This is an R graphing question; I'm spinning my wheels getting a reasonable plot of one row event (bid &\r\nask prices for timeslots 1..100 in the training set). I'm trying to get the\r\nbid series as solid green bars (downwards) and ask as solid red bars (going upward, which is tricky). Alternatively, I could create a stacked barplot with a pseudoseries\r\nspread=ask-bid (of filled black bars stacked on top of the bid series). Maybe slightly less desirable, because it doesn't plot the series directly.
\r\nSecond question: do you normalize the plot, if so to what? the average width of the bid-ask spread during the predictor window (slots 1..50), rounded to nearest unit? the max width of the bid-ask spread?
\r\nThanks in advance,
\r\nStephen
", "messages": [ { "id": "7013", "postDate": "12/08/2011 10:09:37", "content": "This is an R graphing question; I'm spinning my wheels getting a reasonable plot of one row event (bid &\r\nask prices for timeslots 1..100 in the training set). I'm trying to get the\r\nbid series as solid green bars (downwards) and ask as solid red bars (going upward, which is tricky). Alternatively, I could create a stacked barplot with a pseudoseries\r\nspread=ask-bid (of filled black bars stacked on top of the bid series). Maybe slightly less desirable, because it doesn't plot the series directly.
\r\nSecond question: do you normalize the plot, if so to what? the average width of the bid-ask spread during the predictor window (slots 1..50), rounded to nearest unit? the max width of the bid-ask spread?
\r\nThanks in advance,
\r\nStephen
", "rawMarkdown": "", "votes": null }, { "id": "7014", "postDate": "12/08/2011 11:24:12", "content": "Good question. I didn't do any aggregation, just looked at a few examples, and didn't do anything fancy. For the testing data I used
\r\ntesting <- read.csv("Data/testing.csv")
nt <- 50; nr <- nrow(testing)
asknt <- paste("ask",1:nt,sep="")
bidnt <- paste("bid",1:nt,sep="")
par(ask=TRUE)
for(i in 1:nr) {
plot(c(1:nt,1:nt),c(testing[i,match(bidnt,names(testing))],
testing[i,match(asknt,names(testing))]), type="n", xlab= "Index", ylab = "Price")
lines(1:nt,testing[i,match(bidnt,names(testing))],col="green",lwd=2)
lines(1:nt,testing[i,match(asknt,names(testing))],col="red",lwd=2)
}\r\nPress enter 50000 times if you've nothing else to do. And for (a bit of the) training data I used the following. I even coloured them green and red.
\r\ntraining <- read.csv("Data/abitofthetraining.csv")
nt <- 100; nr <- nrow(training)
asknt <- paste("ask",1:nt,sep="")
bidnt <- paste("bid",1:nt,sep="")
par(ask=TRUE)
for(i in 1:nr) {
plot(c(1:nt,1:nt),c(training[i,match(bidnt,names(training))],
training[i,match(asknt,names(training))]), type="n", xlab= "Index", ylab = "Price")
lines(1:nt,training[i,match(bidnt,names(training))],col="green",lwd=2)
lines(1:nt,training[i,match(asknt,names(training))],col="red",lwd=2)
abline(v=50)
}",
"rawMarkdown": "",
"votes": null
},
{
"id": "7015",
"postDate": "12/08/2011 11:53:07",
"content": "And here's those lines the you wanted. Though personally I think it looks ugly. Using filled polygons (the second version below) looks much nicer.
