• using R version 2.11.0 Under development (unstable) (2010-01-14 r50981)
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• this is package 'fOptions' version '2100.76'
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• checking examples ... ERROR
  Running examples in 'fOptions-Ex.R' failed.
  The error most likely occurred in:
  
  > ### * MonteCarloOptions
  >
  > flush(stderr()); flush(stdout())
  >
  > ### Name: MonteCarloOptions
  > ### Title: Monte Carlo Valuation of Options
  > ### Aliases: MonteCarloOptions wienerMCPath plainVanillaMCPayoff
  > ### arithmeticAsianMCPayoff MonteCarloOption
  > ### Keywords: programming
  >
  > ### ** Examples
  >
  > ## How to perform a Monte Carlo Simulation?
  >
  > ## First Step:
  > # Write a function to generate the option's innovations.
  > # Use scrambled normal Sobol numbers:
  > sobolInnovations = function(mcSteps, pathLength, init, ...) {
  + # Create Normal Sobol Innovations:
  + innovations = rnorm.sobol(mcSteps, pathLength, init, ...)
  + # Return Value:
  + innovations }
  >
  > ## Second Step:
  > # Write a function to generate the option's price paths.
  > # Use a Wiener path:
  > wienerPath = function(eps) {
  + # Note, the option parameters must be globally defined!
  + # Generate the Paths:
  + path = (b-sigma*sigma/2)*delta.t + sigma*sqrt(delta.t)*eps
  + # Return Value:
  + path }
  >
  > ## Third Step:
  > # Write a function for the option's payoff
  >
  > # Example 1: use the payoff for a plain Vanilla Call or Put:
  > plainVanillaPayoff = function(path) {
  + # Note, the option parameters must be globally defined!
  + # Compute the Call/Put Payoff Value:
  + ST = S*exp(sum(path))
  + if (TypeFlag == "c") payoff = exp(-r*Time)*max(ST-X, 0)
  + if (TypeFlag == "p") payoff = exp(-r*Time)*max(0, X-ST)
  + # Return Value:
  + payoff }
  >
  > # Example 2: use the payoff for an arithmetic Asian Call or Put:
  > arithmeticAsianPayoff = function(path) {
  + # Note, the option parameters must be globally defined!
  + # Compute the Call/Put Payoff Value:
  + SM = mean(S*exp(cumsum(path)))
  + if (TypeFlag == "c") payoff = exp(-r*Time)*max(SM-X, 0)
  + if (TypeFlag == "p") payoff = exp(-r*Time)*max(0, X-SM)
  + # Return Value:
  + payoff }
  >
  > ## Final Step:
  > # Set Global Parameters for the plain Vanilla / arithmetic Asian Options:
  > TypeFlag <<- "c"; S <<- 100; X <<- 100
  > Time <<- 1/12; sigma <<- 0.4; r <<- 0.10; b <<- 0.1
  >
  > # Do the Asian Simulation with scrambled random numbers:
  > mc = MonteCarloOption(delta.t = 1/360, pathLength = 30, mcSteps = 5000,
  + mcLoops = 50, init = TRUE, innovations.gen = sobolInnovations,
  + path.gen = wienerPath, payoff.calc = arithmeticAsianPayoff,
  + antithetic = TRUE, standardization = FALSE, trace = TRUE,
  + scrambling = 2, seed = 4711)
  
  Monte Carlo Simulation Path:
  
  
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  >
  > # Plot the MC Iteration Path:
  > par(mfrow = c(1, 1))
  > mcPrice = cumsum(mc)/(1:length(mc))
  > plot(mcPrice, type = "l", main = "Arithmetic Asian Option",
  + xlab = "Monte Carlo Loops", ylab = "Option Price")
  Warning in min(x) : no non-missing arguments to min; returning Inf
  Warning in max(x) : no non-missing arguments to max; returning -Inf
  Error in plot.window(...) : need finite 'ylim' values
  Calls: plot -> plot -> plot.default -> localWindow -> plot.window
  Execution halted