Question

我正在寻找一种方法来计算进入和退出日期之间股票市场头寸的每日变化。例如，如果我以价格02/06/08的{{1}}输入，并以价格951.84退出02/19/08，那么基于967.42的每日价格变化是多少？我想Daily market price两个数据框merge，但同时考虑买入和卖出日期并计算两者之间的变化。

merge(df1,df2,all=T)

Answer 1

不幸的是，我不熟悉足够的软件包来提出能够为你处理这类事情的东西。但是，由于这里只交易了一种资产，因此单独编写代码似乎很简单。这是你正在寻找的那种输出吗？

    date  price inv.change inventory pnl.change   pnl
01/21/08 917.75          1         0       0.00  0.00
01/22/08 955.93         -1         1      38.18 38.18
01/23/08 921.28          0         0       0.00 38.18
01/24/08 958.55          0         0       0.00 38.18
01/25/08 961.69          0         0       0.00 38.18
01/28/08 949.08          0         0       0.00 38.18
01/29/08 956.97          0         0       0.00 38.18
01/30/08 951.14          0         0       0.00 38.18
01/31/08 949.04          0         0       0.00 38.18
02/01/08 976.43          0         0       0.00 38.18
02/04/08 976.46          0         0       0.00 38.18
02/05/08 945.63          0         0       0.00 38.18
02/06/08 951.84          1         0       0.00 38.18
02/07/08 925.87          0         1     -25.97 12.21
02/08/08 920.76          0         1      -5.11  7.10
02/11/08 911.39          0         1      -9.37 -2.27
02/12/08 945.41          0         1      34.02 31.75
02/13/08 949.05          0         1       3.64 35.39
02/14/08 950.84          0         1       1.79 37.18
02/15/08 938.79          0         1     -12.05 25.13
02/18/08 962.13          0         1      23.34 48.47
02/19/08 967.42         -1         1       5.29 53.76

如果有，请参阅我用来合并DailyMarketPrice和signals的代码：

DailyMarketPrice <- do.call(rbind, list(
  data.frame(date = "01/21/08", price = 917.75),
  data.frame(date = "01/22/08", price = 955.93),
  data.frame(date = "01/23/08", price = 921.28),
  data.frame(date = "01/24/08", price = 958.55),
  data.frame(date = "01/25/08", price = 961.69),
  data.frame(date = "01/28/08", price = 949.08),
  data.frame(date = "01/29/08", price = 956.97),
  data.frame(date = "01/30/08", price = 951.14),
  data.frame(date = "01/31/08", price = 949.04),
  data.frame(date = "02/01/08", price = 976.43),
  data.frame(date = "02/04/08", price = 976.46),
  data.frame(date = "02/05/08", price = 945.63),
  data.frame(date = "02/06/08", price = 951.84),
  data.frame(date = "02/07/08", price = 925.87),
  data.frame(date = "02/08/08", price = 920.76),
  data.frame(date = "02/11/08", price = 911.39),
  data.frame(date = "02/12/08", price = 945.41),
  data.frame(date = "02/13/08", price = 949.05),
  data.frame(date = "02/14/08", price = 950.84),
  data.frame(date = "02/15/08", price = 938.79),
  data.frame(date = "02/18/08", price = 962.13),
  data.frame(date = "02/19/08", price = 967.42)
))

signals <- setNames(as.data.frame(matrix(c(
  "01/21/08", "Buy",
  "01/22/08", "Sell",
  "02/06/08", "Buy",
  "02/19/08", "Sell"
), ncol = 2, byrow = TRUE)), c("date", "Cond"))

# Set `inv.change` to `+1` on "Buy" days, `-1` on "Sell" days and `0` on every
#  day without a transaction.
merged <- cbind(DailyMarketPrice, inv.change = c(+1, -1, 0)[match(signals$Cond[match(DailyMarketPrice$date, signals$date)], c("Buy", "Sell", NA))])
# Set `inventory` to 0 on "Buy" days, 1 on "Sell" days, and 1 on every day
#  between "Buy" and "Sell" days.
merged$inventory <- head(diffinv(merged$inv.change), -1)
# Mark-to-market the inventory positions by calculating change in prices during
#  holding periods.
merged$pnl.change <- merged$inventory * c(0, diff(merged$price))
# Record the cumulative P&L.
merged$pnl <- tail(diffinv(merged$pnl.change), -1)
print(merged)

从输入退出信号标记到市场的变化

1 个答案: