Problem integrating a option_model in R

Publishing Your Results
5

So, a couple of comments:

  1. The original error you cited simply comes from looping over 10 values when the number of rows in that dataset is 9. The proper way to define j would be j <- nrow(df_data), if that is indeed what you were trying to do. However, that's not the only problem.

  2. You don't need to define v0, vT, rho, k, sig inside each loop, since their values are always the same once you call the func_optim function.

  3. func_optim has return(...) inside a loop. This means that, when the function reaches that return(...) in the first loop, it will stop, returning one single value corresponding to i = 1.

  4. Even if you place return(mserr) outside of the loop, it will still only return one single value, in that case corresponding to the last iteration of the loop. I don't think this is what you want, but I'm not sure.

R functions return a single object, so you should think beforehand what you want this object to be. If you need multiple values, you will need to define a vector, a list, or a similar object which lets you store more than one value.

  1. Finally, and this is just a suggestion, try to avoid repeating names from objects inside functions, to avoid mix-ups. So in this case, var could be the function parameter, and var0 could be the vector with your values:
library(NMOF)

j <- nrow(df_data) # To loop over the number of rows in the dataset

func_optim <- function(var){ # var is the function parameter
  # These values are defined outside the loop:
  v0 <- var[1]
  vT <- var[2]
  rho <- var[3]
  k <- var[4]
  sig <- var[5]
  
  for(i in 1:j){
    prices <- df_data$call_price[i]
    mserr <- (callHestoncf(S=df_data$S[i], X=df_data$K[i], tau=df_data$T[i], r=df_data$r[i], q=0, v0, vT, rho, k, sig)-prices)^2
    # Store each mserr value somewhere if that is what you need
  }
  
  #return(wherever you stored mserr values)
}

var0 <- c(0.2, 0.2, 0.5, 0.2, 0.05) # var0 contains the actual v0, vT, rho, k, sig values
optim(var0, func_optim)

Hope this helps!