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tests/testthat/_snaps/simulate_single_scenario.md
In R4GoodPersonalFinances: Make Optimal Financial Decisions
simulating single scenario with event
Code
scenario$income$income_older
Output
[1] 0 0 0 0 0 0 3000 3000 3000 3000 3000 3000 3000 3000 3000
[16] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[31] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[46] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[61] 3000
simulating single scenario with event and id_on helper functions
Code
scenario$income$income_older
Output
[1] 0 0 0 0 0 0 3000 3000 3000 3000 3000 3000 3000 3000 3000
[16] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[31] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[46] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[61] 3000
benchmarking of simulating single scenario
Code
print(scenario, n = Inf, width = Inf)
Output
# A tibble: 61 x 25
scenario_id index years_left date year survival_prob members$older$age
<chr> <int> <int> <date> <int> <dbl> <dbl>
1 default 0 60 2020-07-15 2020 1 40
2 default 1 59 2021-07-15 2021 0.998 41
3 default 2 58 2022-07-15 2022 0.996 42
4 default 3 57 2023-07-15 2023 0.994 43
5 default 4 56 2024-07-15 2024 0.991 44
6 default 5 55 2025-07-15 2025 0.988 45
7 default 6 54 2026-07-15 2026 0.985 46
8 default 7 53 2027-07-15 2027 0.982 47
9 default 8 52 2028-07-15 2028 0.978 48
10 default 9 51 2029-07-15 2029 0.974 49
11 default 10 50 2030-07-15 2030 0.969 50
12 default 11 49 2031-07-15 2031 0.964 51
13 default 12 48 2032-07-15 2032 0.958 52
14 default 13 47 2033-07-15 2033 0.952 53
15 default 14 46 2034-07-15 2034 0.946 54
16 default 15 45 2035-07-15 2035 0.938 55
17 default 16 44 2036-07-15 2036 0.930 56
18 default 17 43 2037-07-15 2037 0.921 57
19 default 18 42 2038-07-15 2038 0.912 58
20 default 19 41 2039-07-15 2039 0.901 59
21 default 20 40 2040-07-15 2040 0.890 60
22 default 21 39 2041-07-15 2041 0.877 61
23 default 22 38 2042-07-15 2042 0.863 62
24 default 23 37 2043-07-15 2043 0.848 63
25 default 24 36 2044-07-15 2044 0.832 64
26 default 25 35 2045-07-15 2045 0.815 65
27 default 26 34 2046-07-15 2046 0.796 66
28 default 27 33 2047-07-15 2047 0.775 67
29 default 28 32 2048-07-15 2048 0.754 68
30 default 29 31 2049-07-15 2049 0.730 69
31 default 30 30 2050-07-15 2050 0.705 70
32 default 31 29 2051-07-15 2051 0.678 71
33 default 32 28 2052-07-15 2052 0.650 72
34 default 33 27 2053-07-15 2053 0.620 73
35 default 34 26 2054-07-15 2054 0.588 74
36 default 35 25 2055-07-15 2055 0.555 75
37 default 36 24 2056-07-15 2056 0.521 76
38 default 37 23 2057-07-15 2057 0.485 77
39 default 38 22 2058-07-15 2058 0.449 78
40 default 39 21 2059-07-15 2059 0.412 79
41 default 40 20 2060-07-15 2060 0.374 80
42 default 41 19 2061-07-15 2061 0.337 81
43 default 42 18 2062-07-15 2062 0.300 82
44 default 43 17 2063-07-15 2063 0.263 83
45 default 44 16 2064-07-15 2064 0.229 84
46 default 45 15 2065-07-15 2065 0.195 85
47 default 46 14 2066-07-15 2066 0.164 86
48 default 47 13 2067-07-15 2067 0.135 87
49 default 48 12 2068-07-15 2068 0.109 88
50 default 49 11 2069-07-15 2069 0.0866 89
51 default 50 10 2070-07-15 2070 0.0668 90
52 default 51 9 2071-07-15 2071 0.0501 91
53 default 52 8 2072-07-15 2072 0.0365 92
54 default 53 7 2073-07-15 2073 0.0257 93
55 default 54 6 2074-07-15 2074 0.0175 94
56 default 55 5 2075-07-15 2075 0.0114 95
57 default 56 4 2076-07-15 2076 0.00709 96
58 default 57 3 2077-07-15 2077 0.00420 97
59 default 58 2 2078-07-15 2078 0.00236 98
60 default 59 1 2079-07-15 2079 0.00124 99
61 default 60 0 2080-07-15 2080 0.000614 100
income$income_older total_income spending$spending1 nondiscretionary_spending
<dbl> <dbl> <dbl> <dbl>
1 0 0 72000 72000
2 0 0 72000 72000
3 0 0 72000 72000
4 0 0 72000 72000
5 0 0 72000 72000
6 0 0 72000 72000
7 3000 3000 72000 72000
8 3000 3000 72000 72000
9 3000 3000 72000 72000
10 3000 3000 72000 72000
11 3000 3000 72000 72000
12 3000 3000 72000 72000
13 3000 3000 72000 72000
14 3000 3000 72000 72000
15 3000 3000 72000 72000
16 3000 3000 72000 72000
17 3000 3000 72000 72000
18 3000 3000 72000 72000
19 3000 3000 72000 72000
20 3000 3000 72000 72000
21 3000 3000 72000 72000
22 3000 3000 72000 72000
23 3000 3000 72000 72000
24 3000 3000 72000 72000
25 3000 3000 72000 72000
26 3000 3000 72000 72000
27 3000 3000 72000 72000
28 3000 3000 72000 72000
29 3000 3000 72000 72000
30 3000 3000 72000 72000
31 3000 3000 72000 72000
32 3000 3000 72000 72000
33 3000 3000 72000 72000
34 3000 3000 72000 72000
35 3000 3000 72000 72000
36 3000 3000 72000 72000
37 3000 3000 72000 72000
38 3000 3000 72000 72000
39 3000 3000 72000 72000
40 3000 3000 72000 72000
41 3000 3000 72000 72000
42 3000 3000 72000 72000
43 3000 3000 72000 72000
44 3000 3000 72000 72000
45 3000 3000 72000 72000
46 3000 3000 72000 72000
47 3000 3000 72000 72000
48 3000 3000 72000 72000
49 3000 3000 72000 72000
50 3000 3000 72000 72000
51 3000 3000 72000 72000
52 3000 3000 72000 72000
53 3000 3000 72000 72000
54 3000 3000 72000 72000
55 3000 3000 72000 72000
56 3000 3000 72000 72000
57 3000 3000 72000 72000
58 3000 3000 72000 72000
59 3000 3000 72000 72000
60 3000 3000 72000 72000
61 3000 3000 72000 72000
human_capital liabilities portfolio$allocation $returns$GlobalStock
<dbl> <dbl> <list> <dbl>
1 65199. 1964228. <tibble [2 x 4]> 0.0449
2 67315. 1953631. <tibble [2 x 4]> 0.0449
3 69499. 1942690. <tibble [2 x 4]> 0.0449
4 71755. 1931394. <tibble [2 x 4]> 0.0449
5 74083. 1919731. <tibble [2 x 4]> 0.0449
6 76487. 1907690. <tibble [2 x 4]> 0.0449
7 78969. 1895258. <tibble [2 x 4]> 0.0449
8 78434. 1882423. <tibble [2 x 4]> 0.0449
9 77882. 1869171. <tibble [2 x 4]> 0.0449
10 77312. 1855489. <tibble [2 x 4]> 0.0449
11 76723. 1841364. <tibble [2 x 4]> 0.0449
12 76116. 1826780. <tibble [2 x 4]> 0.0449
13 75488. 1811722. <tibble [2 x 4]> 0.0449
14 74841. 1796176. <tibble [2 x 4]> 0.0449
15 74172. 1780126. <tibble [2 x 4]> 0.0449
16 73481. 1763554. <tibble [2 x 4]> 0.0449
17 72769. 1746445. <tibble [2 x 4]> 0.0449
18 72033. 1728781. <tibble [2 x 4]> 0.0449
19 71273. 1710544. <tibble [2 x 4]> 0.0449
20 70488. 1691714. <tibble [2 x 4]> 0.0449
21 69678. 1672274. <tibble [2 x 4]> 0.0449
22 68842. 1652203. <tibble [2 x 4]> 0.0449
23 67978. 1631480. <tibble [2 x 4]> 0.0449
24 67087. 1610086. <tibble [2 x 4]> 0.0449
25 66167. 1587997. <tibble [2 x 4]> 0.0449
26 65216. 1565191. <tibble [2 x 4]> 0.0449
27 64235. 1541645. <tibble [2 x 4]> 0.0449
28 63222. 1517335. <tibble [2 x 4]> 0.0449
29 62176. 1492236. <tibble [2 x 4]> 0.0449
30 61097. 1466322. <tibble [2 x 4]> 0.0449
