Description Usage Details Author(s)
Internal “Schwartz97” functions. These functions are not to be called by the user.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | .clean.rda.data(tmp.list, idx = 1:6)
.get.data(data, type = c("uv", "mv"))
.mu.state.schwartz2f(x0, delta0, mu, sigmaS, kappa,
alpha, sigmaE, rho, time, as.mat = FALSE)
.sigma.state.schwartz2f(sigmaS, kappa, sigmaE, rho, time)
.A.schwartz2f(kappa, sigmaS, sigmaE, rho, alphaT, r, ttm)
.B.schwartz2f(kappa, ttm)
.mu.fut.schwartz2f(x0, delta0, mu, sigmaS, kappa, sigmaE, rho,
alpha, alphaT, r, time, ttm, measure = "P")
.sigma.fut.schwartz2f(sigmaS, kappa, sigmaE, rho, time, ttm)
.sigma.opt.schwartz2f(time, Time, kappa, sigmaS, sigmaE, rho)
.sim.futures(time, dt, ttm = NA, obj = schwartz2f(), r = 0.03, lambda = 0, sd = 0.01)
|
.clean.rda.data
Removes NAs from the internal futures data
sets. This is needed in order to fit parameters to the data.
.get.data
Check whether data is of a particular
format and return a clean version of data.
.mu.state.schwartz2f
Computes the mean vector of the
jointly normally distributed state variables of the Schwartz
two-factor model. The state variables are the spot log-price and the
spot convenience yield.
.sigma.state.schwartz2f
Computes the covariance matrix
of the jointly normally distributed state variables of the Schwartz
two-factor model. The state variables are the spot log-price and the
spot convenience yield.
.A.schwartz2f
Computes the deterministic component
A(t,T) of the affine futures term-structure.
.B.schwartz2f
Computes the deterministic component
B(t,T) of the affine futures term-structure.
.mu.fut.schwartz2f
Computes the parameter mu
of the futures price log-normal distribution.
.sigma.fut.schwartz2f
Computes the parameter
sigma of the futures price log-normal distribution.
.sigma.opt.schwartz2f
Computes the sigma for
the options formula.
.sim.futures
Simulate futures prices and overlay with
noise. This function is used to test fit.schwartz2f.
Philipp Erb, David Luethi, Juri Hinz
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