Description Usage Arguments Details Value Author(s) References Examples
fit.implied.volatility.curve
estimates the coefficients of the quadratic equation for the implied volatilities.
1 |
x |
a set of implied volatilities |
k |
range of strikes |
This function estimates volatility σ as a quadratic function of strike k with the coefficents a_0, a_1, a_2: σ(k) = a_0 + a_1 k + a_2 k^2
a0 |
constant term in the quadratic ploynomial |
a1 |
coefficient term of k in the quadratic ploynomial |
a2 |
coefficient term of k squared in the quadratic polynomial |
summary.obj |
statistical summary of the fit |
Kam Hamidieh
D. Shimko (1993) Bounds of probability. Risk, 6, 33-47
E. Jondeau and S. Poon and M. Rockinger (2007): Financial Modeling Under Non-Gaussian Distributions Springer-Verlag, London
1 2 3 4 5 6 7 8 9 10 11 12 | #
# Suppose we see the following implied volatilities and strikes:
#
implied.sigma = c(0.11, 0.08, 0.065, 0.06, 0.05)
strikes = c(340, 360, 380, 400, 410)
tmp = fit.implied.volatility.curve(x = implied.sigma, k = strikes)
tmp
strike.range = 340:410
plot(implied.sigma ~ strikes)
lines(strike.range, tmp$a0 + tmp$a1 * strike.range + tmp$a2 * strike.range^2)
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