我正在使用R来了解资本资产定价模型。我正在输入来自雅虎财务的历史数据，默认情况下，按日期设置为升序。我正在使用订单功能，但它似乎没有工作。这是我的代码：
#This is the pre-processing for historical stock prices against returns of another stock(usually NASDAQ)
frmkt.returns <- function (file1, file2){
#input downloaded files from excel and convert to workable format
file.1 <- read.table(file1,header = TRUE, sep = ",")[,c("Date","Adj.Close")]
file.2 <- read.table(file2,header = TRUE, sep = ",")[,c("Date","Adj.Close")]
file.1 <- merge(file.1, file.2, by = "Date")
file.1[,c("Date")] <- as.Date(file.1[,c("Date")])
file.1 <- file.1[rev(order(file.1$Date)),]
#Perform operations to get rates of returns on stocks
file.1[-nrow(file.1),-1] <- file.1[-nrow(file.1),-1]/ file.1[-1,-1]-1
file.1 <- file.1[-nrow(file.1),]
#Input 5 year Treasurey Bond as referrence to returns of free market
#Convert to workable format and merge with Stock returns object
tbonds <- read.table("/Users/bhumphreys/Downloads/fiveYR_treasurey.csv", header = TRUE, sep = ",")[,c("Date","Adj.Close")]
names(tbonds)[2] <- "tbonds.returns"
tbonds[,c("Date")] <- as.Date(tbonds[,c("Date")])
file.1 <- merge(file.1, tbonds, by= "Date")
file.1$tbonds.returns <- file.1$tbonds.returns/100
names(file.1)[2:3] <- c("stock.returns", "nasdaq.returns")
file.1[,c("stock.returns","nasdaq.returns")] <- file.1[,c("stock.returns", "nasdaq.returns")]- file.1[,"tbonds.returns"]
return(file.1)
}
这是我一直得到的输出：
frmkt.returns(xomFile,snpFile)
Date stock.returns nasdaq.returns tbonds.returns
1 2012-02-01 3.136297e-02 2.957670e-02 0.00725
2 2012-03-01 -6.330922e-03 2.877178e-02 0.00899
3 2012-04-02 -1.470687e-02 2.250261e-02 0.01021
4 2012-05-01 -9.137423e-02 -1.766622e-02 0.00835
5 2012-06-01 8.206149e-02 -9.709351e-02 0.00620
6 2012-07-02 8.268583e-03 6.175071e-02 0.00669
7 2012-08-01 5.283751e-03 7.540821e-04 0.00643
8 2012-09-04 4.131724e-02 1.531680e-02 0.00622
9 2012-10-01 -9.261786e-03 2.195070e-02 0.00620
10 2012-11-01 -3.446171e-02 -1.897965e-02 0.00728
11 2012-12-03 -2.431944e-02 -1.897973e-02 0.00628
12 2013-01-02 3.188471e-02 2.994473e-02 0.00763
13 2013-02-01 -7.079322e-03 2.593275e-02 0.00877
14 2013-03-01 -1.226536e-03 -4.155914e-03 0.00748
15 2013-04-01 -2.000930e-02 2.138199e-02 0.00758
16 2013-05-01 1.711385e-02 6.591916e-03 0.00655
17 2013-06-03 -1.164647e-02 2.614938e-02 0.01032
18 2013-07-01 2.367151e-02 -2.948047e-02 0.01396
19 2013-08-01 -7.886746e-02 4.191165e-02 0.01500
20 2013-09-03 -2.956996e-02 -5.603171e-02 0.01672
21 2013-10-01 2.738862e-02 1.946154e-02 0.01422
22 2013-11-01 3.643796e-02 2.558564e-02 0.01373
23 2013-12-02 6.837443e-02 8.076057e-03 0.01421
24 2014-01-02 -1.064880e-01 9.801299e-05 0.01716
25 2014-02-03 3.762477e-02 -6.354628e-02 0.01437
26 2014-03-03 3.638218e-05 4.500339e-02 0.01461
27 2014-04-01 3.102342e-02 4.157888e-03 0.01740
28 2014-05-01 -2.822288e-02 -1.750584e-02 0.01653
29 2014-06-02 -1.446795e-02 5.959814e-03 0.01596
30 2014-07-01 -3.384238e-02 8.557262e-03 0.01656
31 2014-08-01 -4.471628e-03 -4.114060e-02 0.01673
32 2014-09-02 -7.125370e-02 2.320441e-02 0.01686
33 2014-10-01 1.145283e-02 -4.485805e-02 0.01683
34 2014-11-03 -7.337974e-02 2.047610e-02 0.01634
35 2014-12-01 5.885659e-03 2.447699e-03 0.01521
36 2015-01-02 -7.058784e-02 -1.386193e-02 0.01618
37 2015-02-02 8.585158e-03 -2.999691e-02 0.01185
38 2015-03-02 -5.576196e-02 3.199194e-02 0.01578
39 2015-04-01 1.462245e-02 -4.051051e-02 0.01326
40 2015-05-01 -3.184140e-02 8.525832e-03 0.01507
41 2015-06-01 -3.903412e-02 -1.392837e-02 0.01556
42 2015-07-01 -6.497674e-02 -3.326737e-02 0.01702
