R/DataPrepare.R
In ivanliu1989/RQuantTrader: A collection of functions for pair trading
Defines functions
prepareForexData
prepareForexOandaData
prepareIBForexPrices
prepareForexOandaPrices
Documented in
prepareForexData
prepareForexOandaData
prepareForexOandaPrices
prepareIBForexPrices
#' Prepare all required datasets for FX daily Modeling
#'
#' Prepare all required datasets for FX daily Modeling.
#'
#' @param ib.duration length of data to retreive from Interactive Broker
#' @param ib.barsize the barsize of IB data
#' @param Cur1 currency one
#' @param Cur2 currency two
#' @param oanda.granularity barsize of Oanda data
#' @param QuandlSymbol1 currency one for Quandl
#' @param QuandlSymbol2 currency two for Quandl
#' @param ibAcc account type of Interactive Brokers (live or paper)
#'
#' @return A \code{list} of \code{xts}
#'
#' @examples
#' res = prepareForexData(ib.duration = "1 Y", ib.barsize = "1 day", Cur1 = "USD", Cur2 = "CAD",
#' oanda.granularity = 'D', QuandlSymbol1 = 'CAN', QuandlSymbol2 = 'USA')
#'
#' @export
prepareForexData <- function(ib.duration = "1 Y", ib.barsize = "1 day", Cur1 = "USD", Cur2 = "CAD",
oanda.granularity = 'D', QuandlSymbol1 = 'CAN', QuandlSymbol2 = 'USA', ibAcc = 'paper'){
library(IBrokers)
library(RQuantAPI)
convertToXts <- function(cm, tzone = ""){
dts <- structure(as.numeric(as.POSIXlt(gsub("(\\d{4})(\\d{2})(\\d{2})",
"\\1-\\2-\\3", cm[, 1], perl = TRUE))),
class = c("POSIXct","POSIXt"), tzone = tzone)
if(ncol(cm) > 2){
x <- xts(as.matrix(apply(cm[, -1], 2, as.numeric)), order.by = dts, tzone = tzone)
}else{
x <- xts(as.numeric(cm[, -1]), order.by = dts, tzone = tzone)
}
return(x)
}
instrument = paste0(Cur1, '_', Cur2)
if(ibAcc == 'live'){
tws <- twsConnect(port = 7496, clientId = 999)
}else{
tws <- twsConnect(port = 7497, clientId = 998)
}
# IB OHLC -----------------------------------------------------------------
cat('\nLoading Interactive Brokers OHLC...\n')
ccy <- reqContractDetails(tws, twsCurrency(Cur1, Cur2))[[1]]$contract
cols = c('Open', 'High', 'Low', 'Close')
# Bid Ask
IB.BIDASK <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='BID_ASK')
IB.BIDASK = IB.BIDASK[, 1:4]
IB.BIDASK = IB.BIDASK[!duplicated(index(IB.BIDASK)), ]
colnames(IB.BIDASK) = paste0('IB.BA.', cols)
# Mid
IB.MID <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='MIDPOINT')
IB.MID = IB.MID[, 1:4]
IB.MID = IB.MID[!duplicated(index(IB.MID)), ]
colnames(IB.MID) = paste0('IB.M.', cols)
# Bid
IB.BID <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='BID')
IB.BID = IB.BID[, 1:4]
IB.BID = IB.BID[!duplicated(index(IB.BID)), ]
colnames(IB.BID) = paste0('IB.B.', cols)
# Ask
IB.ASK <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='ASK')
IB.ASK = IB.ASK[, 1:4]
IB.ASK = IB.ASK[!duplicated(index(IB.ASK)), ]
colnames(IB.ASK) = paste0('IB.A.', cols)
# IB Spreads --------------------------------------------------------------
cat('\nLoading Interactive Brokers Spreads...\n')
IB.SPREADS = IB.ASK - IB.BID
colnames(IB.SPREADS) = paste0('IB.SP.', cols)
IB.SPREADS.Perc = (IB.SPREADS / IB.MID) * 100
colnames(IB.SPREADS.Perc) = paste0('IB.SPP.', cols)
# IB Volatility -----------------------------------------------------------
cat('\nLoading Interactive Brokers Volatility...\n')
IB.VOLATILITY <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='HISTORICAL_VOLATILITY')
IB.VOLATILITY = IB.VOLATILITY[,6]
IB.VOLATILITY = IB.VOLATILITY[!duplicated(index(IB.VOLATILITY)), ]
colnames(IB.VOLATILITY) = paste0('IB.Volatility.',Cur1, '.', Cur2)
# Oanda OHLC --------------------------------------------------------------
cat('\nLoading Oanda OHLC...\n')
oanda.count = nrow(IB.BIDASK) + 1
OA.ALL = getOandaInstrumentCandles(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, INSTRUMENTS = instrument,
price = 'BA', granularity = oanda.granularity, count = oanda.count)
OA.ALL = convertToXts(OA.ALL[, -1])
colnames(OA.ALL) = c('OA.Volume', 'OA.Ask.Close', 'OA.Ask.High', 'OA.Ask.Low', 'OA.Ask.Open'
, 'OA.Bid.Close', 'OA.Bid.High', 'OA.Bid.Low', 'OA.Bid.Open')
OA.BIDASK = OA.ALL[, -1]
# Oanda Spreads -----------------------------------------------------------
# OA.SPREADS = SpreadsOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
# INSTRUMENTS = instrument, PERIOD = '1 year')
cat('\nLoading Oanda Spreads...\n')
OA.SPREADS = OA.ALL[, 2:5] - OA.ALL[, 6:9]
OA.SPREADS.Perc = ((OA.ALL[, 2:5] - OA.ALL[, 6:9])/((OA.ALL[, 2:5] + OA.ALL[, 6:9])/2)) * 100
# Oanda Volume ------------------------------------------------------------
cat('\nLoading Oanda Volume...\n')
OA.VOLUME = OA.ALL[, 1]
# Oanda Net Positions -----------------------------------------------------
cat('\nLoading Oanda New Positions...\n')
OA.HistPos <- HistoricalPositionOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
INSTRUMENTS = instrument, PERIOD = '1 year')
OA.HistPos = convertToXts(as.data.frame(OA.HistPos)[, -1])
colnames(OA.HistPos) = c('OA.LongPosRatio', 'OA.ExRate')
OA.HistPos$OA.PosCorr = rollapply(OA.HistPos, by.column = F, width = 20, function(x) cor(x)[1,2])
# Oanda CBOT --------------------------------------------------------------
cat('\nLoading Oanda / Quandl CBOT...\n')
OA.CBOT = COT.Oanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, INSTRUMENTS = instrument)
OA.CBOT = convertToXts(as.data.frame(OA.CBOT)[, -6])
# calNet <- function(x,y){
# net <- (x-y)/(x+y)
# return(net)
# }
# CFTC.AUD <- Quandl("CFTC/TIFF_CME_AD_ALL")
# CFTC.AUD <- as.xts(calNet(CFTC.AUD$`Lev Money Long Positions`,CFTC.AUD$`Lev Money Short Positions`),CFTC.AUD$Date)
# Oanda Autochartist ------------------------------------------------------
cat('\nLoading Oanda / Autochartist Signals...\n')
Oanda.Autochartist = Autochartist.Oanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN,
INSTRUMENTS = instrument, PERIOD = '1 week')
# Quandl Indexes ----------------------------------------------------------
cat('\nLoading Quandl Equity Indexes...\n')
QuandlConnect()
# AU
EI.ASX <- Quandl("YAHOO/INDEX_AXJO")
# Canada
EI.TSX <- Quandl("YAHOO/INDEX_GSPTSE")
# USA
EI.USA <- Quandl("YAHOO/INDEX_GSPC")
# China
EI.SSEC <- Quandl("YAHOO/INDEX_SSEC")
# Mexico
EI.MXX <- Quandl("YAHOO/INDEX_MXX")
