Pinned Repositories
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's Repositories
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