OpenBB-finance/OpenBB
Nov 2024 – Nov 2024
1 Month active
Languages Used
Python
Technical Skills
Data AnalysisEconometricsPandasPythonStatistical ModelingStatsmodels
Hemu
PROFILE
Hemu
Developed and delivered a Variance Inflation Factor (VIF) calculation feature for the econometrics module in the OpenBB-finance/OpenBB repository, enabling users to assess multicollinearity in regression models. The implementation introduced a new Python function that computes VIF values and returns them as a pandas DataFrame, supporting robust model diagnostics for financial analysis. The work included comprehensive unit tests and detailed documentation updates to guide users through usage, edge cases, and interpretation. By focusing on statistical modeling and disciplined Git-based release practices, the contribution enhanced the reliability and transparency of econometric workflows without introducing or addressing any reported bugs.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
94
Activity Months1
Your Network
31 peopleSame Organization
@buffalo.edu18
Work History
November 2024
1 Commits • 1 Features
Nov 1, 2024In 2024-11, delivered the Variance Inflation Factor (VIF) calculation in the econometrics module for OpenBB, enabling users to quantify multicollinearity in regression models. The feature introduces a new function that computes VIF values and returns them as a DataFrame, with updated tests and accompanying documentation to reflect usage, edge cases, and interpretation. No major bugs were reported this month. Impact: enhances model diagnostics and reliability of econometric analyses, empowering users to build more robust financial models and make better-informed decisions. Tech stack and skills demonstrated: Python, pandas DataFrame handling, unit testing, documentation, and disciplined Git-based release practices. Key commit: 6fa993d15a3176aaf3053de15ec4a56e9ef1d164
1 Commits • 1 Features
Nov 1, 2024In 2024-11, delivered the Variance Inflation Factor (VIF) calculation in the econometrics module for OpenBB, enabling users to quantify multicollinearity in regression models. The feature introduces a new function that computes VIF values and returns them as a DataFrame, with updated tests and accompanying documentation to reflect usage, edge cases, and interpretation. No major bugs were reported this month. Impact: enhances model diagnostics and reliability of econometric analyses, empowering users to build more robust financial models and make better-informed decisions. Tech stack and skills demonstrated: Python, pandas DataFrame handling, unit testing, documentation, and disciplined Git-based release practices. Key commit: 6fa993d15a3176aaf3053de15ec4a56e9ef1d164
November 2024
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data AnalysisEconometricsPandasPythonStatistical ModelingStatsmodels
Repositories Contributed To
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