interpolation example for calls

interpolationCalls.R

#get coordinates of NAs in grid
toInterpolate <- which(is.na(ivGridCalls))
coords <- cbind(toInterpolate%%dim(ivGridCalls)[1], toInterpolate%/%dim(ivGridCalls)[1] + 1)
coords[coords[,1] == 0, 2] <- coords[coords[,1] == 0, 2] - 1 
coords[coords[,1] == 0, 1] <- dim(ivGridCalls)[1]

#loop through NAs and interpolate
for(i in 1:nrow(coords)){
  #get the coordinates of a 10x10 area around the missing value
  x1 <- max(coords[i,1] - 10, 1)
  x2 <- min(coords[i,1] + 10, dim(ivGridCalls)[1])
  y1 <- max(coords[i,2] - 10, 1)
  y2 <- min(coords[i,2] + 10, dim(ivGridCalls)[2])
  
  #get the moneyness/time to mat combination of the missing value
  x0 <- as.numeric(rownames(ivGridCalls)[coords[i,1]])
  y0 <- as.numeric(colnames(ivGridCalls)[coords[i,2]])
  
  #get the part of the grid that is used to interpolate and remove all missing values that are present
  interpGrid <- ivGridCalls[x1:x2,y1:y2]
  interpGrid <- melt(interpGrid)
  interpGrid <- na.omit(interpGrid)
  
  #interpolate linearly
  interpVal <- interp(x = interpGrid$Var1, y = interpGrid$Var2, z = interpGrid$value,
                     xo = x0, yo = y0,
                     linear = TRUE, extrap = TRUE)$z[1,1]
  
  #if linear interpolation doesnt yield a result, use spline interpolation
  if(is.na(interpVal)){
    interpVal <- interp(x = interpGrid$Var1, y = interpGrid$Var2, z = interpGrid$value,
                       xo = x0, yo = y0,
                       linear = FALSE, extrap = TRUE)$z[1,1]
  }
  
  #if the resulting value is clearly wrong, e.g. negative or way outside the values that are used to interpolate,
  #leave it as NA
  if(interpVal < 0 | interpVal > max(interpGrid$value * 1.5)){
    interpVal <- NA
  }
  
  #replace the value with the result of the interpolation
  ivGridCalls[coords[i,1],coords[i,2]] <- interpVal
}