将数据框转换为 XTS 以在 PortfolioAnalytics 包中使用的正确方法
Correct way to convert data frame to XTS to be used in PortfolioAnalytics package
我正在使用包 tidyverse 和 tidyquant 将数据框转换为 XTS 对象。
library(tidyverse)
library(tidyquant)
xts <- na.omit(as.data.frame(new.df))
xts <- as_xts(xts, Date)
好像成功了：
> str(xts)
An ‘xts’ object on 1981-01-29/2017-06-28 containing:
Data: chr [1:9184, 1:36] "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr [1:36] "Ticker" "Open" "High" "Low" ...
Indexed by objects of class: [Date] TZ: UTC
xts Attributes:
NULL
打印的 xts 对象
接下来我希望将其加载到性能分析包中。我提取要加载到包中的列。
data=xts[,35]
然后 str(data) 再次显示一个 xts 对象。
> str(data)
An ‘xts’ object on 1981-01-29/2017-06-28 containing:
Data: chr [1:9184, 1] "-7.671475e-02" "-5.297988e-01" "-2.037823e+00" " 1.221346e+00" " 1.011910e-01" " 8.087721e-01" " 7.482913e-01" ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr "long_exit_eq"
Indexed by objects of class: [Date] TZ: UTC
xts Attributes:
NULL
这仍然是一个带有日期和列的 xts 对象，以及 head(data):
> head(data)
long_exit_eq
1981-01-29 "-7.671475e-02"
1981-01-30 "-5.297988e-01"
1981-02-02 "-2.037823e+00"
1981-02-03 " 1.221346e+00"
1981-02-04 " 1.011910e-01"
1981-02-05 " 8.087721e-01"
投资组合分析：
> # create table of downside risk estimates
> table.DownsideRisk(data)
Error in MAR - r : non-numeric argument to binary operator
In addition: Warning message:
In mean.default(coredata(x), ...) :
argument is not numeric or logical: returning NA
> # chart equity curve, daily performance, and drawdowns
> charts.PerformanceSummary(data)
Error in na.omit.xts(x) : unsupported type
上面的错误我不确定为什么会发生。 na.omit.xts...数据集中没有 na 值。我在开始使用数据框时删除了它们：xts <- na.omit(as.data.frame(new.df))
xts 对象的数据框似乎在工作，拉动我想在投资组合分析中使用的列似乎在工作。
只是为了展示我的 xts 对象的头部：
> head(xts)
Ticker Open High Low Close Volume Open.Interest roll.mean.n3 roll.mean.n5 roll.mean.n7
1981-01-29 "$SPX" " 130.34" " 131.78" " 128.97" " 130.24" " 26900000" "0" " 130.5667" " 130.354" " 130.4843"
1981-01-30 "$SPX" " 130.24" " 131.65" " 128.61" " 129.55" " 29100000" "0" " 130.0433" " 130.218" " 130.2257"
1981-02-02 "$SPX" " 129.48" " 129.48" " 125.82" " 126.91" " 29100000" "0" " 128.9000" " 129.632" " 129.7471"
1981-02-03 "$SPX" " 126.91" " 128.92" " 125.89" " 128.46" " 33400000" "0" " 128.3067" " 129.100" " 129.4943"
1981-02-04 "$SPX" " 128.46" " 129.71" " 127.29" " 128.59" " 32600000" "0" " 127.9867" " 128.750" " 129.3157"
1981-02-05 "$SPX" " 128.59" " 130.49" " 127.99" " 129.63" " 33900000" "0" " 128.8933" " 128.628" " 129.1029"
roll.mean.n10 roll.mean.n12 roll.mean.n14 roll.mean.n17 roll.mean.n20 roll.sd.n3 roll.sd.n5 roll.sd.n7 roll.sd.n10
