TTR 中的 donchian 低是不正确的情节
donchian low in the TTR is incorrect plot
我正在使用 tidy 包绘制 donchian 高点和低点。低值看起来不正确。我可能没有正确调用 donchian 函数，因为 donchian_100_low 是该行的最大值。我不知道如何解决它。
library(tidyverse)
library(tidyquant)
library(ggthemes)
startdt <- "2021-02-01"
AMC <- tq_get(
"AMC",
get = "stock.prices",
from = startdt
)
AMC_values <- AMC %>%
mutate(
# EMA_20 = EMA(close, n = 20),
# EMA_50 = EMA(close, n = 50),
Don_100=DonchianChannel(high,low)
) %>%
na.omit()
head(AMC_values)
结果：
head(AMC_values)
# A tibble: 6 x 9
symbol date open high low close volume adjusted Don_100[,"high"] [,"mid"] [,"low"]
<chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 AMC 2021-02-17 5.58 5.62 5.32 5.55 38849000 5.55 17.2 11.4 5.62
2 AMC 2021-02-18 5.84 6.25 5.46 5.51 130540800 5.51 10.1 7.86 5.62
3 AMC 2021-02-19 5.54 5.77 5.51 5.7 40249100 5.7 9.77 7.70 5.62
4 AMC 2021-02-22 5.93 6.68 5.75 6.55 173409000 6.55 8.74 7.18 5.62
5 AMC 2021-02-23 6.97 7.86 6.01 7.7 264876400 7.7 8.27 6.94 5.62
6 AMC 2021-02-24 7.23 9.83 6.99 9.09 376881800 9.09 9.83 7.72 5.62
问题出在 DonchianChannel 的输入上。输入需要是 2 列的矩阵，而不是 2 个单独的列。如果您查看帮助，它会显示：
Object that is coercible to xts or matrix and contains High-Low
prices.
但是有点不清楚。带有它的示例显示得更好一些，data.frame、矩阵或 xts 对象都可以。
注意，如果你想要n = 100的donchian频道，你需要指定n，默认是：n = 10.
要让它在你的情况下工作，使用 tidyquant：
AMC_values <- AMC %>%
mutate(
Don_100=DonchianChannel(cbind(high,low))
)
%>%
na.omit()
head(AMC_values)
# A tibble: 6 x 9
symbol date open high low close volume adjusted Don_100[,"high"] [,"mid"] [,"low"]
<chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 AMC 2021-02-12 5.72 5.97 5.52 5.59 46773000 5.59 17.2 11.3 5.26
2 AMC 2021-02-16 6.03 6.05 5.49 5.65 61165700 5.65 10.1 7.68 5.26
3 AMC 2021-02-17 5.58 5.62 5.32 5.55 38849000 5.55 9.77 7.52 5.26
4 AMC 2021-02-18 5.84 6.25 5.46 5.51 130540800 5.51 8.74 7 5.26
5 AMC 2021-02-19 5.54 5.77 5.51 5.7 40249100 5.7 8.27 6.76 5.26
6 AMC 2021-02-22 5.93 6.68 5.75 6.55 173409000 6.55 6.89 6.07 5.26
这与您通过 quantmod 执行此操作的时间匹配：
library(quantmod)
startdt <- "2021-02-01"
AMC <- tq_get(
"AMC",
get = "stock.prices",
from = startdt
)
AMC <- getSymbols("AMC", from = startdt, auto.assign = FALSE)
head(na.omit(DonchianChannel(merge(Hi(AMC),Lo(AMC)))))
high mid low
2021-02-12 17.25 11.255 5.26
2021-02-16 10.10 7.680 5.26
2021-02-17 9.77 7.515 5.26
2021-02-18 8.74 7.000 5.26
2021-02-19 8.27 6.765 5.26
2021-02-22 6.89 6.075 5.26
quantmod 还有一种方法可以直接提供 donchian 值。
library(tidyverse)
library(tidyquant)
#> Loading required package: lubridate
#>
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:base':
#>
#> date, intersect, setdiff, union
#> Loading required package: PerformanceAnalytics
#> Loading required package: xts
#> Loading required package: zoo
#>
#> Attaching package: 'zoo'
#> The following objects are masked from 'package:base':
#>
#> as.Date, as.Date.numeric
#>
#> Attaching package: 'xts'
#> The following objects are masked from 'package:dplyr':
#>
#> first, last
#>
#> Attaching package: 'PerformanceAnalytics'
#> The following object is masked from 'package:graphics':
#>
#> legend
#> Loading required package: quantmod
#> Loading required package: TTR
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
#> == Need to Learn tidyquant? ====================================================
#> Business Science offers a 1-hour course - Learning Lab #9: Performance Analysis & Portfolio Optimization with tidyquant!
