surfaceImpliedGFT: Calculate the implied Laplace transform using a joint fitting...

In piotrek-orlowski/impliedCF: Implied Characteristic Functions: power-divergence option portfolios. Magic.

Description

Calculate the implied Laplace transform using a joint fitting of a smooth surface to all options.

Usage

surfaceImpliedGFT(option.panels, mkt.frame, u.t.mat, max.pow = 3,
  doPlot = FALSE, doFitPlot = 0, verbose = FALSE, spline.rank = 6,
  convergence.scale = 0.01, weights = "opt-sqrt")

Arguments

option.panels	A list, each element containing a dataframe with normalized mid OTM option prices and LOG strikes. Each panel should correspond to the SAME day.
u.t.mat	An Nx2 dataframe, consisting of the frequencies and maturities for which the laplace transforms should be calculated
doPlot	Whether fitted / true values should be plotted
doFitPlot	Whether backfitting iterations should provide plot, doFitPlot is an integer: if 0, not plots, otherwise plots every doFitPlot iterations
verbose	Do we want diagnostic information?
spline.rank	This is the k argument to the function s from package mgcv, it determines the spline basis dimension.
convergence.scale	Scaling of the convergence criterion for the backfitting algorithm, a submodel j is deemed as having converged if the sqrt-sample-size-scaled norm of the iteration change in the predicted values is smaller than convergence.scale * sd(cp - sum(k != j)fk)
weights	string which defines the weighting scheme to be used in fitting. opt-sqrt weighs by the square root of the out of the money option price.
mkt.list	A data-frame, where each row corresponds to the market features associated with the n-th option panel (e.g. maturity, interest rate, etc...)

Value

An Nx3 dataframe, where the last column is the calculated transform value

piotrek-orlowski/impliedCF documentation built on May 7, 2019, 8:18 a.m.