Step 1: Author the MODEL clause
select rownumber, a, b, c from dual
MODEL
DIMENSION BY (rownum rownumber)
MEASURES (0 a, 0 b, 0 c)
RULES SEQUENTIAL ORDER ITERATE (10) (
a[1] = 20000,
b[ITERATION_NUMBER + 1] = a[cv(rownumber)] * 6 / 1200,
c[ITERATION_NUMBER + 1] = 600 - b[cv(rownumber)],
a[ITERATION_NUMBER + 2] = a[cv(rownumber)-1] - c[cv(rownumber) - 1]
)
order by rownumber
ROWNUMBER | A | B | C | 1 | 20000 | 100 | 500 | 2 | 19500 | 97.5 | 502.5 | 3 | 18997.5 | 94.9875 | 505.0125 | 4 | 18492.4875 | 92.4624375 | 507.5375625 | 5 | 17984.9499375 | 89.9247496875 | 510.0752503125 | 6 | 17474.8746871875 | 87.3743734359375 | 512.6256265640625 | 7 | 16962.2490606234375 | 84.8112453031171875 | 515.1887546968828125 | 8 | 16447.0603059265546875 | 82.2353015296327734375 | 517.7646984703672265625 | 9 | 15929.2956074561874609375 | 79.6464780372809373046875 | 520.3535219627190626953125 | 10 | 15408.9420854934683982421875 | 77.0447104274673419912109375 | 522.9552895725326580087890625 | 11 | 14885.9867959209357402333984375 | - | - |
---|
Step 2: Separate calculation data from formulas
select rownumber, a, b, c, d from dual
MODEL
DIMENSION BY (rownum rownumber)
-- Change Amount, Payment and Interest Rate here!
MEASURES (20000 a, 0 b, 0 c, 600 d, 6 e)
RULES SEQUENTIAL ORDER ITERATE (500) (
b[ITERATION_NUMBER + 1] = a[cv(rownumber)] * e[cv(rownumber)] / 1200,
c[ITERATION_NUMBER + 1] = d[cv(rownumber)] - b[cv(rownumber)],
a[ITERATION_NUMBER + 2] = a[cv(rownumber)-1] - c[cv(rownumber) - 1],
e[ITERATION_NUMBER + 2] = e[cv(rownumber)-1],
d[ITERATION_NUMBER + 2] = d[cv(rownumber)-1]
)
order by rownumber
ROWNUMBER | A | B | C | D | 1 | 20000 | 100 | 500 | 600 | 2 | 19500 | 97.5 | 502.5 | 600 | 3 | 18997.5 | 94.9875 | 505.0125 | 600 | 4 | 18492.4875 | 92.4624375 | 507.5375625 | 600 | 5 | 17984.9499375 | 89.9247496875 | 510.0752503125 | 600 | 6 | 17474.8746871875 | 87.3743734359375 | 512.6256265640625 | 600 | 7 | 16962.2490606234375 | 84.8112453031171875 | 515.1887546968828125 | 600 | 8 | 16447.0603059265546875 | 82.2353015296327734375 | 517.7646984703672265625 | 600 | 9 | 15929.2956074561874609375 | 79.6464780372809373046875 | 520.3535219627190626953125 | 600 | 10 | 15408.9420854934683982421875 | 77.0447104274673419912109375 | 522.9552895725326580087890625 | 600 | 11 | 14885.9867959209357402333984375 | 74.4299339796046787011669921875 | 525.5700660203953212988330078125 | 600 | 12 | 14360.4167299005404189345654296875 | 71.8020836495027020946728271484375 | 528.1979163504972979053271728515625 | 600 | 13 | 13832.2188135500431210292382568359375 | 69.1610940677502156051461912841796875 | 530.8389059322497843948538087158203125 | 600 | 14 | 13301.3799076177933366343844481201171875 | 66.5068995380889666831719222406005859375 | 533.493100461911033316828077759399414063 | 600 | 15 | 12767.8868071558823033175563703607177734 | 63.839434035779411516587781851803588867 | 536.160565964220588483412218148196411133 | 600 | 16 | 12231.7262411916617148341441522125213623 | 61.1586312059583085741707207610626068115 | 538.841368794041691425829279238937393189 | 600 | 17 | 11692.8848723976200234083148729735839691 | 58.4644243619881001170415743648679198455 | 541.535575638011899882958425635132080155 | 600 | 18 | 11151.3492967596081235253564473384518889 | 55.7567464837980406176267822366922594445 | 544.243253516201959382373217763307740556 | 600 | 19 | 10607.1060432434061641429832295751441483 | 53.0355302162170308207149161478757207415 | 546.964469783782969179285083852124279259 | 600 | 20 | 10060.141573459623194963698145723019869 | 50.300707867298115974818490728615099345 | 549.699292132701884025181509271384900655 | 600 | 21 | 9510.442281326921310938516636451634968345 | 47.55221140663460655469258318225817484175 | 552.447788593365393445307416817741825158 | 600 | 22 | 8957.994492733555917493209219633893143187 | 44.78997246366777958746604609816946571592 | 555.210027536332220412533953901830534284 | 600 | 23 | 8402.784465197223697080675265732062608903 | 42.0139223259861184854033763286603130445 | 557.986077674013881514596623671339686956 | 600 | 24 | 7844.798387523209815566078642060722921947 | 39.22399193761604907783039321030361460975 | 560.77600806238395092216960678969638539 | 600 | 25 | 7284.022379460825864643909035271026536557 | 36.42011189730412932321954517635513268275 | 563.579888102695870676780454823644867317 | 600 | 26 | 6720.44249135812999396712858044738166924 | 33.60221245679064996983564290223690834617 | 566.397787543209350030164357097763091654 | 600 | 27 | 6154.044703814920643936964223349618577586 | 30.77022351907460321968482111674809288792 | 569.229776480925396780315178883251907112 | 600 | 28 | 5584.814927333995247156649044466366670474 | 27.92407463666997623578324522233183335233 | 572.075925363330023764216754777668166648 | 600 | 29 | 5012.739001970665223392432289688698503826 | 25.06369500985332611696216144844349251917 | 574.936304990146673883037838551556507481 | 600 | 30 | 4437.802696980518549509394451137141996345 | 22.18901348490259274754697225568570998175 | 577.810986515097407252453027744314290018 | 600 | 31 | 3859.991710465421142256941423392827706327 | 19.29995855232710571128470711696413853167 | 580.700041447672894288715292883035861468 | 600 | 32 | 3279.291669017748247968226130509791844859 | 16.39645834508874123984113065254895922433 | 583.603541654911258760158869347451040776 | 600 | 33 | 2695.688127362836989208067261162340804083 | 13.47844063681418494604033630581170402042 | 586.52155936318581505395966369418829598 | 600 | 34 | 2109.166567999651174154107597468152508103 | 10.5458328399982558707705379873407625405 | 589.45416716000174412922946201265923746 | 600 | 35 | 1519.712400839649430024878135455493270643 | 7.59856200419824715012439067727746635322 | 592.401437995801752849875609322722533647 | 600 | 36 | 927.310962843847677175002526132770736996 | 4.63655481421923838587501263066385368498 | 595.363445185780761614124987369336146315 | 600 | 37 | 331.947517658066915560877538763434590681 | 1.65973758829033457780438769381717295341 | 598.340262411709665422195612306182827047 | 600 | 38 | -266.392744753642749861318073542748236366 | -1.33196372376821374930659036771374118183 | 601.331963723768213749306590367713741182 | 600 | 39 | -867.724708477410963610624663910461977548 | -4.33862354238705481805312331955230988774 | 604.338623542387054818053123319552309888 | 600 | 40 | -1472.063332019798018428677787230014287436 | -7.36031666009899009214338893615007143718 | 607.360316660098990092143388936150071437 | 600 | 41 | -2079.423648679897008520821176166164358873 | -10.39711824339948504260410588083082179433 | 610.397118243399485042604105880830821794 | 600 | 42 | -2689.820766923296493563425282046995180667 | -13.44910383461648246781712641023497590333 | 613.449103834616482467817126410234975903 | 600 | 43 | -3303.26987075791297603124240845723015657 | -16.51634935378956488015621204228615078283 | 616.516349353789564880156212042286150783 | 600 | 44 | -3919.786220111702540911398620499516307353 | -19.59893110055851270455699310249758153675 | 619.598931100558512704556993102497581537 | 600 | 45 | -4539.38515121226105361595561360201388889 | -22.69692575606130526807977806801006944442 | 622.696925756061305268079778068010069444 | 600 | 46 | -5162.082076968322358884035391670023958334 | -25.81041038484161179442017695835011979167 | 625.810410384841611794420176958350119792 | 600 | 47 | -5787.892487353163970678455568628374078126 | -28.93946243676581985339227784314187039067 | 628.939462436765819853392277843141870391 | 600 | 48 | -6416.831949789929790531847846471515948517 | -32.08415974894964895265923923235757974258 | 632.084159748949648952659239232357579743 | 600 | 49 | -7048.91610953887943948450708570387352826 | -35.24458054769439719742253542851936764133 | 635.244580547694397197422535428519367641 | 600 | 50 | -7684.160690086573836681929621132392895901 | -38.4208034504328691834096481056619644795 | 638.42080345043286918340964810566196448 | 600 |
---|
Step 3: Add a termination condition
select rownumber, a, b, c, d from dual
MODEL
DIMENSION BY (rownum rownumber)
-- Change Amount, Payment and Interest Rate here!
