100
#>  2 2020-01-31       11.7    100
#>  3 2019-12-31       13.3    100
#>  4 2019-11-29       15      100
#>  5 2019-10-31       16.7    100
#>  6 2019-09-30       18.3    100
#>  7 2019-08-30       20       98.3
#>  8 2019-07-31       21.7    100
#>  9 2019-06-28       23.3    100
#> 10 2019-05-31        0       98.3
#> # … with 170 more rows

Sector Performances

av_get(av_fun = "SECTOR")
#> # A tibble: 110 x 3
#>    rank_group                             sector  change
#>    <chr>                                  <chr>    <dbl>
#>  1 Rank A: Real-Time Performance          Energy  0.0125
#>  2 Rank B: 1 Day Performance              Energy  0.0125
#>  3 Rank C: 5 Day Performance              Energy -0.154
#>  4 Rank D: 1 Month Performance            Energy -0.178
#>  5 Rank E: 3 Month Performance            Energy -0.212
#>  6 Rank F: Year-to-Date (YTD) Performance Energy -0.247
#>  7 Rank G: 1 Year Performance             Energy -0.291
#>  8 Rank H: 3 Year Performance             Energy -0.341
#>  9 Rank I: 5 Year Performance             Energy -0.405
#> 10 Rank J: 10 Year Performance            Energy -0.179
#> # … with 100 more rows

Fundamental Data

av_get(symbol = "MSFT",
       av_fun = "OVERVIEW")

#> # A tibble: 59 x 2
#>   rank_group  value
#>   <chr>       <chr>
#> 1 Symbol      MSFT
#> 2 AssetType   Common Stock
#> 3 Name        Microsoft Corporation
#> 4 Description Microsoft Corporation develops, licenses, and supports software,…
#> 5 Exchange    NASDAQ
#> 6 Currency    USD
#> 7 Country     USA
#> 8 Sector      Technology
#> 9 Industry    SoftwareInfrastructure
#> 10 Address     One Microsoft Way, Redmond, WA, United States, 98052-6399
#> # … with 49 more rows

Important Notes: av_get()

  1. The av_fun argument replaces the API parameter “function” because function is a reserved name in R. All other arguments match the Alpha Vantage API parameters.

  2. There is no need to specify the apikey parameter as an argument to av_get(). The required method is to set the API key using av_api_key("YOUR_API_KEY").

  3. There is no need to specify the datatype parameter as an argument to av_get(). The function will return a tibble data frame.

  4. Some data sets only return 100 rows by default. Change the parameter outputsize = "full" to get the full dataset.