Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy

💵 AI-powered financial advisor that analyzes personal transaction data, generates insights, and provides personalized financial advice.

Notebooks based on financial machine learning.

notebooks created on pluto

zipline-broker Examples. Full notebooks plus python code for long term investment strategies using zipline based tools.

Two Jupyter Notebooks written in Python, treating of time series analysis with ARIMA and its seasonal counterpart.

End-to-end financial text-analysis using Bigdata API and the Bigdata-Research-Tools library. Ready-to-use notebooks with RAG & GenAI enabling thematic and risk screening, trend tracking, and automated report generation, extracting insights at scale.

Jupyter notebooks on Econophysics and financial data analysis concepts, including price dynamics modeling, portfolio optimization, and various correlation techniques. The notebooks were created as part of the Econophysics course at the UIB.

This repository contains a collection of Python scripts and Jupyter notebooks for analyzing financial data. Whether you're a data scientist, financial analyst, or just someone interested in finance, you'll find useful tools here to help you make sense of financial data.

EDA on Bank Loan Case Study

An example of working with financial data in elixir livebook (similar to jupyter notebooks).

Used SQL in Jupyter Notebooks to analyze and explore data on international debts and codes.

2022학년도 2학기 금융시장계량분석 수업자료 및 Jupyter Notebook 실습 파일

2022년 1학기 금융시장빅데이터분석 강의자료 및 jupyter notebook 실습 파일

SQL code in Jupyter notebooks for basic banking forecasting scenarios

Notebook to manage specific fundamental investment. Scraping financial statements for automatic valuation.

This repository contains solution notebooks for CL Financial Analysis internship. Certificate here :

Notebooks from the course "Python and Statistics for Financial Analysis", available on Coursera.

Credit lending analysis notebook demonstrating data-driven insights for evaluating customer loan eligibility.

I’ll be creating two financial analysis tools with a single Jupyter notebook: A financial planner for emergencies and retirement.