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R-Bloggers is a wonderful site which offers some great ideas for analysis.
While I have been busy of late, hence could not do much with R, I was inspired by this post by Eric Nguyen on Volume by Price chart.
This chart can be used with a great effect in ones trading strategies. It helps in identifying the support and resistance zones, and a breakout from these levels used as entry/exit points
Extending the work done by Eric, and making few changes in his original code, here is what I have achieved.
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| Reliance EOD Volume by Price chart |
It can now be visually observed the role of volume in providing support/resistance zones.
Future Work: Make animation-like effect to show case the strength offered by volumes at various price levels over a period of time.
Not the best way to code, here is the workable version for more experimentation and extension
It can also be downloaded from here
library(quantmod)
###############################################################
#Original Code
#http://blog.datapunks.com/2011/10/volume-by-price-charts-with-r-first-attempt/
#Change the ticker to get chart of any "yahoo" symbol
ticker = "RELIANCE.NS"
symbol <- getSymbols(ticker)
stock <- xts(get(symbol))
#remove stock name
names(stock)[names(stock)==paste(symbol,'.Open',sep="")] <- 'Open'
names(stock)[names(stock)==paste(symbol,'.Close',sep="")] <- 'Close'
names(stock)[names(stock)==paste(symbol,'.Volume',sep="")] <- 'Volume'
names(stock)[names(stock)==paste(symbol,'.Adjusted',sep="")] <- 'Adjusted'
names(stock)[names(stock)==paste(symbol,'.High',sep="")] <- 'High'
names(stock)[names(stock)==paste(symbol,'.Low',sep="")] <- 'Low'
#Add Positive and Negative Volumes
stock$posVbP <- Vo(stock[which(Lag(Cl(stock)) <= Cl(stock))])
stock$negVbP <- Vo(stock[which(Lag(Cl(stock)) > Cl(stock))])
#Since NAs got generated, replace NAs with 0.
stock[is.na(stock)] <- 0
#Subset for data since May 2011
myQ <- stock['2011-06::']
#Define function to add positive and negative volumes by prices
pVolBlock <- function(x) sum(myQ$posVbP[myQ$t==x])
nVolBlock <- function(x) sum(myQ$negVbP[myQ$t==x])
funcPriceByVol <- function(x){
myDiv <- 50 #Divisor for stock
myQHi <- as.integer(ceiling(max(Cl(myQ))/myDiv)*myDiv) #Identify High of Series
myQLo <- as.integer(floor(min(Cl(myQ))/myDiv)*myDiv) #Identify Low of Series
myBreaks <- as.integer(seq(myQLo, myQHi, by=myDiv)) #Create Breaks of interval divisor
# Identify and assign price intervals
myQ$t <<- myBreaks[findInterval(myQ$Close,myBreaks,all.inside=T)]
myVolsP <- unlist(lapply(myBreaks,pVolBlock)) #Add Positive Volumes to block
myVolsN <- unlist(lapply(myBreaks,nVolBlock)) #Add Negative Volumes to block
myVols <- rbind(myVolsP,myVolsN) #Bind the Positive and Negative Volumes
colnames(myVols) <- myBreaks #Define Column Naes
x=myVols
}
myPBV <- funcPriceByVol()
#lets Plot the graph now
plot(Cl(myQ),yaxt="n", ylab="",xlab="Time",
ylim=c(min(as.integer(colnames(myPBV))),max(as.integer(colnames(myPBV)))),
main=paste(ticker, "Close:- Volume by Price"),sub="Market Analyzer http://mypapertrades.blogspot.com/")
axis(side=2,las=1)
par(new=T)
barplot(height=myPBV,
beside=F,horiz=T, col=c(rgb(0,1,0,alpha=.3),rgb(1,0,0,alpha=.3)),
xlim=c(0,max(myPBV[1,]+myPBV[2,])*1.1),
space=10, width=3,xaxt="n",yaxt="n",
las=2)