[R-SIG-Finance] quantmod Charting

[James Klingsporn]

Thanks for the help.  The chartSeries and addTA helped.  Maybe it
wasn't clear from my first email but the indicators are already
calculated, it is just a matter of loading the data from a file.  I'll
take a look at TTR again;  For the add* function, such as MACD, the TA
is calculated from the begining of the chart data, correct?  This
would then be different from what I'm calculating, simply because the
TA continues from uncharted data.

On Thu, Jul 23, 2009 at 11:53 AM, Brian G. Peterson<brian at braverock.com> wrote:
> You haven't sent us a data series that we can reproduce your problem with.
>  Maybe grab one from an instrument that you don't trade, or simulate a
> series that has some of the same properties that you use to trade.
>
> I typically have no problem using chartSeries on a day of tick data
> (millions of points) or 15-sec OHLC bars (hundreds of thousands of points)
> beyond the time it takes to actually display/render the chart.  This
> includes calling addTA to add extra things to the charts in question.
>
> One thing that comes immediately to mind is that I would probably separate
> the process of creating the indicators from the process of charting.  Run
> through your data series and generate your indicators, then again to
> generate your signals, and *then* chart it from the aligned time series.
>
> There have been multiple previous posts to this list regarding calls to
> chartSeries and addTA from within custom functions, perhaps a review of the
> list archives is in order as well.
>
> Regards,
>
>  - Brian
>
> James Klingsporn wrote:
>>
>> Hello,
>>
>> I am using quantmod to create charts that have buy/sell date times
>> with a window 40 minutes before and after the buy/sell date time.  I
>> want to create ps charts and ultimately pdf charts of the trades.  I'm
>> not concerned with the exit right now.  The number of buy/sell date
>> times can range between 150 – 3000+, so I'd clearly like to automate
>> the process.  The code I’ve been using is attached below.  I've tried
>> putting the below into a function so I call the function with the
>> trade number, but this does not produce the full chart (and a similar
>> problem with 'if' and thus the multipe 'if's below for the same
>> condition).  If I run the below as Source R code it also doesn't
>> produce the full chart.  Also, because the code is so long for each
>> chart, I can't just run the code for all the trades at 1 time; I have
>> to cut and paste the script for about 75 trades/time.  The code has
>> run time of about 5-6 trade charts/min which clearly takes a while for
>> the 3000+ trades and then considering I have also to cut and paste the
>> code.
>>
>> Is there any way to speed up or otherwise improve the script/charting?
>>
>> Thanks,
>> Jim
>>
>>
>> R code for charts -
>>
>>  require(quantmod)
>>
>>        file = 'C:/Consulting/chart.txt'
>>        chart_data <- read.zoo(file, header = FALSE, col.names = c("Date",
>> "Open", "High", "Low", "Close", "MACD1min", "MACD5min", "MACD10min",
>> "Hist1min", "Hist5min", "Hist10min"), sep = ",", dec = ".", tz = "",
>> format = "%Y-%m-%d %H:%M:%S")
>>    ES <- cbind(chart_data$Open, chart_data$High, chart_data$Low,
>> chart_data$Close)
