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在 R 中一次在多個時間序列上滾動平均返回和銳化

[英]Rolling mean returns and sharpe on several time-series at once in R

 原文  2021-02-06 15:35:18  2   1    r/ time-series/ finance

問題描述

我使用此腳本來一次計算單個 etf 的平均滾動回報率和平均滾動夏普比率：

library(quantmod)
library(httr)
library(jsonlite)
library(tidyverse)
library(hrbrthemes)
library(tidyquant)
library(timetk)
library(dplyr)
library(roll)
###
tickers = c('afk'); forex = c('EURUSD')   
tiingo_api_key("XXXXX") #wts = c(0.1,0.2,0.25,0.25,0.2) 
price_data <- tq_get(tickers, from = '2019-10-01', to = '2021-01-29',
                     get = "tiingo")
forex_data <- tq_get(forex, from = '2019-10-01', to = '2021-01-29',
                     get = "tiingo")
forex_data <- forex_data[ ,c(2, 8)]

price_data <- price_data %>%
  # join datasets using date column.
  # non key columns from rhs that have the same names as columns in 
  # the lhs get assigned the suffix "_forex_data"
  left_join(forex_data, by = c("date"), suffix = c("", "_forex_data")) %>%
  # calculate new value of adjusted by dividing by forex value
  mutate(adjusted = adjusted / adjusted_forex_data) %>%
  # exclude adjusted_forex_data column from result
  select(-adjusted_forex_data)

price_data <- na.omit(price_data) 
price_data <- price_data[ ,c(2,8)]
##
xdf <- data.frame()
xdf <- price_data
colnames(xdf)[2] <- "adjClose"
xdf_02 <- xdf %>%
  mutate(lagx = lag(adjClose)) %>%
  mutate(pct_change = (adjClose - lagx)/adjClose)%>%
  mutate(rollmeanx = roll_mean(pct_change, width = 68),rollsdx = roll_sd(pct_change, width=68)) %>%
  mutate(roll_sharpe = rollmeanx / rollsdx)

xdf_02 <- xdf_02[ ,c(1, 4, 5, 7)]

#write.csv(xdf_02,'afk_r.csv')

我需要對幾個 etfs 重復這個操作。 為此，我嘗試了這個腳本：

library(quantmod)
library(httr)
library(jsonlite)
library(tidyverse)
library(hrbrthemes)
library(tidyquant)
library(timetk)
library(dplyr)
library(roll)

###
tickers = c('xly', 'xlv', 'xli'); forex = c('EURUSD')   
tiingo_api_key("XXXX") #wts = c(0.1,0.2,0.25,0.25,0.2) 
price_data <- tq_get(tickers, from = '2019-08-19', to = '2019-10-19',
                     get = "tiingo")
forex_data <- tq_get(forex, from = '2019-08-19', to = '2019-10-19',
                     get = "tiingo")
forex_data <- forex_data[ ,c(2, 8)]

price_data <- price_data %>%
  # join datasets using date column.
  # non key columns from rhs that have the same names as columns in 
  # the lhs get assigned the suffix "_forex_data"
  left_join(forex_data, by = c("date"), suffix = c("", "_forex_data")) %>%
  # calculate new value of adjusted by dividing by forex value
  mutate(adjusted = adjusted / adjusted_forex_data) %>%
  # exclude adjusted_forex_data column from result
  select(-adjusted_forex_data)

price_data <- na.omit(price_data) 
price_data <- price_data[ ,c(1, 2,8)]

colnames(price_data)[3] <- "adjClose"
price_data_02 <- price_data %>%
  mutate(lagx = lag(adjClose)) %>%
  mutate(pct_change = (adjClose - lagx)/adjClose)%>%
  mutate(rollmeanx = roll_mean(pct_change, width = 10),rollsdx = roll_sd(pct_change, width=10)) %>%
  mutate(roll_sharpe = rollmeanx / rollsdx^5)

但它不能正常工作。 這是 price_data02 的輸入。

structure(list(symbol = c("XLY", "XLY", "XLY", "XLY", "XLY", 
"XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", 
"XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", 
"XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", 
"XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", 
"XLY", "XLY", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", 
"XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", 
"XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", 
"XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", 
"XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", 
"XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", 
"XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", 
"XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", 
"XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", 
"XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI"), date = structure(c(1566172800, 
1566259200, 1566345600, 1566432000, 1566518400, 1566864000, 1566950400, 
1567036800, 1567123200, 1567468800, 1567555200, 1567641600, 1567728000, 
1567987200, 1568073600, 1568160000, 1568246400, 1568332800, 1568592000, 
1568678400, 1568764800, 1568851200, 1568937600, 1569196800, 1569283200, 
1569369600, 1569456000, 1569542400, 1569801600, 1569888000, 1569974400, 
1570060800, 1570147200, 1570406400, 1570492800, 1570579200, 1570665600, 
1570752000, 1571011200, 1571097600, 1571184000, 1571270400, 1571356800, 
1566172800, 1566259200, 1566345600, 1566432000, 1566518400, 1566864000, 
1566950400, 1567036800, 1567123200, 1567468800, 1567555200, 1567641600, 
1567728000, 1567987200, 1568073600, 1568160000, 1568246400, 1568332800, 
1568592000, 1568678400, 1568764800, 1568851200, 1568937600, 1569196800, 
1569283200, 1569369600, 1569456000, 1569542400, 1569801600, 1569888000, 
1569974400, 1570060800, 1570147200, 1570406400, 1570492800, 1570579200, 
1570665600, 1570752000, 1571011200, 1571097600, 1571184000, 1571270400, 
1571356800, 1566172800, 1566259200, 1566345600, 1566432000, 1566518400, 
1566864000, 1566950400, 1567036800, 1567123200, 1567468800, 1567555200, 
1567641600, 1567728000, 1567987200, 1568073600, 1568160000, 1568246400, 
1568332800, 1568592000, 1568678400, 1568764800, 1568851200, 1568937600, 
1569196800, 1569283200, 1569369600, 1569456000, 1569542400, 1569801600, 
1569888000, 1569974400, 1570060800, 1570147200, 1570406400, 1570492800, 
1570579200, 1570665600, 1570752000, 1571011200, 1571097600, 1571184000, 
1571270400, 1571356800), tzone = "UTC", class = c("POSIXct", 
"POSIXt")), adjClose = c(103.88979190684, 103.985536180942, 105.940631520236, 
106.096510680224, 103.014000529557, 103.656054210621, 105.123520157882, 
106.773230698533, 106.651057131133, 106.752183731718, 107.124677149076, 
109.040842730252, 109.247378023503, 109.568338069556, 109.302004838183, 
109.941910107034, 110.128764894984, 109.409045218438, 108.834273053662, 
108.989530382645, 108.827860236458, 108.570749369651, 107.757863416592, 
108.300501919417, 107.120516287642, 108.465962815583, 108.199545227096, 
107.750358633043, 109.129846724491, 108.075096442047, 105.832515699236, 
105.961569473432, 107.027904160657, 106.408985827586, 105.658867955606, 
106.324973528198, 106.787293972671, 107.68727179356, 107.752492580939, 
108.604244285425, 108.882370462176, 108.528286758828, 108.098752156478, 
79.7690744415815, 79.1411361629132, 79.6907748306897, 79.3948067613073, 
77.3621365050958, 77.8143629822358, 78.5120834734553, 79.1591091551872, 
79.6413048138808, 79.5765650643146, 79.1234362097159, 79.8078108166086, 
79.9828303406139, 79.1766667827908, 79.5272422185871, 80.6357079172772, 
80.3610764188852, 79.9539261939731, 80.3891963088317, 80.1405701177907, 
80.0521265098073, 80.455259611697, 81.2234506709137, 80.9154011793777, 
80.1550223863104, 80.0379887611256, 79.7427685476557, 79.3351813102774, 
