R/egcm_extras.R

In matthewclegg/egcm: Engle-Granger Cointegration Models

# egcm_extras.R
# Copyright (C) 2014 by Matthew Clegg

# A few extra helper routines for the egcm module.

#  This program is free software; you can redistribute it and/or modify
#  it under the terms of the GNU General Public License as published by
#  the Free Software Foundation; either version 2 of the License, or
#  (at your option) any later version.
#
#  This program is distributed in the hope that it will be useful,
#  but WITHOUT ANY WARRANTY; without even the implied warranty of
#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#  GNU General Public License for more details.
#
#  A copy of the GNU General Public License is available at
#  http://www.r-project.org/Licenses/

library(quantmod)


# Helper function to replace NAs and Inf values with the last available price
na.inf.locf<-function(ts){
  if(sum(is.infinite(ts)) > 0){
    find.inf<-which(is.infinite(ts),arr.ind = TRUE)
    for(i in 1:nrow(find.inf)){
      
      ts[find.inf[i,1],find.inf[i,2]]<-NA
    }
  }
  
  result<-zoo::na.locf(ts)
  return(result)
}



multigetYahooPrices <- function (
  components,     # Character vector of Yahoo ticker symbols
  start,          # First date of desired data in YYYYMMDD format.
  end,        # Last date of desired data in YYYYMMDD format.
  iwarnings = FALSE, # Suppress warnings generated by getSymbols()
  src = "yahoo", # source to fetch the data from
  auto.assign=FALSE, # If TRUE, price data are automatically assigend to an R-object within the global.env with a name equal to the ticker
  quiet=FALSE, # If False, ticker names are printed
  choose.col=c("Adjusted"), # A vector of Strings containing the columns which should be included within the analysis
  clear.na.inf = TRUE # Replaces "NA" and "inf" values by the last available price
) {
  # Given a list of ticker symbols, fetches the
  # adjusted closing prices of each of the symbols in the
  # list from Yahoo!, and creates a return.class data.frame.
  
  
  
  yahooParams <- list(Symbols="NA", warnings=iwarnings,src = src, auto.assign=auto.assign, quiet=quiet)
  if (!missing(start)) yahooParams["from"] <- start
  if (!missing(end)) yahooParams["to"] <- end
  get_ticker <- function (t) { 
    if (!quiet) cat(t, " ")
    p <- NULL
    #    try (p <- getYahooData (t, startdate, enddate, adjust=adjust) )
    yahooParams["Symbols"] <- t
    
    try (p <- do.call("getSymbols",yahooParams))
    
    if (is.null(dim(p))) return(NULL)
    select.col<-paste(t,choose.col,sep = ".")
    
    p<-as.xts(zoo::coredata(p[,select.col]),index(p))
  
      if(clear.na.inf == TRUE){
        p_san<-na.inf.locf(p)
        return(p_san)
      } else {
        return(p)
      }
  }  
  
  
  
  all_prices <- lapply(components, get_ticker)
  if (!quiet) cat("\n")
  not_null <- !c(lapply(all_prices, is.null), recursive=TRUE)
  all_prices <- do.call("cbind", all_prices[not_null])
  if(length(choose.col)==1){
    colnames.final<-paste(components,choose.col,sep = ".")
    colnames(all_prices)<-colnames.final
  }
  
  all_prices
}

yegcm<-function(ticker1, ticker2, 
                start = format(Sys.Date() - 365, "%Y-%m-%d"),
                end = format(Sys.Date(), "%Y-%m-%d"),
                clear.na.inf=TRUE,
                ...){ 
  prices.ticker<-multigetYahooPrices(components = c(ticker1,ticker2), start= start, end = end,
                                     clear.na.inf=clear.na.inf)
  p1 <- prices.ticker[,1]
  p2 <- prices.ticker[,2]
  prices <- cbind(p1, p2)
  colnames(prices) <- c(ticker1, ticker2)
  e <- egcm(prices, ...)
  e
}



