如何在R中计算向量的收益率？

要计算向量的收益率，可以使用收益率公式。例如，如果我们有一个名为x的向量，则可以使用语法`diff(x)/x[-length(x)]`计算收益率。输出将为小数形式，如果要将其转换为百分比，则需要将输出乘以100，也可以在公式中直接输入`(diff(x)/x[-length(x)])*100`。

示例

 在线演示

x1<-rpois(100,80)
x1

输出

[1]  59 74 66 82 88 78 66 63 68 70 82 77 73 82 87 86 78 83
[19] 101 75 70 77 71 77 79 68 90 81 85 79 81 99 64 64 74 90
[37] 90 71 70 88 74 91 89 80 96 78 80 74 72 90 101 63 89 77
[55] 67 81 74 79 76 75 82 95 65 74 80 77 73 83 110 92 93 71
[73] 87 84 70 74 101 72 89 68 94 77 71 87 89 87 66 80 67 65
[91] 84 80 92 85 86 73 75 78 78 81

示例

RateOfReturn_x1<-diff(x1)/x1[-length(x1)]
RateOfReturn_x1

输出

[1]   0.25423729 -0.10810811  0.24242424  0.07317073 -0.11363636 -0.15384615
[7]  -0.04545455  0.07936508  0.02941176  0.17142857 -0.06097561 -0.05194805
[13]  0.12328767  0.06097561 -0.01149425 -0.09302326  0.06410256  0.21686747
[19] -0.25742574 -0.06666667  0.10000000 -0.07792208  0.08450704  0.02597403
[25] -0.13924051  0.32352941 -0.10000000  0.04938272 -0.07058824  0.02531646
[31]  0.22222222 -0.35353535  0.00000000  0.15625000  0.21621622  0.00000000
[37] -0.21111111 -0.01408451  0.25714286 -0.15909091  0.22972973 -0.02197802
[43] -0.10112360  0.20000000 -0.18750000  0.02564103 -0.07500000 -0.02702703
[49]  0.25000000  0.12222222 -0.37623762  0.41269841 -0.13483146 -0.12987013
[55]  0.20895522 -0.08641975  0.06756757 -0.03797468 -0.01315789  0.09333333
[61]  0.15853659 -0.31578947  0.13846154  0.08108108 -0.03750000 -0.05194805
[67]  0.13698630  0.32530120 -0.16363636  0.01086957 -0.23655914  0.22535211
[73] -0.03448276 -0.16666667  0.05714286  0.36486486 -0.28712871  0.23611111
[79] -0.23595506  0.38235294 -0.18085106 -0.07792208  0.22535211  0.02298851
[85] -0.02247191 -0.24137931  0.21212121 -0.16250000 -0.02985075  0.29230769
[91] -0.04761905  0.15000000 -0.07608696  0.01176471 -0.15116279  0.02739726
[97]  0.04000000  0.00000000  0.03846154

示例

 在线演示

x2<-rpois(100,50)
x2

输出

[1]  58 53 67 49 49 52 57 41 51 50 44 61 55 54 53 49 53 52 63 42 50 46 60 57 55
[26] 44 47 59 54 35 66 46 48 40 55 52 49 59 59 59 44 58 44 50 55 45 58 48 67 40
[51] 38 40 58 48 49 51 50 54 35 34 52 62 61 58 47 53 49 54 48 47 43 44 60 55 61
[76] 45 62 51 66 53 57 43 45 47 57 48 52 54 42 55 51 43 45 42 49 38 48 46 54 55

示例

RateOfReturn_x2<-diff(x2)/x2[-length(x2)]
RateOfReturn_x2

输出

[1]  -0.08620690  0.26415094 -0.26865672  0.00000000  0.06122449  0.09615385
[7]  -0.28070175  0.24390244 -0.01960784 -0.12000000  0.38636364 -0.09836066
[13] -0.01818182 -0.01851852 -0.07547170  0.08163265 -0.01886792  0.21153846
[19] -0.33333333  0.19047619 -0.08000000  0.30434783 -0.05000000 -0.03508772
[25] -0.20000000  0.06818182  0.25531915 -0.08474576 -0.35185185  0.88571429
[31] -0.30303030  0.04347826 -0.16666667  0.37500000 -0.05454545 -0.05769231
[37]  0.20408163  0.00000000  0.00000000 -0.25423729  0.31818182 -0.24137931
[43]  0.13636364  0.10000000 -0.18181818  0.28888889 -0.17241379  0.39583333
[49] -0.40298507 -0.05000000  0.05263158  0.45000000 -0.17241379  0.02083333
[55]  0.04081633 -0.01960784  0.08000000 -0.35185185 -0.02857143  0.52941176
[61]  0.19230769 -0.01612903 -0.04918033 -0.18965517  0.12765957 -0.07547170
[67]  0.10204082 -0.11111111 -0.02083333 -0.08510638  0.02325581  0.36363636
[73] -0.08333333  0.10909091 -0.26229508  0.37777778 -0.17741935  0.29411765
[79] -0.19696970  0.07547170 -0.24561404  0.04651163  0.04444444  0.21276596
[85] -0.15789474  0.08333333  0.03846154 -0.22222222  0.30952381 -0.07272727
[91] -0.15686275  0.04651163 -0.06666667  0.16666667 -0.22448980  0.26315789
[97] -0.04166667  0.17391304  0.01851852

