Once the quantmod package is installed and library is loaded, we can start using the library. We will start by showing some examples of how to download data from the web and load the data into the environment.

Quantmod provides a very powerful function for downloading financial data from the web. This function is called getSymbols. The getSymbols() method sends a request to download and manage data from public sources or local data. It is necessary to pass some parameters within this method to make the desired request. The first argument of this function is a character vector specifying the names of the symbols to be downloaded. Then you can specify the source from which you want to get the data.

The quantmod package is capable of downloading data from a variety of sources. The current supported sources are: yahoo, google, MySQL, FRED, csv, RData, and oanda. For example, FRED (Federal Reserve Economic Data), is a database of 20,070 U.S. economic time series (see http://research.stlouisfed.org/fred2/).

Example: USD/EUR exchange rates from Oanda

For example, we can run the following command to get the data of the USD/EUR exchange rates from Oanda.

getSymbols(Symbols = 'USD/EUR', src = "oanda")

# On success it will display the following and create USDEUR object
[1] "USD/EUR"

Here we have loaded the data for USD/EUR from the Oanda API which provides free currency data. The getSymbols() method doesn’t return any output. Instead, it creates an internal object in the Global Environment which in this case is the USDEUR object. The data object is an “extensible time series” (xts) object.

To see the starting point of the data, type the following command. It fetches and displays the first 15 rows of the data.

head(USDEUR,15) # You should see the following result.
 
            USD.EUR
2019-02-11 0.884834
2019-02-12 0.885164
2019-02-13 0.884514
2019-02-14 0.886430
2019-02-15 0.886331
2019-02-16 0.885238
2019-02-17 0.885267
2019-02-18 0.883885
2019-02-19 0.883780
2019-02-20 0.881384
2019-02-21 0.881816
2019-02-22 0.881970
2019-02-23 0.882340
2019-02-24 0.882317
2019-02-25 0.880924

Downloading Multiple Symbols

We can also make a request for multiple symbols. Suppose we want to request data for multiple ETFs, such as SPY, IVV, QQQ and IWF. We will first create a vector containing symbols of these ETFs. Let’s call this vector ‘etfs’. Once we have the vector, we will create two more variables defining the start date and end date for the period for which we want the data. Then we will use the getSymbols() command to actually request the data.

 
#Lists of ETFs to load
 
etfs <- c('SPY' # SPDR S&P 500 ETF TRUST 
          ,'IVV',# iShares Core S&P 500 ETF 
          'QQQ', # PowerShares QQQ Trust, Series 1
          'IWF' ) #iShares Russell 1000 Growth ETF
 
start_date <- '2014-02-01'
 
end_date <- '2019-08-06'
 
getSymbols(Symbols = etfs, src = "yahoo",  index.class = "POSIXct", from =start_date, to = end_date)
 
[1] "SPY" "IVV" "QQQ" "IWF"
 

In this example the getSymbols function returns 4 objects that are “SPY”, “IVV”, “QQQ” and “IWF”. These objects are loaded in the Global Environment. Each object should be called separately and returns only its own information.

head(SPY)
 
           SPY.Open SPY.High SPY.Low SPY.Close SPY.Volume SPY.Adjusted
2014-02-03   177.97   178.37  173.83    174.17  254837100     156.2863
2014-02-04   174.95   175.84  174.11    175.39  165012400     157.3810
2014-02-05   174.78   175.56  173.71    175.17  164230500     157.1836
2014-02-06   175.58   177.48  175.22    177.48  132877600     159.2564
2014-02-07   178.31   179.87  177.73    179.68  170787200     161.2306
2014-02-10   179.70   180.07  179.21    180.01   92218800     161.5267


head(IWF)
 
           IWF.Open IWF.High IWF.Low IWF.Close IWF.Volume IWF.Adjusted
2014-02-03    83.33    83.57   81.30     81.42    2564900     75.79685
2014-02-04    81.78    82.33   81.53     82.17    2604700     76.49506
2014-02-05    81.86    82.18   81.15     81.92    2871200     76.26232
2014-02-06    82.26    83.07   82.21     83.05    2421900     77.31428
2014-02-07    83.53    84.31   83.28     84.25    2575800     78.43140
2014-02-10    84.39    84.53   84.08     84.48    1538900     78.64553

Quantmod provides built-in functions to retrieve individual columns from the above data. In order to take separate columns for one of the above objects, we can use the following commands:

Open <- Op(IVV)   # Get only the Open Price column of IVV ETF
High <- Hi(IVV)    # Get only the High price column of IVV ETF
Low <- Lo(IVV)  # Get only the Low price column of IVV ETF
Close<- Cl(IVV)   # Get only the Close Price column of IVV ETF
Volume <- Vo(IVV)   # Get only the Volume column of IVV ETF
AdjClose <- Ad(IVV) # Get only the Adjusted close column of IVV ETF

Load Data from SQL Database

The getSymbols() function also allows loading data from a SQL database such as MySQL or Sqlite. To load data through MySQL, this function needs additional parameters such as database name, user, password and host. An example of this is described below:

getSymbols(Symbols = etfs,  src = "MySQL",  dbname = db,  user = user,  password = password, host = host, index.class = "POSIXct", from = start_date,  to = end_date)

Load Data from FRED Database

With getSymbols() we can get data from the FRED database which has thousands of datasets that cover financial, economic and production indexes, interest rates, macroeconomic indexes, monetary and international trade transactions. 

In the below example, we are downloading the Fed Fund Rate (shortest interest rate term settled by the Federal Reserve of United States) data:

getSymbols(Symbols = 'FEDFUNDS',  src = "FRED", adjust=TRUE)
 
tail(FEDFUNDS,15) # tail() gets us the last rows of the dataset
 
           FEDFUNDS
2018-07-01     1.91
2018-08-01     1.91
2018-09-01     1.95
2018-10-01     2.19
2018-11-01     2.20
2018-12-01     2.27
2019-01-01     2.40
2019-02-01     2.40
2019-03-01     2.41
2019-04-01     2.42
2019-05-01     2.39
2019-06-01     2.38
2019-07-01     2.40