[R-SIG-Finance] how to avoid loops & using xts, quantmod

[Immanuel]

Hey all,

I'm struggling with my first lines of R code.
It would be great if someone could help me to get the code
below runing, or show me how to do this task more efficient.

- can I avoid to use the loops?
- why does "Lo(GDAXI[i]) < tmp.lowest" not return a boolean?

best regards
Immanuel

-----------------------------------------------------------------------------
# clear workspace
rm(list = ls())
# set working directory
setwd("~/Ue1")

# load libraries
library(quantmod)
library(TTR)

# load costum functions
source("A2_func.R")

underlying = "GDAXI"

getSymbols("^GDAXI")
# trendfilter: -1 down-trend, 1 up-trend
# nothing smart, just an xts object containing 1 & -1
# according to trendfilter
direction = dir.macd(GDAXI)

period.lowest = xts(Inf, Sys.Date())
period.highest = xts(-Inf, Sys.Date())
tmp.lowest <- xts(Inf , Sys.Date()) # max value nehmen...
tmp.highest <- xts(-Inf, Sys.Date())
# now i want to find the max value (increasing) for every 
up-trend-periode (1,1,1)
# and min value for every down-trend-periode (decreasing) (-1,-1,-1)
for ( i in 1 : length(direction) ) {

     if (direction[i] == -1)    {
         tmp.highest <- -Inf
         if ( Lo(GDAXI[i]) < tmp.lowest)
             period.lowest[i] <- tmp.lowest
     }
     if (direction[i] == 1)    {
         tmp.lowest <- Inf
         if (Hi(GDAXI[i] > tmp.highest)
             period.highest <- tmp.highest
     }

}

------------------------------------------------------------------------------------------------

----------------------------------------------------------------------------------------------
dir.macd <- function(priceSeries) {
     library(quantmod)
     library(TTR)
     # MACD settings
     slow = 10
     fast = 25
     av = 5

     # Calculate the MACD indicator
     macd <- MACD(priceSeries, fast,slow,av )

     # Create the long (up) and short (dn) signals
     sigup <- ifelse(macd$macd < macd$signal, 1, 0)
     sigdn <- ifelse(macd$macd > macd$signal, -1, 0)

     # Lag signals to align with days in market,
     # not days signals were generated
     #sigup <- Lag(sigup,1) # Use lag() to avoid Toby's error
     #sigdn <- Lag(sigdn,1) # Use lag() to avoid Toby's error
     sigup <- lag(sigup,1) # Note k=1 implies a move *forward*
     sigdn <- lag(sigdn,1) # Note k=1 implies a move *forward*

     # Replace missing signals with no position
     # (generally just at beginning of series)
     sigup[is.na(sigup)] <- 0
     sigdn[is.na(sigdn)] <- 0

     # Combine both signals into one vector
     sig <- sigup + sigdn

     # Calculate SAR-direction
     for ( i in 2 : length(sig) ) {
         if (sig[i] == 0)
             sig[i]=sig[i-1]
     }
     sig
}