如何找到R中向量值的回报率？
为了找到矢量值的收益率，我们可以使用收益率公式。例如，如果我们有一个称为x的向量，则可以使用语法diff(x)/x[-length(x)]计算返回率。输出将采用十进制格式，如果要将其转换为百分比，则需要将输出乘以100，我们也可以在公式中输入与（diff(x)/x[-length(x)]）*100相同的值。
示例
x1<-rpois(100,80) x1输出结果
[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输出结果
[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
x2<-rpois(100,50) x2输出结果
[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输出结果
[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
x3<-sample(1:100,100,replace=TRUE) x3输出结果
[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输出结果
[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
x4<-sample(1:10,100,replace=TRUE) x4输出结果
[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输出结果
[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