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adv_fin_ml_exercises

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

alternative-bars

Generate various Alternative Bars both historically and at real-time.

cap.octolane.com

decisiveml

Machine learning end-to-end research and trade execution

django-chartjs-example

How to Use Chart.js with Django

dsignals

Utilities and information for the signals.numer.ai tournament

feature-engineering-book

Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018

finance-news-aggregator

A news aggregator in python, that focuses primarily on business and market news sources.

home-assistantconfig

:house: Home Assistant configuration & Documentation for my Smart House. Write-ups, videos, part lists, and links throughout. Be sure to :star: it. Updated FREQUENTLY!

ibapi-tools

A set of simple tools to assist users of the Interactive Brokers API.

interactive-broker-python-api

A python packaged used to interact with the Interactive Brokers REST API.

interactive-brokers-api

A python application used to interact with the Interactive Brokers REST API.

kitchensink-ml

Machine learning strategy that trains the model using "everything and the kitchen sink": fundamentals, technical indicators, returns, price levels, volume and volatility spikes, liquidity, market breadth, and more. Runs in Moonshot. Utilizes data from Sharadar and IB.

machine-learning-for-asset-managers

Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.

meta-labeling

Code base for the meta-labeling papers published with the Journal of Financial Data Science

meta_labeling_simplified

Machine learning trading method using meta-labeling. You can see the details in 'Advances in Financial Machine Learning' by Lopez de Prado.

mlfinlab

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

numerai-guides

Repository for Numer.ai guides

pdf-lib

Create and modify PDF documents in any JavaScript environment

portfolio-optimization

A python application, that demonstrates optimizing a portfolio using machine learning.

project_next_13_ai_prompt_sharing

Next.js recently became the official React framework as outlined in React docs. In this course, you'll learn the most important Next.js concepts and how they fit into the React ecosystem. Finally, you'll put your skills to the test by building a modern full-stack Next 13 application.

python-bureau-economic-analysis-api-client

A Python API client used to pull and retrieve data from the US Bureau of Economic Analysis

python-feature-engineering-cookbook-second-edition

Python Feature Engineering Cookbook Second Edition, published by Packt

python-for-starters

A guide on how to get up and running with Python, VSCode, Git, & GitHub on Windows.

python-sec

A simple python library that allows for easy access of the SEC website so that someone can parse filings, collect data, and query documents.

python-trading-robot

A trading robot, that can submit basic orders in an automated fashion using the TD API.

research

Contains all the Jupyter Notebooks used in our research.

riskfolio-lib

Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

sp500-prediction-sentiment-xgboost

In this work an application of the Triple-Barrier Method and Meta-Labeling techniques is explored with XGBoost for the creation of a sentiment-based trading signal on the S&P 500 stock market index. The results confirm that sentiment data have predictive power, but a lot of work is to be carried out prior to implementing a strategy.

td-ameritrade-api

The unofficial Python API client library for TD Ameritrade. This library allows for easy access of the Standard REST API and Streaming API.