addTA not working

This question has been asked many, many times on this list and on
StackOverflow.  You need to either 1) include the addTA call in your
chartSeries call, or 2) wrap the addTA call in plot().

# 1)
candleChart(sym, subset='2016-01::2016', name=ticker,
   theme="white", TA='addTA(Forecast,col="blue",on=1)')
# 2)
candleChart(sym, subset='2016-01::2016', name=ticker, theme="white", TA=NULL)
plot(addTA(Forecast,col="blue",on=1))

On Thu, Mar 3, 2016 at 11:28 AM, George Schmoll
<george.schmoll at sbcglobal.net> wrote:

I have been trying to display multiple chart using a TDNN creating a
forecast. When done on a individual time series, there is no problem.
When trying to do multiple charts, the forecast line is missing.
The entire source code follows.

library(quantmod)
library(TTR)
library(forecast)
library(nnet)

from<-as.Date("2010-12-01")

tickers<-c("MSFT")#,"ORCL","IBM","HPQ")
getSymbols(tickers,from=from,auto.assign=TRUE)

for(ticker in tickers)
    {
    sym        <-eval((parse(text=ticker)))
    clse       <- Cl(sym)
    hi         <- Hi(sym)
    lo         <- Lo(sym)
    vo         <- Vo(sym)
    DataLength <-length(clse)
    MidPoint   <- DataLength-10
    MaxHigh    <- max(hi);
    MinLow     <- min(lo);
    MaxVol     <- max(vo)
    MinVol     <- min(vo)
    xiLag0     <- (clse-MinLow)/(MaxHigh-MinLow)
    xiLag1     <- lag(xiLag0,1,na.pad=TRUE)
    xiLag2     <- lag(xiLag0,2,na.pad=TRUE)
    xiLag3     <- lag(xiLag0,3,na.pad=TRUE)
    xiLag4     <- lag(xiLag0,4,na.pad=TRUE)
    volLag0    <- (vo-MinVol)/(MaxVol-MinVol)
    volLag1    <- lag(volLag0,1,na.pad=TRUE)
    volLag2    <- lag(volLag0,2,na.pad=TRUE)
    volLag3    <- lag(volLag0,3,na.pad=TRUE)
    volLag4    <- lag(volLag0,4,na.pad=TRUE)

    DeltaClose <- diff(clse)
    Max        <-max(na.omit(DeltaClose))
    Min        <-min(na.omit(DeltaClose))
    scaleDeltaClose<-(DeltaClose-Min)/(Max-Min)

    DeltaClose <-lag(DeltaClose,-1,na.pad=TRUE)
    scaleDeltaClose<-lag(scaleDeltaClose,-1,na.pad=TRUE)

    data.all   <-cbind(sym,xiLag0,
                    xiLag1,xiLag2,xiLag3,xiLag4,
                    volLag0,volLag1,volLag2,volLag3,
                    volLag4,scaleDeltaClose)
    colnames(data.all)<-c("Open","High","Low",
                          "Close","Volume","Adj",
                          "xiLag0","xiLag1","xiLag2",
                          "xiLag3","xiLag4","volLag0",
                          "volLag1","volLag2","volLag3",
                          "volLag4","scaleDeltaClose")
    data.train <-data.all[10:MidPoint]
    data.eval  <-data.all[MidPoint:DataLength]
    learn<-nnet(scaleDeltaClose~
                xiLag0+xiLag1+xiLag2+xiLag3+xiLag4+
                volLag0+volLag1+volLag2+volLag3+volLag4,
                data=data.train,size=5,maxit=10000)
    prdct<-predict(learn,data.eval,type="raw")
    Change<-prdct*(Max-Min)+Min
    Forecast<-data.eval$Close+Change
candleChart(sym,subset='2016-01::2016',name=ticker,theme="white",TA=NULL)
    addTA(Forecast,col="blue",on=1)
    }

Thanks in advance. George
--
<mailto:gschmoll at acm.org>


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