80.3786481095186, 79.4897334845071, 78.1095846438923, 78.5264905136837, 
79.8090839437686, 79.4299037039426, 78.1920270560489, 78.5873352799982, 
78.7947931577411, 79.2211265351062, 79.2732953079122, 80.6482408791092, 
80.4180877363704, 80.541688641759, 80.0837798356084, 65.5316291319365, 
65.1905505248625, 65.5636513034318, 65.7399118984554, 63.8180764075688, 
64.0429801055418, 64.9374155819368, 66.0930691100842, 66.6878168783335, 
66.1144476016407, 66.529346485538, 67.6427423430565, 67.7458012282476, 
67.8875770062091, 68.6161415417236, 69.5324528883564, 69.3622868620804, 
69.4247838104348, 69.893912323993, 69.5359752503656, 69.3616314471594, 
69.033862777913, 68.8724115050268, 68.8456157054001, 68.4405021069962, 
69.1184940526835, 69.345285107955, 69.0237442710668, 69.4092222987107, 
67.6575658763924, 66.1922748854133, 66.3878761442095, 67.1240973679064, 
66.6914199010372, 65.8941095924985, 66.3089478833794, 66.7582685555905, 
67.8212228997667, 67.7634712310145, 68.2513378525342, 68.1106187139345, 
68.0448169006413, 67.3224024690253), lagx = c(NA, 103.88979190684, 
103.985536180942, 105.940631520236, 106.096510680224, 103.014000529557, 
103.656054210621, 105.123520157882, 106.773230698533, 106.651057131133, 
106.752183731718, 107.124677149076, 109.040842730252, 109.247378023503, 
109.568338069556, 109.302004838183, 109.941910107034, 110.128764894984, 
109.409045218438, 108.834273053662, 108.989530382645, 108.827860236458, 
108.570749369651, 107.757863416592, 108.300501919417, 107.120516287642, 
108.465962815583, 108.199545227096, 107.750358633043, 109.129846724491, 
108.075096442047, 105.832515699236, 105.961569473432, 107.027904160657, 
106.408985827586, 105.658867955606, 106.324973528198, 106.787293972671, 
107.68727179356, 107.752492580939, 108.604244285425, 108.882370462176, 
108.528286758828, 108.098752156478, 79.7690744415815, 79.1411361629132, 
79.6907748306897, 79.3948067613073, 77.3621365050958, 77.8143629822358, 
78.5120834734553, 79.1591091551872, 79.6413048138808, 79.5765650643146, 
79.1234362097159, 79.8078108166086, 79.9828303406139, 79.1766667827908, 
79.5272422185871, 80.6357079172772, 80.3610764188852, 79.9539261939731, 
80.3891963088317, 80.1405701177907, 80.0521265098073, 80.455259611697, 
81.2234506709137, 80.9154011793777, 80.1550223863104, 80.0379887611256, 
79.7427685476557, 79.3351813102774, 80.3786481095186, 79.4897334845071, 
78.1095846438923, 78.5264905136837, 79.8090839437686, 79.4299037039426, 
78.1920270560489, 78.5873352799982, 78.7947931577411, 79.2211265351062, 
79.2732953079122, 80.6482408791092, 80.4180877363704, 80.541688641759, 
80.0837798356084, 65.5316291319365, 65.1905505248625, 65.5636513034318, 
65.7399118984554, 63.8180764075688, 64.0429801055418, 64.9374155819368, 
66.0930691100842, 66.6878168783335, 66.1144476016407, 66.529346485538, 
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69.5324528883564, 69.3622868620804, 69.4247838104348, 69.893912323993, 
69.5359752503656, 69.3616314471594, 69.033862777913, 68.8724115050268, 
68.8456157054001, 68.4405021069962, 69.1184940526835, 69.345285107955, 
69.0237442710668, 69.4092222987107, 67.6575658763924, 66.1922748854133, 
66.3878761442095, 67.1240973679064, 66.6914199010372, 65.8941095924985, 
66.3089478833794, 66.7582685555905, 67.8212228997667, 67.7634712310145, 
68.2513378525342, 68.1106187139345, 68.0448169006413), pct_change = c(NA, 
0.000920746073145609, 0.0184546317238109, 0.00146922042005707, 
-0.0299232156291454, 0.00619407796248412, 0.0139594445187539, 
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0.00574740309766703, 0.112976854387956, 0.112955109139078, 0.112980351066087, 
0.112705243098847, 0.111760609431317, 0.111973609162597, 0.112021291860913, 
0.112259036897868, 0.112608787611361, 0.112713414274796, 0.0108370376131496, 
0.0108978560310096, 0.0107044567314341, 0.0111601414489364, 0.00646492261696063, 
