Why is Excel considered the source of truth in this skill?

In many business contexts, complex financial logic is first signed off in Excel models. This skill ensures that production code implementations produce equivalent results within defined tolerances.

What financial invariants does this skill enforce?

It focuses on mass conservation (ensuring total distributions match contributions plus remaining balance) and monotonicity (ensuring cumulative values like DPI do not decrease over time).

How does it handle IRR/XIRR discrepancies?

The skill provides specific solver configurations, such as max iterations and convergence thresholds, to align code-based solvers with the behavior of Excel's XIRR function.

Does this skill help with different day count conventions?

Yes, it provides guidance for documenting and enforcing consistency across conventions like ACT/360, ACT/365, and 30/360 to prevent interest calculation errors.

Financial Calculation Correctness & Excel Parity

Name: Financial Calculation Correctness & Excel Parity
Author: nikhillinit

bynikhillinit

Security & Testing

Validates financial logic against Excel models to ensure numerical accuracy and parity across IRR, waterfalls, and complex cash flow computations.

About

This skill provides a standardized framework for developers to maintain high-fidelity financial calculations within their code by establishing Excel as the primary source of truth. It enforces critical invariants like mass conservation and monotonicity while providing specific guidance on day count conventions, precision tolerances, and solver configurations. It is particularly useful for teams building investment platforms, fintech applications, or automated reporting systems where rounding errors or algorithmic discrepancies between code and spreadsheets can lead to significant financial risk.

Key Features

Enforces mass conservation and monotonicity invariants to prevent logical errors in distribution waterfalls.
Provides standardized precision and tolerance norms for currency, IRR, and intermediate calculations.
Standardizes solver configurations for Newton-Raphson and Bisection methods to ensure consistent XIRR results.
Establishes a structured Excel Parity Workflow to compare code results against vetted spreadsheet models.
Defines Truth Case validation rules for documenting and auditing calculation changes and intentional deviations.
0 GitHub stars

Use Cases

Auditing existing financial codebases for numeric drift and mass conservation failures during refactoring.
Building investment waterfall distribution systems that must match audited legal Excel models.
Developing fintech reporting tools that require precise XIRR calculations across varying day count conventions.

About

Key Features

Enforces mass conservation and monotonicity invariants to prevent logical errors in distribution waterfalls.
Provides standardized precision and tolerance norms for currency, IRR, and intermediate calculations.
Standardizes solver configurations for Newton-Raphson and Bisection methods to ensure consistent XIRR results.
Establishes a structured Excel Parity Workflow to compare code results against vetted spreadsheet models.
Defines Truth Case validation rules for documenting and auditing calculation changes and intentional deviations.
0 GitHub stars

Use Cases

Auditing existing financial codebases for numeric drift and mass conservation failures during refactoring.
Building investment waterfall distribution systems that must match audited legal Excel models.
Developing fintech reporting tools that require precise XIRR calculations across varying day count conventions.