1981-01-29 " 131.418" " 131.8225" " 132.0486" " 132.3706" " 133.1365" " 0.48179878" " 0.4689130" " 0.5449115" " 1.7603142"
1981-01-30 " 130.896" " 131.4958" " 131.7650" " 132.0453" " 132.7970" " 0.43015730" " 0.5954159" " 0.4864105" " 1.3911236"
1981-02-02 " 130.150" " 130.8867" " 131.3093" " 131.6835" " 132.2440" " 1.75758738" " 1.6202694" " 1.3422092" " 1.3195694"
1981-02-03 " 129.831" " 130.3608" " 130.9514" " 131.3882" " 131.7610" " 1.32666306" " 1.4357411" " 1.4014972" " 1.3021291"
1981-02-04 " 129.554" " 129.8792" " 130.5493" " 131.0982" " 131.4365" " 0.93468608" " 1.2604983" " 1.4294622" " 1.2335503"
1981-02-05 " 129.491" " 129.7108" " 130.1821" " 130.8829" " 131.2650" " 0.64127139" " 1.0994631" " 1.2101207" " 1.2093379"
roll.sd.n12 roll.sd.n14 roll.sd.n17 roll.sd.n20 roll.z.score.n3 roll.z.score.n5 roll.z.score.n7 roll.z.score.n10
1981-01-29 " 1.8583186" " 1.8039775" " 1.8166778" " 2.5260546" "-6.780009e-01" "-2.430984e-01" "-4.482851e-01" "-0.6691924632"
1981-01-30 " 1.8867068" " 1.8658535" " 1.7961940" " 2.5291296" "-1.146875e+00" "-1.121908e+00" "-1.389185e+00" "-0.9675624607"
1981-02-02 " 2.0957110" " 2.2117916" " 2.1612750" " 2.5475899" "-1.132236e+00" "-1.679969e+00" "-2.113787e+00" "-2.4553457398"
1981-02-03 " 1.8040970" " 2.2404173" " 2.2419181" " 2.2761866" " 1.155832e-01" "-4.457586e-01" "-7.379812e-01" "-1.0528840651"
1981-02-04 " 1.3511217" " 2.1100825" " 2.2676411" " 2.2404529" " 6.454894e-01" "-1.269371e-01" "-5.076854e-01" "-0.7814849363"
1981-02-05 " 1.2309297" " 1.7326141" " 2.2197845" " 2.2409161" " 1.148754e+00" " 9.113521e-01" " 4.356094e-01" " 0.1149372685"
roll.z.score.n12 roll.z.score.n14 roll.z.score.n17 roll.z.score.n20 ocret clret sig_long long_exit_eq
1981-01-29 "-8.515704e-01" "-1.002540e+00" "-1.1727875453" "-1.146645e+00" "-7.671475e-02" "-7.671475e-02" "1" "-7.671475e-02"
1981-01-30 "-1.031338e+00" "-1.187124e+00" "-1.3892112666" "-1.283841e+00" "-5.297988e-01" "-5.297988e-01" "1" "-5.297988e-01"
1981-02-02 "-1.897526e+00" "-1.989014e+00" "-2.2086630159" "-2.093743e+00" "-1.984863e+00" "-2.037823e+00" "1" "-2.037823e+00"
1981-02-03 "-1.053615e+00" "-1.112033e+00" "-1.3061247727" "-1.450228e+00" " 1.221346e+00" " 1.221346e+00" "1" " 1.221346e+00"
1981-02-04 "-9.541455e-01" "-9.285351e-01" "-1.1060986231" "-1.270502e+00" " 1.011910e-01" " 1.011910e-01" "1" " 1.011910e-01"
1981-02-05 "-6.566920e-02" "-3.186762e-01" "-0.5644427193" "-7.296121e-01" " 8.087721e-01" " 8.087721e-01" "1" " 8.087721e-01"
cum_eq_long_exit
1981-01-29 " -1.06592882"
1981-01-30 " -1.59572761"
1981-02-02 " -3.63355084"
1981-02-03 " -2.41220501"
1981-02-04 " -2.31101398"
1981-02-05 " -1.50224192"
我到底错过了什么？？
编辑**
这是我的 new.df 在转换为 xts 之前的格式....
