Volatility Violins
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Unlike many humans, markets love change. In fact, they look forward to it with great anticipation. Regular people like stability, for the most part. Unless you’re a career gypsy, you like to stay in one place for some time. Making a home. Settling in, as it were. Unlike markets, where volatility is the raison d’etre.Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
I’ve plotted the values for VIX, which is the CBOE’s volatility index calculated by some magic formula that considers 30-day expectation of price movement, in the chart below. Next to it is a plot of 30-day returns for the SPX, or a graph that plots all the percentage changes for each 30-day window. Quite frankly, I’m not sure what conclusions to draw from this, except that expectations in markets usually fall short.
The R code:
library(vioplot) library(quantmod) VIX <- getSymbols("^VIX", auto.assign=FALSE)[,4] SPX <- getSymbols("^GSPC", auto.assign=FALSE)[,4] VIX <- VIX/100 SPX <- Delt(SPX, k=30) SPX <- na.locf(SPX, na.rm=TRUE) SPX <- abs(SPX) vioplot(VIX, SPX, names=c("VIX", "SPX"), col="red3") title("Violins of Volatility")
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