# Germany
EI.GDAXI <- Quandl("YAHOO/INDEX_GDAXI")
# Japan
EI.NIKKEI <- Quandl("NIKKEI/INDEX")
# South Korea
EI.KS11 <- Quandl("YAHOO/INDEX_KS11")
# France
EI.FCHI <- Quandl("YAHOO/INDEX_FCHI")
# Switzerland
EI.SSMI <- Quandl("YAHOO/INDEX_SSMI")
# India
EI.BSESN <- Quandl("YAHOO/INDEX_BSESN")
# Brazil
EI.BCB <- Quandl("BCB/7")
# Netherlands
EI.AEX <- Quandl("YAHOO/INDEX_AEX")
# Germany
EI.GDAXI <- Quandl("YAHOO/INDEX_GDAXI")
# Singapore
EI.STI <- Quandl("YAHOO/INDEX_STI")
# New Zealand
EI.NZ50 <- Quandl("YAHOO/INDEX_NZ50")
# Indonesia
EI.JKSE <- Quandl("YAHOO/INDEX_JKSE")
# Malaysia
# India
# Peru
# Thailand
# Vietnam
# UK
# Italy
all.equity.index <- merge(as.xts(EI.ASX$`Adjusted Close`, EI.ASX$Date)
,as.xts(EI.TSX$`Adjusted Close`, EI.TSX$Date)
,as.xts(EI.USA$`Adjusted Close`, EI.USA$Date)
,as.xts(EI.SSEC$`Adjusted Close`, EI.SSEC$Date)
,as.xts(EI.MXX$`Adjusted Close`, EI.MXX$Date)
,as.xts(EI.GDAXI$`Adjusted Close`, EI.GDAXI$Date)
,as.xts(EI.NIKKEI$`Close Price`, EI.NIKKEI$Date)
,as.xts(EI.KS11$`Adjusted Close`, EI.KS11$Date)
,as.xts(EI.FCHI$`Adjusted Close`, EI.FCHI$Date)
,as.xts(EI.SSMI$`Adjusted Close`, EI.SSMI$Date)
,as.xts(EI.BSESN$`Adjusted Close`, EI.BSESN$Date)
,as.xts(EI.BCB$Value, EI.BCB$Date)
,as.xts(EI.AEX$`Adjusted Close`, EI.AEX$Date)
,as.xts(EI.GDAXI$`Adjusted Close`, EI.GDAXI$Date)
,as.xts(EI.STI$`Adjusted Close`, EI.STI$Date)
,as.xts(EI.NZ50$`Adjusted Close`, EI.NZ50$Date)
,as.xts(EI.JKSE$`Adjusted Close`, EI.JKSE$Date))
names(all.equity.index) <- c("ASX", "TSX", "SP500", "SSEC", "MXX", "GDAXI",
"NIKKEI", "KS11", "FCHI", "SSMI", "BSESN", "BCB",
"AEX", "GDAXI", "STI", "NZ50", "JKSE")
Quandl.EquityIndex <- na.omit(all.equity.index)
# Interest Rates ----------------------------------------------------------
cat('\nLoading Quandl Government Bond Yield...\n')
Quandl.YC.2Y <- Quandl(paste0("YC/",QuandlSymbol1, "2Y"), collapse = 'daily')
Quandl.YC.2Y = convertToXts(Quandl.YC.2Y)
colnames(Quandl.YC.2Y) = 'Quandl.YC.2Y'
Quandl.YC.3Y <- Quandl(paste0("YC/",QuandlSymbol1, "3Y"), collapse = 'daily')
Quandl.YC.3Y = convertToXts(Quandl.YC.3Y)
colnames(Quandl.YC.3Y) = 'Quandl.YC.3Y'
Quandl.YC.5Y <- Quandl(paste0("YC/",QuandlSymbol1, "5Y"), collapse = 'daily')
Quandl.YC.5Y = convertToXts(Quandl.YC.5Y)
colnames(Quandl.YC.5Y) = 'Quandl.YC.5Y'
Quandl.YC.10Y <- Quandl(paste0("YC/",QuandlSymbol1, "10Y"), collapse = 'daily')
Quandl.YC.10Y = convertToXts(Quandl.YC.10Y)
colnames(Quandl.YC.10Y) = 'Quandl.YC.10Y'
Quandl.YC.Bond = na.omit(merge(Quandl.YC.2Y, Quandl.YC.3Y, Quandl.YC.5Y, Quandl.YC.10Y))
Quandl.YC.2Y <- Quandl(paste0("YC/",QuandlSymbol2, "2Y"), collapse = 'daily')
Quandl.YC.2Y = convertToXts(Quandl.YC.2Y)
colnames(Quandl.YC.2Y) = 'Quandl.YC.2Y'
Quandl.YC.3Y <- Quandl(paste0("YC/",QuandlSymbol2, "3Y"), collapse = 'daily')
Quandl.YC.3Y = convertToXts(Quandl.YC.3Y)
colnames(Quandl.YC.3Y) = 'Quandl.YC.3Y'
Quandl.YC.5Y <- Quandl(paste0("YC/",QuandlSymbol2, "5Y"), collapse = 'daily')
Quandl.YC.5Y = convertToXts(Quandl.YC.5Y)
colnames(Quandl.YC.5Y) = 'Quandl.YC.5Y'
Quandl.YC.10Y <- Quandl(paste0("YC/",QuandlSymbol2, "10Y"), collapse = 'daily')
Quandl.YC.10Y = convertToXts(Quandl.YC.10Y)
colnames(Quandl.YC.10Y) = 'Quandl.YC.10Y'
Quandl.YC.Bond2 = na.omit(merge(Quandl.YC.2Y, Quandl.YC.3Y, Quandl.YC.5Y, Quandl.YC.10Y))
# Commodities -------------------------------------------------------------
cat('\nLoading Comodity...\n')
# Eco Calendars -----------------------------------------------------------
cat('\nLoading Economic Calendars...\n')
# Fundamental Data --------------------------------------------------------3
cat('\nLoading Fundamental Data...\n')
cat('\nEnsembling Final Data Output...\n')
res = list(IB.BIDASK = IB.BIDASK,
IB.MID = IB.MID,
IB.BID = IB.BID,
IB.ASK = IB.ASK,
IB.SPREADS = IB.SPREADS,
IB.SPREADS.Perc = IB.SPREADS.Perc,
IB.VOLATILITY = IB.VOLATILITY,
OA.BIDASK = OA.BIDASK,
OA.SPREADS = OA.SPREADS,
OA.SPREADS.Perc = OA.SPREADS.Perc,
OA.VOLUME = OA.VOLUME,
OA.HistPos = OA.HistPos,
OA.CBOT = OA.CBOT,
Oanda.Autochartist = Oanda.Autochartist,
Quandl.EquityIndex = Quandl.EquityIndex,
Quandl.YC.Bond = Quandl.YC.Bond,
Quandl.YC.Bond2 = Quandl.YC.Bond2
)
twsDisconnect(tws)
return(res)
}
#' Prepare all required datasets for Oanda FX daily Modeling
#'
#' Prepare all required datasets for Oanda FX daily Modeling.
#'
#' @param oanda.count length of data to retreive
#' @param Cur1 currency one
#' @param Cur2 currency two
#' @param oanda.granularity barsize of Oanda data
#' @param QuandlSymbol1 currency one for Quandl
#' @param QuandlSymbol2 currency two for Quandl
#'
#' @return A \code{list} of \code{xts}
#'
#' @examples
#' res = prepareForexOandaData(oanda.count = 2500, Cur1 = "USD", Cur2 = "CAD", oanda.granularity = 'D', QuandlSymbol1 = 'CAN', QuandlSymbol2 = 'USA')
#'
#' @export
prepareForexOandaData <- function(oanda.count = 250, Cur1 = "USD", Cur2 = "CAD", oanda.granularity = 'D', QuandlSymbol1 = 'CAN', QuandlSymbol2 = 'USA'){
library(RQuantAPI)
convertToXts <- function(cm, tzone = ""){
dts <- structure(as.numeric(as.POSIXlt(gsub("(\\d{4})(\\d{2})(\\d{2})",
"\\1-\\2-\\3", cm[, 1], perl = TRUE))),
class = c("POSIXct","POSIXt"), tzone = tzone)
if(ncol(cm) > 2){
x <- xts(as.matrix(apply(cm[, -1], 2, as.numeric)), order.by = dts, tzone = tzone)
}else{
x <- xts(as.numeric(cm[, -1]), order.by = dts, tzone = tzone)
}
return(x)
}
instrument = paste0(Cur1, '_', Cur2)
# Oanda OHLC --------------------------------------------------------------
cat('\nLoading Oanda OHLC...\n')
OA.ALL = getOandaInstrumentCandles(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, INSTRUMENTS = instrument,
price = 'MBA', granularity = oanda.granularity, count = oanda.count)
OA.ALL = convertToXts(OA.ALL[, -1])
colnames(OA.ALL) = c('OA.Volume', 'OA.Ask.Close', 'OA.Ask.High', 'OA.Ask.Low', 'OA.Ask.Open'
, 'OA.Bid.Close', 'OA.Bid.High', 'OA.Bid.Low', 'OA.Bid.Open'
, 'OA.Mid.Close', 'OA.Mid.High', 'OA.Mid.Low', 'OA.Mid.Open')
OA.MID = OA.ALL[, c('OA.Mid.Close', 'OA.Mid.High', 'OA.Mid.Low', 'OA.Mid.Open')]
OA.BID = OA.ALL[, c('OA.Bid.Close', 'OA.Bid.High', 'OA.Bid.Low', 'OA.Bid.Open')]
OA.ASK = OA.ALL[, c('OA.Ask.Close', 'OA.Ask.High', 'OA.Ask.Low', 'OA.Ask.Open')]