>>        ES <- as.quantmod.OHLC(ES, col.names = c("Open", "High", "Low",
>> "Close"))
>>
>>    time_before = 40
>>    time_after = 40
>>    time_before <- time_before * 60
>>    time_after <- time_after * 60
>>
>>    enter_times_path = 'C:/Consulting/ES_trades_with_slope_rule.txt'
>>    enter_times <- read.zoo(enter_times_path, header = FALSE,
>> col.names = c("Date", "Position"), sep = ",", dec = ".", tz = "",
>> format = "%Y-%m-%d %H:%M:%S")
>>
>>        ctheme <- chartTheme(theme = 'white', area = 'white', up.col =
>> '#0C481A', dn.col = '#B12525')
>>
>> i = 1
>> # Trade number repeats for number of trades
>>
>> display_range <- window(ES, start = time(enter_times[i]) - time_before
>> , end = time(enter_times[i]) + time_after)
>> m <- window(chart_data, start = time(enter_times[i]) - time_before ,
>> end = time(enter_times[i]) + time_after)
>> MACD <- cbind(m$MACD1min, m$MACD5min, m$MACD10min)
>>
>> chartSeries(display_range, theme = ctheme)
>>
>> Hist_range_5 = c(min(range(m$Hist5min)[1], - 0.2),
>> max(range(m$Hist5min)[2], 0.2))
>> Hist_range_10 = c(min(range(m$Hist10min)[1], - 0.2),
>> max(range(m$Hist10min)[2], 0.2))
>>
>> h_steep_slope_1min <- m[abs(diff(m$Hist1min)) >= 0.1]
>> h_slope_1min <- m[abs(diff(m$Hist1min)) >= 0.05 & abs(diff(m$Hist1min)) <
>> 0.1]
>> h_no_slope_1min <- m[abs(diff(m$Hist1min)) < 0.05]
>> h_slope_macd_above_1min <- h_slope_1min[abs(h_slope_1min$Hist1min) > 0.2,]
>> h_slope_macd_below_1min <- h_slope_1min[abs(h_slope_1min$Hist1min) <=
>> 0.2,]
>> h_no_slope_above_1min <- h_no_slope_1min[abs(h_no_slope_1min$Hist1min) >
>> 0.2,]
>> h_no_slope_below_1min <- h_no_slope_1min[abs(h_no_slope_1min$Hist1min) <=
>> 0.2,]
>> h_steep_slope_above_1min <-
>> h_steep_slope_1min[abs(h_steep_slope_1min$Hist1min) > 0.2,]
>> h_steep_slope_below_1min <-
>> h_steep_slope_1min[abs(h_steep_slope_1min$Hist1min) <= 0.2,]
>>
>> a = h_slope_macd_below_1min$Hist1min
>> b = h_no_slope_below_1min$Hist1min
>> f =     h_steep_slope_below_1min$Hist1min
>>
>> c = h_steep_slope_above_1min$Hist1min
>> d = h_no_slope_above_1min$Hist1min
>> e = h_slope_macd_above_1min$Hist1min
>>
>> zero_times = time(m)
>> zero = zoo(0, order.by = zero_times)
>>
>> addTA(a, on = NA, col = '#C03E15' , type = 'h', lwd = 3, yrange =
>> range(m$Hist1min))
>> addTA(b, on = 2, col = '#C03E15', type = 'h', lwd = 1)
>> addTA(f, on = 2, col = '#C03E15', type = 'h', lwd = 6)
>> addTA(c, on = 2, col = '#060440', type = 'h', lwd = 3)
>> addTA(d, on = 2, col = '#060440', type = 'h', lwd = 1)
>> addTA(e, on = 2, col = '#060440', type = 'h', lwd = 6)
>> addTA(zero, on = 2, col = 'black', type = 'l', lwd = 1)
>>
>> h_steep_slope_5min <- m[abs(diff(m$Hist5min)) >= 0.1]
>> h_slope_5min <- m[abs(diff(m$Hist5min)) >= 0.05 & abs(diff(m$Hist5min)) <
>> 0.1]
>> h_no_slope_5min <- m[abs(diff(m$Hist5min)) < 0.05]
>>
>> h_slope_macd_above_5min <- h_slope_5min[abs(h_slope_5min$Hist5min) > 0.7,]
>> h_slope_macd_below_5min <- h_slope_5min[abs(h_slope_5min$Hist5min) <=
>> 0.7,]
>>
>> h_no_slope_above_5min <- h_no_slope_5min[abs(h_no_slope_5min$Hist5min) >
>> 0.7,]
>> h_no_slope_below_5min <- h_no_slope_5min[abs(h_no_slope_5min$Hist5min) <=
>> 0.7,]
>>
>> h_steep_slope_above_5min <-
>> h_steep_slope_5min[abs(h_steep_slope_5min$Hist5min) > 0.7,]
>> h_steep_slope_below_5min <-