31 59982. 1439568. <tibble [2 x 4]> 0.0449
32 58831. 1411946. <tibble [2 x 4]> 0.0449
33 57643. 1383427. <tibble [2 x 4]> 0.0449
34 56416. 1353983. <tibble [2 x 4]> 0.0449
35 55149. 1323583. <tibble [2 x 4]> 0.0449
36 53842. 1292197. <tibble [2 x 4]> 0.0449
37 52491. 1259792. <tibble [2 x 4]> 0.0449
38 51097. 1226336. <tibble [2 x 4]> 0.0449
39 49658. 1191794. <tibble [2 x 4]> 0.0449
40 48172. 1156132. <tibble [2 x 4]> 0.0449
41 46638. 1119312. <tibble [2 x 4]> 0.0449
42 45054. 1081297. <tibble [2 x 4]> 0.0449
43 43419. 1042049. <tibble [2 x 4]> 0.0449
44 41730. 1001527. <tibble [2 x 4]> 0.0449
45 39987. 959690. <tibble [2 x 4]> 0.0449
46 38187. 916496. <tibble [2 x 4]> 0.0449
47 36329. 871899. <tibble [2 x 4]> 0.0449
48 34411. 825856. <tibble [2 x 4]> 0.0449
49 32430. 778319. <tibble [2 x 4]> 0.0449
50 30385. 729239. <tibble [2 x 4]> 0.0449
51 28274. 678566. <tibble [2 x 4]> 0.0449
52 26094. 626249. <tibble [2 x 4]> 0.0449
53 23843. 572235. <tibble [2 x 4]> 0.0449
54 21519. 516467. <tibble [2 x 4]> 0.0449
55 19120. 458890. <tibble [2 x 4]> 0.0449
56 16644. 399445. <tibble [2 x 4]> 0.0449
57 14086. 338070. <tibble [2 x 4]> 0.0449
58 11446. 274704. <tibble [2 x 4]> 0.0449
59 8720. 209282. <tibble [2 x 4]> 0.0449
60 5906. 141737. <tibble [2 x 4]> 0.0449
61 3000 72000 <tibble [2 x 4]> 0.0449
$$EDOBonds financial_wealth net_worth discretionary_spending
<dbl> <dbl> <dbl> <dbl>
1 0.02 375000 -1524029. -81453.
2 0.02 393867. -1492449. -80866.
3 0.02 412806. -1460385. -80266.
4 0.02 431611. -1428028. -79662.
5 0.02 450343. -1395305. -79051.
6 0.02 469582. -1361621. -78395.
7 0.02 488886. -1327404. -77717.
8 0.02 511338. -1292651. -77015.
9 0.02 533919. -1257370. -76287.
10 0.02 556608. -1221569. -75529.
11 0.02 579379. -1185261. -74739.
12 0.02 602204. -1148459. -73915.
13 0.02 625051. -1111183. -73054.
14 0.02 647882. -1073454. -72151.
15 0.02 670655. -1035299. -71205.
16 0.02 693324. -996749. -70211.
17 0.02 715838. -957839. -69166.
18 0.02 738138. -918611. -68066.
19 0.02 760161. -879110. -66906.
20 0.02 781837. -839390. -65683.
21 0.02 803088. -799508. -64392.
22 0.02 823830. -759531. -63029.
23 0.02 843972. -719530. -61589.
24 0.02 863413. -679585. -60069.
25 0.02 882046. -639784. -58464.
26 0.02 899756. -600219. -56771.
27 0.02 916417. -560992. -54986.
28 0.02 931900. -522212. -53107.
29 0.02 946064. -483995. -51132.
30 0.02 958764. -446461. -49060.
31 0.02 969848. -409738. -46891.
32 0.02 979157. -373957. -44628.
33 0.02 986532. -339253. -42274.
34 0.02 991807. -305760. -39834.
35 0.02 994826. -273608. -37315.
36 0.02 995415. -242940. -34730.
37 0.02 993425. -213876. -32091.
38 0.02 988706. -186533. -29414.
39 0.02 981121. -161015. -26716.
40 0.02 970547. -137413. -24021.
41 0.02 956879. -115794. -21352.
42 0.02 940034. -96209. -18736.
43 0.02 919953. -78677. -16200.
44 0.02 896602. -63194. -13774.
45 0.02 869980. -49723. -11485.
46 0.02 840109. -38199. -9360.
47 0.02 807046. -28525. -7422.
48 0.02 770870. -20576. -5692.
49 0.02 731685. -14204. -4182.
50 0.02 689613. -9241. -2899.
51 0.02 644788. -5505. -1843.
52 0.02 597347. -2809. -1005.
53 0.02 547424. -968. -371.
54 0.02 497728. 2780. 1148.
55 0.02 446779. 7009. 3131.
56 0.02 387452. 4651. 2270.
57 0.02 325148. 1164. 631.
58 0.02 263708. 450. 279.
59 0.02 200112. -450. -336.
60 0.02 135936. 105. 0
61 0.02 68999. -0.634 0
total_spending financial_wealth_end risk_tolerance
<dbl> <dbl> <dbl>
1 -9453. 393867. 0.5
2 -8866. 412806. 0.5
3 -8266. 431611. 0.5
4 -7662. 450343. 0.5
5 -7051. 469582. 0.5
6 -6395. 488886. 0.5
7 -5717. 511338. 0.5
8 -5015. 533919. 0.5
9 -4287. 556608. 0.5
10 -3529. 579379. 0.5
11 -2739. 602204. 0.5
12 -1915. 625051. 0.5
13 -1054. 647882. 0.5
14 -151. 670655. 0.5
15 795. 693324. 0.5
16 1789. 715838. 0.5
17 2834. 738138. 0.5
18 3934. 760161. 0.5
19 5094. 781837. 0.5
20 6317. 803088. 0.5
21 7608. 823830. 0.5
22 8971. 843972. 0.5
23 10411. 863413. 0.5
24 11931. 882046. 0.5
25 13536. 899756. 0.5
26 15229. 916417. 0.5
27 17014. 931900. 0.5
28 18893. 946064. 0.5
29 20868. 958764. 0.5
30 22940. 969848. 0.5
31 25109. 979157. 0.5
32 27372. 986532. 0.5
33 29726. 991807. 0.5
34 32166. 994826. 0.5
35 34685. 995415. 0.5
36 37270. 993425. 0.5
37 39909. 988706. 0.5
38 42586. 981121. 0.5
39 45284. 970547. 0.5
40 47979. 956879. 0.5
41 50648. 940034. 0.5
42 53264. 919953. 0.5
43 55800. 896602. 0.5
44 58226. 869980. 0.5
45 60515. 840109. 0.5
46 62640. 807046. 0.5
47 64578. 770870. 0.5
48 66308. 731685. 0.5
49 67818. 689613. 0.5
50 69101. 644788. 0.5
51 70157. 597347. 0.5
52 70995. 547424. 0.5
53 71629. 497728. 0.5
54 73148. 446779. 0.5
55 75131. 387452. 0.5
56 74270. 325148. 0.5
57 72631. 263708. 0.5
58 72279. 200112. 0.5
59 71664. 135936. 0.5
60 72000 68999. 0.5
61 72000 -0.658 0.5
smooth_consumption_preference consumption_impatience_preference
<dbl> <dbl>
1 1 0.04
2 1 0.04
3 1 0.04
4 1 0.04
5 1 0.04
6 1 0.04
7 1 0.04
8 1 0.04
9 1 0.04
10 1 0.04
11 1 0.04
12 1 0.04
13 1 0.04
14 1 0.04
15 1 0.04
16 1 0.04
17 1 0.04
18 1 0.04
19 1 0.04
20 1 0.04
21 1 0.04
22 1 0.04
23 1 0.04
24 1 0.04
25 1 0.04
26 1 0.04
27 1 0.04
28 1 0.04
29 1 0.04
30 1 0.04
31 1 0.04
32 1 0.04
33 1 0.04
34 1 0.04
35 1 0.04
36 1 0.04
37 1 0.04
38 1 0.04
39 1 0.04
40 1 0.04
41 1 0.04
42 1 0.04
43 1 0.04
44 1 0.04
45 1 0.04
46 1 0.04
47 1 0.04
48 1 0.04
49 1 0.04
50 1 0.04
51 1 0.04
52 1 0.04
53 1 0.04
54 1 0.04
55 1 0.04
56 1 0.04
57 1 0.04
58 1 0.04
59 1 0.04
60 1 0.04
61 1 0.04
time_value_discount discretionary_spending_utility
<dbl> <dbl>
1 1 0
2 0.962 0
3 0.925 0
4 0.889 0
5 0.855 0
6 0.822 0
7 0.790 0
8 0.760 0
9 0.731 0
10 0.703 0
11 0.676 0
12 0.650 0
13 0.625 0
14 0.601 0
15 0.577 0
16 0.555 0
17 0.534 0
18 0.513 0
19 0.494 0
20 0.475 0
21 0.456 0
22 0.439 0
23 0.422 0
24 0.406 0
25 0.390 0
26 0.375 0
27 0.361 0
28 0.347 0
29 0.333 0
30 0.321 0
31 0.308 0
32 0.296 0
33 0.285 0
34 0.274 0
35 0.264 0
36 0.253 0
37 0.244 0
38 0.234 0
39 0.225 0
40 0.217 0
41 0.208 0
42 0.200 0
43 0.193 0
44 0.185 0
45 0.178 0
46 0.171 0
47 0.165 0
48 0.158 0
49 0.152 0
50 0.146 0
51 0.141 0
52 0.135 0
53 0.130 0
54 0.125 7.05
55 0.120 8.05
56 0.116 7.73
57 0.111 6.45
58 0.107 5.63
59 0.103 0
60 0.0989 0
61 0.0951 0
discretionary_spending_utility_weighted
<dbl>
1 0
2 0
3 0
4 0
5 0
6 0
7 0
8 0
9 0
10 0
11 0
12 0
13 0
14 0
15 0
16 0
17 0
18 0
19 0
20 0
21 0
22 0
23 0
24 0
25 0
26 0
27 0
28 0
29 0
30 0
31 0
32 0
33 0
34 0
35 0
36 0
37 0
38 0
39 0
40 0
41 0
42 0
43 0
44 0
45 0
46 0
47 0
48 0
49 0
50 0
51 0
52 0
53 0
54 0.0227
55 0.0169
56 0.0102
57 0.00508
58 0.00253
59 0
60 0
61 0