# Oanda Spreads -----------------------------------------------------------
# OA.SPREADS = SpreadsOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
# INSTRUMENTS = instrument, PERIOD = '1 year')
cat('\nLoading Oanda Spreads...\n')
OA.SPREADS = OA.ALL[, 2:5] - OA.ALL[, 6:9]
OA.SPREADS.Perc = ((OA.ALL[, 2:5] - OA.ALL[, 6:9])/((OA.ALL[, 2:5] + OA.ALL[, 6:9])/2)) * 100
# Oanda Volume ------------------------------------------------------------
cat('\nLoading Oanda Volume...\n')
OA.VOLUME = OA.ALL[, 1]
# Oanda Net Positions -----------------------------------------------------
cat('\nLoading Oanda New Positions...\n')
OA.HistPos <- HistoricalPositionOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
INSTRUMENTS = instrument, PERIOD = '1 year')
OA.HistPos = convertToXts(as.data.frame(OA.HistPos)[, -1])
colnames(OA.HistPos) = c('OA.LongPosRatio', 'OA.ExRate')
OA.HistPos$OA.PosCorr = rollapply(OA.HistPos, by.column = F, width = 20, function(x) cor(x)[1,2])
# Oanda CBOT --------------------------------------------------------------
cat('\nLoading Oanda / Quandl CBOT...\n')
OA.CBOT = COT.Oanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, INSTRUMENTS = instrument)
OA.CBOT = convertToXts(as.data.frame(OA.CBOT)[, -6])
# Oanda Autochartist ------------------------------------------------------
cat('\nLoading Oanda / Autochartist Signals...\n')
Oanda.Autochartist = Autochartist.Oanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN,
INSTRUMENTS = instrument, PERIOD = '1 week')
# Quandl Indexes ----------------------------------------------------------
cat('\nLoading Quandl Equity Indexes...\n')
QuandlConnect()
# AU
EI.ASX <- Quandl("YAHOO/INDEX_AXJO")
# Canada
EI.TSX <- Quandl("YAHOO/INDEX_GSPTSE")
# USA
EI.USA <- Quandl("YAHOO/INDEX_GSPC")
# China
EI.SSEC <- Quandl("YAHOO/INDEX_SSEC")
# Mexico
EI.MXX <- Quandl("YAHOO/INDEX_MXX")
# Germany
EI.GDAXI <- Quandl("YAHOO/INDEX_GDAXI")
# Japan
EI.NIKKEI <- Quandl("NIKKEI/INDEX")
# South Korea
EI.KS11 <- Quandl("YAHOO/INDEX_KS11")
# France
EI.FCHI <- Quandl("YAHOO/INDEX_FCHI")
# Switzerland
EI.SSMI <- Quandl("YAHOO/INDEX_SSMI")
# India
EI.BSESN <- Quandl("YAHOO/INDEX_BSESN")
# Brazil
EI.BCB <- Quandl("BCB/7")
# Netherlands
EI.AEX <- Quandl("YAHOO/INDEX_AEX")
# Germany
EI.GDAXI <- Quandl("YAHOO/INDEX_GDAXI")
# Singapore
EI.STI <- Quandl("YAHOO/INDEX_STI")
# New Zealand
EI.NZ50 <- Quandl("YAHOO/INDEX_NZ50")
# Indonesia
EI.JKSE <- Quandl("YAHOO/INDEX_JKSE")
# Malaysia
# India
# Peru
# Thailand
# Vietnam
# UK
# Italy
all.equity.index <- merge(as.xts(EI.ASX$`Adjusted Close`, EI.ASX$Date)
,as.xts(EI.TSX$`Adjusted Close`, EI.TSX$Date)
,as.xts(EI.USA$`Adjusted Close`, EI.USA$Date)
,as.xts(EI.SSEC$`Adjusted Close`, EI.SSEC$Date)
,as.xts(EI.MXX$`Adjusted Close`, EI.MXX$Date)
,as.xts(EI.GDAXI$`Adjusted Close`, EI.GDAXI$Date)
,as.xts(EI.NIKKEI$`Close Price`, EI.NIKKEI$Date)
,as.xts(EI.KS11$`Adjusted Close`, EI.KS11$Date)
,as.xts(EI.FCHI$`Adjusted Close`, EI.FCHI$Date)
,as.xts(EI.SSMI$`Adjusted Close`, EI.SSMI$Date)
,as.xts(EI.BSESN$`Adjusted Close`, EI.BSESN$Date)
,as.xts(EI.BCB$Value, EI.BCB$Date)
,as.xts(EI.AEX$`Adjusted Close`, EI.AEX$Date)
,as.xts(EI.GDAXI$`Adjusted Close`, EI.GDAXI$Date)
,as.xts(EI.STI$`Adjusted Close`, EI.STI$Date)
,as.xts(EI.NZ50$`Adjusted Close`, EI.NZ50$Date)
,as.xts(EI.JKSE$`Adjusted Close`, EI.JKSE$Date))
names(all.equity.index) <- c("ASX", "TSX", "SP500", "SSEC", "MXX", "GDAXI",
"NIKKEI", "KS11", "FCHI", "SSMI", "BSESN", "BCB",
"AEX", "GDAXI", "STI", "NZ50", "JKSE")
Quandl.EquityIndex <- na.omit(all.equity.index)
# Interest Rates ----------------------------------------------------------
cat('\nLoading Quandl Government Bond Yield...\n')
Quandl.YC.2Y <- Quandl(paste0("YC/",QuandlSymbol1, "2Y"), collapse = 'daily')
Quandl.YC.2Y = convertToXts(Quandl.YC.2Y)
colnames(Quandl.YC.2Y) = 'Quandl.YC.2Y'
Quandl.YC.3Y <- Quandl(paste0("YC/",QuandlSymbol1, "3Y"), collapse = 'daily')
Quandl.YC.3Y = convertToXts(Quandl.YC.3Y)
colnames(Quandl.YC.3Y) = 'Quandl.YC.3Y'
Quandl.YC.5Y <- Quandl(paste0("YC/",QuandlSymbol1, "5Y"), collapse = 'daily')
Quandl.YC.5Y = convertToXts(Quandl.YC.5Y)
colnames(Quandl.YC.5Y) = 'Quandl.YC.5Y'
Quandl.YC.10Y <- Quandl(paste0("YC/",QuandlSymbol1, "10Y"), collapse = 'daily')
Quandl.YC.10Y = convertToXts(Quandl.YC.10Y)
colnames(Quandl.YC.10Y) = 'Quandl.YC.10Y'
Quandl.YC.Bond = na.omit(merge(Quandl.YC.2Y, Quandl.YC.3Y, Quandl.YC.5Y, Quandl.YC.10Y))
Quandl.YC.2Y <- Quandl(paste0("YC/",QuandlSymbol2, "2Y"), collapse = 'daily')
Quandl.YC.2Y = convertToXts(Quandl.YC.2Y)
colnames(Quandl.YC.2Y) = 'Quandl.YC.2Y'
Quandl.YC.3Y <- Quandl(paste0("YC/",QuandlSymbol2, "3Y"), collapse = 'daily')
Quandl.YC.3Y = convertToXts(Quandl.YC.3Y)
colnames(Quandl.YC.3Y) = 'Quandl.YC.3Y'
Quandl.YC.5Y <- Quandl(paste0("YC/",QuandlSymbol2, "5Y"), collapse = 'daily')
Quandl.YC.5Y = convertToXts(Quandl.YC.5Y)
colnames(Quandl.YC.5Y) = 'Quandl.YC.5Y'
Quandl.YC.10Y <- Quandl(paste0("YC/",QuandlSymbol2, "10Y"), collapse = 'daily')
Quandl.YC.10Y = convertToXts(Quandl.YC.10Y)
colnames(Quandl.YC.10Y) = 'Quandl.YC.10Y'
Quandl.YC.Bond2 = na.omit(merge(Quandl.YC.2Y, Quandl.YC.3Y, Quandl.YC.5Y, Quandl.YC.10Y))
# Commodities -------------------------------------------------------------
cat('\nLoading Comodity...\n')
# Eco Calendars -----------------------------------------------------------
cat('\nLoading Economic Calendars...\n')
# Fundamental Data --------------------------------------------------------3
cat('\nLoading Fundamental Data...\n')
cat('\nEnsembling Final Data Output...\n')
res = list(OA.MID = OA.MID,
OA.BID = OA.BID,
OA.ASK = OA.ASK,
OA.SPREADS = OA.SPREADS,
OA.SPREADS.Perc = OA.SPREADS.Perc,
OA.VOLUME = OA.VOLUME,
OA.HistPos = OA.HistPos,
OA.CBOT = OA.CBOT,
Oanda.Autochartist = Oanda.Autochartist,
Quandl.EquityIndex = Quandl.EquityIndex,
Quandl.YC.Bond = Quandl.YC.Bond,
Quandl.YC.Bond2 = Quandl.YC.Bond2
)
return(res)
}
#' Prepare Interactive Brokers FX data
#'
#' Prepare Interactive Brokers FX data
#'
#' @param ib.duration length of data to retreive from Interactive Broker
#' @param ib.barsize the barsize of IB data
#' @param Cur1 currency one
#' @param Cur2 currency two