allpairs.egcm <- function (tickers, # A list of ticker symbols of securites
    startdate = format(Sys.Date() - 365, "%Y-%m-%d"), # Starting date
    enddate = format(Sys.Date(), "%Y-%m-%d"),   # Ending date
    clear.na.inf=TRUE, # replaces NA and Inf values by the latest available price
    ...  # Additional parameters for egcm
) {
    # Constructs Engle-Granger cointegration models for all pairs
    # of tickers, using data from startdate to enddate.  The data
    # is fetched from Yahoo! using TTR.
    #
    # Copyright (C) 2014 Matthew Clegg
    #
    # Example:
    #   allpairs.egcm(c("SPY","DIA","QQQ","VOO"), 20130101, 20131231)
    #
    # Input parameters:
    #   tickers:    A list of ticker symbols
    #   startdate:  Starting date for the data.  Given as YYYYMMDD
    #   enddate:    Ending date for the data.  Given as YYYYMMDD
    #   ...:        Additional parameters to be passed to egcm function
    #
    # Returns:
    #   A data.frame containing the results of performing pairwise
    #   cointegration tests.  The columns of the data.frame are as
    #   follows:
    #
    #	series1:  Name of the first ticker in this cointegration test
    #	series2:  Name of the second ticker in this cointegration test
    #   log:      Boolean which if TRUE indicates that the cointegration
    #             test is performed on the logs of the series
    #   i1test:   Name of the test used for checking that the series are
    #             integrated.
    #   urtest:   Name of the test used for checking for a unit root in
    #             the residual series
    #   alpha:    Constant term of the linear relation between the series
    #   alpha.se: Standard error of alpha
    #   beta:     Linear term of the linear relation between the series
    #   beta.se:  Standard error of beta
    #   rho:      Coefficient of mean reversion
    #   rho.se:   Standard error of rho
    #   s1.i1.stat: Statistic computed for integration test of first series
    #   s1.i1.p:   p-value for integration test of first series
    #   s2.i1.stat: Statistic computed for integration test of second series
    #   s2.i1.p:   p-value for integration test of second series
    #   r.stat:    Statistic computed for cointegration test (e.g. whether
    #              the residual series contains a unit root)
    #   r.p:       p-value associated with r.stat
    #   eps.ljungbox.stat:  Ljung-Box statistic computed on the innovations
    #              of the series
    #   eps.ljungbox.p:  p-value associated with the Ljung-Box statistic
    #   s1.dsd:    Standard deviation of the first differences of the first series
    #   s2.dsd:    Standard deviation of the first differences of the second series
    #   residuals.sd: Standard deviation of the residual series
    #   eps.sd:    Standard deviation of the innovations
    #   is.cointegrated:  TRUE if the pair is cointegrated at the 5% confidence level

#    require(TTR)

    if (missing(tickers) || (length(tickers) < 2)) {
        stop("tickers must contain at least two ticker symbols")
    }
    
    if (!is.null(dim(tickers)) && length(dim(tickers)) > 1) {
        data <- as.data.frame(tickers)
        tickers <- colnames(data)
    } else {
        data <- do.call("cbind", lapply(tickers, 
            function(t) try(multigetYahooPrices(t, start = startdate, end = enddate,clear.na.inf=clear.na.inf,
                                                          auto.assign = FALSE), silent=TRUE)))
        colnames(data) <- tickers
    }
    
    if (any(is.na(data))) {
        missing_cols <- apply(data, 2, function(x) any(is.na(x)))
        stop ("There were missing observations in the data for ", tickers[missing_cols])
    }
    
    idf <- expand.grid(1:length(tickers), 1:length(tickers))
    idf <- idf[idf[,1] < idf[,2],]
    egcm.df <- do.call("rbind", lapply(1:nrow(idf), 
        function(k) as.data.frame(egcm(data[,c(idf[k,1], idf[k,2])], ...))))
    egcm.df$is.cointegrated <- (egcm.df$s1.i1.p > 0.05) & (egcm.df$s2.i1.p > 0.05) &
        (egcm.df$r.p <= 0.05)
        
    egcm.df
}