In John Mauldin’s most recent letter, he had these wise words (among others) to offer…
I queried several venture capitalists, who see literally thousands and thousands of business proposals. While lots of people are working on it, they are aware of nothing on the near horizon. Water may be my #1 concern about the future. It is an intractable problem and one that must be solved. There is Microsoft- or Google-type wealth awaiting the team that creates an inexpensive way to purify water. Water management will be a major issue in the future. There are those who think we will go to war over oil or energy in the future. I rather doubt it. Water rights are going to be the issue that will divide nations and peoples unless we can find new technologies to create cheap supplies of fresh water and move it to where it is needed.
Solve for Implied Volatility in R
I have written a fairly basic “Effective Position & Risk Management System” in R, for managing asset positions with several option legs.
Every morning, it paints me a pie chart of where I’m getting my theta decay, as well as my effective exposure to each of the major asset classes.
One of the requirements, is calculating the Implied Volatility of each option. I found some approximations, interesting, but none seem to be as intelligent as using a brute force method or bi-section method.
I wrote a recursive function and used it for a month, but it took forever, or got lost and produced errors. Obviously, I was faced with playing with step size/factor and accuracy trade-offs.
So, I’m currently using a brute-force method, which seems to work well and faster than the recursive algorithm. It’s not perfect, but it’s working. If anybody out there on the interwebs has a better or more beautiful solution, let me know. Here it is:
FindIV <- function(OptionMarketPrice, AssetPrice, Time, Strike, r, LowRange, HighRange, Right)
{
Range <- seq(LowRange,HighRange,by=((HighRange-LowRange)/100000))
OptionBasedOnGuess <- GBSOption(Right, AssetPrice, Strike, Time, r, 0.000, Range, "wtf", "xx")
Error <- OptionBasedOnGuess@price - OptionMarketPrice
Key <- which.min(abs(Error))
Range[Key]
}