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simulating single scenario with event
Code
scenario$income$income_older
Output
[1] 0 0 0 0 0 0 3000 3000 3000 3000 3000 3000 3000 3000 3000
[16] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[31] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[46] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[61] 3000
simulating single scenario with event and id_on helper functions
Code
scenario$income$income_older
Output
[1] 0 0 0 0 0 0 3000 3000 3000 3000 3000 3000 3000 3000 3000
[16] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[31] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[46] 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000 3000
[61] 3000
benchmarking of simulating single scenario
Code
print(scenario, n = Inf, width = Inf)
Output
# A tibble: 61 x 25
scenario_id index years_left date year survival_prob members$older$age
<chr> <int> <int> <date> <int> <dbl> <dbl>
1 default 0 60 2020-07-15 2020 1 40
2 default 1 59 2021-07-15 2021 0.998 41
3 default 2 58 2022-07-15 2022 0.996 42
4 default 3 57 2023-07-15 2023 0.994 43
5 default 4 56 2024-07-15 2024 0.991 44
6 default 5 55 2025-07-15 2025 0.988 45
7 default 6 54 2026-07-15 2026 0.985 46
8 default 7 53 2027-07-15 2027 0.982 47
9 default 8 52 2028-07-15 2028 0.978 48
10 default 9 51 2029-07-15 2029 0.974 49
11 default 10 50 2030-07-15 2030 0.969 50
12 default 11 49 2031-07-15 2031 0.964 51
13 default 12 48 2032-07-15 2032 0.958 52
14 default 13 47 2033-07-15 2033 0.952 53
15 default 14 46 2034-07-15 2034 0.946 54
16 default 15 45 2035-07-15 2035 0.938 55
17 default 16 44 2036-07-15 2036 0.930 56
18 default 17 43 2037-07-15 2037 0.921 57
19 default 18 42 2038-07-15 2038 0.912 58
20 default 19 41 2039-07-15 2039 0.901 59
21 default 20 40 2040-07-15 2040 0.890 60
22 default 21 39 2041-07-15 2041 0.877 61
23 default 22 38 2042-07-15 2042 0.863 62
24 default 23 37 2043-07-15 2043 0.848 63
25 default 24 36 2044-07-15 2044 0.832 64
26 default 25 35 2045-07-15 2045 0.815 65
27 default 26 34 2046-07-15 2046 0.796 66
28 default 27 33 2047-07-15 2047 0.775 67
29 default 28 32 2048-07-15 2048 0.754 68
30 default 29 31 2049-07-15 2049 0.730 69
31 default 30 30 2050-07-15 2050 0.705 70
32 default 31 29 2051-07-15 2051 0.678 71
33 default 32 28 2052-07-15 2052 0.650 72
34 default 33 27 2053-07-15 2053 0.620 73
35 default 34 26 2054-07-15 2054 0.588 74
36 default 35 25 2055-07-15 2055 0.555 75
37 default 36 24 2056-07-15 2056 0.521 76
38 default 37 23 2057-07-15 2057 0.485 77
39 default 38 22 2058-07-15 2058 0.449 78
40 default 39 21 2059-07-15 2059 0.412 79
41 default 40 20 2060-07-15 2060 0.374 80
42 default 41 19 2061-07-15 2061 0.337 81
43 default 42 18 2062-07-15 2062 0.300 82
44 default 43 17 2063-07-15 2063 0.263 83
45 default 44 16 2064-07-15 2064 0.229 84
46 default 45 15 2065-07-15 2065 0.195 85
47 default 46 14 2066-07-15 2066 0.164 86
48 default 47 13 2067-07-15 2067 0.135 87
49 default 48 12 2068-07-15 2068 0.109 88
50 default 49 11 2069-07-15 2069 0.0866 89
51 default 50 10 2070-07-15 2070 0.0668 90
52 default 51 9 2071-07-15 2071 0.0501 91
53 default 52 8 2072-07-15 2072 0.0365 92
54 default 53 7 2073-07-15 2073 0.0257 93
55 default 54 6 2074-07-15 2074 0.0175 94