示例

 在线演示

x3<-sample(1:100,100,replace=TRUE)
x3

输出

[1]  68 56 58 33 53 60 75 31 2 39 7 34 12 65 82 79 69 37
[19] 14 88 34 74 85 94 34 13 73 13 9 61 99 45 26 48 87 99
[37] 42 55 37 48 85 16 33 86 22 31 64 13 1 26 34 23 37 40
[55] 51 3 86 55 47 77 50 93 73 43 82 37 11 29 44 34 86 99
[73] 32 62 31 11 25 30 54 8 40 22 85 41 65 61 78 76 49 7
[91] 54 74 36 84 100 68 23 68 60 93

示例

RateOfReturn_x3<-diff(x3)/x3[-length(x3)]
RateOfReturn_x3

输出

[1]  -0.17647059  0.03571429 -0.43103448  0.60606061  0.13207547  0.25000000
[7]  -0.58666667 -0.93548387 18.50000000 -0.82051282  3.85714286 -0.64705882
[13]  4.41666667  0.26153846 -0.03658537 -0.12658228 -0.46376812 -0.62162162
[19]  5.28571429 -0.61363636  1.17647059  0.14864865  0.10588235 -0.63829787
[25] -0.61764706  4.61538462 -0.82191781 -0.30769231  5.77777778  0.62295082
[31] -0.54545455 -0.42222222  0.84615385  0.81250000  0.13793103 -0.57575758
[37]  0.30952381 -0.32727273  0.29729730  0.77083333 -0.81176471  1.06250000
[43]  1.60606061 -0.74418605  0.40909091  1.06451613 -0.79687500 -0.92307692
[49] 25.00000000  0.30769231 -0.32352941  0.60869565  0.08108108  0.27500000
[55] -0.94117647 27.66666667 -0.36046512 -0.14545455  0.63829787 -0.35064935
[61]  0.86000000 -0.21505376 -0.41095890  0.90697674 -0.54878049 -0.70270270
[67]  1.63636364  0.51724138 -0.22727273  1.52941176  0.15116279 -0.67676768
[73]  0.93750000 -0.50000000 -0.64516129  1.27272727  0.20000000  0.80000000
[79] -0.85185185  4.00000000 -0.45000000  2.86363636 -0.51764706  0.58536585
[85] -0.06153846  0.27868852 -0.02564103 -0.35526316 -0.85714286  6.71428571
[91]  0.37037037 -0.51351351  1.33333333  0.19047619 -0.32000000 -0.66176471
[97]  1.95652174 -0.11764706  0.55000000

示例

 在线演示

x4<-sample(1:10,100,replace=TRUE)
x4

输出

[1]  3 2 5 10 10 10 3 2 6 3 5 9 8 9 4 2 2 10 7 5 7 5 10 4 4
[26] 6 6 9 8 3 9 5 9 10 5 5 3 2 3 1 8 9 5 10 9 6 10 4 4 8
[51] 6 2 10 10 10 6 4 9 4 9 1 8 3 8 5 1 10 7 4 2 10 9 4 10 3
[76] 2 3 10 1 4 7 3 1 9 10 2 1 8 5 7 10 1 5 3 1 6 9 2 1 4

示例

RateOfReturn_x4<-diff(x4)/x4[-length(x4)]
RateOfReturn_x4

输出

[1]  -0.3333333  1.5000000  1.0000000  0.0000000  0.0000000 -0.7000000
[7]  -0.3333333  2.0000000 -0.5000000  0.6666667  0.8000000 -0.1111111
[13]  0.1250000 -0.5555556 -0.5000000  0.0000000  4.0000000 -0.3000000
[19] -0.2857143  0.4000000 -0.2857143  1.0000000 -0.6000000  0.0000000
[25]  0.5000000  0.0000000  0.5000000 -0.1111111 -0.6250000  2.0000000
[31] -0.4444444  0.8000000  0.1111111 -0.5000000  0.0000000 -0.4000000
[37] -0.3333333  0.5000000 -0.6666667  7.0000000  0.1250000 -0.4444444
[43]  1.0000000 -0.1000000 -0.3333333  0.6666667 -0.6000000  0.0000000
[49]  1.0000000 -0.2500000 -0.6666667  4.0000000  0.0000000  0.0000000
[55] -0.4000000 -0.3333333  1.2500000 -0.5555556  1.2500000 -0.8888889
[61]  7.0000000 -0.6250000  1.6666667 -0.3750000 -0.8000000  9.0000000
[67] -0.3000000 -0.4285714 -0.5000000  4.0000000 -0.1000000 -0.5555556
[73]  1.5000000 -0.7000000 -0.3333333  0.5000000  2.3333333 -0.9000000
[79]  3.0000000  0.7500000 -0.5714286 -0.6666667  8.0000000  0.1111111
[85] -0.8000000 -0.5000000  7.0000000 -0.3750000  0.4000000  0.4285714
[91] -0.9000000  4.0000000 -0.4000000 -0.6666667  5.0000000  0.5000000
[97] -0.7777778 -0.5000000  3.0000000

更新于：2021年2月10日

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