\r\ntraining <- read.csv("Data/abitofthetraining.csv")
nt <- 100; nr <- nrow(training)
asknt <- paste("ask",1:nt,sep="")
bidnt <- paste("bid",1:nt,sep="")
par(ask=TRUE)
for(i in 1:nr) {
plot(c(1:nt,1:nt),c(training[i,match(bidnt,names(training))],
training[i,match(asknt,names(training))]), type="n", xlab= "Index", ylab = "Price")
segments(1:nt,as.numeric(training[i,match(bidnt,names(training))]),y1=rep(par("usr")[3],nt),col="red")
segments(1:nt,as.numeric(training[i,match(asknt,names(training))]),y1=rep(par("usr")[4],nt),col="green")
abline(v=50)
}
par(ask=TRUE)
for(i in 1:nr) {
plot(c(1:nt,1:nt),c(training[i,match(bidnt,names(training))],
training[i,match(asknt,names(training))]), type="n", xlab= "Index", ylab = "Price")
polygon(c(1:nt,nt:1),c(as.numeric(training[i,match(bidnt,names(training))]),rep(par("usr")[3],nt)),col="red")
polygon(c(1:nt,nt:1),c(as.numeric(training[i,match(asknt,names(training))]),rep(par("usr")[4],nt)),col="green")
abline(v=50)
}",
"rawMarkdown": "",
"votes": null
}
],
"comments": [
{
"id": 7014,
"author_name": "alecstephenson",
"author_url": "",
"post_date": "12/08/2011 11:24:12",
"content": "Good question. I didn't do any aggregation, just looked at a few examples, and didn't do anything fancy. For the testing data I used
\r\ntesting <- read.csv("Data/testing.csv")
nt <- 50; nr <- nrow(testing)
asknt <- paste("ask",1:nt,sep="")
bidnt <- paste("bid",1:nt,sep="")
par(ask=TRUE)
for(i in 1:nr) {
plot(c(1:nt,1:nt),c(testing[i,match(bidnt,names(testing))],
testing[i,match(asknt,names(testing))]), type="n", xlab= "Index", ylab = "Price")
lines(1:nt,testing[i,match(bidnt,names(testing))],col="green",lwd=2)
lines(1:nt,testing[i,match(asknt,names(testing))],col="red",lwd=2)
}\r\nPress enter 50000 times if you've nothing else to do. And for (a bit of the) training data I used the following. I even coloured them green and red.
\r\ntraining <- read.csv("Data/abitofthetraining.csv")
nt <- 100; nr <- nrow(training)
asknt <- paste("ask",1:nt,sep="")
bidnt <- paste("bid",1:nt,sep="")
par(ask=TRUE)
for(i in 1:nr) {
plot(c(1:nt,1:nt),c(training[i,match(bidnt,names(training))],
training[i,match(asknt,names(training))]), type="n", xlab= "Index", ylab = "Price")
lines(1:nt,training[i,match(bidnt,names(training))],col="green",lwd=2)
lines(1:nt,training[i,match(asknt,names(training))],col="red",lwd=2)
abline(v=50)
}",
"votes": null,
"replies": []
},
{
"id": 7015,
"author_name": "alecstephenson",
"author_url": "",
"post_date": "12/08/2011 11:53:07",
"content": "And here's those lines the you wanted. Though personally I think it looks ugly. Using filled polygons (the second version below) looks much nicer.
\r\ntraining <- read.csv("Data/abitofthetraining.csv")
nt <- 100; nr <- nrow(training)
asknt <- paste("ask",1:nt,sep="")
bidnt <- paste("bid",1:nt,sep="")
par(ask=TRUE)
for(i in 1:nr) {
plot(c(1:nt,1:nt),c(training[i,match(bidnt,names(training))],
training[i,match(asknt,names(training))]), type="n", xlab= "Index", ylab = "Price")
segments(1:nt,as.numeric(training[i,match(bidnt,names(training))]),y1=rep(par("usr")[3],nt),col="red")
segments(1:nt,as.numeric(training[i,match(asknt,names(training))]),y1=rep(par("usr")[4],nt),col="green")
abline(v=50)
}
par(ask=TRUE)
for(i in 1:nr) {
plot(c(1:nt,1:nt),c(training[i,match(bidnt,names(training))],
training[i,match(asknt,names(training))]), type="n", xlab= "Index", ylab = "Price")
polygon(c(1:nt,nt:1),c(as.numeric(training[i,match(bidnt,names(training))]),rep(par("usr")[3],nt)),col="red")
polygon(c(1:nt,nt:1),c(as.numeric(training[i,match(asknt,names(training))]),rep(par("usr")[4],nt)),col="green")
abline(v=50)
}",
"votes": null,
"replies": []
}
],
"raw_markdown_by_id": {
"7013": "",
"7014": "",
"7015": ""
},
"source": "meta"
}