Skip to content

Aditya-Gupta09/Portfolio-Performance-Analyzer

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

14 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Smart-Portfolio-Analyzer

Smart Portfolio Performance Analyzer

🚧 Status: Actively Developing

Overview

Smart Portfolio Performance Analyzer is a modular Python-based analytics tool designed to compute portfolio returns, risk metrics, sector exposure, and benchmark-relative insights in a structured, client-ready format.

This project focuses on combining financial theory with clean software architecture. It is structured for scalability and future production-grade implementation.


Problem Statement

Portfolio performance reporting is often fragmented across spreadsheets and ad-hoc scripts.

This project aims to build a clean analytics engine that:

  • Computes annualized returns and volatility
  • Measures Sharpe ratio and drawdowns
  • Evaluates sector allocation
  • Compares performance against benchmarks
  • Generates structured performance reports

Architecture

The system follows a layered design:

Core Layer (src/core)

  • Return calculations
  • Risk metrics
  • Drawdown analysis
  • Attribution logic

Data Layer (src/data)

  • Market data ingestion
  • Portfolio loader
  • Sector mapping

Reporting Layer (src/reporting)

  • Chart generation
  • PDF reporting
  • Performance commentary

Current Status

✔ Repository structure finalized
✔ Modular architecture defined
🔄 Core analytics modules under development
🔄 Reporting engine in progress


Roadmap

See docs/roadmap.md


Technologies

  • Python
  • pandas
  • numpy
  • yfinance
  • matplotlib
  • fpdf
  • streamlit (planned)

Motivation

This project bridges financial analytics and system design, simulating portfolio reporting workflows used in buy-side and wealth management environments.

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages