Tutorials for SimFin - Simple financial data for Python

Jupyter notebooks, accompanying the FinDS Python repo: contains code examples and results for 30+ financial data science projects

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

notebooks created on pluto

Explore OpenBB SDK without having to install anything on your local machine. You just need a GitHub and a GitPod account.

Notebooks documenting different endpoints and parsing methods for SEC data

A collection of IPython notebooks for scraping and cleaning publically available U.S. government data

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

Jupyter notebook for the Kaggle task "Company Bankruptcy Prediction" - all relevant info and code are contained in the notebook

2022년 1학기 금융시장빅데이터분석 강의자료 및 jupyter notebook 실습 파일

This is a financial time series lab in Jupyter notebook. You may treat it as a live cheat sheet.

This repository features notebooks and datasets for predicting Tesla (TSLA) stock prices using LSTM models. Explore historical data, forecast trends, and gain insights into TSLA's market movements.

Here you can find jupyter notebooks to visualiza data related to financial markets, such as equity returns, volatilities, payoffs, etc

This repository contains an algorithmic trading project whose aim is to detect automatically divergences between a given asset, an a given momentum indicator. The algorithm is still to improve, and its efficiency and robustness to be tested (See the Notebook file in the Trading_project folder).

This repository offers a detailed exploration of KNeighbors Regressor techniques applied to time series data, specifically for financial forecasting. It features code and examples, including the KNeighbors_Model.ipynb notebook, showcasing data preprocessing, model training, and performance evaluation with visualization.

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.

This Jupyter Notebook analyzes NVIDIA (NVDA) stock data to compute risk metrics like Value at Risk (VaR), Expected Shortfall (ES), Sharpe Ratio, Sortino Ratio, Maximum Drawdown, and Beta. It includes visualizations of daily returns and metrics to assess the stock’s risk and performance.