Python Guide to Accompany Introductory Econometrics forFinance

ArXiv ID: ssrn-3475303 “View on arXiv”

Authors: Unknown

Abstract

This free software guide for Python with freely downloadable datasets brings the econometric techniques to life, showing readers how to implement the approaches

Keywords: Python, econometric techniques, software guide, dataset, data analysis, Multi-Asset

Complexity vs Empirical Score

• Math Complexity: 5.0/10
• Empirical Rigor: 7.0/10
• Quadrant: Street Traders
• Why: The paper is a practical Python guide with downloadable datasets and implementation code, indicating high empirical rigor, while the mathematics is introductory and applied, placing it in the low-to-moderate range.

  flowchart TD
    A["Research Goal: <br>Implement Econometrics for Finance"] --> B["Data/Inputs: <br>Freely Downloadable Datasets"]
    B --> C["Methodology: <br>Apply Econometric Techniques"]
    C --> D["Computational Process: <br>Python Implementation"]
    D --> E["Outcome: <br>Multi-Asset Data Analysis"]
    E --> F["Deliverable: <br>Software Guide & Insights"]