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License: MIT License
An Elixir package for calculating XIRR.
License: MIT License
diregard
Describe the bug
Thanks for the library. We are currently using LegacyFinance.xirr()
which matches our expectations for the results. It is quite a bit slower than the newer version, but the slowness is unnecessary. Removing pmap
results in a dramatic speed up. As a test, I created a Finance
based on LegacyFinance
module that replaces pmap
with Enum.map
. This is the result using your benchmark:
##### With input date_values #####
Name ips average deviation median 99th %
finance 3.93 K 254.18 μs ±2.71% 252.99 μs 272.99 μs
ex xirr 3.25 K 307.28 μs ±12.77% 299.99 μs 421.99 μs
legacy finance 0.44 K 2284.52 μs ±6.76% 2273.99 μs 2761.35 μs
As you can see, there is an order of magnitude speedup simply by making this change.
I did some experimentation with Stream.map
as well, but it turned out that Enum.map
was the fastest.
Running this calculation results in an invalid value 0.006097 (correct value is closer to 0.120581416 according to google spreadsheets).
d = [{2038, 2, 4}, {2037, 11, 2}, {2037, 8, 2}, {2037, 5, 3}, {2037, 2, 4}, {2036, 11, 2}, {2036, 8, 2}, {2036, 5, 3}, {2036, 2, 5}, {2035, 11, 2}, {2035, 8, 2}, {2035, 5, 3}, {2035, 2, 4}, {2034, 11, 2}, {2034, 8, 2}, {2034, 5, 3}, {2034, 2, 4}, {2033, 11, 2}, {2033, 8, 2}, {2033, 5, 3}, {2033, 2, 4}, {2032, 11, 2}, {2032, 8, 2}, {2032, 5, 3}, {2032, 2, 5}, {2031, 11, 2}, {2031, 8, 2}, {2031, 5, 3}, {2031, 2, 4}, {2030, 11, 2}, {2030, 8, 2}, {2030, 5, 3}, {2030, 2, 4}, {2029, 11, 2}, {2029, 8, 2}, {2029, 5, 3}, {2029, 2, 4}, {2028, 11, 2}, {2028, 8, 2}, {2028, 5, 3}, {2028, 2, 5}, {2027, 11, 2}, {2027, 8, 2}, {2027, 5, 3}, {2027, 2, 4}, {2026, 11, 2}, {2026, 8, 2}, {2026, 5, 3}, {2026, 2, 4}, {2025, 11, 2}, {2025, 8, 2}, {2025, 5, 3}, {2025, 2, 4}, {2024, 11, 2}, {2024, 8, 2}, {2024, 5, 3}, {2024, 2, 5}, {2023, 11, 2}, {2023, 8, 2}, {2023, 5, 3}, {2023, 2, 4}, {2022, 11, 2}, {2022, 8, 2}, {2022, 5, 3}, {2022, 2, 4}, {2021, 11, 2}, {2021, 8, 2}, {2021, 5, 3}, {2021, 2, 4}, {2020, 11, 2}, {2020, 8, 2}, {2020, 5, 3}, {2020, 2, 5}, {2019, 11, 2}, {2019, 8, 2}, {2019, 5, 3}, {2019, 2, 4}, {2018, 11, 2}, {2018, 8, 2}, {2018, 5, 31}]
v = [-305, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, 188.0]
iex(91)> ExXirr.xirr(d, v)
{:ok, 0.006097}
Weirdly enough, if you just change the last -5 to -4.8 the calculation will return the expected value, like this.
d = [{2038, 2, 4}, {2037, 11, 2}, {2037, 8, 2}, {2037, 5, 3}, {2037, 2, 4}, {2036, 11, 2}, {2036, 8, 2}, {2036, 5, 3}, {2036, 2, 5}, {2035, 11, 2}, {2035, 8, 2}, {2035, 5, 3}, {2035, 2, 4}, {2034, 11, 2}, {2034, 8, 2}, {2034, 5, 3}, {2034, 2, 4}, {2033, 11, 2}, {2033, 8, 2}, {2033, 5, 3}, {2033, 2, 4}, {2032, 11, 2}, {2032, 8, 2}, {2032, 5, 3}, {2032, 2, 5}, {2031, 11, 2}, {2031, 8, 2}, {2031, 5, 3}, {2031, 2, 4}, {2030, 11, 2}, {2030, 8, 2}, {2030, 5, 3}, {2030, 2, 4}, {2029, 11, 2}, {2029, 8, 2}, {2029, 5, 3}, {2029, 2, 4}, {2028, 11, 2}, {2028, 8, 2}, {2028, 5, 3}, {2028, 2, 5}, {2027, 11, 2}, {2027, 8, 2}, {2027, 5, 3}, {2027, 2, 4}, {2026, 11, 2}, {2026, 8, 2}, {2026, 5, 3}, {2026, 2, 4}, {2025, 11, 2}, {2025, 8, 2}, {2025, 5, 3}, {2025, 2, 4}, {2024, 11, 2}, {2024, 8, 2}, {2024, 5, 3}, {2024, 2, 5}, {2023, 11, 2}, {2023, 8, 2}, {2023, 5, 3}, {2023, 2, 4}, {2022, 11, 2}, {2022, 8, 2}, {2022, 5, 3}, {2022, 2, 4}, {2021, 11, 2}, {2021, 8, 2}, {2021, 5, 3}, {2021, 2, 4}, {2020, 11, 2}, {2020, 8, 2}, {2020, 5, 3}, {2020, 2, 5}, {2019, 11, 2}, {2019, 8, 2}, {2019, 5, 3}, {2019, 2, 4}, {2018, 11, 2}, {2018, 8, 2}, {2018, 5, 31}]
v = [-305, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -4.8, 188.0]
iex(102)> ExXirr.xirr(d, v)
{:ok, 0.120448}
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