efpm04013 Goto Github PK

actor-critic-methods-paper-to-code

adv_fin_ml_exercises

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

advanced-python-programming

Course by David Beazley

backtrader

Python Backtesting library for trading strategies

cftc-cot

Parses historical and current CFTC Commitments of Traders reports into easy-to-use pandas dataframes

coroutines

A Curious Course on Coroutines and Concurrency - David Beazley

dabeaz-compilers

Code for David Beazley's compilers course, June 2019

dark-pool-buying

Calculates estimate of dark pool buying based on publicly available exchange data

davebeaz-advcourse

Material for a course given by David Beazley https://www.dabeaz.com/. Advanced Concepts.

dbeaz_sicp

Notes from David Beazley SICP course

deep-q-learning-paper-to-code

deep-q-learning-trading-system-on-hk-stocks-market

Deep q learning on determining buy/sell signal and placing orders

deepreinforcementlearninginaction

Code from the Deep Reinforcement Learning in Action book from Manning, Inc

dnnrec_eswa

dstrading

Digital Signal Trading (John Ehlers indicators)

ehlers-homodyne-discriminator-python

First test case

elitequant

A list of online resources for quantitative modeling, trading, portfolio management

experiment3

featurebyte

Python Library for FeatureOps

finalexp34

financial-astrology-machine-learning

We use advanced machine learning techniques to build models that correlate planet cycles and aspects (cosmic energy) with markets price action to forecast the daily trend direction. Join us at Discord:

financial-data

Intraday 1 minute pricing data for S&P 500, NIKKEI 225, DAX 30 and more 📈 💶

financial-data-structures

financial-machine-learning

A curated list of practical financial machine learning tools and applications.

financial-machine-learning-research

go_ehlers_indicators

A collection of John Ehlers technical analysis indicators / Filters written in pure go, with links to original papers

hangukquant.github.io

Documentation for hangukquant/quantpylib

hudson-and-thames-research

Research Repo (Archive)

ibswigsystematicexamples

Automatically exported from code.google.com/p/ibswigsystematicexamples

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.