Library term·FinTech & data science
Quantitative Finance Basics in Python
NumPy vectors for returns, pandas for panels, statsmodels for inference — clarity beats cleverness.
Authored by·Editorially reviewed
Onur Erkan YıldızFounder, Financial Engineer · CMB-licensed
Higher education in Financial Engineering and Money & Capital Markets. SPK (Turkey CMB) licence. 16 years across institutional markets, research, and quant-driven analytics.
Overview
Build pipelines: ingest → clean → feature → backtest → report. Version datasets and code together (DVC, git-lfs).Practical takeaway
Mind lookahead when aligning as-of dates for fundamentals.How this connects to Finvestopia
Conceptually aligned with Finvestopia Radar statistics — empirical, not narrative-only.Related entries
Educational content authored by our team — informational only, not investment advice.