#' @param ibAcc account type of Interactive Brokers (live or paper)
#' @param midOnly only retreive mid prices
#'
#' @return A \code{list} of \code{xts}
#'
#' @export
prepareIBForexPrices <- function(ib.duration = "1 Y", ib.barsize = "1 day", Cur1 = "USD", Cur2 = "CAD", ibAcc = 'paper', midOnly = TRUE){
library(IBrokers)
library(RQuantAPI)
if(ibAcc == 'live'){
tws <- twsConnect(port = 7496, clientId = 999)
}else{
tws <- twsConnect(port = 7497, clientId = 998)
}
# IB OHLC -----------------------------------------------------------------
cat('\nLoading Interactive Brokers OHLC...\n')
ccy <- reqContractDetails(tws, twsCurrency(Cur1, Cur2))[[1]]$contract
cols = c('Open', 'High', 'Low', 'Close')
if(midOnly){
# Mid
IB.MID <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='MIDPOINT')
IB.MID = IB.MID[, 1:4]
IB.MID = IB.MID[!duplicated(index(IB.MID)), ]
colnames(IB.MID) = paste0('IB.M.', cols)
res = list(IB.MID = IB.MID)
}else{
# Bid Ask
IB.BIDASK <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='BID_ASK')
IB.BIDASK = IB.BIDASK[, 1:4]
IB.BIDASK = IB.BIDASK[!duplicated(index(IB.BIDASK)), ]
colnames(IB.BIDASK) = paste0('IB.BA.', cols)
# Mid
IB.MID <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='MIDPOINT')
IB.MID = IB.MID[, 1:4]
IB.MID = IB.MID[!duplicated(index(IB.MID)), ]
colnames(IB.MID) = paste0('IB.M.', cols)
# Bid
IB.BID <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='BID')
IB.BID = IB.BID[, 1:4]
IB.BID = IB.BID[!duplicated(index(IB.BID)), ]
colnames(IB.BID) = paste0('IB.B.', cols)
# Ask
IB.ASK <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='ASK')
IB.ASK = IB.ASK[, 1:4]
IB.ASK = IB.ASK[!duplicated(index(IB.ASK)), ]
colnames(IB.ASK) = paste0('IB.A.', cols)
# IB Spreads --------------------------------------------------------------
cat('\nLoading Interactive Brokers Spreads...\n')
IB.SPREADS = IB.ASK - IB.BID
colnames(IB.SPREADS) = paste0('IB.SP.', cols)
IB.SPREADS.Perc = (IB.SPREADS / IB.MID) * 100
colnames(IB.SPREADS.Perc) = paste0('IB.SPP.', cols)
# IB Volatility -----------------------------------------------------------
# cat('\nLoading Interactive Brokers Volatility...\n')
# IB.VOLATILITY <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
# duration = ib.duration, useRTH = "1", whatToShow='HISTORICAL_VOLATILITY')
# IB.VOLATILITY = IB.VOLATILITY[,6]
# IB.VOLATILITY = IB.VOLATILITY[!duplicated(index(IB.VOLATILITY)), ]
# colnames(IB.VOLATILITY) = paste0('IB.Volatility.',Cur1, '.', Cur2)
cat('\nEnsembling Final Data Output...\n')
res = list(IB.BIDASK = IB.BIDASK,
IB.MID = IB.MID,
IB.BID = IB.BID,
IB.ASK = IB.ASK,
IB.SPREADS = IB.SPREADS,
IB.SPREADS.Perc = IB.SPREADS.Perc
# IB.VOLATILITY = IB.VOLATILITY
)
}
twsDisconnect(tws)
return(res)
}
#' Prepare all required datasets for Oanda FX daily Modeling
#'
#' Prepare all required datasets for Oanda FX daily Modeling.
#'
#' @param ACCOUNT_TYPE Account type (e.g. "real" or "paper")
#' @param ACCESS_TOKEN Account API Token
#' @param oanda.count length of data to retreive
#' @param Cur1 currency one
#' @param Cur2 currency two
#' @param oanda.granularity barsize of Oanda data
#'
#' @return A \code{list} of \code{xts}
#'
#' @examples
#' res = prepareForexOandaPrices(oanda.count = 2500, Cur1 = "USD", Cur2 = "CAD", oanda.granularity = 'D')
#'
#' @export
prepareForexOandaPrices <- function(ACCOUNT_TYPE = .oandaEnv$ACCOUNT_TYPE, ACCESS_TOKEN = .oandaEnv$ACCESS_TOKEN, oanda.count = 250, Cur1 = "USD", Cur2 = "CAD", oanda.granularity = 'D'){
library(RQuantAPI)
convertToXts <- function(cm, tzone = ""){
dts <- structure(as.numeric(as.POSIXlt(gsub("(\\d{4})(\\d{2})(\\d{2})",
"\\1-\\2-\\3", cm[, 1], perl = TRUE))),
class = c("POSIXct","POSIXt"), tzone = tzone)
dts[wday(dts) == 1] = dts[wday(dts) == 1] - 3600 * 48 # <=============================== Check if it's Oanda's Bug
if(ncol(cm) > 2){
x <- xts(as.matrix(apply(cm[, -1], 2, as.numeric)), order.by = dts, tzone = tzone)
}else{
x <- xts(as.numeric(cm[, -1]), order.by = dts, tzone = tzone)
}
return(x)
}
instrument = paste0(Cur1, '_', Cur2)
# Oanda OHLC --------------------------------------------------------------
# cat('\nLoading Oanda OHLC...\n')
OA.ALL = getOandaInstrumentCandles(ACCOUNT_TYPE, ACCESS_TOKEN, INSTRUMENTS = instrument,
price = 'MBA', granularity = oanda.granularity, count = oanda.count)
OA.ALL = convertToXts(OA.ALL[, -1])
colnames(OA.ALL) = c('OA.Volume', 'OA.Bid.Open', 'OA.Bid.High', 'OA.Bid.Low', 'OA.Bid.Close'
, 'OA.Ask.Open', 'OA.Ask.High', 'OA.Ask.Low', 'OA.Ask.Close'
, 'OA.Mid.Open', 'OA.Mid.High', 'OA.Mid.Low', 'OA.Mid.Close')
OA.MID = OA.ALL[, c('OA.Mid.Close', 'OA.Mid.High', 'OA.Mid.Low', 'OA.Mid.Open', 'OA.Volume')]
OA.BID = OA.ALL[, c('OA.Bid.Close', 'OA.Bid.High', 'OA.Bid.Low', 'OA.Bid.Open', 'OA.Volume')]
OA.ASK = OA.ALL[, c('OA.Ask.Close', 'OA.Ask.High', 'OA.Ask.Low', 'OA.Ask.Open', 'OA.Volume')]
# Oanda Spreads -----------------------------------------------------------
# OA.SPREADS = SpreadsOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
# INSTRUMENTS = instrument, PERIOD = '1 year')
# cat('\nLoading Oanda Spreads...\n')
# OA.SPREADS = OA.ALL[, 2:5] - OA.ALL[, 6:9]
# OA.SPREADS.Perc = ((OA.ALL[, 2:5] - OA.ALL[, 6:9])/((OA.ALL[, 2:5] + OA.ALL[, 6:9])/2)) * 100
# Oanda Volume ------------------------------------------------------------
# cat('\nLoading Oanda Volume...\n')
# OA.VOLUME = OA.ALL[, 1]
# Oanda Net Positions -----------------------------------------------------
# cat('\nLoading Oanda New Positions...\n')
# OA.HistPos <- HistoricalPositionOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
# INSTRUMENTS = instrument, PERIOD = '1 year')
# OA.HistPos = convertToXts(as.data.frame(OA.HistPos)[, -1])
# colnames(OA.HistPos) = c('OA.LongPosRatio', 'OA.ExRate')
# OA.HistPos$OA.PosCorr = rollapply(OA.HistPos, by.column = F, width = 20, function(x) cor(x)[1,2])
# cat('\nEnsembling Final Data Output...\n')
res = list(OA.MID = OA.MID,
OA.BID = OA.BID,
OA.ASK = OA.ASK,
OA.ALL = OA.ALL
# OA.SPREADS = OA.SPREADS,
# OA.SPREADS.Perc = OA.SPREADS.Perc,
# OA.VOLUME = OA.VOLUME,
# OA.HistPos = OA.HistPos
)
return(res)
}
ivanliu1989/RQuantTrader documentation built on Sept. 13, 2019, 11:54 a.m.
