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R code snippet : Read Historical Prices of Cryptocurrencies

sang-heon lee
[This article was first published on SH Fintech Modeling, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
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< !--shlee --> This post shows how to read prices of cryptocurrencies given symbols as a string.


Read historical prices of cryptocurrencies



Pairs trading also can be applied to cryptocurrencies. It is, therefore, a starting point of pairs trading backtest to collect daily prices of them. I collected the symbols of major cryptocurrencies at

https://finance.yahoo.com/cryptocurrencies/


Some limitations : data lengths


It is worth noting that the quantmod R package we used in this work does not provide the full or longer history of crypto prices. For example the first historical data of BTC begins at 2014-09-17 and ETH at 2017-11-09. The available sample periods of some coins are similar to or less than that of ETH.


R code


The following R code retrieves historical daily prices of major cryptocurrencies given their symbols as of 2022-08-13.


< !--shlee -->
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#========================================================#
# Quantitative ALM, Financial Econometrics & Derivatives 
# ML/DL using R, Python, Tensorflow by Sang-Heon Lee 
#
# https://kiandlee.blogspot.com
#——————————————————–#
# read prices of cryptocurrencies
#========================================================#
 
graphics.off(); rm(list = ls())
 
library(quantmod)
 
#————————————————-
# Major cryptocurrencies, as of 2022-08-13
#————————————————-
vstr_crypto <– “
    code        ,    name
    BTC-USD     ,    Bitcoin USD        
    ETH-USD     ,    Ethereum USD
    USDT-USD    ,    Tether USD
    USDC-USD    ,    USD Coin USD
    BNB-USD     ,    Binance Coin USD
    ADA-USD     ,    Cardano USD
    XRP-USD     ,    XRP USD
    BUSD-USD    ,    Binance USD USD
    SOL-USD     ,    Solana USD
    HEX-USD     ,    HEX USD
    DOT-USD     ,    Polkadot USD
    DOGE-USD    ,    Dogecoin USD
    AVAX-USD    ,    Avalanche USD
    MATIC-USD   ,    Polygon USD
    DAI-USD     ,    Dai USD
    WTRX-USD    ,    Wrapped TRON USD
    SHIB-USD    ,    SHIBA INU USD
    STETH-USD   ,    Lido stETH USD
    UNI1-USD    ,    Uniswap USD
    TRX-USD     ,    TRON USD
    ETC-USD     ,    Ethereum Classic USD
    WBTC-USD    ,    Wrapped Bitcoin USD
    LEO-USD     ,    UNUS SED LEO USD
    LTC-USD     ,    Litecoin USD
    NEAR-USD    ,    NEAR-USD
“
 
#——————————————-
# split symbols and make vector
#——————————————-
df      <– read.table(text = vstr_crypto, 
                      sep = “,”, header = TRUE)
df      <– as.data.frame(df)
df$code <– gsub(“[\t\r\n ,]”,“”,df$code)
df$name <– gsub(“[\t\r\n ,]”,“”,df$name)
df
nc <– nrow(df) # number of crypto
 
#——————————————-
# read price information
#——————————————-
 
# limitation of data length
# BTC                 : from 2014-09-17
# ETH and some coins  : from 2017-11-09
# others              : short period
 
sdate <– as.Date(“2017-11-09”)
edate <– as.Date(“2022-08-12”)
getSymbols(df$code,from=sdate,to=edate)
 
#——————————————-
# collect only adjusted prices
#——————————————-
price <– NULL
for(i in 1:nc) {
    eval(parse(text=paste0(
        “price <- cbind(price,`”,
         df$code[i],“`[,6])”)))
}
 
# modify column name as only symbol
colnames(price) <– gsub(“.USD.Adjusted”, “”, 
                        colnames(price))
 
#——————————————-
# print time series of daily prices
#——————————————-
head(price)
tail(price)
 
cs


< !--shlee --> Running the above R code displays the status of data reading process as follows.



Finally, we can get the collection of individual cryptocurrency prices.




< !--shlee -->
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