#> </> Learn more at: https://university.business-science.io/p/learning-labs-pro </>
library(ggthemes)
startdt <- "2021-02-01"
AMC <- tq_get(
"AMC",
get = "stock.prices",
from = startdt
)
test1<-AMC %>%
tq_mutate(select = c("high", "low"), mutate_fun = DonchianChannel,n=20,col_rename = c("DonH","DonM","DonL" ))
head(test1,30) %>%
na.omit()
#> # A tibble: 11 x 11
#> symbol date open high low close volume adjusted DonH DonM DonL
#> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 AMC 2021-03-01 8.86 9.45 8.42 9.18 1.44e8 9.18 17.2 11.3 5.26
#> 2 AMC 2021-03-02 9.14 9.4 8.51 8.93 7.81e7 8.93 11 8.13 5.26
#> 3 AMC 2021-03-03 8.95 9.14 8.5 8.58 5.57e7 8.58 11 8.13 5.26
#> 4 AMC 2021-03-04 8.25 8.59 7.5 8.03 7.78e7 8.03 11 8.13 5.26
#> 5 AMC 2021-03-05 8.08 8.27 7.63 8.05 5.97e7 8.05 11 8.13 5.26
#> 6 AMC 2021-03-08 8.53 9.48 8.31 9.29 1.14e8 9.29 11 8.13 5.26
#> 7 AMC 2021-03-09 9.38 10.8 9.22 10.5 1.50e8 10.5 11 8.13 5.26
#> 8 AMC 2021-03-10 11.0 12.5 9.51 9.85 2.62e8 9.85 12.5 8.90 5.32
#> 9 AMC 2021-03-11 10.6 10.9 9.9 10.3 8.39e7 10.3 12.5 8.90 5.32
#> 10 AMC 2021-03-12 10.2 11.4 9.94 11.2 1.11e8 11.2 12.5 8.90 5.32
#> 11 AMC 2021-03-15 12.2 14.5 11.8 14.0 2.78e8 14.0 14.5 9.91 5.32
我正在使用 tidy 包绘制 donchian 高点和低点。低值看起来不正确。我可能没有正确调用 donchian 函数，因为 donchian_100_low 是该行的最大值。我不知道如何解决它。
library(tidyverse)
library(tidyquant)
library(ggthemes)
startdt <- "2021-02-01"
AMC <- tq_get(
"AMC",
get = "stock.prices",
from = startdt
)
AMC_values <- AMC %>%
mutate(
# EMA_20 = EMA(close, n = 20),
# EMA_50 = EMA(close, n = 50),
Don_100=DonchianChannel(high,low)
) %>%
na.omit()
head(AMC_values)
结果：
head(AMC_values)
# A tibble: 6 x 9
symbol date open high low close volume adjusted Don_100[,"high"] [,"mid"] [,"low"]
<chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 AMC 2021-02-17 5.58 5.62 5.32 5.55 38849000 5.55 17.2 11.4 5.62
2 AMC 2021-02-18 5.84 6.25 5.46 5.51 130540800 5.51 10.1 7.86 5.62
3 AMC 2021-02-19 5.54 5.77 5.51 5.7 40249100 5.7 9.77 7.70 5.62
4 AMC 2021-02-22 5.93 6.68 5.75 6.55 173409000 6.55 8.74 7.18 5.62
5 AMC 2021-02-23 6.97 7.86 6.01 7.7 264876400 7.7 8.27 6.94 5.62
6 AMC 2021-02-24 7.23 9.83 6.99 9.09 376881800 9.09 9.83 7.72 5.62
问题出在 DonchianChannel 的输入上。输入需要是 2 列的矩阵，而不是 2 个单独的列。如果您查看帮助，它会显示：
Object that is coercible to xts or matrix and contains High-Low prices.
但是有点不清楚。带有它的示例显示得更好一些，data.frame、矩阵或 xts 对象都可以。
注意，如果你想要n = 100的donchian频道，你需要指定n，默认是：n = 10.