56 default 55 5 2075-07-15 2075 0.0114 95
57 default 56 4 2076-07-15 2076 0.00709 96
58 default 57 3 2077-07-15 2077 0.00420 97
59 default 58 2 2078-07-15 2078 0.00236 98
60 default 59 1 2079-07-15 2079 0.00124 99
61 default 60 0 2080-07-15 2080 0.000614 100
income$income_older total_income spending$spending1 nondiscretionary_spending
<dbl> <dbl> <dbl> <dbl>
1 0 0 72000 72000
2 0 0 72000 72000
3 0 0 72000 72000
4 0 0 72000 72000
5 0 0 72000 72000
6 0 0 72000 72000
7 3000 3000 72000 72000
8 3000 3000 72000 72000
9 3000 3000 72000 72000
10 3000 3000 72000 72000
11 3000 3000 72000 72000
12 3000 3000 72000 72000
13 3000 3000 72000 72000
14 3000 3000 72000 72000
15 3000 3000 72000 72000
16 3000 3000 72000 72000
17 3000 3000 72000 72000
18 3000 3000 72000 72000
19 3000 3000 72000 72000
20 3000 3000 72000 72000
21 3000 3000 72000 72000
22 3000 3000 72000 72000
23 3000 3000 72000 72000
24 3000 3000 72000 72000
25 3000 3000 72000 72000
26 3000 3000 72000 72000
27 3000 3000 72000 72000
28 3000 3000 72000 72000
29 3000 3000 72000 72000
30 3000 3000 72000 72000
31 3000 3000 72000 72000
32 3000 3000 72000 72000
33 3000 3000 72000 72000
34 3000 3000 72000 72000
35 3000 3000 72000 72000
36 3000 3000 72000 72000
37 3000 3000 72000 72000
38 3000 3000 72000 72000
39 3000 3000 72000 72000
40 3000 3000 72000 72000
41 3000 3000 72000 72000
42 3000 3000 72000 72000
43 3000 3000 72000 72000
44 3000 3000 72000 72000
45 3000 3000 72000 72000
46 3000 3000 72000 72000
47 3000 3000 72000 72000
48 3000 3000 72000 72000
49 3000 3000 72000 72000
50 3000 3000 72000 72000
51 3000 3000 72000 72000
52 3000 3000 72000 72000
53 3000 3000 72000 72000
54 3000 3000 72000 72000
55 3000 3000 72000 72000
56 3000 3000 72000 72000
57 3000 3000 72000 72000
58 3000 3000 72000 72000
59 3000 3000 72000 72000
60 3000 3000 72000 72000
61 3000 3000 72000 72000
human_capital liabilities portfolio$allocation $returns$GlobalStock
<dbl> <dbl> <list> <dbl>
1 65199. 1964228. <tibble [2 x 4]> 0.0449
2 67315. 1953631. <tibble [2 x 4]> 0.0449
3 69499. 1942690. <tibble [2 x 4]> 0.0449
4 71755. 1931394. <tibble [2 x 4]> 0.0449
5 74083. 1919731. <tibble [2 x 4]> 0.0449
6 76487. 1907690. <tibble [2 x 4]> 0.0449
7 78969. 1895258. <tibble [2 x 4]> 0.0449
8 78434. 1882423. <tibble [2 x 4]> 0.0449
9 77882. 1869171. <tibble [2 x 4]> 0.0449
10 77312. 1855489. <tibble [2 x 4]> 0.0449
11 76723. 1841364. <tibble [2 x 4]> 0.0449
12 76116. 1826780. <tibble [2 x 4]> 0.0449
13 75488. 1811722. <tibble [2 x 4]> 0.0449
14 74841. 1796176. <tibble [2 x 4]> 0.0449
15 74172. 1780126. <tibble [2 x 4]> 0.0449
16 73481. 1763554. <tibble [2 x 4]> 0.0449
17 72769. 1746445. <tibble [2 x 4]> 0.0449
18 72033. 1728781. <tibble [2 x 4]> 0.0449
19 71273. 1710544. <tibble [2 x 4]> 0.0449
20 70488. 1691714. <tibble [2 x 4]> 0.0449
21 69678. 1672274. <tibble [2 x 4]> 0.0449
22 68842. 1652203. <tibble [2 x 4]> 0.0449
23 67978. 1631480. <tibble [2 x 4]> 0.0449
24 67087. 1610086. <tibble [2 x 4]> 0.0449
25 66167. 1587997. <tibble [2 x 4]> 0.0449
26 65216. 1565191. <tibble [2 x 4]> 0.0449
27 64235. 1541645. <tibble [2 x 4]> 0.0449
28 63222. 1517335. <tibble [2 x 4]> 0.0449
29 62176. 1492236. <tibble [2 x 4]> 0.0449
30 61097. 1466322. <tibble [2 x 4]> 0.0449
31 59982. 1439568. <tibble [2 x 4]> 0.0449
