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开始回测一些交易数据，特别是一个非常基本的均值回归想法，我无法理解如何处理这个概念。

一旦 DifFromFv（与公允价值的偏差）达到 -10 并且随后随着 DifFromFv 扩展 -3 的倍数（-13，-16，- 19等）而每次DifFromFv从上次更改的'posy'恢复+5时'posy'减少1？简而言之，一旦 DifFromFv 达到 10 点并平均每 3 点，我就买入，同时将每个单独的平均值取出以获取 5 点的利润。

例如：

  DifFromFv posy
     0.00    0
   -10.00    1   #initial clip (target profit -5.00)
   -11.50    1
   -13.00    2   #avg #1 (target profit -8.00)
   -16.60    3   #avg #2 (target profit -11.00)
   -12.30    3    
   -11.00    2   #taking profit on avg #2
   -14.10    2   
    -8.00    1   #taking profit on avg #1
    -7.00    1
    -5.00    0   #taking profit on initial clip

应该注意的是，每个剪辑的止盈始终设置为 -5、-8、-11 等。增量，无论在哪里填充平均值，如 avg #2 的目标利润为 -11.00 而不是 -11.60。这既是为了减少现实填充与数据填充中的误差幅度，而且我很确定应该使这个概念的方法更容易思考。

提前致谢！

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1 回答 1

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下次请提供一些代码，即使您的解释很清楚。但是，您没有提到要如何处理 DifFromFv 中的大跳跃（例如，如果它从 -3 变为 -18），所以我把它留给您。

这是带有注释的代码：

library(plyr)

firstPosy = FALSE

DiffFair <- c(0, -10, -11.5, -13, -16.6, -12.3, -11, -14.1, -8, -7, -5) # Your data here
posy <- c(0)

buyPrices <- c(0) # Stores the prices at which you by your asset
targetProfit <- c(0) # Stores the target profit alongside with the vector above

steps <- c(0) # Stores your multiples of -3 after -10 (-10, -13, -16...)
PNL = 0

for (i in 2:length(DiffFair)) {

  # Case where posy increments for the first time by one

  if (DiffFair[i] <= -10 & DiffFair[i] > -13 & firstPosy == FALSE) {
    firstPosy = TRUE
    posy <- c(posy, 1)
    steps <- c(steps, round_any(DiffFair[i], 10, f = ceiling))
    lastChangePosy = DiffFair[i]
    buyPrices <- c(buyPrices, DiffFair[i])
    targetProfit <- c(targetProfit, -5)
  } 

else if (DiffFair[i] <= -13 & firstPosy == FALSE) {
    firstPosy = TRUE
    lastChangePosy = DiffFair[i]
    steps <- c(steps, round_any(DiffFair[i] + 10, 3, f = ceiling) - 10)
    buyPrices <- c(buyPrices, DiffFair[i])
    targetProfit <- c(targetProfit, -5)
    posy <- c(posy, tail(posy, n=1) + (-round_any(DiffFair[i] + 10, 3, f = ceiling) / 3) + 1)
  }

  # Posy increase

  else if (tail(steps, n=1) > round_any(DiffFair[i] + 10, 3, f = ceiling) - 10 & DiffFair[i] <= -10) {
    posy <- c(posy, posy[i-1] + 1)
    steps <- c(steps, round_any(DiffFair[i] + 10, 3, f = ceiling) -10)
    lastChangePosy = DiffFair[i]

    buyPrices <- c(buyPrices, DiffFair[i])
    targetProfit <- c(targetProfit, tail(targetProfit, n=1) - 3)
  }

  # Posy decrease

 else if (DiffFair[i] >= tail(targetProfit, n=1) & tail(posy, n=1) > 0) {
    if (tail(targetProfit, n=1) == -5) {
      posy <- c(posy, 0)
    }
    else {
      posy <- c(posy, posy[i-1] - 1)
    }
    lastChangePosy = DiffFair[i]

    # Compute PNL and delete the target profit and buy price from the vectors
    PNL = PNL + (DiffFair[i] - tail(buyPrices, n=1))
    buyPrices <- buyPrices[-length(buyPrices)]
    targetProfit <- targetProfit[-length(targetProfit)]
    steps <- steps[-length(steps)]

    if (DiffFair[i] > -10) {
      firstPosy = FALSE
    }

  }

  # Posy doesn't change

  else {
    posy <- c(posy, posy[i-1])
  }

}

print(PNL)
于 2017-09-29T12:08:21.967 回答