我不明白为什么我两次得到ATR和DonchianChannel列,所以最后tibble有ATR和ATR.1列,还有DonchianChannel和DonchianChannel.1列。价值观也各不相同?有人可以帮忙吗?感谢。
tq_get(c("DTE.DE", "SAP.DE"), get = "stock.prices", from = "2017-12-01") %>%
group_by(symbol) %>%
tq_mutate(select = c("high", "low", "close"), n=14, mutate_fun = ATR) %>%
tq_mutate(select = c("high", "low"), mutate_fun = DonchianChannel)
# A tibble: 38 x 15
# Groups: symbol [2]
symbol date open high low close volume adjusted tr atr ATR ATR.1 DonchianChannel mid DonchianChannel.1
<chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 DTE.DE 2017-12-01 15.065 15.140 14.975 14.975 14796786 14.975 NA NA NA NA NA NA NA
2 DTE.DE 2017-12-04 15.140 15.345 15.050 15.245 13463710 15.245 0.370 NA 15.345 14.975 NA NA NA
3 DTE.DE 2017-12-05 15.335 15.425 15.265 15.275 9877870 15.275 0.180 NA 15.425 15.245 NA NA NA
4 DTE.DE 2017-12-06 15.200 15.425 15.175 15.360 8934058 15.360 0.250 NA 15.425 15.175 NA NA NA
5 DTE.DE 2017-12-07 15.405 15.690 15.370 15.620 13318348 15.620 0.330 NA 15.690 15.360 NA NA NA
6 DTE.DE 2017-12-08 15.710 15.730 15.520 15.520 13255747 15.520 0.210 NA 15.730 15.520 NA NA NA
7 DTE.DE 2017-12-11 15.505 15.505 15.255 15.330 11920247 15.330 0.265 NA 15.520 15.255 NA NA NA
8 DTE.DE 2017-12-12 15.360 15.370 15.160 15.280 10615751 15.280 0.210 NA 15.370 15.160 NA NA NA
9 DTE.DE 2017-12-13 15.270 15.325 15.165 15.200 8826821 15.200 0.160 NA 15.325 15.165 NA NA NA
10 DTE.DE 2017-12-14 15.260 15.270 15.025 15.175 12976932 15.175 0.245 NA 15.270 15.025 15.73 15.3525 14.975
# ... with 28 more rows
答案 0 :(得分:1)
在函数文档中,您将看到TTR::ART
返回与HLC相同类的对象或包含列的矩阵(如果try.xts失败): {{1} },tr
,atr
和trueHigh
。 trueLow
返回与HL相同类的对象或包含列的矩阵(如果try.xts失败): TTR::DonchianChannel
,high
,{{1 }}
mid
重命名新创建的列,以便它们不会与现有列名冲突。使用low
,tq_mutate
,"open"
和/或"high"
等字符串(这是"low"
内函数"close"
的作用,看一下源代码here。)
例如,如果您使用replace_bad_names
代替tq_mutate
,则可以看到tq_transmute
列是tq_mutate
中提到的列。 (结果是一个只有新创建的列的对象,因此没有命名冲突。)
names
所以你的代码运行正常。但是,您可以重命名列以了解它们的含义。
?TTR::ATR
同时检查library(tidyquant)
tq_get(c("DTE.DE", "SAP.DE"), get = "stock.prices", from = "2017-12-01") %>%
group_by(symbol) %>%
tq_transmute(select = c("high", "low", "close"), n = 14, mutate_fun = ATR) %>%
names(.)
[1] "symbol" "date" "tr" "atr" "trueHigh" "trueLow"
的{{1}}参数。