R Package Documentation
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Defines functions prepareForexData prepareForexOandaData prepareIBForexPrices prepareForexOandaPrices
Documented in prepareForexData prepareForexOandaData prepareForexOandaPrices prepareIBForexPrices
#' Prepare all required datasets for FX daily Modeling
#'
#' Prepare all required datasets for FX daily Modeling.
#'
#' @param ib.duration length of data to retreive from Interactive Broker
#' @param ib.barsize the barsize of IB data
#' @param Cur1 currency one
#' @param Cur2 currency two
#' @param oanda.granularity barsize of Oanda data
#' @param QuandlSymbol1 currency one for Quandl
#' @param QuandlSymbol2 currency two for Quandl
#' @param ibAcc account type of Interactive Brokers (live or paper)
#'
#' @return A \code{list} of \code{xts}
#'
#' @examples
#' res = prepareForexData(ib.duration = "1 Y", ib.barsize = "1 day", Cur1 = "USD", Cur2 = "CAD",
#' oanda.granularity = 'D', QuandlSymbol1 = 'CAN', QuandlSymbol2 = 'USA')
#'
#' @export
prepareForexData <- function(ib.duration = "1 Y", ib.barsize = "1 day", Cur1 = "USD", Cur2 = "CAD",
oanda.granularity = 'D', QuandlSymbol1 = 'CAN', QuandlSymbol2 = 'USA', ibAcc = 'paper'){
library(IBrokers)
library(RQuantAPI)
convertToXts <- function(cm, tzone = ""){
dts <- structure(as.numeric(as.POSIXlt(gsub("(\\d{4})(\\d{2})(\\d{2})",
"\\1-\\2-\\3", cm[, 1], perl = TRUE))),
class = c("POSIXct","POSIXt"), tzone = tzone)
if(ncol(cm) > 2){
x <- xts(as.matrix(apply(cm[, -1], 2, as.numeric)), order.by = dts, tzone = tzone)
}else{
x <- xts(as.numeric(cm[, -1]), order.by = dts, tzone = tzone)
}
return(x)
}
instrument = paste0(Cur1, '_', Cur2)
if(ibAcc == 'live'){
tws <- twsConnect(port = 7496, clientId = 999)
}else{
tws <- twsConnect(port = 7497, clientId = 998)
}
# IB OHLC -----------------------------------------------------------------
cat('\nLoading Interactive Brokers OHLC...\n')
ccy <- reqContractDetails(tws, twsCurrency(Cur1, Cur2))[[1]]$contract
cols = c('Open', 'High', 'Low', 'Close')
# Bid Ask
IB.BIDASK <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='BID_ASK')
IB.BIDASK = IB.BIDASK[, 1:4]
IB.BIDASK = IB.BIDASK[!duplicated(index(IB.BIDASK)), ]
colnames(IB.BIDASK) = paste0('IB.BA.', cols)
# Mid
IB.MID <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='MIDPOINT')
IB.MID = IB.MID[, 1:4]
IB.MID = IB.MID[!duplicated(index(IB.MID)), ]
colnames(IB.MID) = paste0('IB.M.', cols)
# Bid
IB.BID <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='BID')
IB.BID = IB.BID[, 1:4]
IB.BID = IB.BID[!duplicated(index(IB.BID)), ]
colnames(IB.BID) = paste0('IB.B.', cols)
# Ask
IB.ASK <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='ASK')
IB.ASK = IB.ASK[, 1:4]
IB.ASK = IB.ASK[!duplicated(index(IB.ASK)), ]
colnames(IB.ASK) = paste0('IB.A.', cols)
# IB Spreads --------------------------------------------------------------
cat('\nLoading Interactive Brokers Spreads...\n')
IB.SPREADS = IB.ASK - IB.BID
colnames(IB.SPREADS) = paste0('IB.SP.', cols)
IB.SPREADS.Perc = (IB.SPREADS / IB.MID) * 100
colnames(IB.SPREADS.Perc) = paste0('IB.SPP.', cols)
# IB Volatility -----------------------------------------------------------
cat('\nLoading Interactive Brokers Volatility...\n')
IB.VOLATILITY <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='HISTORICAL_VOLATILITY')
IB.VOLATILITY = IB.VOLATILITY[,6]
IB.VOLATILITY = IB.VOLATILITY[!duplicated(index(IB.VOLATILITY)), ]
colnames(IB.VOLATILITY) = paste0('IB.Volatility.',Cur1, '.', Cur2)
# Oanda OHLC --------------------------------------------------------------
cat('\nLoading Oanda OHLC...\n')
oanda.count = nrow(IB.BIDASK) + 1
OA.ALL = getOandaInstrumentCandles(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, INSTRUMENTS = instrument,
price = 'BA', granularity = oanda.granularity, count = oanda.count)
OA.ALL = convertToXts(OA.ALL[, -1])
colnames(OA.ALL) = c('OA.Volume', 'OA.Ask.Close', 'OA.Ask.High', 'OA.Ask.Low', 'OA.Ask.Open'
, 'OA.Bid.Close', 'OA.Bid.High', 'OA.Bid.Low', 'OA.Bid.Open')
OA.BIDASK = OA.ALL[, -1]
# Oanda Spreads -----------------------------------------------------------
# OA.SPREADS = SpreadsOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
# INSTRUMENTS = instrument, PERIOD = '1 year')
cat('\nLoading Oanda Spreads...\n')
OA.SPREADS = OA.ALL[, 2:5] - OA.ALL[, 6:9]
OA.SPREADS.Perc = ((OA.ALL[, 2:5] - OA.ALL[, 6:9])/((OA.ALL[, 2:5] + OA.ALL[, 6:9])/2)) * 100
# Oanda Volume ------------------------------------------------------------
cat('\nLoading Oanda Volume...\n')
OA.VOLUME = OA.ALL[, 1]
# Oanda Net Positions -----------------------------------------------------
cat('\nLoading Oanda New Positions...\n')
OA.HistPos <- HistoricalPositionOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
INSTRUMENTS = instrument, PERIOD = '1 year')
OA.HistPos = convertToXts(as.data.frame(OA.HistPos)[, -1])
colnames(OA.HistPos) = c('OA.LongPosRatio', 'OA.ExRate')
OA.HistPos$OA.PosCorr = rollapply(OA.HistPos, by.column = F, width = 20, function(x) cor(x)[1,2])
# Oanda CBOT --------------------------------------------------------------
cat('\nLoading Oanda / Quandl CBOT...\n')
OA.CBOT = COT.Oanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, INSTRUMENTS = instrument)
OA.CBOT = convertToXts(as.data.frame(OA.CBOT)[, -6])
# calNet <- function(x,y){
# net <- (x-y)/(x+y)
# return(net)
# }
# CFTC.AUD <- Quandl("CFTC/TIFF_CME_AD_ALL")
# CFTC.AUD <- as.xts(calNet(CFTC.AUD$`Lev Money Long Positions`,CFTC.AUD$`Lev Money Short Positions`),CFTC.AUD$Date)
# Oanda Autochartist ------------------------------------------------------
cat('\nLoading Oanda / Autochartist Signals...\n')
Oanda.Autochartist = Autochartist.Oanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN,
INSTRUMENTS = instrument, PERIOD = '1 week')
# Quandl Indexes ----------------------------------------------------------
cat('\nLoading Quandl Equity Indexes...\n')
QuandlConnect()
# AU
EI.ASX <- Quandl("YAHOO/INDEX_AXJO")
# Canada
EI.TSX <- Quandl("YAHOO/INDEX_GSPTSE")
# USA
EI.USA <- Quandl("YAHOO/INDEX_GSPC")
# China
EI.SSEC <- Quandl("YAHOO/INDEX_SSEC")
# Mexico
EI.MXX <- Quandl("YAHOO/INDEX_MXX")
# Germany
EI.GDAXI <- Quandl("YAHOO/INDEX_GDAXI")