0.00731519373885582, 0.00734898883967546, 0.00736835445412688, 
0.00732195255143012, 0.00741697708347617, 0.00711097945850556, 
0.00677861308008291, 0.00731422581505028, 0.00640260188748834, 
0.00730279244956732, 0.00570760955999991, 0.00572303229458311, 
0.00572682863211845, 0.00699715000072969, 0.00781004948429501, 
0.00945506088599968, 0.00948183569894266, 0.0105738720243143, 
0.010598563559126, 0.0112714010510982, 0.0115245038249566, 0.0115877964390116, 
0.0116735206347549, 0.0107398588037852, 0.011571832681135, 0.00965048221251629, 
0.00961808834911209, 0.00861511313052298, 0.0710011590048217, 
0.0711727459280912, 0.0711992266027793, 0.0712009559938597, 0.0706618069135388, 
0.0707773921050657, 0.0705759483304227, 0.0715359995763646, 0.071841585236276, 
0.0717773132977845, 0.0135599568444965, 0.0141004602638644, 0.0140933169605556, 
0.0140968950343196, 0.00798765419203688, 0.00807692022915802, 
0.00844556579314001, 0.00764769054788447, 0.00754941651863466, 
0.00691330255424837, 0.00728477294878403, 0.00632186623256007, 
0.00647184586794521, 0.00649967123494101, 0.00597070454265456, 
0.00516857370156232, 0.00525784228032607, 0.00543847992799762, 
0.00527550470494566, 0.00955597962169792, 0.0113423807347606, 
0.0116002247919026, 0.0125344993925396, 0.0125609042910873, 0.0128552074244012, 
0.0124786360633152, 0.0127545719186988, 0.0141600338472121, 0.0139309924988578, 
0.0114638806205139, 0.00832687176592357, 0.0084118832879582, 
0.0087564030983619), roll_sharpe = c(NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 6685936.72065089, 8017614.08588343, 7018420.49412074, 
7390175.58759154, 303457831.38321, 301701990.16466, 343915160.124637, 
234319932.365587, 145122636.528603, 149313338.457622, 107805345.140361, 
-513696634.595997, -890314621.582531, -559092284.016373, -376976210.725815, 
-91112795.8598865, -126007475.754857, -121801635.87812, 8356196.78334217, 
-20849530.8685462, -21359871.763186, -17991989.5949062, -4230158.78094462, 
-10907459.3475125, -9800073.06957493, -19850034.8662731, -12026988.4026027, 
-804856.828796049, -15588869.806185, 5618212.74691359, 434139357.655666, 
282887772.972616, 156297275.131569, -1844.70949236578, -1851.02676904941, 
-1845.52487756475, -1912.46516501926, -2193.29199296906, -2142.93355275844, 
-2132.4578924304, -2078.45287781833, -1994.92100566292, -1968.30892082855, 
-5789470.07687758, 5111012.83362099, 2239290.17721102, -1910094.15459264, 
242413530.602272, 168571180.195937, 107329952.244829, 44848329.2430647, 
43246080.3576327, 30348748.7220495, 62885843.8430733, 54984232.2037732, 
72319252.6797467, 199955402.250585, 36682642.0431574, -125300350.018944, 
-128258096.728735, -128567718.189978, -2100051.88283564, -29019751.9921323, 
-33080305.4832977, -32226447.4516634, -13682492.5573323, -14246728.2791774, 
-13960409.9188887, -9299579.50478395, -6016253.88136516, -946033.172647721, 
-10060090.7869726, 6678121.87804663, 34244930.9891507, 30239721.4485301, 
6534622.28640464, -11870.4745751393, -11147.7029903439, -11090.8894943484, 
-11086.9035534244, -13531.2737991098, -13260.476946954, -13637.835605511, 
-11660.8071126149, -11029.073503579, -11233.6184909524, 3114562.13693613, 
6453302.74222076, 5719765.60187294, 5606026.48211451, 221247589.049459, 
237410120.344228, 152160342.169442, 186519350.922088, 189982252.319422, 
317341525.476637, 201622249.257587, 199605333.614001, 143478695.887835, 
119074960.747121, -35905618.217015, -165203371.531602, -9203619.27340462, 
-124610074.081346, -173431195.233419, -34924146.3939243, -25277786.0464064, 
-18927625.9791942, -8547243.41782084, -10408171.0343201, -11030595.382811, 
-13972733.3601454, -11500198.7808806, -3247442.34902245, -4744205.82362176, 
4113861.09463618, 70483686.0815983, 57701874.5526117, 5058502.40572489
)), row.names = c(NA, -129L), class = c("tbl_df", "tbl", "data.frame"
), na.action = structure(c(`6` = 6L, `50` = 50L, `94` = 94L), class = "omit"))

