parandcor's Stars
Machine-Learning-Tokyo/AI_Curriculum
Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.
arwes/arwes
Futuristic Sci-Fi UI Web Framework.
jamesmawm/High-Frequency-Trading-Model-with-IB
A high-frequency trading model using Interactive Brokers API with pairs and mean-reversion in Python
hardmaru/slimevolleygym
A simple OpenAI Gym environment for single and multi-agent reinforcement learning
changwookjun/StudyBook
Study E-Book(ComputerVision DeepLearning MachineLearning Math NLP Python ReinforcementLearning)
parandcor/RSI-Analysis
The objective is to understand how many companies are above or below a specific threshold to understand the level of overbought or oversold of the companies within a specific index
mChataign/DupireNN
Neural network local volatility with dupire formula
grananqvist/Awesome-Quant-Machine-Learning-Trading
Quant/Algorithm trading resources with an emphasis on Machine Learning
leeaaron629/ML-in-Trading
stefan-jansen/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
cantaro86/Financial-Models-Numerical-Methods
Collection of notebooks about quantitative finance, with interactive python code.
areed1192/td-ameritrade-python-api
Unofficial Python API client library for TD Ameritrade. This library allows for easy access of the Standard API and allows users to build data pipelines for the Streaming API.
parandcor/Data-Science--Cheat-Sheet
Cheat Sheets
borisbanushev/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.
je-suis-tm/quant-trading
Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, Shooting Star, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD
wilsonfreitas/awesome-quant
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
firmai/financial-machine-learning
A curated list of practical financial machine learning tools and applications.
parandcor/myBooks-1