32 58831. 1411946. <tibble [2 x 4]> 0.0449
33 57643. 1383427. <tibble [2 x 4]> 0.0449
34 56416. 1353983. <tibble [2 x 4]> 0.0449
35 55149. 1323583. <tibble [2 x 4]> 0.0449
36 53842. 1292197. <tibble [2 x 4]> 0.0449
37 52491. 1259792. <tibble [2 x 4]> 0.0449
38 51097. 1226336. <tibble [2 x 4]> 0.0449
39 49658. 1191794. <tibble [2 x 4]> 0.0449
40 48172. 1156132. <tibble [2 x 4]> 0.0449
41 46638. 1119312. <tibble [2 x 4]> 0.0449
42 45054. 1081297. <tibble [2 x 4]> 0.0449
43 43419. 1042049. <tibble [2 x 4]> 0.0449
44 41730. 1001527. <tibble [2 x 4]> 0.0449
45 39987. 959690. <tibble [2 x 4]> 0.0449
46 38187. 916496. <tibble [2 x 4]> 0.0449
47 36329. 871899. <tibble [2 x 4]> 0.0449
48 34411. 825856. <tibble [2 x 4]> 0.0449
49 32430. 778319. <tibble [2 x 4]> 0.0449
50 30385. 729239. <tibble [2 x 4]> 0.0449
51 28274. 678566. <tibble [2 x 4]> 0.0449
52 26094. 626249. <tibble [2 x 4]> 0.0449
53 23843. 572235. <tibble [2 x 4]> 0.0449
54 21519. 516467. <tibble [2 x 4]> 0.0449
55 19120. 458890. <tibble [2 x 4]> 0.0449
56 16644. 399445. <tibble [2 x 4]> 0.0449
57 14086. 338070. <tibble [2 x 4]> 0.0449
58 11446. 274704. <tibble [2 x 4]> 0.0449
59 8720. 209282. <tibble [2 x 4]> 0.0449
60 5906. 141737. <tibble [2 x 4]> 0.0449
61 3000 72000 <tibble [2 x 4]> 0.0449
$$EDOBonds financial_wealth net_worth discretionary_spending
<dbl> <dbl> <dbl> <dbl>
1 0.02 375000 -1524029. -81453.
2 0.02 393867. -1492449. -80866.
3 0.02 412806. -1460385. -80266.
4 0.02 431611. -1428028. -79662.
5 0.02 450343. -1395305. -79051.
6 0.02 469582. -1361621. -78395.
7 0.02 488886. -1327404. -77717.
8 0.02 511338. -1292651. -77015.
9 0.02 533919. -1257370. -76287.
10 0.02 556608. -1221569. -75529.
11 0.02 579379. -1185261. -74739.
12 0.02 602204. -1148459. -73915.
13 0.02 625051. -1111183. -73054.
14 0.02 647882. -1073454. -72151.
15 0.02 670655. -1035299. -71205.
16 0.02 693324. -996749. -70211.
17 0.02 715838. -957839. -69166.
18 0.02 738138. -918611. -68066.
19 0.02 760161. -879110. -66906.
20 0.02 781837. -839390. -65683.
21 0.02 803088. -799508. -64392.
22 0.02 823830. -759531. -63029.
23 0.02 843972. -719530. -61589.
24 0.02 863413. -679585. -60069.
25 0.02 882046. -639784. -58464.
26 0.02 899756. -600219. -56771.
27 0.02 916417. -560992. -54986.
28 0.02 931900. -522212. -53107.
29 0.02 946064. -483995. -51132.
30 0.02 958764. -446461. -49060.
31 0.02 969848. -409738. -46891.
32 0.02 979157. -373957. -44628.
33 0.02 986532. -339253. -42274.
34 0.02 991807. -305760. -39834.
35 0.02 994826. -273608. -37315.
36 0.02 995415. -242940. -34730.
37 0.02 993425. -213876. -32091.
38 0.02 988706. -186533. -29414.
39 0.02 981121. -161015. -26716.
40 0.02 970547. -137413. -24021.
41 0.02 956879. -115794. -21352.
42 0.02 940034. -96209. -18736.
43 0.02 919953. -78677. -16200.
44 0.02 896602. -63194. -13774.
45 0.02 869980. -49723. -11485.
46 0.02 840109. -38199. -9360.
47 0.02 807046. -28525. -7422.
48 0.02 770870. -20576. -5692.
49 0.02 731685. -14204. -4182.
50 0.02 689613. -9241. -2899.
51 0.02 644788. -5505. -1843.
52 0.02 597347. -2809. -1005.
53 0.02 547424. -968. -371.
54 0.02 497728. 2780. 1148.
55 0.02 446779. 7009. 3131.
56 0.02 387452. 4651. 2270.
57 0.02 325148. 1164. 631.
58 0.02 263708. 450. 279.
59 0.02 200112. -450. -336.