> str(new.df)
'data.frame': 9203 obs. of 37 variables:
$ Date : Date, format: "1981-01-02" "1981-01-05" "1981-01-06" "1981-01-07" ...
$ Ticker : chr "$SPX" "$SPX" "$SPX" "$SPX" ...
$ Open : num 136 136 138 136 135 ...
$ High : num 137 139 140 136 136 ...
$ Low : num 135 136 136 132 132 ...
$ Close : num 136 138 138 135 133 ...
$ Volume : num 19400000 41200000 49000000 58800000 39400000 35900000 34600000 28500000 28900000 27100000 ...
$ Open.Interest : int 0 0 0 0 0 0 0 0 0 0 ...
$ roll.mean.n3 : num 0 0 137 137 135 ...
$ roll.mean.n5 : num 0 0 0 0 136 ...
$ roll.mean.n7 : num 0 0 0 0 0 ...
$ roll.mean.n10 : num 0 0 0 0 0 ...
$ roll.mean.n12 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.mean.n14 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.mean.n17 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.mean.n20 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.sd.n3 : num 0 0 0.987 1.713 2.547 ...
$ roll.sd.n5 : num 0 0 0 0 2.12 ...
$ roll.sd.n7 : num 0 0 0 0 0 ...
$ roll.sd.n10 : num 0 0 0 0 0 ...
$ roll.sd.n12 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.sd.n14 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.sd.n17 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.sd.n20 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.z.score.n3 : num 0 0 0.652 -1.154 -0.927 ...
$ roll.z.score.n5 : num 0 0 0 0 -1.44 ...
$ roll.z.score.n7 : num 0 0 0 0 0 ...
$ roll.z.score.n10: num 0 0 0 0 0 ...
$ roll.z.score.n12: num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.z.score.n14: num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.z.score.n17: num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.z.score.n20: num 0 0 0 0 0 0 0 0 0 0 ...
$ ocret : num 0.427 1.196 0.109 -0.691 -1.495 ...
$ clret : num 0 1.196 0.109 -2.201 -1.495 ...
$ sig_long : num [1:9203, 1] 0 0 0 0 0 0 0 0 0 0 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : NULL
.. ..$ : chr "Lag.1"
$ long_exit_eq : num 0 0 0 0 0 0 0 0 0 0 ...
$ cum_eq_long_exit: num 0 0 0 0 0 0 0 0 0 0 ...
您收到不支持的类型错误，因为您的数据是字符。结构调用 (str) 将其显示为 Data: chr ... 您也可以通过查看输出来判断，数字周围的引号表示它们是字符。 charts.PerformanceSummary 函数需要数值。我不确定您的数据框是什么样的，但要么尝试将数据框值转换为数值，请参阅 as.numeric，要么将您的数据作为数值拉入并避免使用数据框。 Quantmod 中的 getSymbols 函数可以将财务数据作为 xts 拉入。
https://stat.ethz.ch/R-manual/R-devel/library/base/html/numeric.html http://www.quantmod.com/documentation/getSymbols.html
我找到了解决方案。将整个数据帧转换为 XTS 时。即使数据框的原始格式是正确的，即 date = date 和 numbers = num。 XTS 转换将导致格式更改。因此，为什么数字会更改为字符，从而导致 PortfolioAnalytics 包出现错误。
这里的答案是将特定列从数据框中拉出。将其转换为 XTS，同时在此过程中保持正确的格式。
下面从数据帧转换为 XTS 时保留数字格式：
xts = xts(new.df$long_exit_eq, order.by=as.Date(new.df$Date, format="%m/%d/%Y"))
如果您想从数据框中提取两列。假设它是你的信号 return 列并买入并持有 return 列。
可以像下面这样从数据框中拉出它们作为 xts，然后将它们绑定在一起。
# Pull select columns from data frame to make XTS whilst retaining formats
xts = xts(new.df$long_exit_eq, order.by=as.Date(new.df$Date, format="%m/%d/%Y"))
xts1 = xts(new.df$clret, order.by=as.Date(new.df$Date, format="%m/%d/%Y"))
# Join XTS together
compare <- cbind(xts,xts1)
我正在使用包 tidyverse 和 tidyquant 将数据框转换为 XTS 对象。
library(tidyverse)
library(tidyquant)
xts <- na.omit(as.data.frame(new.df))
xts <- as_xts(xts, Date)
好像成功了：
> str(xts)
An ‘xts’ object on 1981-01-29/2017-06-28 containing:
Data: chr [1:9184, 1:36] "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" "$SPX" ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr [1:36] "Ticker" "Open" "High" "Low" ...
