R/stock_correlation.R

In gabrielebonvicini/aaa: What the Package Does (One Line, Title Case)

#' Compute and Plot a correlation diagram between stocks
#' 
#' Compute and Plot a correlation diagram between sotcks, or between stocks and a (single)
#' market index. 
#' 
#' @exportS3Method 
#' 
#' @param ticker A character vector storing the tickers of the stocks of which you want the 
#' correlation. 
#' Note that since data are downloaded from Yahoo finance, the ticker should be the same as
#' the ones reported on Yahoo finance. See examples.
#' 
#' @param from A single character variable storing the starting date from which we want to
#' download the data. The format should be "yyyy-mm-dd"
#' 
#' @param to A single character variable storing the ending date from which we want to
#' download the data. The format should be "yyyy-mm-dd" 
#' 
#' @param market_index A single character vector storing the ticker of the market index 
#' you want to download. Default to NULL 
#' 
#' @examples 
#' \dontrun{ 
#' x = c("AAPL", "AMZN", "F", "JPM", "DD", "IBM", "INTC") 
#' start = "1998-01-01"
#' end = "2015-01-01"
#' 
#' 
#' stock.correlation(ticker = x, market_index = "^GSPC", from = start, to = end  ) #S&P500
#' stock.correlation(ticker = x, market_index = "^IXIC", from = start, to= end  ) #Nasdaq Index
#' stock.correlation(ticker = x, market_index = "FTSEMIB.MI", from = start, to = end ) #FTSE MIB Index 
#' stock.correlation(ticker = x, from = start, to = end) #No market index
#' }
#' 
#' 
#'  




stock.correlation <- function( ticker, from, to, market_index = NULL) { 
if ( is.null(market_index) ) { 
  #download data 
data <- getSymbols(ticker, from = from, to = to, 
                   auto.assign = T  ) %>% 
  purrr::map(~Ad(get(.))) %>% reduce(merge)


#remove NA cells 
data <- na.omit(data)
#appropraite name 
colnames(data) <-  ticker  
#significance test 
mtest = cor.mtest(data)   #put the data here and not the correlations


#start plotting 
if ( length(ticker) > 6 ) { 
  corrplot( cor(data), method = "number", mar = c(1,1,1,1),
            number.font = 4, number.cex = 0.6, 
            p.mat = mtest$p, sig.level = 0.05 , insig = "blank",
            col = COL1( sequential =  "YlOrRd" ) , tl.cex = 0.7 )
  print("Please expand the Area dedicated to Images to better visualize the correlation plot")
  print("Blank spaces are non significant correlations (sig.level = 0.05)")
  
} else { 
  corrplot( cor(data), method = "number", mar = c(1,1,1,1), 
            cl.ratio = 0.25, tl.cex = 0.9, number.cex = 0.9, 
            p.mat = mtest$p, sig.level = 0.05) 
  print("Non significant correlation are crossed (sign.level = 0.05)")
} 
 } else { 
  data <- getSymbols(ticker, from = from, to = to, 
                     auto.assign = T  ) %>% 
    purrr::map(~Ad(get(.))) %>% reduce(merge)
  
  data2 <- getSymbols(market_index, from = from, to = to, 
                      env = NULL )
  data2 <- data2[ ,6]
  
  
  #remove NA cells 
  data <- merge(data, data2)
  data <- na.omit(data)
  #appropraite name 
  colnames(data) <- c( ticker , market_index ) 
  #significance test 
  mtest = cor.mtest(data)   #put the data here and not the correlations
  
  
  #start plotting 
  if ( length(ticker) > 6 ) { 
    corrplot( cor(data), method = "number", mar = c(1,1,1,1),
              number.font = 4, number.cex = 0.6, 
              p.mat = mtest$p, sig.level = 0.05 , insig = "blank",
              col = COL1( sequential =  "YlOrRd" ) , tl.cex = 0.7 )
    print("Please expand the Area dedicated to Images to better visualize the correlation plot")
    print("Blank spaces are non significant correlations (sig.level = 0.05)")
    
  } else { 
    corrplot( cor(data), method = "number", mar = c(1,1,1,1), 
              cl.ratio = 0.25, tl.cex = 0.9, number.cex = 0.9, 
              p.mat = mtest$p, sig.level = 0.05) 
    print("Non significant correlation are crossed (sign.level = 0.05)")
  } 
  
 }
}

#TRY 
x = c("AAPL", "AMZN", "F", "JPM", "DD", "IBM", "INTC") 
market_index = "^GSPC"
from = "1998-01-01"
to = "2015-01-01"

stock.correlation(ticker = x, market_index = "^GSPC" , from,to )
stock.correlation(ticker = x  , market_index = "^IXIC" , from,to ) #nasdaq
stock.correlation(ticker = x  , market_index = "FTSEMIB.MI" , from,to ) #Ftsemib
stock.correlation(ticker = x  , from,to ) #No market index