這是 price_data 的輸出：

structure(list(symbol = c("XLY", "XLY", "XLY", "XLY", "XLY", 
"XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", 
"XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", 
"XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", 
"XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", "XLY", 
"XLY", "XLY", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", 
"XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", 
"XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", 
"XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", 
"XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", "XLV", 
"XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", 
"XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", 
"XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", 
"XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI", 
"XLI", "XLI", "XLI", "XLI", "XLI", "XLI", "XLI"), date = structure(c(1566172800, 
1566259200, 1566345600, 1566432000, 1566518400, 1566864000, 1566950400, 
1567036800, 1567123200, 1567468800, 1567555200, 1567641600, 1567728000, 
1567987200, 1568073600, 1568160000, 1568246400, 1568332800, 1568592000, 
1568678400, 1568764800, 1568851200, 1568937600, 1569196800, 1569283200, 
1569369600, 1569456000, 1569542400, 1569801600, 1569888000, 1569974400, 
1570060800, 1570147200, 1570406400, 1570492800, 1570579200, 1570665600, 
1570752000, 1571011200, 1571097600, 1571184000, 1571270400, 1571356800, 
1566172800, 1566259200, 1566345600, 1566432000, 1566518400, 1566864000, 
1566950400, 1567036800, 1567123200, 1567468800, 1567555200, 1567641600, 
1567728000, 1567987200, 1568073600, 1568160000, 1568246400, 1568332800, 
1568592000, 1568678400, 1568764800, 1568851200, 1568937600, 1569196800, 
1569283200, 1569369600, 1569456000, 1569542400, 1569801600, 1569888000, 
1569974400, 1570060800, 1570147200, 1570406400, 1570492800, 1570579200, 
1570665600, 1570752000, 1571011200, 1571097600, 1571184000, 1571270400, 
1571356800, 1566172800, 1566259200, 1566345600, 1566432000, 1566518400, 
1566864000, 1566950400, 1567036800, 1567123200, 1567468800, 1567555200, 
1567641600, 1567728000, 1567987200, 1568073600, 1568160000, 1568246400,

問題出現在 pct_change 計算中，因為腳本在兩個不同的 etfs 時間序列之間進行 pct_change 計算，這會錯誤地誇大（縮小）最高（最低）價格的 etf 的夏普值。 感謝每一個貢獻

1 個解決方案

解決方案1
 0 已采納  2021-02-06 17:23:14

使用 group_by 解決了這個問題。 Tnx Phiver

library(quantmod)
library(httr)
library(jsonlite)
library(tidyverse)
library(hrbrthemes)
library(tidyquant)
library(timetk)
library(dplyr)
library(roll)

###
tickers = c('xly', 'xlv', 'xli'); forex = c('EURUSD')   
tiingo_api_key("XXXX") #wts = c(0.1,0.2,0.25,0.25,0.2) 
price_data <- tq_get(tickers, from = '2019-08-19', to = '2019-10-19',
                     get = "tiingo")
forex_data <- tq_get(forex, from = '2019-08-19', to = '2019-10-19',
                     get = "tiingo")
forex_data <- forex_data[ ,c(2, 8)]

price_data <- price_data %>%
  # join datasets using date column.
  # non key columns from rhs that have the same names as columns in 
  # the lhs get assigned the suffix "_forex_data"
  left_join(forex_data, by = c("date"), suffix = c("", "_forex_data")) %>%
  # calculate new value of adjusted by dividing by forex value
  mutate(adjusted = adjusted / adjusted_forex_data) %>%
  # exclude adjusted_forex_data column from result
  select(-adjusted_forex_data)

price_data <- na.omit(price_data) 
price_data <- price_data[ ,c(1, 2,8)]

colnames(price_data)[3] <- "adjClose"

by_etf <- price_data %>% group_by(symbol)

price_data_02 <- by_etf %>%
  mutate(lagx = lag(adjClose)) %>%
  mutate(pct_change = (adjClose - lagx)/adjClose)%>%
  mutate(rollmeanx = roll_mean(pct_change, width = 10),rollsdx = roll_sd(pct_change, width=10)) %>%
  mutate(roll_sharpe = rollmeanx / rollsdx^5)

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