进入退出信号的市值变化

Question

我正在寻找一种方法来计算股票市场头寸在进入和退出日期之间的每日变化。例如，如果我在 02/06/08 以价格 951.84 入场，并在 02/19/08 以价格 967.42 退出，基于 Daily market price 的每日价格变化是多少我想 merge 两个数据框 merge(df1,df2,all=T) 但同时考虑买卖日期并计算两者之间的变化。

>DailyMarketPrice

date        price
01/21/08    917.75
01/22/08    955.93
01/23/08    921.28
01/24/08    958.55
01/25/08    961.69
01/28/08    949.08
01/29/08    956.97
01/30/08    951.14
01/31/08    949.04
02/01/08    976.43
02/04/08    976.46
02/05/08    945.63
02/06/08    951.84
02/07/08    925.87
02/08/08    920.76
02/11/08    911.39
02/12/08    945.41
02/13/08    949.05
02/14/08    950.84
02/15/08    938.79
02/18/08    962.13
02/19/08    967.42


>signals

date    Cond
01/21/08    Buy
01/22/08    Sell
02/06/08    Buy
02/19/08    Sell

Answer 1

不幸的是，我对包的了解还不够多，无法想出可以为您处理此类问题的包。但是，由于这里只交易一种资产，因此自行编写代码似乎很简单。这是您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

如果是这样，这是我用来合并 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)

进入退出信号的市值变化

mark-to-market change from enter exit signals

r

quantitative-finance

performanceanalytics