# Japan
EI.NIKKEI <- Quandl("NIKKEI/INDEX")
# South Korea
EI.KS11 <- Quandl("YAHOO/INDEX_KS11")
# France
EI.FCHI <- Quandl("YAHOO/INDEX_FCHI")
# Switzerland
EI.SSMI <- Quandl("YAHOO/INDEX_SSMI")
# India
EI.BSESN <- Quandl("YAHOO/INDEX_BSESN")
# Brazil
EI.BCB <- Quandl("BCB/7")
# Netherlands
EI.AEX <- Quandl("YAHOO/INDEX_AEX")
# Germany
EI.GDAXI <- Quandl("YAHOO/INDEX_GDAXI")
# Singapore
EI.STI <- Quandl("YAHOO/INDEX_STI")
# New Zealand
EI.NZ50 <- Quandl("YAHOO/INDEX_NZ50")
# Indonesia
EI.JKSE <- Quandl("YAHOO/INDEX_JKSE")
# Malaysia
# India
# Peru
# Thailand
# Vietnam
# UK
# Italy
all.equity.index <- merge(as.xts(EI.ASX$`Adjusted Close`, EI.ASX$Date)
,as.xts(EI.TSX$`Adjusted Close`, EI.TSX$Date)
,as.xts(EI.USA$`Adjusted Close`, EI.USA$Date)
,as.xts(EI.SSEC$`Adjusted Close`, EI.SSEC$Date)
,as.xts(EI.MXX$`Adjusted Close`, EI.MXX$Date)
,as.xts(EI.GDAXI$`Adjusted Close`, EI.GDAXI$Date)
,as.xts(EI.NIKKEI$`Close Price`, EI.NIKKEI$Date)
,as.xts(EI.KS11$`Adjusted Close`, EI.KS11$Date)
,as.xts(EI.FCHI$`Adjusted Close`, EI.FCHI$Date)
,as.xts(EI.SSMI$`Adjusted Close`, EI.SSMI$Date)
,as.xts(EI.BSESN$`Adjusted Close`, EI.BSESN$Date)
,as.xts(EI.BCB$Value, EI.BCB$Date)
,as.xts(EI.AEX$`Adjusted Close`, EI.AEX$Date)
,as.xts(EI.GDAXI$`Adjusted Close`, EI.GDAXI$Date)
,as.xts(EI.STI$`Adjusted Close`, EI.STI$Date)
,as.xts(EI.NZ50$`Adjusted Close`, EI.NZ50$Date)
,as.xts(EI.JKSE$`Adjusted Close`, EI.JKSE$Date))
names(all.equity.index) <- c("ASX", "TSX", "SP500", "SSEC", "MXX", "GDAXI",
"NIKKEI", "KS11", "FCHI", "SSMI", "BSESN", "BCB",
"AEX", "GDAXI", "STI", "NZ50", "JKSE")
Quandl.EquityIndex <- na.omit(all.equity.index)
# Interest Rates ----------------------------------------------------------
cat('\nLoading Quandl Government Bond Yield...\n')
Quandl.YC.2Y <- Quandl(paste0("YC/",QuandlSymbol1, "2Y"), collapse = 'daily')
Quandl.YC.2Y = convertToXts(Quandl.YC.2Y)
colnames(Quandl.YC.2Y) = 'Quandl.YC.2Y'
Quandl.YC.3Y <- Quandl(paste0("YC/",QuandlSymbol1, "3Y"), collapse = 'daily')
Quandl.YC.3Y = convertToXts(Quandl.YC.3Y)
colnames(Quandl.YC.3Y) = 'Quandl.YC.3Y'
Quandl.YC.5Y <- Quandl(paste0("YC/",QuandlSymbol1, "5Y"), collapse = 'daily')
Quandl.YC.5Y = convertToXts(Quandl.YC.5Y)
colnames(Quandl.YC.5Y) = 'Quandl.YC.5Y'
Quandl.YC.10Y <- Quandl(paste0("YC/",QuandlSymbol1, "10Y"), collapse = 'daily')
Quandl.YC.10Y = convertToXts(Quandl.YC.10Y)
colnames(Quandl.YC.10Y) = 'Quandl.YC.10Y'
Quandl.YC.Bond = na.omit(merge(Quandl.YC.2Y, Quandl.YC.3Y, Quandl.YC.5Y, Quandl.YC.10Y))
Quandl.YC.2Y <- Quandl(paste0("YC/",QuandlSymbol2, "2Y"), collapse = 'daily')
Quandl.YC.2Y = convertToXts(Quandl.YC.2Y)
colnames(Quandl.YC.2Y) = 'Quandl.YC.2Y'
Quandl.YC.3Y <- Quandl(paste0("YC/",QuandlSymbol2, "3Y"), collapse = 'daily')
Quandl.YC.3Y = convertToXts(Quandl.YC.3Y)
colnames(Quandl.YC.3Y) = 'Quandl.YC.3Y'
Quandl.YC.5Y <- Quandl(paste0("YC/",QuandlSymbol2, "5Y"), collapse = 'daily')
Quandl.YC.5Y = convertToXts(Quandl.YC.5Y)
colnames(Quandl.YC.5Y) = 'Quandl.YC.5Y'
Quandl.YC.10Y <- Quandl(paste0("YC/",QuandlSymbol2, "10Y"), collapse = 'daily')
Quandl.YC.10Y = convertToXts(Quandl.YC.10Y)
colnames(Quandl.YC.10Y) = 'Quandl.YC.10Y'
Quandl.YC.Bond2 = na.omit(merge(Quandl.YC.2Y, Quandl.YC.3Y, Quandl.YC.5Y, Quandl.YC.10Y))
# Commodities -------------------------------------------------------------
cat('\nLoading Comodity...\n')
# Eco Calendars -----------------------------------------------------------
cat('\nLoading Economic Calendars...\n')
# Fundamental Data --------------------------------------------------------3
cat('\nLoading Fundamental Data...\n')
cat('\nEnsembling Final Data Output...\n')
res = list(IB.BIDASK = IB.BIDASK,
IB.MID = IB.MID,
IB.BID = IB.BID,
IB.ASK = IB.ASK,
IB.SPREADS = IB.SPREADS,
IB.SPREADS.Perc = IB.SPREADS.Perc,
IB.VOLATILITY = IB.VOLATILITY,
OA.BIDASK = OA.BIDASK,
OA.SPREADS = OA.SPREADS,
OA.SPREADS.Perc = OA.SPREADS.Perc,
OA.VOLUME = OA.VOLUME,
OA.HistPos = OA.HistPos,
OA.CBOT = OA.CBOT,
Oanda.Autochartist = Oanda.Autochartist,
Quandl.EquityIndex = Quandl.EquityIndex,
Quandl.YC.Bond = Quandl.YC.Bond,
Quandl.YC.Bond2 = Quandl.YC.Bond2
)
twsDisconnect(tws)
return(res)
}
#' Prepare all required datasets for Oanda FX daily Modeling
#'
#' Prepare all required datasets for Oanda FX daily Modeling.
#'
#' @param oanda.count length of data to retreive
#' @param Cur1 currency one
#' @param Cur2 currency two
#' @param oanda.granularity barsize of Oanda data
#' @param QuandlSymbol1 currency one for Quandl
#' @param QuandlSymbol2 currency two for Quandl
#'
#' @return A \code{list} of \code{xts}
#'
#' @examples
#' res = prepareForexOandaData(oanda.count = 2500, Cur1 = "USD", Cur2 = "CAD", oanda.granularity = 'D', QuandlSymbol1 = 'CAN', QuandlSymbol2 = 'USA')
#'
#' @export
prepareForexOandaData <- function(oanda.count = 250, Cur1 = "USD", Cur2 = "CAD", oanda.granularity = 'D', QuandlSymbol1 = 'CAN', QuandlSymbol2 = 'USA'){
library(RQuantAPI)
convertToXts <- function(cm, tzone = ""){
dts <- structure(as.numeric(as.POSIXlt(gsub("(\\d{4})(\\d{2})(\\d{2})",
"\\1-\\2-\\3", cm[, 1], perl = TRUE))),
class = c("POSIXct","POSIXt"), tzone = tzone)
if(ncol(cm) > 2){
x <- xts(as.matrix(apply(cm[, -1], 2, as.numeric)), order.by = dts, tzone = tzone)
}else{
x <- xts(as.numeric(cm[, -1]), order.by = dts, tzone = tzone)
}
return(x)
}
instrument = paste0(Cur1, '_', Cur2)
# Oanda OHLC --------------------------------------------------------------
cat('\nLoading Oanda OHLC...\n')
OA.ALL = getOandaInstrumentCandles(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, INSTRUMENTS = instrument,
price = 'MBA', granularity = oanda.granularity, count = oanda.count)
OA.ALL = convertToXts(OA.ALL[, -1])
colnames(OA.ALL) = c('OA.Volume', 'OA.Ask.Close', 'OA.Ask.High', 'OA.Ask.Low', 'OA.Ask.Open'
, 'OA.Bid.Close', 'OA.Bid.High', 'OA.Bid.Low', 'OA.Bid.Open'
, 'OA.Mid.Close', 'OA.Mid.High', 'OA.Mid.Low', 'OA.Mid.Open')
OA.MID = OA.ALL[, c('OA.Mid.Close', 'OA.Mid.High', 'OA.Mid.Low', 'OA.Mid.Open')]
OA.BID = OA.ALL[, c('OA.Bid.Close', 'OA.Bid.High', 'OA.Bid.Low', 'OA.Bid.Open')]
OA.ASK = OA.ALL[, c('OA.Ask.Close', 'OA.Ask.High', 'OA.Ask.Low', 'OA.Ask.Open')]
