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-tensorflow-1.x-deep-learning-recipes-for-artificial-intelligence-applications-v-

Code Repository for TensorFlow 1.X Deep Learning Recipes for Artificial Intelligence Applications (v), Published by Packt

2016.m3.tqf-ml

2016-17 Module 3, Topics in Quantitative Finance: Machine Learning for Finance

2016.m3.tqf-ml.project

2017.m3.tqf-ml

2017-18 Module 3 (Spring), Topics in Quantitative Finance: Machine Learning for Finance

2018-summer-main

6883-cpp-in-finance

active_portfolio_management

NYU FRE-GY 9713 Active Portfolio Management

adv_fin_ml_exercises

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

advanced-financial-economics

Repo of homework and research code for ECON 525: Advanced Financial Economics

agents

TF-Agents is a library for Reinforcement Learning in TensorFlow

ai-for-trading

code repository for Udacity nanodegree Artificial Intelligence for Trading

ai-for-trading-1

Artificial Intelligence for Trading

ai-for-trading-2

Udacity AI for Trading programme. Using AI to generate signals for Risk-Factor models in quantitative trading

ai_for_trading_udacity_nanodgree

aind_p7_enhanced-alpha

combine signals on a random forest for enhanced alpha

aitnd_p7_combining_signals_for_enhanced_alpha

Udacity - AI for Trading Nanodegree - Term 2 - Project 7: Combining Signals for Enhanced Alpha

algo_trading_and_quant_strategies

Supplemental Material for Algorithmic Trading and Quantitative Strategies

algorithmic-portfolio-management-in-r-programming-language

The course, authored by Prof. Jerzy in NYU, applies the R programming language to momentum trading, statistical arbitrage (pairs trading), and other active portfolio management strategies. The course implements volatility and price forecasting models, asset pricing and factor models, and portfolio optimization. The course will apply machine learning techniques, such as backtesting (cross-validation) and parameter regularization (shrinkage).

algotrade

Jupyter notebook containing a backtested systematic trading strategy written in Python.

alphatrading

An workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implement APT model, BARRA's risk model and dynamic multi-factor model in this project.

amf_research

The Valuation of Convertible Bonds with Credit Risk (for Honours in Advanced Mathematics of Finance research project, at the University of the Witwatersrand)

artificial-intelligence-for-trading

Content for Udacity's AI in Trading NanoDegree.

assetpricing

assetpricing1

assetpricing2

create assetPricing2

assetpricingml

Codes for Empirical Stock Analysis: A comparative Analyses between CAPM and Machine Learning Algorithms

awesome-deep-reinforcement-learning-in-finance

🔬 A collection for those AI (RL / DL / SL / Evoluation / Genetic Algorithm) used in financial market. otherwise, we add Technology Analysis / Alpha Research / Arbitrage and other useful strategies tools & docs in quantitative finance market.

awesome-quantitative-bitcoin

A curated list for understanding bitcoin using quantitative methods

barra-model

An internship project: Implement Barra model to take risk or style factor attribution based on multi-factor model.

barra_risk

A risk evaluation program that follows BARRA's CNE6 and USE4 risk model to predict the risk and distribution of factors in a portfolio. Created by Rosemary He Sept. 2019, under Zhiqiang Zhang.