Indexed by objects of class: [Date] TZ: UTC
xts Attributes:
NULL
打印的 xts 对象
接下来我希望将其加载到性能分析包中。我提取要加载到包中的列。
data=xts[,35]
然后 str(data) 再次显示一个 xts 对象。
> str(data)
An ‘xts’ object on 1981-01-29/2017-06-28 containing:
Data: chr [1:9184, 1] "-7.671475e-02" "-5.297988e-01" "-2.037823e+00" " 1.221346e+00" " 1.011910e-01" " 8.087721e-01" " 7.482913e-01" ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr "long_exit_eq"
Indexed by objects of class: [Date] TZ: UTC
xts Attributes:
NULL
这仍然是一个带有日期和列的 xts 对象，以及 head(data):
> head(data)
long_exit_eq
1981-01-29 "-7.671475e-02"
1981-01-30 "-5.297988e-01"
1981-02-02 "-2.037823e+00"
1981-02-03 " 1.221346e+00"
1981-02-04 " 1.011910e-01"
1981-02-05 " 8.087721e-01"
投资组合分析：
> # create table of downside risk estimates
> table.DownsideRisk(data)
Error in MAR - r : non-numeric argument to binary operator
In addition: Warning message:
In mean.default(coredata(x), ...) :
argument is not numeric or logical: returning NA
> # chart equity curve, daily performance, and drawdowns
> charts.PerformanceSummary(data)
Error in na.omit.xts(x) : unsupported type
上面的错误我不确定为什么会发生。 na.omit.xts...数据集中没有 na 值。我在开始使用数据框时删除了它们：xts <- na.omit(as.data.frame(new.df))
xts 对象的数据框似乎在工作，拉动我想在投资组合分析中使用的列似乎在工作。
只是为了展示我的 xts 对象的头部：
> head(xts)
Ticker Open High Low Close Volume Open.Interest roll.mean.n3 roll.mean.n5 roll.mean.n7
1981-01-29 "$SPX" " 130.34" " 131.78" " 128.97" " 130.24" " 26900000" "0" " 130.5667" " 130.354" " 130.4843"
1981-01-30 "$SPX" " 130.24" " 131.65" " 128.61" " 129.55" " 29100000" "0" " 130.0433" " 130.218" " 130.2257"
1981-02-02 "$SPX" " 129.48" " 129.48" " 125.82" " 126.91" " 29100000" "0" " 128.9000" " 129.632" " 129.7471"
1981-02-03 "$SPX" " 126.91" " 128.92" " 125.89" " 128.46" " 33400000" "0" " 128.3067" " 129.100" " 129.4943"
1981-02-04 "$SPX" " 128.46" " 129.71" " 127.29" " 128.59" " 32600000" "0" " 127.9867" " 128.750" " 129.3157"
1981-02-05 "$SPX" " 128.59" " 130.49" " 127.99" " 129.63" " 33900000" "0" " 128.8933" " 128.628" " 129.1029"
roll.mean.n10 roll.mean.n12 roll.mean.n14 roll.mean.n17 roll.mean.n20 roll.sd.n3 roll.sd.n5 roll.sd.n7 roll.sd.n10
1981-01-29 " 131.418" " 131.8225" " 132.0486" " 132.3706" " 133.1365" " 0.48179878" " 0.4689130" " 0.5449115" " 1.7603142"
1981-01-30 " 130.896" " 131.4958" " 131.7650" " 132.0453" " 132.7970" " 0.43015730" " 0.5954159" " 0.4864105" " 1.3911236"
1981-02-02 " 130.150" " 130.8867" " 131.3093" " 131.6835" " 132.2440" " 1.75758738" " 1.6202694" " 1.3422092" " 1.3195694"