MEASURES (20000 a, 0 b, 0 c, 600 d, 6 e)
RULES SEQUENTIAL ORDER ITERATE (500) UNTIL (a[ITERATION_NUMBER + 1] <= 0) (
b[ITERATION_NUMBER + 1] = a[cv(rownumber)] * e[cv(rownumber)] / 1200,
d[ITERATION_NUMBER + 1] = least(d[cv(rownumber)], a[cv(rownumber)] + b[cv(rownumber)]),
c[ITERATION_NUMBER + 1] = d[cv(rownumber)] - b[cv(rownumber)],
a[ITERATION_NUMBER + 2] = a[cv(rownumber)-1] - c[cv(rownumber) - 1],
e[ITERATION_NUMBER + 2] = e[cv(rownumber)-1],
d[ITERATION_NUMBER + 2] = d[cv(rownumber)-1]
)
order by rownumber
ROWNUMBER | A | B | C | D | 1 | 20000 | 100 | 500 | 600 | 2 | 19500 | 97.5 | 502.5 | 600 | 3 | 18997.5 | 94.9875 | 505.0125 | 600 | 4 | 18492.4875 | 92.4624375 | 507.5375625 | 600 | 5 | 17984.9499375 | 89.9247496875 | 510.0752503125 | 600 | 6 | 17474.8746871875 | 87.3743734359375 | 512.6256265640625 | 600 | 7 | 16962.2490606234375 | 84.8112453031171875 | 515.1887546968828125 | 600 | 8 | 16447.0603059265546875 | 82.2353015296327734375 | 517.7646984703672265625 | 600 | 9 | 15929.2956074561874609375 | 79.6464780372809373046875 | 520.3535219627190626953125 | 600 | 10 | 15408.9420854934683982421875 | 77.0447104274673419912109375 | 522.9552895725326580087890625 | 600 | 11 | 14885.9867959209357402333984375 | 74.4299339796046787011669921875 | 525.5700660203953212988330078125 | 600 | 12 | 14360.4167299005404189345654296875 | 71.8020836495027020946728271484375 | 528.1979163504972979053271728515625 | 600 | 13 | 13832.2188135500431210292382568359375 | 69.1610940677502156051461912841796875 | 530.8389059322497843948538087158203125 | 600 | 14 | 13301.3799076177933366343844481201171875 | 66.5068995380889666831719222406005859375 | 533.493100461911033316828077759399414063 | 600 | 15 | 12767.8868071558823033175563703607177734 | 63.839434035779411516587781851803588867 | 536.160565964220588483412218148196411133 | 600 | 16 | 12231.7262411916617148341441522125213623 | 61.1586312059583085741707207610626068115 | 538.841368794041691425829279238937393189 | 600 | 17 | 11692.8848723976200234083148729735839691 | 58.4644243619881001170415743648679198455 | 541.535575638011899882958425635132080155 | 600 | 18 | 11151.3492967596081235253564473384518889 | 55.7567464837980406176267822366922594445 | 544.243253516201959382373217763307740556 | 600 | 19 | 10607.1060432434061641429832295751441483 | 53.0355302162170308207149161478757207415 | 546.964469783782969179285083852124279259 | 600 | 20 | 10060.141573459623194963698145723019869 | 50.300707867298115974818490728615099345 | 549.699292132701884025181509271384900655 | 600 | 21 | 9510.442281326921310938516636451634968345 | 47.55221140663460655469258318225817484175 | 552.447788593365393445307416817741825158 | 600 | 22 | 8957.994492733555917493209219633893143187 | 44.78997246366777958746604609816946571592 | 555.210027536332220412533953901830534284 | 600 | 23 | 8402.784465197223697080675265732062608903 | 42.0139223259861184854033763286603130445 | 557.986077674013881514596623671339686956 | 600 | 24 | 7844.798387523209815566078642060722921947 | 39.22399193761604907783039321030361460975 | 560.77600806238395092216960678969638539 | 600 | 25 | 7284.022379460825864643909035271026536557 | 36.42011189730412932321954517635513268275 | 563.579888102695870676780454823644867317 | 600 | 26 | 6720.44249135812999396712858044738166924 | 33.60221245679064996983564290223690834617 | 566.397787543209350030164357097763091654 | 600 | 27 | 6154.044703814920643936964223349618577586 | 30.77022351907460321968482111674809288792 | 569.229776480925396780315178883251907112 | 600 | 28 | 5584.814927333995247156649044466366670474 | 27.92407463666997623578324522233183335233 | 572.075925363330023764216754777668166648 | 600 | 29 | 5012.739001970665223392432289688698503826 | 25.06369500985332611696216144844349251917 | 574.936304990146673883037838551556507481 | 600 | 30 | 4437.802696980518549509394451137141996345 | 22.18901348490259274754697225568570998175 | 577.810986515097407252453027744314290018 | 600 | 31 | 3859.991710465421142256941423392827706327 | 19.29995855232710571128470711696413853167 | 580.700041447672894288715292883035861468 | 600 | 32 | 3279.291669017748247968226130509791844859 | 16.39645834508874123984113065254895922433 | 583.603541654911258760158869347451040776 | 600 | 33 | 2695.688127362836989208067261162340804083 | 13.47844063681418494604033630581170402042 | 586.52155936318581505395966369418829598 | 600 | 34 | 2109.166567999651174154107597468152508103 | 10.5458328399982558707705379873407625405 | 589.45416716000174412922946201265923746 | 600 | 35 | 1519.712400839649430024878135455493270643 | 7.59856200419824715012439067727746635322 | 592.401437995801752849875609322722533647 | 600 | 36 | 927.310962843847677175002526132770736996 | 4.63655481421923838587501263066385368498 | 595.363445185780761614124987369336146315 | 600 | 37 | 331.947517658066915560877538763434590681 | 1.65973758829033457780438769381717295341 | 331.947517658066915560877538763434590681 | 333.607255246357250138681926457251763634 | 38 | 0 | 0 | 0 | 0 | 39 | 0 | - | - | 0 |
---|
Step 4: Add some formatting
select
add_months(trunc(sysdate, 'MONTH'), rownumber) as mon,
to_char(a,'9G999G990D00') amount,
to_char(b,'9G999G990D00') interest,
to_char(c,'9G999G990D00') redemption,
to_char(d,'9G999G990D00') payment
from dual
MODEL
DIMENSION BY (rownum rownumber)
-- Change Amount, Payment and Interest Rate here!
MEASURES (20000 a, 0 b, 0 c, 600 d, 6 e)
RULES SEQUENTIAL ORDER ITERATE (500) UNTIL (a[ITERATION_NUMBER + 1] <= 0) (
