R 中的滚动计算，季度数据，但滚动应以年度为基础，cumprod

Question

我有以下数据

PERIOD    GROWTH    PRICE
2011K1    0.88    0.88
2011K2    0.93    0.93
2011K3    0.96    0.96
2011K4    0.98    0.98
2012K1    1.13
2012K2    1.16
2012K3    1.12
2012K4    1.17
2013K1    1.07
2013K2    1.11
2013K3    1.03
2013K4    1.03

In 2011 PRICE = GROWTH
In 2012K1 PRICE = GROWTH[2012K1]*avg(PRICE in 2011)
In 2012K2 PRICE = GROWTH[2012K2]*avg(PRICE in 2011)
In 2012K3 PRICE = GROWTH[2012K3]*avg(PRICE in 2011)
In 2012K4 PRICE = GROWTH[2012K4]*avg(PRICE in 2011)
In 2013K1 PRICE = GROWTH[2013K1]*avg(PRICE in 2012)
In 2013K2 PRICE = GROWTH[2013K2]*avg(PRICE in 2012)
In 2013K3 PRICE = GROWTH[2013K3]*avg(PRICE in 2012)
In 2013K4 PRICE = GROWTH[2013K4]*avg(PRICE in 2012)

...

在每个季度，上一季度的平均价格用于乘以该特定季度的 GROWTH，即同年的每个季度乘以相同的平均价格，即前一年的平均价格。

我尝试使用 cumprod() 但未能在我的数据为季度时每年滚动一次。 我可以做 for 循环，问题是我必须为数千个产品做这个。

有什么建议？

Answer 1

给定最后 Note 中的数据计算季度， qtr ，然后循环计算 PRICE 的行。 不使用任何包。

run <- function(DF, k = 4) {
  nr <- nrow(DF)
  DF$qtr <- 1:k
  for(i in (k+1):nr) DF$PRICE[i] <- DF$GROWTH[i] * mean(DF$PRICE[i-DF$qtr[i]-(k-1):0])
  DF
}
run(DF)

给予：

   PERIOD GROWTH    PRICE qtr
1  2011K1   0.88 0.880000   1
2  2011K2   0.93 0.930000   2
3  2011K3   0.96 0.960000   3
4  2011K4   0.98 0.980000   4
5  2012K1   1.13 1.059375   1
6  2012K2   1.16 1.087500   2
7  2012K3   1.12 1.050000   3
8  2012K4   1.17 1.096875   4
9  2013K1   1.07 1.148578   1
10 2013K2   1.11 1.191516   2
11 2013K3   1.03 1.105641   3
12 2013K4   1.03 1.105641   4

笔记

Lines <- "PERIOD    GROWTH    PRICE
2011K1    0.88    0.88
2011K2    0.93    0.93
2011K3    0.96    0.96
2011K4    0.98    0.98
2012K1    1.13
2012K2    1.16
2012K3    1.12
2012K4    1.17
2013K1    1.07
2013K2    1.11
2013K3    1.03
2013K4    1.03"
DF.orig <- read.table(text = Lines, header = TRUE, fill = TRUE, as.is = TRUE)

Answer 2

-- 更新：意识到这个答案产生了错误的结果 -- @Rebecca

另外一个选项 ：）

# I'll use tidyverse for this approach.
library(tidyverse)

# First, I'll generate a dataset similar to yours.
data <- tibble(year = rep(2011:2013, each=4),
               quarter = rep(1:4, times=3),
               growth_quarter = c(0.88,
                          0.93,
                          0.96,
                          0.98,
                          1.13,
                          1.16,
                          1.12,
                          1.17,
                          1.07,
                          1.11,
                          1.03,
                          1.03))

# Create a new tibble with desired output.
data_m <- data %>%

  # Find the average growth per year.
  group_by(year) %>%
  mutate(growth_annual = mean(growth_quarter)) %>%

  # Remove grouping by year for next calculations.
  ungroup() %>%

  # Organize by year and quarter to ensure consistent results for calculation in next step.
  arrange(year, quarter) %>%

  # Multiply current quarter's growth by last year's average growth.
  mutate(growth_quarter*lag(growth_annual))

请让我知道，如果你有任何问题！