1981-02-03 " 129.831" " 130.3608" " 130.9514" " 131.3882" " 131.7610" " 1.32666306" " 1.4357411" " 1.4014972" " 1.3021291"
1981-02-04 " 129.554" " 129.8792" " 130.5493" " 131.0982" " 131.4365" " 0.93468608" " 1.2604983" " 1.4294622" " 1.2335503"
1981-02-05 " 129.491" " 129.7108" " 130.1821" " 130.8829" " 131.2650" " 0.64127139" " 1.0994631" " 1.2101207" " 1.2093379"
roll.sd.n12 roll.sd.n14 roll.sd.n17 roll.sd.n20 roll.z.score.n3 roll.z.score.n5 roll.z.score.n7 roll.z.score.n10
1981-01-29 " 1.8583186" " 1.8039775" " 1.8166778" " 2.5260546" "-6.780009e-01" "-2.430984e-01" "-4.482851e-01" "-0.6691924632"
1981-01-30 " 1.8867068" " 1.8658535" " 1.7961940" " 2.5291296" "-1.146875e+00" "-1.121908e+00" "-1.389185e+00" "-0.9675624607"
1981-02-02 " 2.0957110" " 2.2117916" " 2.1612750" " 2.5475899" "-1.132236e+00" "-1.679969e+00" "-2.113787e+00" "-2.4553457398"
1981-02-03 " 1.8040970" " 2.2404173" " 2.2419181" " 2.2761866" " 1.155832e-01" "-4.457586e-01" "-7.379812e-01" "-1.0528840651"
1981-02-04 " 1.3511217" " 2.1100825" " 2.2676411" " 2.2404529" " 6.454894e-01" "-1.269371e-01" "-5.076854e-01" "-0.7814849363"
1981-02-05 " 1.2309297" " 1.7326141" " 2.2197845" " 2.2409161" " 1.148754e+00" " 9.113521e-01" " 4.356094e-01" " 0.1149372685"
roll.z.score.n12 roll.z.score.n14 roll.z.score.n17 roll.z.score.n20 ocret clret sig_long long_exit_eq
1981-01-29 "-8.515704e-01" "-1.002540e+00" "-1.1727875453" "-1.146645e+00" "-7.671475e-02" "-7.671475e-02" "1" "-7.671475e-02"
1981-01-30 "-1.031338e+00" "-1.187124e+00" "-1.3892112666" "-1.283841e+00" "-5.297988e-01" "-5.297988e-01" "1" "-5.297988e-01"
1981-02-02 "-1.897526e+00" "-1.989014e+00" "-2.2086630159" "-2.093743e+00" "-1.984863e+00" "-2.037823e+00" "1" "-2.037823e+00"
1981-02-03 "-1.053615e+00" "-1.112033e+00" "-1.3061247727" "-1.450228e+00" " 1.221346e+00" " 1.221346e+00" "1" " 1.221346e+00"
1981-02-04 "-9.541455e-01" "-9.285351e-01" "-1.1060986231" "-1.270502e+00" " 1.011910e-01" " 1.011910e-01" "1" " 1.011910e-01"
1981-02-05 "-6.566920e-02" "-3.186762e-01" "-0.5644427193" "-7.296121e-01" " 8.087721e-01" " 8.087721e-01" "1" " 8.087721e-01"
cum_eq_long_exit
1981-01-29 " -1.06592882"
1981-01-30 " -1.59572761"
1981-02-02 " -3.63355084"
1981-02-03 " -2.41220501"
1981-02-04 " -2.31101398"
1981-02-05 " -1.50224192"
我到底错过了什么？？
编辑**
这是我的 new.df 在转换为 xts 之前的格式....
> str(new.df)
'data.frame': 9203 obs. of 37 variables:
$ Date : Date, format: "1981-01-02" "1981-01-05" "1981-01-06" "1981-01-07" ...