b[ITERATION_NUMBER + 1] = a[cv(rownumber)] * e[cv(rownumber)] / 1200,
d[ITERATION_NUMBER + 1] = least(d[cv(rownumber)], a[cv(rownumber)] + b[cv(rownumber)]),
c[ITERATION_NUMBER + 1] = d[cv(rownumber)] - b[cv(rownumber)],
a[ITERATION_NUMBER + 2] = a[cv(rownumber)-1] - c[cv(rownumber) - 1],
e[ITERATION_NUMBER + 2] = e[cv(rownumber)-1],
d[ITERATION_NUMBER + 2] = d[cv(rownumber)-1]
)
order by rownumber
MON | AMOUNT | INTEREST | REDEMPTION | PAYMENT | 01-AUG-18 | 20,000.00 | 100.00 | 500.00 | 600.00 | 01-SEP-18 | 19,500.00 | 97.50 | 502.50 | 600.00 | 01-OCT-18 | 18,997.50 | 94.99 | 505.01 | 600.00 | 01-NOV-18 | 18,492.49 | 92.46 | 507.54 | 600.00 | 01-DEC-18 | 17,984.95 | 89.92 | 510.08 | 600.00 | 01-JAN-19 | 17,474.87 | 87.37 | 512.63 | 600.00 | 01-FEB-19 | 16,962.25 | 84.81 | 515.19 | 600.00 | 01-MAR-19 | 16,447.06 | 82.24 | 517.76 | 600.00 | 01-APR-19 | 15,929.30 | 79.65 | 520.35 | 600.00 | 01-MAY-19 | 15,408.94 | 77.04 | 522.96 | 600.00 | 01-JUN-19 | 14,885.99 | 74.43 | 525.57 | 600.00 | 01-JUL-19 | 14,360.42 | 71.80 | 528.20 | 600.00 | 01-AUG-19 | 13,832.22 | 69.16 | 530.84 | 600.00 | 01-SEP-19 | 13,301.38 | 66.51 | 533.49 | 600.00 | 01-OCT-19 | 12,767.89 | 63.84 | 536.16 | 600.00 | 01-NOV-19 | 12,231.73 | 61.16 | 538.84 | 600.00 | 01-DEC-19 | 11,692.88 | 58.46 | 541.54 | 600.00 | 01-JAN-20 | 11,151.35 | 55.76 | 544.24 | 600.00 | 01-FEB-20 | 10,607.11 | 53.04 | 546.96 | 600.00 | 01-MAR-20 | 10,060.14 | 50.30 | 549.70 | 600.00 | 01-APR-20 | 9,510.44 | 47.55 | 552.45 | 600.00 | 01-MAY-20 | 8,957.99 | 44.79 | 555.21 | 600.00 | 01-JUN-20 | 8,402.78 | 42.01 | 557.99 | 600.00 | 01-JUL-20 | 7,844.80 | 39.22 | 560.78 | 600.00 | 01-AUG-20 | 7,284.02 | 36.42 | 563.58 | 600.00 | 01-SEP-20 | 6,720.44 | 33.60 | 566.40 | 600.00 | 01-OCT-20 | 6,154.04 | 30.77 | 569.23 | 600.00 | 01-NOV-20 | 5,584.81 | 27.92 | 572.08 | 600.00 | 01-DEC-20 | 5,012.74 | 25.06 | 574.94 | 600.00 | 01-JAN-21 | 4,437.80 | 22.19 | 577.81 | 600.00 | 01-FEB-21 | 3,859.99 | 19.30 | 580.70 | 600.00 | 01-MAR-21 | 3,279.29 | 16.40 | 583.60 | 600.00 | 01-APR-21 | 2,695.69 | 13.48 | 586.52 | 600.00 | 01-MAY-21 | 2,109.17 | 10.55 | 589.45 | 600.00 | 01-JUN-21 | 1,519.71 | 7.60 | 592.40 | 600.00 | 01-JUL-21 | 927.31 | 4.64 | 595.36 | 600.00 | 01-AUG-21 | 331.95 | 1.66 | 331.95 | 333.61 | 01-SEP-21 | 0.00 | 0.00 | 0.00 | 0.00 | 01-OCT-21 | 0.00 | - | - | 0.00 |
---|
Second example (different parameters)
select
add_months(trunc(sysdate, 'MONTH'), rownumber) as mon,
to_char(a,'9G999G990D00') amount,
to_char(b,'9G999G990D00') interest,
to_char(c,'9G999G990D00') redemption,
to_char(d,'9G999G990D00') payment
from dual
MODEL
DIMENSION BY (rownum rownumber)
-- Change Amount, Payment and Interest Rate here!
