June 16th, 2006, 4:18 pm
I'm working on a simple tool for a brokerage(not trader) that needs an indicator for an equity's "volatility". I've been given the CDS(5 yr) and equity history for Ford for about 18 months, and from that I've been unable to correlate the variables because clearly a two-variable regression for something so complex would have correlated error terms(I haven't tried to fit this data to a marginal distribution, but I'm not convinced it's even elliptical, and so how the hell can... whatever: I'm not getting into copulas yet). I looked at the % changes of both the cds and stock price(using various sample sizes, shifts, etc), and I get correlatations that fluctuate like mad, like I've no idea how to even bs this one. Right now, since people want results immediately, I'm telling them to use a parity change in the 4 day sample mean of cds percent change as an indicator of volatility. They really want me to find how the cds changes lead the stock changes, but this seems an insanely difficult problem to solve! Ideas?