goldenwalden

AA228-CS238-Student

Starter code and data files for AA228/CS238 at Stanford University

AATA-Solutions

Solutions to "Abstract Algebra Theory and Applications"

adversarial-policies

Find best-response to a fixed policy in multi-agent RL

alpaca-backtrader-api

Alpaca Trading API integrated with backtrader

attentive-neural-algo

Attentive neural processes for deep reinforcement learning

awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

BayesianOptimization

A Python implementation of global optimization with gaussian processes.

CCMLWI

Predicting the stock market with sentiment analysis and LSTM techniques

CppTrader

High performance components for building Trading Platform such as ultra fast matching engine, order book processor

MNIST-Classification-with-NeuralNet

MNIST Handwritten Digits Classification using 3 Layer Neural Net 98.7% Accuracy

goldenwalden/CppTrader

High performance components for building Trading Platform such as ultra fast matching engine, order book processor

goldenwalden/AA228-CS238-Student

Starter code and data files for AA228/CS238 at Stanford University

goldenwalden/adversarial-policies

Find best-response to a fixed policy in multi-agent RL

goldenwalden/alpaca-backtrader-api

Alpaca Trading API integrated with backtrader

goldenwalden/awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

goldenwalden/BayesianOptimization

A Python implementation of global optimization with gaussian processes.

goldenwalden/coronavirus-data

goldenwalden/CrossSection

Code to accompany our paper Chen and Zimmermann (2020), "Open source cross-sectional asset pricing"

goldenwalden/cs228-notes

Course notes for CS228: Probabilistic Graphical Models.

goldenwalden/CS238-2048

goldenwalden/DecisiveML

Exploration for machine learning

goldenwalden/Deep-Learning-in-Asset-Pricing

https://arxiv.org/abs/1805.01104

goldenwalden/DeepEarnings

goldenwalden/eiten

Statistical and Algorithmic Investing Strategies for Everyone

goldenwalden/gym-continuousDoubleAuction

A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray (RLLib) is used for training.

goldenwalden/High-Frequency-Trading-Model-with-IB

A high-frequency trading model using Interactive Brokers API with pairs and mean-reversion in Python

goldenwalden/homework

Assignments for CS294-112.

goldenwalden/homework_fall2019

goldenwalden/mlfinlab

Package based on the work of Dr Marcos Lopez de Prado regarding his research with respect to Advances in Financial Machine Learning

goldenwalden/multiagent-particle-envs

Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

goldenwalden/offline-rl

goldenwalden/Paper-Implementation-DSTP-RNN-For-Stock-Prediction-Based-On-DA-RNN

基於DA-RNN之DSTP-RNN論文試做(Ver1.0)

goldenwalden/pgmpy_notebook

Short Tutorial to Probabilistic Graphical Models(PGM) and pgmpy

goldenwalden/planet

Learning Latent Dynamics for Planning from Pixels

goldenwalden/reinforcement-learning-1

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

goldenwalden/reinforcement-learning-an-introduction

Python Implementation of Reinforcement Learning: An Introduction

goldenwalden/rmm.arl

Robust Market Making via Adversarial Reinforcement Learning

goldenwalden/stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

goldenwalden/trading-rl

Deep Reinforcement Learning for Financial Trading using Price Trailing @ ICASSP 2019

goldenwalden/VineCopula

Statistical inference of vine copulas