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book-mathematical-foundation-of-reinforcement-learning

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

crawlee-python-web-scrap

Crawlee—A web scraping and browser automation library for Python to build reliable crawlers. Extract data for AI, LLMs, RAG, or GPTs. Download HTML, PDF, JPG, PNG, and other files from websites. Works with BeautifulSoup, Playwright, and raw HTTP. Both headful and headless mode. With proxy rotation.

fin-ml

This github repository of "Machine Learning and Data Science Blueprints for Finance". Please star.

finanzascuantitativas

módulos de finanzas cuantitativas

handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

implementing-var-in-python

Implementing VaR in Python. Historical, Parametric and Monte Carlo Simulation Methods.

indicadores_tecnicos

islp_labs

Up-to-date version of labs for ISLP

moving-average-strategy

openbb

Investment Research for Everyone, Everywhere.

optionpricing_toolkit_python_package

pairs-trading-with-ml

pdf

Unir diferentes archivos pdf en uno solo.

portfolio-optimization-and-value-at-risk

Portfolio Optimization and Value at Risk using Monte Carlo Simulation and Scipy Optimize

portfolio-optimization-using-riskfolio-lib

Portfolio Optimization using Riskfolio-Lib

prueba

pyportfolioopt

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

pytube

A lightweight, dependency-free Python library (and command-line utility) for downloading YouTube Videos.

qstrader

QuantStart.com - QSTrader backtesting simulation engine.

quantitative_finance

Codes for all the concepts related to quantitative finance

regime_switch_model

Regime-Switching Model

stirring

What happens within your mug when you stir your coffee? In this OpenFOAM case we get to see this process unfold, courtesy of Computation Fluid Dynamics (CFD).

stock-prediction-using-markov-chain

We model stock market movements using a Markov chain process with discrete states for price changes. The study estimates transition probabilities from historical data to predict future stock behavior and assess stock performance. The algorithm shows a 50% accuracy in predicting stock movements for the next day and average of the next two days.

sunday-quant-scientist

A Free Newsletter for Quantitative and Algorithmic Trading, Portfolio Analysis, and Investing

tf-quant-finance

High-performance TensorFlow library for quantitative finance.

ucema-quant-ejercicios