# Oanda Spreads -----------------------------------------------------------
# OA.SPREADS = SpreadsOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
# INSTRUMENTS = instrument, PERIOD = '1 year')
cat('\nLoading Oanda Spreads...\n')
OA.SPREADS = OA.ALL[, 2:5] - OA.ALL[, 6:9]
OA.SPREADS.Perc = ((OA.ALL[, 2:5] - OA.ALL[, 6:9])/((OA.ALL[, 2:5] + OA.ALL[, 6:9])/2)) * 100
# Oanda Volume ------------------------------------------------------------
cat('\nLoading Oanda Volume...\n')
OA.VOLUME = OA.ALL[, 1]
# Oanda Net Positions -----------------------------------------------------
cat('\nLoading Oanda New Positions...\n')
OA.HistPos <- HistoricalPositionOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
INSTRUMENTS = instrument, PERIOD = '1 year')
OA.HistPos = convertToXts(as.data.frame(OA.HistPos)[, -1])
colnames(OA.HistPos) = c('OA.LongPosRatio', 'OA.ExRate')
OA.HistPos$OA.PosCorr = rollapply(OA.HistPos, by.column = F, width = 20, function(x) cor(x)[1,2])
# Oanda CBOT --------------------------------------------------------------
cat('\nLoading Oanda / Quandl CBOT...\n')
OA.CBOT = COT.Oanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, INSTRUMENTS = instrument)
OA.CBOT = convertToXts(as.data.frame(OA.CBOT)[, -6])
# Oanda Autochartist ------------------------------------------------------
cat('\nLoading Oanda / Autochartist Signals...\n')
Oanda.Autochartist = Autochartist.Oanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN,
INSTRUMENTS = instrument, PERIOD = '1 week')
# Quandl Indexes ----------------------------------------------------------
cat('\nLoading Quandl Equity Indexes...\n')
QuandlConnect()
# AU
EI.ASX <- Quandl("YAHOO/INDEX_AXJO")
# Canada
EI.TSX <- Quandl("YAHOO/INDEX_GSPTSE")
# USA
EI.USA <- Quandl("YAHOO/INDEX_GSPC")
# China
EI.SSEC <- Quandl("YAHOO/INDEX_SSEC")
# Mexico
EI.MXX <- Quandl("YAHOO/INDEX_MXX")
# Germany
EI.GDAXI <- Quandl("YAHOO/INDEX_GDAXI")
# Japan
EI.NIKKEI <- Quandl("NIKKEI/INDEX")
# South Korea
EI.KS11 <- Quandl("YAHOO/INDEX_KS11")
# France
EI.FCHI <- Quandl("YAHOO/INDEX_FCHI")
# Switzerland
EI.SSMI <- Quandl("YAHOO/INDEX_SSMI")
# India
EI.BSESN <- Quandl("YAHOO/INDEX_BSESN")
# Brazil
EI.BCB <- Quandl("BCB/7")
# Netherlands
EI.AEX <- Quandl("YAHOO/INDEX_AEX")
# Germany
EI.GDAXI <- Quandl("YAHOO/INDEX_GDAXI")
# Singapore
EI.STI <- Quandl("YAHOO/INDEX_STI")
# New Zealand
EI.NZ50 <- Quandl("YAHOO/INDEX_NZ50")
# Indonesia
EI.JKSE <- Quandl("YAHOO/INDEX_JKSE")
# Malaysia
# India
# Peru
# Thailand
# Vietnam
# UK
# Italy
all.equity.index <- merge(as.xts(EI.ASX$`Adjusted Close`, EI.ASX$Date)
,as.xts(EI.TSX$`Adjusted Close`, EI.TSX$Date)
,as.xts(EI.USA$`Adjusted Close`, EI.USA$Date)
,as.xts(EI.SSEC$`Adjusted Close`, EI.SSEC$Date)
,as.xts(EI.MXX$`Adjusted Close`, EI.MXX$Date)
,as.xts(EI.GDAXI$`Adjusted Close`, EI.GDAXI$Date)
,as.xts(EI.NIKKEI$`Close Price`, EI.NIKKEI$Date)
,as.xts(EI.KS11$`Adjusted Close`, EI.KS11$Date)
,as.xts(EI.FCHI$`Adjusted Close`, EI.FCHI$Date)
,as.xts(EI.SSMI$`Adjusted Close`, EI.SSMI$Date)
,as.xts(EI.BSESN$`Adjusted Close`, EI.BSESN$Date)
,as.xts(EI.BCB$Value, EI.BCB$Date)
,as.xts(EI.AEX$`Adjusted Close`, EI.AEX$Date)
,as.xts(EI.GDAXI$`Adjusted Close`, EI.GDAXI$Date)
,as.xts(EI.STI$`Adjusted Close`, EI.STI$Date)
,as.xts(EI.NZ50$`Adjusted Close`, EI.NZ50$Date)
,as.xts(EI.JKSE$`Adjusted Close`, EI.JKSE$Date))
names(all.equity.index) <- c("ASX", "TSX", "SP500", "SSEC", "MXX", "GDAXI",
"NIKKEI", "KS11", "FCHI", "SSMI", "BSESN", "BCB",
"AEX", "GDAXI", "STI", "NZ50", "JKSE")
Quandl.EquityIndex <- na.omit(all.equity.index)
# Interest Rates ----------------------------------------------------------
cat('\nLoading Quandl Government Bond Yield...\n')
Quandl.YC.2Y <- Quandl(paste0("YC/",QuandlSymbol1, "2Y"), collapse = 'daily')
Quandl.YC.2Y = convertToXts(Quandl.YC.2Y)
colnames(Quandl.YC.2Y) = 'Quandl.YC.2Y'
Quandl.YC.3Y <- Quandl(paste0("YC/",QuandlSymbol1, "3Y"), collapse = 'daily')
Quandl.YC.3Y = convertToXts(Quandl.YC.3Y)
colnames(Quandl.YC.3Y) = 'Quandl.YC.3Y'
Quandl.YC.5Y <- Quandl(paste0("YC/",QuandlSymbol1, "5Y"), collapse = 'daily')
Quandl.YC.5Y = convertToXts(Quandl.YC.5Y)
colnames(Quandl.YC.5Y) = 'Quandl.YC.5Y'
Quandl.YC.10Y <- Quandl(paste0("YC/",QuandlSymbol1, "10Y"), collapse = 'daily')
Quandl.YC.10Y = convertToXts(Quandl.YC.10Y)
colnames(Quandl.YC.10Y) = 'Quandl.YC.10Y'
Quandl.YC.Bond = na.omit(merge(Quandl.YC.2Y, Quandl.YC.3Y, Quandl.YC.5Y, Quandl.YC.10Y))
Quandl.YC.2Y <- Quandl(paste0("YC/",QuandlSymbol2, "2Y"), collapse = 'daily')
Quandl.YC.2Y = convertToXts(Quandl.YC.2Y)
colnames(Quandl.YC.2Y) = 'Quandl.YC.2Y'
Quandl.YC.3Y <- Quandl(paste0("YC/",QuandlSymbol2, "3Y"), collapse = 'daily')
Quandl.YC.3Y = convertToXts(Quandl.YC.3Y)
colnames(Quandl.YC.3Y) = 'Quandl.YC.3Y'
Quandl.YC.5Y <- Quandl(paste0("YC/",QuandlSymbol2, "5Y"), collapse = 'daily')
Quandl.YC.5Y = convertToXts(Quandl.YC.5Y)
colnames(Quandl.YC.5Y) = 'Quandl.YC.5Y'
Quandl.YC.10Y <- Quandl(paste0("YC/",QuandlSymbol2, "10Y"), collapse = 'daily')
Quandl.YC.10Y = convertToXts(Quandl.YC.10Y)
colnames(Quandl.YC.10Y) = 'Quandl.YC.10Y'
Quandl.YC.Bond2 = na.omit(merge(Quandl.YC.2Y, Quandl.YC.3Y, Quandl.YC.5Y, Quandl.YC.10Y))
# Commodities -------------------------------------------------------------
cat('\nLoading Comodity...\n')
# Eco Calendars -----------------------------------------------------------
cat('\nLoading Economic Calendars...\n')
# Fundamental Data --------------------------------------------------------3
cat('\nLoading Fundamental Data...\n')
cat('\nEnsembling Final Data Output...\n')
res = list(OA.MID = OA.MID,
OA.BID = OA.BID,
OA.ASK = OA.ASK,
OA.SPREADS = OA.SPREADS,
OA.SPREADS.Perc = OA.SPREADS.Perc,
OA.VOLUME = OA.VOLUME,
OA.HistPos = OA.HistPos,
OA.CBOT = OA.CBOT,
Oanda.Autochartist = Oanda.Autochartist,
Quandl.EquityIndex = Quandl.EquityIndex,
Quandl.YC.Bond = Quandl.YC.Bond,
Quandl.YC.Bond2 = Quandl.YC.Bond2
)
return(res)
}
#' Prepare Interactive Brokers FX data
#'
#' Prepare Interactive Brokers FX data
#'
#' @param ib.duration length of data to retreive from Interactive Broker
#' @param ib.barsize the barsize of IB data
#' @param Cur1 currency one
#' @param Cur2 currency two
#' @param ibAcc account type of Interactive Brokers (live or paper)
