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options-trading-strategies-in-python

Developing Options Trading Strategies using Technical Indicators and Quantitative Methods

pandas-ta

Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 130+ Indicators

pandas-technical-indicators

Technical Indicators implemented in Python using Pandas

plotly-tutorial

This Jupyter Notebook condenses the Plotly API into one easy to use document with examples

plotting_examples

50 common plots in matplotlib seperated by chart type/purpose.

pylivetrader

Python live trade execution library with zipline interface.

python-and-oop

Object-Oriented Programming concepts in Python

python-object-oriented-programming---4th-edition

Code Repository for Python Object-Oriented Programming - 4th edition, Published by Packt

python-programming-exercises

100+ Python challenging programming exercises

quantitative-big-imaging-2018

(Latest semester at https://github.com/kmader/Quantitative-Big-Imaging-2019) The material for the Quantitative Big Imaging course at ETHZ for the Spring Semester 2018

reddit-twitter-convo-data

riskfolio-lib

Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

second_strategy_aka_meta_labeling

Machine learning trading method using meta-labeling. You can see the details in 'Advances in Financial Machine Learning' by Lopez de Prado.

sigma_coding_youtube

This is a collection of all the code that can be found on my YouTube channel Sigma Coding.

solutions

Solutions for projects.

son_of_big_e

stats-maths-with-python

General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python

stock-market-trend-analysis-using-hmm-lstm

Stock Market Trend Analysis Using Hidden Markov Model and Long Short Term Memory

stock-selection-a-framework

This project demonstrates how to apply machine learning algorithms to distinguish "good" stocks from the "bad" stocks.

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.

stock_price_movement_prediction_rnn_cnn_ffnn

The random forest, FFNN, CNN and RNN models are developed to predict the movement of future trading price of Netflix (NFLX) stock using transaction data from the Limit Order Book (LOB).

tensorflow-examples

TensorFlow Tutorial and Examples for Beginners with Latest APIs

time-series-forecasting-of-amazon-stock-prices-using-neural-networks-lstm-and-gan-

Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then sentimental analysis is performed using news and reddit sentiments. GANs are used to predict stock data too where Amazon data is taken from an API as Generator and CNNs are used as discriminator.

trading-indicators-and-chart-patterns

ATR, SuperTrend, Heiken Ashi, Renko

trading-rules-using-machine-learning

This is my financial trading system using ML (Random forest & LSTM). Most of the methods are based on 'Advances in Financial Machine Learning' by Lopez de Prado.

trading_backtesting

Example of writing a backtesting framework from scratch

tutorials

Ipython notebooks for math and finance tutorials

tvdatafeed

A simple TradingView historical Data Downloader

twitch

Twitch stream notebooks

vggnet-smaller_version-on-mnist-dataset