Linear Algebra for Financial Data

Approved: No
Title: Linear Algebra for Financial Data
Category: Learning
Skill Level:
Beginner (304), Intermediate (305)

Description:
This project demonstrates how *core linear algebra concepts* can be applied
to real-world financial data using *least squares regression*.

The jupyter notebook formulates linear regression explicitly as a matrix
equation *Ax = b* and solves it using linear algebra, not black-box machine
learning libraries.

This is an *educational, beginner-friendly project* intended to bridge linear
algebra theory and practical data analysis.
*Why This Project Is Useful*

If you are learning linear algebra and wondering:

  * /Where does Ax = b show up in real problems?/
  * /What does least squares actually do geometrically?/
  * /How do regression coefficients relate to real data?/

This notebook answers those questions with a concrete financial example.
*What This Project Does*

  * Models *percentage price change (**change_pct**)* as a linear combination
    of market features
  * Constructs a *design matrix (A)* and target vector (b)
  * Solves an *overdetermined system* using the least-squares solution
  * Interprets regression coefficients in a financial context

The focus is on *understanding*, not prediction performance.
*Who This Project Is For*

  * Beginners learning linear algebra
  * Students applying math to real data for the first time
  * Anyone curious how regression emerges from linear algebra



Link to Resource:
- Linear-Algebra-for-Financial-Data (https://github.com/PrathyushTuraga/Linear-Algebra-for-Financial-Data)

Tags:
data-analysis (422), linear-programming (70), professional-development (18), python (69), statistics (877), supervised-learning (803)

Domain:
{Empty}

Would you like to associate this resource with an Affinity Group?: {Empty}