$ Ticker : chr "$SPX" "$SPX" "$SPX" "$SPX" ...
$ Open : num 136 136 138 136 135 ...
$ High : num 137 139 140 136 136 ...
$ Low : num 135 136 136 132 132 ...
$ Close : num 136 138 138 135 133 ...
$ Volume : num 19400000 41200000 49000000 58800000 39400000 35900000 34600000 28500000 28900000 27100000 ...
$ Open.Interest : int 0 0 0 0 0 0 0 0 0 0 ...
$ roll.mean.n3 : num 0 0 137 137 135 ...
$ roll.mean.n5 : num 0 0 0 0 136 ...
$ roll.mean.n7 : num 0 0 0 0 0 ...
$ roll.mean.n10 : num 0 0 0 0 0 ...
$ roll.mean.n12 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.mean.n14 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.mean.n17 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.mean.n20 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.sd.n3 : num 0 0 0.987 1.713 2.547 ...
$ roll.sd.n5 : num 0 0 0 0 2.12 ...
$ roll.sd.n7 : num 0 0 0 0 0 ...
$ roll.sd.n10 : num 0 0 0 0 0 ...
$ roll.sd.n12 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.sd.n14 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.sd.n17 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.sd.n20 : num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.z.score.n3 : num 0 0 0.652 -1.154 -0.927 ...
$ roll.z.score.n5 : num 0 0 0 0 -1.44 ...
$ roll.z.score.n7 : num 0 0 0 0 0 ...
$ roll.z.score.n10: num 0 0 0 0 0 ...
$ roll.z.score.n12: num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.z.score.n14: num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.z.score.n17: num 0 0 0 0 0 0 0 0 0 0 ...
$ roll.z.score.n20: num 0 0 0 0 0 0 0 0 0 0 ...
$ ocret : num 0.427 1.196 0.109 -0.691 -1.495 ...
$ clret : num 0 1.196 0.109 -2.201 -1.495 ...
$ sig_long : num [1:9203, 1] 0 0 0 0 0 0 0 0 0 0 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : NULL
.. ..$ : chr "Lag.1"
$ long_exit_eq : num 0 0 0 0 0 0 0 0 0 0 ...
$ cum_eq_long_exit: num 0 0 0 0 0 0 0 0 0 0 ...
您收到不支持的类型错误，因为您的数据是字符。结构调用 (str) 将其显示为 Data: chr ... 您也可以通过查看输出来判断，数字周围的引号表示它们是字符。 charts.PerformanceSummary 函数需要数值。我不确定您的数据框是什么样的，但要么尝试将数据框值转换为数值，请参阅 as.numeric，要么将您的数据作为数值拉入并避免使用数据框。 Quantmod 中的 getSymbols 函数可以将财务数据作为 xts 拉入。
https://stat.ethz.ch/R-manual/R-devel/library/base/html/numeric.html http://www.quantmod.com/documentation/getSymbols.html
我找到了解决方案。将整个数据帧转换为 XTS 时。即使数据框的原始格式是正确的，即 date = date 和 numbers = num。 XTS 转换将导致格式更改。因此，为什么数字会更改为字符，从而导致 PortfolioAnalytics 包出现错误。
这里的答案是将特定列从数据框中拉出。将其转换为 XTS，同时在此过程中保持正确的格式。
下面从数据帧转换为 XTS 时保留数字格式：
xts = xts(new.df$long_exit_eq, order.by=as.Date(new.df$Date, format="%m/%d/%Y"))
如果您想从数据框中提取两列。假设它是你的信号 return 列并买入并持有 return 列。
可以像下面这样从数据框中拉出它们作为 xts，然后将它们绑定在一起。
# Pull select columns from data frame to make XTS whilst retaining formats
xts = xts(new.df$long_exit_eq, order.by=as.Date(new.df$Date, format="%m/%d/%Y"))
xts1 = xts(new.df$clret, order.by=as.Date(new.df$Date, format="%m/%d/%Y"))
# Join XTS together
compare <- cbind(xts,xts1)