>> h_steep_slope_5min[abs(h_steep_slope_5min$Hist5min) <= 0.7,]
>>
>> a5 = h_slope_macd_below_5min$Hist5min
>> b5 = h_no_slope_below_5min$Hist5min
>> f5 = h_steep_slope_below_5min$Hist5min
>>
>> c5 = h_steep_slope_above_5min$Hist5min
>> d5 = h_no_slope_above_5min$Hist5min
>> e5 = h_slope_macd_above_5min$Hist5min
>>
>> addTA(a5, on = NA, col = '#C03E15' , type = 'h', lwd = 3, yrange =
>> range(Hist_range_5))
>> addTA(b5, on = 3, col = '#C03E15', type = 'h', lwd = 1)
>> addTA(f5, on = 3, col = '#C03E15', type = 'h', lwd = 6)
>> addTA(c5, on = 3, col = '#060440', type = 'h', lwd = 3)
>> addTA(d5, on = 3, col = '#060440', type = 'h', lwd = 1)
>> addTA(e5, on = 3, col = '#060440', type = 'h', lwd = 6)
>> addTA(zero, on = 3, col = 'black', type = 'l', lwd = 1)
>>
>> h_steep_slope_10min <- m[abs(diff(m$Hist10min)) >= 0.1]
>> h_slope_10min <- m[abs(diff(m$Hist10min)) >= 0.05 &
>> abs(diff(m$Hist10min)) < 0.1]
>> h_no_slope_10min <- m[abs(diff(m$Hist10min)) < 0.05]
>>
>> h_slope_macd_above_10min <- h_slope_10min[abs(h_slope_10min$Hist10min) >
>> 0.7,]
>> h_slope_macd_below_10min <- h_slope_10min[abs(h_slope_10min$Hist10min) <=
>> 0.7,]
>>
>> h_no_slope_above_10min <-
>> h_no_slope_10min[abs(h_no_slope_10min$Hist10min) > 0.7,]
>> h_no_slope_below_10min <-
>> h_no_slope_10min[abs(h_no_slope_10min$Hist10min) <= 0.7,]
>>
>> h_steep_slope_above_10min <-
>> h_steep_slope_10min[abs(h_steep_slope_10min$Hist10min) > 0.7,]
>> h_steep_slope_below_10min <-
>> h_steep_slope_10min[abs(h_steep_slope_10min$Hist10min) <= 0.7,]
>>
>> a10 = h_slope_macd_below_10min$Hist10min
>> b10 = h_no_slope_below_10min$Hist10min
>> f10 = h_steep_slope_below_10min$Hist10min
>>
>> c10 = h_steep_slope_above_10min$Hist10min
>> d10 = h_no_slope_above_10min$Hist10min
>> e10 = h_slope_macd_above_10min$Hist10min
>>
>> addTA(d10, on = NA, col = '#060440', type = 'h', lwd = 1)
>> addTA(a10, on = 4, col = '#C03E15' , type = 'h', lwd = 3, yrange =
>> range(Hist_range_10))
>> addTA(b10, on = 4, col = '#C03E15', type = 'h', lwd = 1)
>> addTA(f10, on = 4, col = '#C03E15', type = 'h', lwd = 6)
>> addTA(c10, on = 4, col = '#060440', type = 'h', lwd = 3)
>>
>> addTA(e10, on = 4, col = '#060440', type = 'h', lwd = 6)
>> addTA(zero, on = 4, col = 'black', type = 'l', lwd = 1)
>>
>> addTA(MACD, on = NA, col = c('blue', 'red', 'green'), type = c('l',
>> 'l', 'l'), lwd = c(4, 2, 1))
>> addTA(zero, on = 5, col = 'black', type = 'l', lwd = 1)
>>
>> if (as.character(enter_times[i]) == "Long")     Buy <- ES[time(ES) ==
>> time(enter_times[i]) + 60]$ES.Open
>> if (as.character(enter_times[i]) == "Long")     addTA(Buy, on = 1, col =
>> 'red', type = 'p', pch = 6, lwd = 2)
>> if (as.character(enter_times[i]) == "Long")     addTA(Buy > 0, on =
>> -(1:5), col = '#FFCAFD', border = NA)
>>
>> if (as.character(enter_times[i]) == "Short")    Short <- ES[time(ES) ==
>> time(enter_times[i]) + 60]$ES.Open
>> if (as.character(enter_times[i]) == "Short")    addTA(Short, on = 1,
>> col = 'blue', type = 'p', pch = 2, lwd = 2)
>> if (as.character(enter_times[i]) == "Short")    addTA(Short > 0, on =
>> -(1:5), col = '#FF7878', border = NA)
>>
>> # Repeats with i = 2...
>>
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>
>
> --
> Brian G. Peterson
> http://braverock.com/brian/
> Ph: 773-459-4973
> IM: bgpbraverock
>
>