#' @param midOnly only retreive mid prices
#'
#' @return A \code{list} of \code{xts}
#'
#' @export
prepareIBForexPrices <- function(ib.duration = "1 Y", ib.barsize = "1 day", Cur1 = "USD", Cur2 = "CAD", ibAcc = 'paper', midOnly = TRUE){
library(IBrokers)
library(RQuantAPI)
if(ibAcc == 'live'){
tws <- twsConnect(port = 7496, clientId = 999)
}else{
tws <- twsConnect(port = 7497, clientId = 998)
}
# IB OHLC -----------------------------------------------------------------
cat('\nLoading Interactive Brokers OHLC...\n')
ccy <- reqContractDetails(tws, twsCurrency(Cur1, Cur2))[[1]]$contract
cols = c('Open', 'High', 'Low', 'Close')
if(midOnly){
# Mid
IB.MID <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='MIDPOINT')
IB.MID = IB.MID[, 1:4]
IB.MID = IB.MID[!duplicated(index(IB.MID)), ]
colnames(IB.MID) = paste0('IB.M.', cols)
res = list(IB.MID = IB.MID)
}else{
# Bid Ask
IB.BIDASK <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='BID_ASK')
IB.BIDASK = IB.BIDASK[, 1:4]
IB.BIDASK = IB.BIDASK[!duplicated(index(IB.BIDASK)), ]
colnames(IB.BIDASK) = paste0('IB.BA.', cols)
# Mid
IB.MID <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='MIDPOINT')
IB.MID = IB.MID[, 1:4]
IB.MID = IB.MID[!duplicated(index(IB.MID)), ]
colnames(IB.MID) = paste0('IB.M.', cols)
# Bid
IB.BID <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='BID')
IB.BID = IB.BID[, 1:4]
IB.BID = IB.BID[!duplicated(index(IB.BID)), ]
colnames(IB.BID) = paste0('IB.B.', cols)
# Ask
IB.ASK <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
duration = ib.duration, useRTH = "1", whatToShow='ASK')
IB.ASK = IB.ASK[, 1:4]
IB.ASK = IB.ASK[!duplicated(index(IB.ASK)), ]
colnames(IB.ASK) = paste0('IB.A.', cols)
# IB Spreads --------------------------------------------------------------
cat('\nLoading Interactive Brokers Spreads...\n')
IB.SPREADS = IB.ASK - IB.BID
colnames(IB.SPREADS) = paste0('IB.SP.', cols)
IB.SPREADS.Perc = (IB.SPREADS / IB.MID) * 100
colnames(IB.SPREADS.Perc) = paste0('IB.SPP.', cols)
# IB Volatility -----------------------------------------------------------
# cat('\nLoading Interactive Brokers Volatility...\n')
# IB.VOLATILITY <- reqHistoricalData(conn = tws, Contract = ccy, barSize = ib.barsize,
# duration = ib.duration, useRTH = "1", whatToShow='HISTORICAL_VOLATILITY')
# IB.VOLATILITY = IB.VOLATILITY[,6]
# IB.VOLATILITY = IB.VOLATILITY[!duplicated(index(IB.VOLATILITY)), ]
# colnames(IB.VOLATILITY) = paste0('IB.Volatility.',Cur1, '.', Cur2)
cat('\nEnsembling Final Data Output...\n')
res = list(IB.BIDASK = IB.BIDASK,
IB.MID = IB.MID,
IB.BID = IB.BID,
IB.ASK = IB.ASK,
IB.SPREADS = IB.SPREADS,
IB.SPREADS.Perc = IB.SPREADS.Perc
# IB.VOLATILITY = IB.VOLATILITY
)
}
twsDisconnect(tws)
return(res)
}
#' Prepare all required datasets for Oanda FX daily Modeling
#'
#' Prepare all required datasets for Oanda FX daily Modeling.
#'
#' @param ACCOUNT_TYPE Account type (e.g. "real" or "paper")
#' @param ACCESS_TOKEN Account API Token
#' @param oanda.count length of data to retreive
#' @param Cur1 currency one
#' @param Cur2 currency two
#' @param oanda.granularity barsize of Oanda data
#'
#' @return A \code{list} of \code{xts}
#'
#' @examples
#' res = prepareForexOandaPrices(oanda.count = 2500, Cur1 = "USD", Cur2 = "CAD", oanda.granularity = 'D')
#'
#' @export
prepareForexOandaPrices <- function(ACCOUNT_TYPE = .oandaEnv$ACCOUNT_TYPE, ACCESS_TOKEN = .oandaEnv$ACCESS_TOKEN, oanda.count = 250, Cur1 = "USD", Cur2 = "CAD", oanda.granularity = 'D'){
library(RQuantAPI)
convertToXts <- function(cm, tzone = ""){
dts <- structure(as.numeric(as.POSIXlt(gsub("(\\d{4})(\\d{2})(\\d{2})",
"\\1-\\2-\\3", cm[, 1], perl = TRUE))),
class = c("POSIXct","POSIXt"), tzone = tzone)
dts[wday(dts) == 1] = dts[wday(dts) == 1] - 3600 * 48 # <=============================== Check if it's Oanda's Bug
if(ncol(cm) > 2){
x <- xts(as.matrix(apply(cm[, -1], 2, as.numeric)), order.by = dts, tzone = tzone)
}else{
x <- xts(as.numeric(cm[, -1]), order.by = dts, tzone = tzone)
}
return(x)
}
instrument = paste0(Cur1, '_', Cur2)
# Oanda OHLC --------------------------------------------------------------
# cat('\nLoading Oanda OHLC...\n')
OA.ALL = getOandaInstrumentCandles(ACCOUNT_TYPE, ACCESS_TOKEN, INSTRUMENTS = instrument,
price = 'MBA', granularity = oanda.granularity, count = oanda.count)
OA.ALL = convertToXts(OA.ALL[, -1])
colnames(OA.ALL) = c('OA.Volume', 'OA.Bid.Open', 'OA.Bid.High', 'OA.Bid.Low', 'OA.Bid.Close'
, 'OA.Ask.Open', 'OA.Ask.High', 'OA.Ask.Low', 'OA.Ask.Close'
, 'OA.Mid.Open', 'OA.Mid.High', 'OA.Mid.Low', 'OA.Mid.Close')
OA.MID = OA.ALL[, c('OA.Mid.Close', 'OA.Mid.High', 'OA.Mid.Low', 'OA.Mid.Open', 'OA.Volume')]
OA.BID = OA.ALL[, c('OA.Bid.Close', 'OA.Bid.High', 'OA.Bid.Low', 'OA.Bid.Open', 'OA.Volume')]
OA.ASK = OA.ALL[, c('OA.Ask.Close', 'OA.Ask.High', 'OA.Ask.Low', 'OA.Ask.Open', 'OA.Volume')]
# Oanda Spreads -----------------------------------------------------------
# OA.SPREADS = SpreadsOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
# INSTRUMENTS = instrument, PERIOD = '1 year')
# cat('\nLoading Oanda Spreads...\n')
# OA.SPREADS = OA.ALL[, 2:5] - OA.ALL[, 6:9]
# OA.SPREADS.Perc = ((OA.ALL[, 2:5] - OA.ALL[, 6:9])/((OA.ALL[, 2:5] + OA.ALL[, 6:9])/2)) * 100
# Oanda Volume ------------------------------------------------------------
# cat('\nLoading Oanda Volume...\n')
# OA.VOLUME = OA.ALL[, 1]
# Oanda Net Positions -----------------------------------------------------
# cat('\nLoading Oanda New Positions...\n')
# OA.HistPos <- HistoricalPositionOanda(.oandaEnv$ACCOUNT_TYPE, .oandaEnv$ACCESS_TOKEN, .oandaEnv$ACCOUNT_ID,
# INSTRUMENTS = instrument, PERIOD = '1 year')
# OA.HistPos = convertToXts(as.data.frame(OA.HistPos)[, -1])
# colnames(OA.HistPos) = c('OA.LongPosRatio', 'OA.ExRate')
# OA.HistPos$OA.PosCorr = rollapply(OA.HistPos, by.column = F, width = 20, function(x) cor(x)[1,2])
# cat('\nEnsembling Final Data Output...\n')
res = list(OA.MID = OA.MID,
OA.BID = OA.BID,
OA.ASK = OA.ASK,
OA.ALL = OA.ALL
# OA.SPREADS = OA.SPREADS,
# OA.SPREADS.Perc = OA.SPREADS.Perc,
# OA.VOLUME = OA.VOLUME,
# OA.HistPos = OA.HistPos
)
return(res)
}
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