Exhaustive Search Optimization

修改

evaluate <- function(PARAM, minVal = NA, maxVal = NA, y = 2014,
                     transform = FALSE, verbose = FALSE,
                     negative = FALSE, transformOnly = FALSE,
                     returnData = FALSE, accountParams = NULL){
  
  # 第一步
  # 转变并声明参数，如果它们存在于无界 (-inf,inf) 域中
  if( transform | transformOnly ){
    PARAM <- minVal +
      (maxVal - minVal) * unlist(lapply( PARAM, function(v) (1 + exp(-v))^(-1) ))
    if( transformOnly ){

    }
  }
 return(PARAM)  
}  ## 修改

Listing 8-2. Exhaustive Optimization

Declare bounds and step size for optimization

lowerBound <- c(n1 = 5, nFact = 3, nSharpe = 22, shThresh = 0.05)
upperBound <- c(n1 = 80, nFact = 3, nSharpe = 22, shThresh = 0.95)
stepSize <- c(n1 = 5, nFact = 1, nSharpe = 1, shThresh = 0.05)
pnames <- names(stepSize)
np <- length(pnames) 

Declare list of all test points

POINTS <- list()
for( p in pnames ){
  POINTS[[p]] <- seq(lowerBound[[p]], upperBound[[p]], stepSize[[p]])
}
OPTIM <- data.frame(matrix(NA, nrow = prod(unlist(lapply(POINTS, length))),
                           ncol = np + 1))
names(OPTIM)[1:np] <- names(POINTS)
names(OPTIM)[np + 1] <- "obj"

Store all possible combinations of parameters

for( i in 1:np ){
  each <- prod(unlist(lapply(POINTS, length))[-(1:i)])
  times <- prod(unlist(lapply(POINTS, length))[-(i:length(pnames))])
  OPTIM[,i] <- rep(POINTS[[pnames[i]]], each = each, times = times)
}

Test each row of OPTIM

timeLapse <- proc.time()[3]
for( i in 1:nrow(OPTIM) ){
  OPTIM[i,np+1] <- evaluate(OPTIM[i,1:np], transform = FALSE, y = 2014)
  cat(paste0("## ", floor( 100 * i / nrow(OPTIM)), "% complete\n"))
  cat(paste0("## ",
             round( ((proc.time()[3] - timeLapse) *
                       ((nrow(OPTIM) - i)/ i))/60, 2),
             " minutes remaining\n\n"))
}

Listing 8-3. Surface Plots and Level Plots for Exhaustive Optimization

library(lattice)
wireframe(obj ~ n1*shThresh, data = OPTIM,
          xlab = "n1", ylab = "shThresh",
          main = "Long-Only MACD Exhaustive Optimization",
          drape = TRUE,
          colorkey = TRUE,
          screen = list(z = 15, x = -60)
)

levelplot(obj ~ n1*shThresh, data = OPTIM,
          xlab = "n1", ylab = "shThresh",
          main = "Long-Only MACD Exhaustive Optimization"
)