R/Quantmod: Multiple Charts All Using the Same Y-Axis

R/quantmod: multiple charts all using the same y-axis

With chartSeries, you can set the layout argument to NULL to prevent the layout() command from being called: this is what disables the mfrow setting.

library(quantmod)
getSymbols("AA")

op <- par(mfrow=c(3,2))
for(i in 1:6) {
  chartSeries(
    AA["2011-01"], "candlesticks", 
    TA=NULL, # No volume plot
    layout=NULL, 
    yrange=c(15,18)
  )
}
par(op)

If you want to keep the volume, you can call layout instead of setting mfrow: it does basically the same thing, but allows you to have plots of different sizes and choose the order in which they are plotted.

layout( matrix( c(
    1, 3,
    2, 4,
    5, 7,
    6, 8,
    9, 11,
   10, 12
  ), nc=2, byrow=TRUE),
  heights = rep( c(2,1), 3 )
)
#layout.show(12) # To check that the order is as desired
for(i in 1:6) {
  chartSeries( 
    AA[sprintf("2011-%02d",i)], 
    "candlesticks", layout=NULL, yrange=c(15,19) 
  )
}

Adding Multiple Chart Series in Quantmod R

You could use chart_Series instead of chartSeries.

chart_Series(Cl(data$GLD))
add_TA(Cl(data$GDX), on = 1)

And then if you want RSI below in a sub panel, just add add_RSI().

Another approach is to use version >= 0.10.0 of xts (i.e. don't use quantmod at all), which you can get from https://github.com/joshuaulrich/xts (0.10.0 is not yet on CRAN). The new plot function in xts is very friendly with plotting multiple columns of an xts object all at once. Check out ?plot.xts for examples of new functionality.

Edit #2:

To see relative changes more easily, you can normalise your price series in many ways. This is a typical approach (using a 0 origin is what Google charts does):

normalise_series <- function(xdat) xdat / coredata(xdat)[1]
getSymbols("USO")
window <- "2013/"

# Define colour of default chart line to chart_Series in mytheme object
# which is passed to chart_Series:
mytheme <- chart_theme()
mytheme$col$line.col <- "darkgreen"
chart_Series(normalise_series(Cl(data$GLD)[window]) - 1, theme = mytheme)
add_TA(normalise_series(Cl(data$GDX)[window]) - 1, on = 1, col = "red", lty = 3)
add_TA(normalise_series(Cl(USO)[window]) - 1, on = 1, col = "blue", lty =2)

add_TA(RSI(Cl(data$GLD)), on = NA, col = "darkgreen")
add_TA(RSI(Cl(data$GDX)), on = 2, col = "red", lty = 3)
# Or add RSIs on different subpanels to improve readability of charts:
add_TA(RSI(Cl(USO)), on = NA, col = "blue", lty = 2)

get multiple chart using chart_Series of quantmod package

I don't have access to a Bloomberg terminal, so your example is not reproducible for me. My guess is that crcy.ohcl has missing and/or NaN values.

You can test with range(crcy.ohcl). If the output is [1] NA NA, then you need to take care of the missing values in your data with something like na.omit(crcy.ohcl), na.locf(crcy.ohcl), etc.

---

EDIT: Thanks to GSee, I can replicate this via:

require(quantmod)
data(sample_matrix)
x <- as.xts(sample_matrix)
y <- as.quantmod.OHLC(x, col.names=c("Open", "High", "Low", "Close"))
chart_Series(y)          # error
chart_Series(as.xts(y))  # works

So it looks like chart_Series expects an xts object, but as.quantmod.OHLC doesn't have an xts method, so it returns a zoo object if you pass it a xts object.

R quantmod chartSeries: Add multiple TA overlay to single chart

Well, on=1 is what you need. I'm having trouble getting the TA="" to work, with the data I had to hand, but this did work:

chartSeries(x,TA=NULL);addTA(EMA(x$Close),on=1)

(The TA=NULL is to remove the volume chart.)

Or, use newTA to define your TA with all the desired parameters in advance, and then the TA argument does accept it:

myEMA = newTA(EMA, Cl, on=1, col=7)
chartSeries(x, TA="myEMA()")

(See ?newTA, which is where I stole that first line from!)

quantmod barChart (or chartSeries) formatting options

1. This functionality isn't available (patches welcome).
2. This functionality isn't available (patches welcome).
3. This functionality isn't available (patches welcome).
4. See the sparse documentation for ?addTA, specifically the on argument.
5. Plot the bottom chart as two separate up/down series, using two different colors, or perhaps chartTheme.
6. Not sure what you mean; just don't plot the bottom chart...
7. See the sparse documentation for the major.ticks argument to chartSeries. I don't think you can change the y axis grid line spacings, and the x axis spacing will be the same for the top and bottom chart.
8. See ?png and ?pdf.

How to overlay multiple TA in new plot using quantmod?

Here is an option which preserves largely your original code.
You can obtain the desired result using the option on=2 for each TA after the first:

library(quantmod)
getSymbols("PSEC")
price <- Cl(PSEC)
I1 <- SMA(price,3)
I2 <- SMA(price,10)
I3 <- SMA(price,15)
chartSeries(price, TA=list("addTA(I1, col=2)", "addTA(I2, col=4, on=2)",
                           "addTA(I3, col=5, on=2)"), subset = "last 6 months")

If you want to overlay the price and the SMAs in one chart, you can use the option on=1 for each TA.

Thanks to @hvollmeier who made me realize with his answer that I had misunderstood your question in the previous version of my answer.

PS: Note that several options are described in ?addSMA(), including with.col which can be used to select a specific column of the time series (Cl is the default column).

Multiple Charts Same Plot

using layout, it is easy once you create the right matrix

     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]    1    1    1    1    1    1    1    1    1     1
[2,]    2    3    4    5    6    7    8    9   10    11

layout(matrix(c(rep(1,10),2:11),nrow=2,byrow=T))
 x=c(1,2,3324,324)
 y=c(1,2,32,2323)
 plot(x,y)
 replicate(n=10,plot(x,y))

EDIT give different widths

mat <- matrix(c(rep(1,10),2:11),nrow=2,byrow=T)
layout(mat, widths = c(rep(1,5),rep(2,3),rep(3,2)))

I like the layout.show function. It is very convenient to control your layout.

layout.show(n = 11)

Overlay of multiple time series in Quantmod in R

The green blob is what you asked R to plot. c(PSEC, ARCC) is the same as rbind(PSEC, ARCC), which creates a single OHLCVA object with two observations per index value (one for PSEC, one for ARCC). You said you tried addTA, but it "didn't work". Saying something "doesn't work" does not help people help you, especially when you don't even show the code that "doesn't work".

Here's a chartSeries call that uses addTA, and a corresponding chart_Series version. Note that chart_Series automatically handles the y-axis range for you.

> chartSeries(Cl(PSEC), TA="addTA(Cl(ARCC), on=1)")
> chart_Series(Cl(PSEC), TA="add_TA(Cl(ARCC), on=1)")

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