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BUG: rate returning incorrect value #126
Description
Describe the issue:
I found a situation where npf.rate is not returning the same thing as my BA II Plus financial calculator or npf.irr. Even setting guess to the correct value does not get the expected answer.
Reproduce the code example:
import numpy_financial as npf
# This returns -1.8964420585461792
npf.rate(8, -440_000, 263_175, 25_500)
# This returns 0.5838779110248231 - Matches financial calculator
npf.irr([-440_000, 263_175, 263_175, 263_175, 263_175, 263_175, 263_175, 263_175, 263_175 + 25_500])
# Still returns -1.8964420585461792
npf.rate(8, -440_000, 263_175, 25_500, 0, 0.5838779110248231)Error message:
No response
Runtime information:
print(numpy.version)
1.26.4
print(sys.version)
3.12.3 (main, Apr 9 2024, 08:09:14) [Clang 15.0.0 (clang-1500.3.9.4)]
print(numpy.show_runtime())
WARNING: threadpoolctl not found in system! Install it by pip install threadpoolctl. Once installed, try np.show_runtime again for more detailed build information
[{'numpy_version': '1.26.4',
'python': '3.12.3 (main, Apr 9 2024, 08:09:14) [Clang 15.0.0 '
'(clang-1500.3.9.4)]',
'uname': uname_result(system='Darwin', node='HCOB-003406.local', release='23.4.0', version='Darwin Kernel Version 23.4.0: Fri Mar 15 00:12:49 PDT 2024; root:xnu-10063.101.17~1/RELEASE_ARM64_T6020', machine='arm64')},
{'simd_extensions': {'baseline': ['NEON', 'NEON_FP16', 'NEON_VFPV4', 'ASIMD'],
'found': ['ASIMDHP'],
'not_found': ['ASIMDFHM']}}]
None
Context for the issue:
No response
Activity
Kai-Striega commentedon Jun 14, 2024
Hi @jestover,
Thanks for reporting this, I'll take a look at it.
What version of NumPy-Financial are you using?
jestover commentedon Jun 18, 2024
I'm using version 1.0.0
lcrmorin commentedon Sep 19, 2026
The main policy question is whether to restrict the default search to
r > -1, and howguessshould guide selection when multiple roots exist. We should also handle the zero-rate limit explicitly and check the equation residual before accepting convergence.I tested Brent, TOMS 748, and bisection on a sign-changing bracket
[0, 2]. All found0.583877911024823for the corrected inputs.Would Brent’s method or safeguarded Newton with bisection fallback be worth considering? The latter could reuse the existing derivative without adding a SciPy dependency.
lcrmorin commentedon Sep 28, 2026
I’ve opened #158 to enforce
r > -1for returned rates. Lower roots can satisfy the equation algebraically, but don’t make sense as compounding rates for conventional loans or investments.The change keeps Newton for ordinary cases and falls back to bracketed bisection when it converges outside that domain. Guesses at or below −1 are rejected.
The corrected example returns
0.583877911, and the original inputs return1.671183828.All tests pass locally.