43 2015-08-03 -5.637230e-02 -5.214170e-03 0.01514
44 2015-09-01 -2.686886e-02 -1.028315e-01 0.01504
45 2015-10-01 9.914473e-02 -8.490621e-03 0.01370
46 2015-11-02 -2.008928e-02 7.804346e-02 0.01564
47 2015-12-01 -6.139235e-02 -1.663497e-02 0.01596
48 2016-01-04 -1.863287e-02 -6.013920e-02 0.01735
49 2016-02-01 2.505843e-02 -5.023954e-02 0.01383
>
我为冗长的代码道歉，但正如您所看到的，数据没有从默认值更改。我也试过了
file.1 <- file.1[order(file.1$Date, decreasing = TRUE),]
请帮我扭转这些数据。
答案 0 :(得分：0)
使用lubridate包更改日期格式，然后订购。
#Get your data
df2 <- read.table(text =
' Date stock.returns nasdaq.returns tbonds.returns
1 2012-02-01 3.136297e-02 2.957670e-02 0.00725
2 2012-03-01 -6.330922e-03 2.877178e-02 0.00899
3 2012-04-02 -1.470687e-02 2.250261e-02 0.01021
4 2012-05-01 -9.137423e-02 -1.766622e-02 0.00835
5 2012-06-01 8.206149e-02 -9.709351e-02 0.00620
6 2012-07-02 8.268583e-03 6.175071e-02 0.00669
7 2012-08-01 5.283751e-03 7.540821e-04 0.00643
8 2012-09-04 4.131724e-02 1.531680e-02 0.00622
9 2012-10-01 -9.261786e-03 2.195070e-02 0.00620
10 2012-11-01 -3.446171e-02 -1.897965e-02 0.00728
11 2012-12-03 -2.431944e-02 -1.897973e-02 0.00628
12 2013-01-02 3.188471e-02 2.994473e-02 0.00763
13 2013-02-01 -7.079322e-03 2.593275e-02 0.00877
14 2013-03-01 -1.226536e-03 -4.155914e-03 0.00748
15 2013-04-01 -2.000930e-02 2.138199e-02 0.00758
16 2013-05-01 1.711385e-02 6.591916e-03 0.00655
17 2013-06-03 -1.164647e-02 2.614938e-02 0.01032
18 2013-07-01 2.367151e-02 -2.948047e-02 0.01396
19 2013-08-01 -7.886746e-02 4.191165e-02 0.01500
20 2013-09-03 -2.956996e-02 -5.603171e-02 0.01672
21 2013-10-01 2.738862e-02 1.946154e-02 0.01422
22 2013-11-01 3.643796e-02 2.558564e-02 0.01373
23 2013-12-02 6.837443e-02 8.076057e-03 0.01421
24 2014-01-02 -1.064880e-01 9.801299e-05 0.01716
25 2014-02-03 3.762477e-02 -6.354628e-02 0.01437
26 2014-03-03 3.638218e-05 4.500339e-02 0.01461
27 2014-04-01 3.102342e-02 4.157888e-03 0.01740
28 2014-05-01 -2.822288e-02 -1.750584e-02 0.01653
29 2014-06-02 -1.446795e-02 5.959814e-03 0.01596
30 2014-07-01 -3.384238e-02 8.557262e-03 0.01656
31 2014-08-01 -4.471628e-03 -4.114060e-02 0.01673
32 2014-09-02 -7.125370e-02 2.320441e-02 0.01686
33 2014-10-01 1.145283e-02 -4.485805e-02 0.01683
34 2014-11-03 -7.337974e-02 2.047610e-02 0.01634
35 2014-12-01 5.885659e-03 2.447699e-03 0.01521
36 2015-01-02 -7.058784e-02 -1.386193e-02 0.01618
37 2015-02-02 8.585158e-03 -2.999691e-02 0.01185
38 2015-03-02 -5.576196e-02 3.199194e-02 0.01578
39 2015-04-01 1.462245e-02 -4.051051e-02 0.01326
40 2015-05-01 -3.184140e-02 8.525832e-03 0.01507
41 2015-06-01 -3.903412e-02 -1.392837e-02 0.01556
42 2015-07-01 -6.497674e-02 -3.326737e-02 0.01702
43 2015-08-03 -5.637230e-02 -5.214170e-03 0.01514
44 2015-09-01 -2.686886e-02 -1.028315e-01 0.01504
45 2015-10-01 9.914473e-02 -8.490621e-03 0.01370
46 2015-11-02 -2.008928e-02 7.804346e-02 0.01564
47 2015-12-01 -6.139235e-02 -1.663497e-02 0.01596
48 2016-01-04 -1.863287e-02 -6.013920e-02 0.01735
49 2016-02-01 2.505843e-02 -5.023954e-02 0.01383', header = TRUE)
# Convert the date to required format I am assuming it is ymd format
df2 <- df2[order(df2$Date, decreasing = TRUE), , drop = FALSE]
# order the data according to date in descending order
df2 <- df2[order(df2$Date, decreasing = TRUE), , drop = FALSE]
答案 1 :(得分：0)
目前，您通过降序日期在订单tbonds后第二次与file.1合并。默认情况下，merge按by列排序：
考虑在第二次合并时不指定排序：
file.1 <- merge(file.1, tbonds, by= "Date", sort=FALSE)
或者，在所有合并后移动降序：
file.1 <- merge(file.1, tbonds, by= "Date")
file.1 <- file.1[order(file.1$Date, decreasing = TRUE),]