我有一个包含每月库存 returns 的时间序列数据框,我想为每个月提取并创建一个向量 returns
I have a time series dataframe with monthly stock returns, and i want to extract and create a vector for each months returns
我有一个包含每月股票 returns 的时间序列数据框,我想为每个月提取并创建一个向量 returns。
这是数据框的样子。 (MKT 向量包含每月 returns)
这就是我想要完成的(最后):
通过运行输入:
结构(c(0.0286195, 0.03618317, -0.01363269, 0.02977401, 0.04461314,
0.0015209, -0.03207303, -0.0079275, 0.01882991, 0.00584478, 0.02372219,
0.03299206, -0.017908, 0.02540426, 0.04163062, -0.00317315, -0.03732322,
-0.0109474, 0.0147047, 0.00087712, 0.00608527826274047, 0.00495046849033236,
0.00503506482970477, 0.00481634688889247, 0.00424210936461577,
0.00358500724272255, 0.00424210936461577, 0.00480928182207086,
0.00485872460615713, 0.00487990531586144, 1, 1, 1, 1, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0,
0, 0), .Dim = c(10L, 6L), .Dimnames = list(NULL, c("MKT", "CAP",
"RF", "dummy", "dummyJAN", "adjdummy")), index = structure(c(-36494,
-36466, -36435, -36405, -36374, -36344, -36313, -36282, -36252,
-36221), class = "日期"), class = "动物园")
请试试这个:
df=structure(c(0.0286195, 0.03618317, -0.01363269, 0.02977401, 0.04461314, 0.0015209, -0.03207303, -0.0079275, 0.01882991, 0.00584478, 0.02372219, 0.03299206, -0.017908, 0.02540426, 0.04163062, -0.00317315, -0.03732322, -0.0109474, 0.0147047, 0.00087712, 0.00608527826274047, 0.00495046849033236, 0.00503506482970477, 0.00481634688889247, 0.00424210936461577, 0.00358500724272255, 0.00424210936461577, 0.00480928182207086, 0.00485872460615713, 0.00487990531586144, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 6L), .Dimnames = list(NULL, c("MKT", "CAP", "RF", "dummy", "dummyJAN", "adjdummy")), index = structure(c(-36494, -36466, -36435, -36405, -36374, -36344, -36313, -36282, -36252, -36221), class = "Date"), class = "zoo")
library(zoo)
library(foqat)
df2=fortify.zoo(df)
df3=svri(df2, bkip = "1 day", mode = "recipes", value = "year")
df3
# month of year MKT CAP RF dummy dummyJAN adjdummy
#1 1 0.02861950 0.02372219 0.006085278 1 1 0
#2 2 0.03618317 0.03299206 0.004950468 1 0 1
#3 3 -0.01363269 -0.01790800 0.005035065 1 0 1
#4 4 0.02977401 0.02540426 0.004816347 1 0 1
#5 5 0.04461314 0.04163062 0.004242109 0 0 0
#6 6 0.00152090 -0.00317315 0.003585007 0 0 0
#7 7 -0.03207303 -0.03732322 0.004242109 0 0 0
#8 8 -0.00792750 -0.01094740 0.004809282 0 0 0
#9 9 0.01882991 0.01470470 0.004858725 0 0 0
#10 10 0.00584478 0.00087712 0.004879905 0 0 0
我有一个包含每月股票 returns 的时间序列数据框,我想为每个月提取并创建一个向量 returns。
这是数据框的样子。 (MKT 向量包含每月 returns)
这就是我想要完成的(最后):
通过运行输入:
结构(c(0.0286195, 0.03618317, -0.01363269, 0.02977401, 0.04461314, 0.0015209, -0.03207303, -0.0079275, 0.01882991, 0.00584478, 0.02372219, 0.03299206, -0.017908, 0.02540426, 0.04163062, -0.00317315, -0.03732322, -0.0109474, 0.0147047, 0.00087712, 0.00608527826274047, 0.00495046849033236, 0.00503506482970477, 0.00481634688889247, 0.00424210936461577, 0.00358500724272255, 0.00424210936461577, 0.00480928182207086, 0.00485872460615713, 0.00487990531586144, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 6L), .Dimnames = list(NULL, c("MKT", "CAP", "RF", "dummy", "dummyJAN", "adjdummy")), index = structure(c(-36494, -36466, -36435, -36405, -36374, -36344, -36313, -36282, -36252, -36221), class = "日期"), class = "动物园")
请试试这个:
df=structure(c(0.0286195, 0.03618317, -0.01363269, 0.02977401, 0.04461314, 0.0015209, -0.03207303, -0.0079275, 0.01882991, 0.00584478, 0.02372219, 0.03299206, -0.017908, 0.02540426, 0.04163062, -0.00317315, -0.03732322, -0.0109474, 0.0147047, 0.00087712, 0.00608527826274047, 0.00495046849033236, 0.00503506482970477, 0.00481634688889247, 0.00424210936461577, 0.00358500724272255, 0.00424210936461577, 0.00480928182207086, 0.00485872460615713, 0.00487990531586144, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 6L), .Dimnames = list(NULL, c("MKT", "CAP", "RF", "dummy", "dummyJAN", "adjdummy")), index = structure(c(-36494, -36466, -36435, -36405, -36374, -36344, -36313, -36282, -36252, -36221), class = "Date"), class = "zoo")
library(zoo)
library(foqat)
df2=fortify.zoo(df)
df3=svri(df2, bkip = "1 day", mode = "recipes", value = "year")
df3
# month of year MKT CAP RF dummy dummyJAN adjdummy
#1 1 0.02861950 0.02372219 0.006085278 1 1 0
#2 2 0.03618317 0.03299206 0.004950468 1 0 1
#3 3 -0.01363269 -0.01790800 0.005035065 1 0 1
#4 4 0.02977401 0.02540426 0.004816347 1 0 1
#5 5 0.04461314 0.04163062 0.004242109 0 0 0
#6 6 0.00152090 -0.00317315 0.003585007 0 0 0
#7 7 -0.03207303 -0.03732322 0.004242109 0 0 0
#8 8 -0.00792750 -0.01094740 0.004809282 0 0 0
#9 9 0.01882991 0.01470470 0.004858725 0 0 0
#10 10 0.00584478 0.00087712 0.004879905 0 0 0