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r - 尝试将特定功能应用于我的数据

问题描述

我正在学习一个教程，我正在尝试对我的数据应用一些功能。本教程通过以下方式下载数据；

library(tidyquant)
library(tidyverse)
library(timetk)


symbols <- c("SPY","EFA", "IJS", "EEM","AGG")

prices <- 
  getSymbols(symbols, src = 'yahoo', 
             from = "2012-12-31",
             to = "2017-12-31",
             auto.assign = TRUE, warnings = FALSE) %>% 
  map(~Ad(get(.))) %>%
  reduce(merge) %>% 
  `colnames<-`(symbols)

wide以以下格式返回：

> head(prices)
                SPY      EFA      IJS      EEM      AGG
2012-12-31 125.8673 47.69352 73.92869 39.04684 95.47135
2013-01-02 129.0933 48.43166 75.95714 39.81280 95.35963
2013-01-03 128.8016 47.96195 75.85664 39.53108 95.11894
2013-01-04 129.3673 48.20519 76.45055 39.61031 95.22212
2013-01-07 129.0137 47.99550 76.00284 39.31097 95.17055
2013-01-08 128.6425 47.72708 75.71043 38.95880 95.25651

然后他们应用以下内容；

asset_returns_long <-  
  prices %>% 
  to.monthly(indexAt = "lastof", OHLC = FALSE) %>% 
  tk_tbl(preserve_index = TRUE, rename_index = "date") %>%
  gather(asset, returns, -date) %>% 
  group_by(asset) %>%  
  mutate(returns = (log(returns) - log(lag(returns)))) %>% 
  na.omit()

它以长格式给出以下输出：

> head(asset_returns_long)
# A tibble: 6 x 3
# Groups:   asset [1]
  date       asset returns
  <date>     <chr>   <dbl>
1 2013-01-31 SPY    0.0499
2 2013-02-28 SPY    0.0127
3 2013-03-31 SPY    0.0373
4 2013-04-30 SPY    0.0190
5 2013-05-31 SPY    0.0233
6 2013-06-30 SPY   -0.0134

作者获取了他们的数据并在数据上执行to.monthly和转换并将其转换为数据。tk_tblwidelong

我也在尝试应用相同的功能，但是我的数据是long格式的。我尝试将其转换为wide格式，但我有重复的名称。

我的问题是，我怎样才能直接对长数据执行这些功能。我正在尝试的一切（转换为宽、grouping_by 等都返回不正确的结果）。

我正在使用的数据如下所示：

           ID         date         prc     
2015-06-02 "88250810" "2015-06-02" "55.250"
2015-06-02 "40414L10" "2015-06-02" "38.910"
2015-06-03 "88250810" "2015-06-03" "54.885"
2015-06-03 "40414L10" "2015-06-03" "38.240"
2015-06-04 "88250810" "2015-06-04" "53.980"
2015-06-04 "40414L10" "2015-06-04" "38.290"

该函数来自以下链接，并将每日价格转换为每月日志收益。

https://www.rdocumentation.org/packages/xts/versions/0.11-2/topics/to.period

设置为ts。d <- as.xts(d, order.by = d$date)

数据：

    data <- structure(c("88250810", "40414L10", "88250810", "40414L10", "88250810", 
"40414L10", "88250810", "40414L10", "88250810", "40414L10", "88250810", 
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"2016-05-23", "2016-05-24", "2016-05-24", "2016-05-25", "2016-05-26", 
"2016-05-27", "55.250", "38.910", "54.885", "38.240", "53.980", 
"38.290", "53.785", "37.360", "52.820", "37.260", "52.915", "37.190", 
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标签： r

解决方案

如果问题是如何创建一个广泛的时间序列，data那么这会创建一个广泛的 zoo object z。您可以直接使用它，或者如果您需要使用 data.framefortify.zoo(z)或者如果您需要使用 xts 对象as.xts(z)。

library(zoo)
z <- read.zoo(data, index = "date", split = "ID")

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