MEASURES (50000 a, 0 b, 0 c, 800 d, 2 e)
RULES SEQUENTIAL ORDER ITERATE (500) UNTIL (a[ITERATION_NUMBER + 1] <= 0) (
b[ITERATION_NUMBER + 1] = a[cv(rownumber)] * e[cv(rownumber)] / 1200,
d[ITERATION_NUMBER + 1] = least(d[cv(rownumber)], a[cv(rownumber)] + b[cv(rownumber)]),
c[ITERATION_NUMBER + 1] = d[cv(rownumber)] - b[cv(rownumber)],
a[ITERATION_NUMBER + 2] = a[cv(rownumber)-1] - c[cv(rownumber) - 1],
e[ITERATION_NUMBER + 2] = e[cv(rownumber)-1],
d[ITERATION_NUMBER + 2] = d[cv(rownumber)-1]
)
order by rownumber
MON | AMOUNT | INTEREST | REDEMPTION | PAYMENT | 01-AUG-18 | 50,000.00 | 83.33 | 716.67 | 800.00 | 01-SEP-18 | 49,283.33 | 82.14 | 717.86 | 800.00 | 01-OCT-18 | 48,565.47 | 80.94 | 719.06 | 800.00 | 01-NOV-18 | 47,846.41 | 79.74 | 720.26 | 800.00 | 01-DEC-18 | 47,126.16 | 78.54 | 721.46 | 800.00 | 01-JAN-19 | 46,404.70 | 77.34 | 722.66 | 800.00 | 01-FEB-19 | 45,682.04 | 76.14 | 723.86 | 800.00 | 01-MAR-19 | 44,958.18 | 74.93 | 725.07 | 800.00 | 01-APR-19 | 44,233.11 | 73.72 | 726.28 | 800.00 | 01-MAY-19 | 43,506.83 | 72.51 | 727.49 | 800.00 | 01-JUN-19 | 42,779.34 | 71.30 | 728.70 | 800.00 | 01-JUL-19 | 42,050.64 | 70.08 | 729.92 | 800.00 | 01-AUG-19 | 41,320.73 | 68.87 | 731.13 | 800.00 | 01-SEP-19 | 40,589.59 | 67.65 | 732.35 | 800.00 | 01-OCT-19 | 39,857.24 | 66.43 | 733.57 | 800.00 | 01-NOV-19 | 39,123.67 | 65.21 | 734.79 | 800.00 | 01-DEC-19 | 38,388.88 | 63.98 | 736.02 | 800.00 | 01-JAN-20 | 37,652.86 | 62.75 | 737.25 | 800.00 | 01-FEB-20 | 36,915.62 | 61.53 | 738.47 | 800.00 | 01-MAR-20 | 36,177.14 | 60.30 | 739.70 | 800.00 | 01-APR-20 | 35,437.44 | 59.06 | 740.94 | 800.00 | 01-MAY-20 | 34,696.50 | 57.83 | 742.17 | 800.00 | 01-JUN-20 | 33,954.33 | 56.59 | 743.41 | 800.00 | 01-JUL-20 | 33,210.92 | 55.35 | 744.65 | 800.00 | 01-AUG-20 | 32,466.27 | 54.11 | 745.89 | 800.00 | 01-SEP-20 | 31,720.38 | 52.87 | 747.13 | 800.00 | 01-OCT-20 | 30,973.25 | 51.62 | 748.38 | 800.00 | 01-NOV-20 | 30,224.87 | 50.37 | 749.63 | 800.00 | 01-DEC-20 | 29,475.24 | 49.13 | 750.87 | 800.00 | 01-JAN-21 | 28,724.37 | 47.87 | 752.13 | 800.00 | 01-FEB-21 | 27,972.24 | 46.62 | 753.38 | 800.00 | 01-MAR-21 | 27,218.86 | 45.36 | 754.64 | 800.00 | 01-APR-21 | 26,464.23 | 44.11 | 755.89 | 800.00 | 01-MAY-21 | 25,708.33 | 42.85 | 757.15 | 800.00 | 01-JUN-21 | 24,951.18 | 41.59 | 758.41 | 800.00 | 01-JUL-21 | 24,192.77 | 40.32 | 759.68 | 800.00 | 01-AUG-21 | 23,433.09 | 39.06 | 760.94 | 800.00 | 01-SEP-21 | 22,672.14 | 37.79 | 762.21 | 800.00 | 01-OCT-21 | 21,909.93 | 36.52 | 763.48 | 800.00 | 01-NOV-21 | 21,146.45 | 35.24 | 764.76 | 800.00 | 01-DEC-21 | 20,381.69 | 33.97 | 766.03 | 800.00 | 01-JAN-22 | 19,615.66 | 32.69 | 767.31 | 800.00 | 01-FEB-22 | 18,848.35 | 31.41 | 768.59 | 800.00 | 01-MAR-22 | 18,079.77 | 30.13 | 769.87 | 800.00 | 01-APR-22 | 17,309.90 | 28.85 | 771.15 | 800.00 | 01-MAY-22 | 16,538.75 | 27.56 | 772.44 | 800.00 | 01-JUN-22 | 15,766.31 | 26.28 | 773.72 | 800.00 | 01-JUL-22 | 14,992.59 | 24.99 | 775.01 | 800.00 | 01-AUG-22 | 14,217.58 | 23.70 | 776.30 | 800.00 | 01-SEP-22 | 13,441.28 | 22.40 | 777.60 | 800.00 |
---|