> folder <- "C:/Cauldron/garage/R/soulcraft/Data/Pairs/"
> rdata <- read.csv(paste(folder, "bhavcopy.csv", sep = ""), header = T)
> rdata <- rdata[rdata$SERIES == "EQ", ] |
> round(quantile(rdata$CLOSE/(1), probs = seq(0, 1, 0.1)))
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
0 18 36 55 82 120 163 244 380 716 8626 |
50 pct of stocks < 120 bucks 80 pct of stocks < 380 bucks max value is about 8626 bucks
> library(ggplot2)
> rdata1 <- rdata[rdata$TOTTRDVAL/(1e+07) > 90, ]
> rdata1 <- rdata1[order(rdata1$TOTTRDVAL, decreasing = T), ]
> rdata1$TOTTRDVAL <- rdata1$TOTTRDVAL/1e+07
> rdata1$SYMBOLF <- factor(rdata1$SYMBOL, levels = rdata1$SYMBOL)
> p <- ggplot(rdata1, aes(y = factor(SYMBOLF), x = TOTTRDVAL))
> q <- p + geom_point()
> q <- q + scale_x_continuous("Total Traded Value('00 Cr)")
> q <- q + scale_y_discrete("")
> q |
> round(quantile(rdata$TOTTRDVAL/(1e+07), probs = seq(0, 1, 0.05)))
0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75%
0 0 0 0 0 0 0 0 0 0 1 1 1 2 3 4
80% 85% 90% 95% 100%
8 14 26 64 648 |
50 percent of the stocks have less than 1 crore trading value 80 percent of the stocks have trades less than 8 crore trading value 95 percent of the stocks have trades less than 64 crore trading value Max trading volume is about 648 crore