60 0.02 135936. 105. 0
61 0.02 68999. -0.634 0
total_spending financial_wealth_end risk_tolerance
<dbl> <dbl> <dbl>
1 -9453. 393867. 0.5
2 -8866. 412806. 0.5
3 -8266. 431611. 0.5
4 -7662. 450343. 0.5
5 -7051. 469582. 0.5
6 -6395. 488886. 0.5
7 -5717. 511338. 0.5
8 -5015. 533919. 0.5
9 -4287. 556608. 0.5
10 -3529. 579379. 0.5
11 -2739. 602204. 0.5
12 -1915. 625051. 0.5
13 -1054. 647882. 0.5
14 -151. 670655. 0.5
15 795. 693324. 0.5
16 1789. 715838. 0.5
17 2834. 738138. 0.5
18 3934. 760161. 0.5
19 5094. 781837. 0.5
20 6317. 803088. 0.5
21 7608. 823830. 0.5
22 8971. 843972. 0.5
23 10411. 863413. 0.5
24 11931. 882046. 0.5
25 13536. 899756. 0.5
26 15229. 916417. 0.5
27 17014. 931900. 0.5
28 18893. 946064. 0.5
29 20868. 958764. 0.5
30 22940. 969848. 0.5
31 25109. 979157. 0.5
32 27372. 986532. 0.5
33 29726. 991807. 0.5
34 32166. 994826. 0.5
35 34685. 995415. 0.5
36 37270. 993425. 0.5
37 39909. 988706. 0.5
38 42586. 981121. 0.5
39 45284. 970547. 0.5
40 47979. 956879. 0.5
41 50648. 940034. 0.5
42 53264. 919953. 0.5
43 55800. 896602. 0.5
44 58226. 869980. 0.5
45 60515. 840109. 0.5
46 62640. 807046. 0.5
47 64578. 770870. 0.5
48 66308. 731685. 0.5
49 67818. 689613. 0.5
50 69101. 644788. 0.5
51 70157. 597347. 0.5
52 70995. 547424. 0.5
53 71629. 497728. 0.5
54 73148. 446779. 0.5
55 75131. 387452. 0.5
56 74270. 325148. 0.5
57 72631. 263708. 0.5
58 72279. 200112. 0.5
59 71664. 135936. 0.5
60 72000 68999. 0.5
61 72000 -0.658 0.5
smooth_consumption_preference consumption_impatience_preference
<dbl> <dbl>
1 1 0.04
2 1 0.04
3 1 0.04
4 1 0.04
5 1 0.04
6 1 0.04
7 1 0.04
8 1 0.04
9 1 0.04
10 1 0.04
11 1 0.04
12 1 0.04
13 1 0.04
14 1 0.04
15 1 0.04
16 1 0.04
17 1 0.04
18 1 0.04
19 1 0.04
20 1 0.04
21 1 0.04
22 1 0.04
23 1 0.04
24 1 0.04
25 1 0.04
26 1 0.04
27 1 0.04
28 1 0.04
29 1 0.04
30 1 0.04
31 1 0.04
32 1 0.04
33 1 0.04
34 1 0.04
35 1 0.04
36 1 0.04
37 1 0.04
38 1 0.04
39 1 0.04
40 1 0.04
41 1 0.04
42 1 0.04
43 1 0.04
44 1 0.04
45 1 0.04
46 1 0.04
47 1 0.04
48 1 0.04
49 1 0.04
50 1 0.04
51 1 0.04
52 1 0.04
53 1 0.04
54 1 0.04
55 1 0.04
56 1 0.04
57 1 0.04
58 1 0.04
59 1 0.04
60 1 0.04
61 1 0.04
time_value_discount discretionary_spending_utility
<dbl> <dbl>
1 1 0
2 0.962 0
3 0.925 0
4 0.889 0
5 0.855 0
6 0.822 0
7 0.790 0
8 0.760 0
9 0.731 0
10 0.703 0
11 0.676 0
12 0.650 0
13 0.625 0
14 0.601 0
15 0.577 0
16 0.555 0
17 0.534 0
18 0.513 0
19 0.494 0
20 0.475 0
21 0.456 0
22 0.439 0
23 0.422 0
24 0.406 0
25 0.390 0
26 0.375 0
27 0.361 0
28 0.347 0
29 0.333 0
30 0.321 0
31 0.308 0
32 0.296 0
33 0.285 0
34 0.274 0
35 0.264 0
36 0.253 0
37 0.244 0
38 0.234 0
39 0.225 0
40 0.217 0
41 0.208 0
42 0.200 0
43 0.193 0
44 0.185 0
45 0.178 0
46 0.171 0
47 0.165 0
48 0.158 0
49 0.152 0
50 0.146 0
51 0.141 0
52 0.135 0
53 0.130 0
54 0.125 7.05
55 0.120 8.05
56 0.116 7.73
57 0.111 6.45
58 0.107 5.63
59 0.103 0
60 0.0989 0
61 0.0951 0
discretionary_spending_utility_weighted
<dbl>
1 0
2 0
3 0
4 0
5 0
6 0
7 0
8 0
9 0
10 0
11 0
12 0
13 0
14 0
15 0
16 0
17 0
18 0
19 0
20 0
21 0
22 0
23 0
24 0
25 0
26 0
27 0
28 0
29 0
30 0
31 0
32 0
33 0
34 0
35 0
36 0
37 0
38 0
39 0
40 0
41 0
42 0
43 0
44 0
45 0
46 0
47 0
48 0
49 0
50 0
51 0
52 0
53 0
54 0.0227
55 0.0169
56 0.0102
57 0.00508
58 0.00253
59 0
60 0
61 0
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