要让它在你的情况下工作，使用 tidyquant：
AMC_values <- AMC %>%
mutate(
Don_100=DonchianChannel(cbind(high,low))
)
%>%
na.omit()
head(AMC_values)
# A tibble: 6 x 9
symbol date open high low close volume adjusted Don_100[,"high"] [,"mid"] [,"low"]
<chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 AMC 2021-02-12 5.72 5.97 5.52 5.59 46773000 5.59 17.2 11.3 5.26
2 AMC 2021-02-16 6.03 6.05 5.49 5.65 61165700 5.65 10.1 7.68 5.26
3 AMC 2021-02-17 5.58 5.62 5.32 5.55 38849000 5.55 9.77 7.52 5.26
4 AMC 2021-02-18 5.84 6.25 5.46 5.51 130540800 5.51 8.74 7 5.26
5 AMC 2021-02-19 5.54 5.77 5.51 5.7 40249100 5.7 8.27 6.76 5.26
6 AMC 2021-02-22 5.93 6.68 5.75 6.55 173409000 6.55 6.89 6.07 5.26
这与您通过 quantmod 执行此操作的时间匹配：
library(quantmod)
startdt <- "2021-02-01"
AMC <- tq_get(
"AMC",
get = "stock.prices",
from = startdt
)
AMC <- getSymbols("AMC", from = startdt, auto.assign = FALSE)
head(na.omit(DonchianChannel(merge(Hi(AMC),Lo(AMC)))))
high mid low
2021-02-12 17.25 11.255 5.26
2021-02-16 10.10 7.680 5.26
2021-02-17 9.77 7.515 5.26
2021-02-18 8.74 7.000 5.26
2021-02-19 8.27 6.765 5.26
2021-02-22 6.89 6.075 5.26
quantmod 还有一种方法可以直接提供 donchian 值。
library(tidyverse)
library(tidyquant)
#> Loading required package: lubridate
#>
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:base':
#>
#> date, intersect, setdiff, union
#> Loading required package: PerformanceAnalytics
#> Loading required package: xts
#> Loading required package: zoo
#>
#> Attaching package: 'zoo'
#> The following objects are masked from 'package:base':
#>
#> as.Date, as.Date.numeric
#>
#> Attaching package: 'xts'
#> The following objects are masked from 'package:dplyr':
#>
#> first, last
#>
#> Attaching package: 'PerformanceAnalytics'
#> The following object is masked from 'package:graphics':
#>
#> legend
#> Loading required package: quantmod
#> Loading required package: TTR
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
#> == Need to Learn tidyquant? ====================================================
#> Business Science offers a 1-hour course - Learning Lab #9: Performance Analysis & Portfolio Optimization with tidyquant!
#> </> Learn more at: https://university.business-science.io/p/learning-labs-pro </>
library(ggthemes)
startdt <- "2021-02-01"
AMC <- tq_get(
"AMC",
get = "stock.prices",
from = startdt
)
test1<-AMC %>%
tq_mutate(select = c("high", "low"), mutate_fun = DonchianChannel,n=20,col_rename = c("DonH","DonM","DonL" ))
head(test1,30) %>%
na.omit()
#> # A tibble: 11 x 11
#> symbol date open high low close volume adjusted DonH DonM DonL
#> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 AMC 2021-03-01 8.86 9.45 8.42 9.18 1.44e8 9.18 17.2 11.3 5.26
#> 2 AMC 2021-03-02 9.14 9.4 8.51 8.93 7.81e7 8.93 11 8.13 5.26
#> 3 AMC 2021-03-03 8.95 9.14 8.5 8.58 5.57e7 8.58 11 8.13 5.26
#> 4 AMC 2021-03-04 8.25 8.59 7.5 8.03 7.78e7 8.03 11 8.13 5.26
#> 5 AMC 2021-03-05 8.08 8.27 7.63 8.05 5.97e7 8.05 11 8.13 5.26
#> 6 AMC 2021-03-08 8.53 9.48 8.31 9.29 1.14e8 9.29 11 8.13 5.26
#> 7 AMC 2021-03-09 9.38 10.8 9.22 10.5 1.50e8 10.5 11 8.13 5.26
#> 8 AMC 2021-03-10 11.0 12.5 9.51 9.85 2.62e8 9.85 12.5 8.90 5.32
#> 9 AMC 2021-03-11 10.6 10.9 9.9 10.3 8.39e7 10.3 12.5 8.90 5.32
#> 10 AMC 2021-03-12 10.2 11.4 9.94 11.2 1.11e8 11.2 12.5 8.90 5.32
#> 11 AMC 2021-03-15 12.2 14.5 11.8 14.0 2.78e8 14.0 14.5 9.91 5.32