Internal “Schwartz97” functions. These functions are not to be called by the user.
.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.