前篇IRR級距 (躉繳) ,
以六年為例,
此篇重新寫完整,
表格的左上角為本金100
縱軸為年,最多到10年
橫軸為年化複利或IRR
表格中的數字當然就是
年末本利和或保單的解約金:
IRR=1.3%~1.7%
| 100 | 1.30% | 1.40% | 1.50% | 1.60% | 1.70% |
| 1 | 101.3000 | 101.4000 | 101.5000 | 101.6000 | 101.7000 |
| 2 | 102.6169 | 102.8196 | 103.0225 | 103.2256 | 103.4289 |
| 3 | 103.9509 | 104.2591 | 104.5678 | 104.8772 | 105.1872 |
| 4 | 105.3023 | 105.7187 | 106.1364 | 106.5552 | 106.9754 |
| 5 | 106.6712 | 107.1988 | 107.7284 | 108.2601 | 108.7940 |
| 6 | 108.0579 | 108.6995 | 109.3443 | 109.9923 | 110.6435 |
| 7 | 109.4627 | 110.2213 | 110.9845 | 111.7522 | 112.5244 |
| 8 | 110.8857 | 111.7644 | 112.6493 | 113.5402 | 114.4373 |
| 9 | 112.3272 | 113.3291 | 114.3390 | 115.3568 | 116.3827 |
| 10 | 113.7875 | 114.9157 | 116.0541 | 117.2026 | 118.3612 |
IRR=1.8%~2.6%
| 100 | 1.80% | 2.00% | 2.20% | 2.40% | 2.60% |
| 1 | 101.8000 | 102.0000 | 102.2000 | 102.4000 | 102.6000 |
| 2 | 103.6324 | 104.0400 | 104.4484 | 104.8576 | 105.2676 |
| 3 | 105.4978 | 106.1208 | 106.7463 | 107.3742 | 108.0046 |
| 4 | 107.3967 | 108.2432 | 109.0947 | 109.9512 | 110.8127 |
| 5 | 109.3299 | 110.4081 | 111.4948 | 112.5900 | 113.6938 |
| 6 | 111.2978 | 112.6162 | 113.9477 | 115.2922 | 116.6498 |
| 7 | 113.3012 | 114.8686 | 116.4545 | 118.0592 | 119.6827 |
| 8 | 115.3406 | 117.1659 | 119.0165 | 120.8926 | 122.7945 |
| 9 | 117.4167 | 119.5093 | 121.6349 | 123.7940 | 125.9871 |
| 10 | 119.5302 | 121.8994 | 124.3108 | 126.7651 | 129.2628 |
| 100 | 2.80% | 3.00% | 3.20% | 3.30% | 3.40% |
| 1 | 102.8000 | 103.0000 | 103.2000 | 103.3000 | 103.4000 |
| 2 | 105.6784 | 106.0900 | 106.5024 | 106.7089 | 106.9156 |
| 3 | 108.6374 | 109.2727 | 109.9105 | 110.2303 | 110.5507 |
| 4 | 111.6792 | 112.5509 | 113.4276 | 113.8679 | 114.3095 |
| 5 | 114.8063 | 115.9274 | 117.0573 | 117.6255 | 118.1960 |
| 6 | 118.0208 | 119.4052 | 120.8031 | 121.5072 | 122.2146 |
| 7 | 121.3254 | 122.9874 | 124.6688 | 125.5169 | 126.3699 |
| 8 | 124.7225 | 126.6770 | 128.6582 | 129.6590 | 130.6665 |
| 9 | 128.2148 | 130.4773 | 132.7753 | 133.9377 | 135.1092 |
| 10 | 131.8048 | 134.3916 | 137.0241 | 138.3577 | 139.7029 |
![Python: 如何逐row讀取DataFrame的資料?使用 pandas 的 df.itertuples() 方法(namedtuple讀取每一列); df.iterrows() 用Tuple[index, pd.Series] 讀取每一列](https://i2.wp.com/savingking.com.tw/wp-content/uploads/2024/10/20241023105826_0_bab0ff.png?quality=90&zoom=2&ssl=1&resize=350%2C233 "Python: 如何逐row讀取DataFrame的資料?使用 pandas 的 df.itertuples() 方法(namedtuple讀取每一列); df.iterrows() 用Tuple[index, pd.Series] 讀取每一列")
近期留言