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hishamzain's Projects

algotradingrepolist

This repository contains basic information about different algotrading repo I like.

alphapy

Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost

binance-trading-bot

Automated Binance trading bot - Buy low/Sell high with stop loss limit/Trade multiple cryptocurrencies

blackbird

Blackbird Bitcoin Arbitrage: a long/short market-neutral strategy

cryptocurrency-trading-bots-python-beginner-advance

Crypto Trading Bots in Python - Triangular Arbitrage, Beginner & Advanced Cryptocurrency Trading Bots Written in Python

deepdow

Portfolio optimization with deep learning.

eiten

Statistical and Algorithmic Investing Strategies for Everyone

faker

A library for generating fake data such as names, addresses, and phone numbers.

financial-machine-learning

A curated list of practical financial machine learning tools and applications.

finrl

A Deep Reinforcement Learning Library for Automated Trading in Quantitative Finance. NeurIPS 2020. 🔥

finta

Common financial technical indicators implemented in Pandas.

hummingbot

Hummingbot: a client for crypto market making

jesse

An advanced crypto trading bot written in Python

machine-learning-for-trading

Code for Machine Learning for Algorithmic Trading, 2nd edition.

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

pyportfolioopt

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

qlib

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.

qlib-server

Qlib-Server is the data server system for Qlib. It enable Qlib to run in online mode. Under online mode, the data will be deployed as a shared data service. The data and their cache will be shared by all the clients. The data retrieval performance is expected to be improved due to a higher rate of cache hits. It will consume less disk space, too.

qqwing

QQwing is a Sudoku puzzle generator and solver.

quant-trading

Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD

stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

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.

zvt

modular quant framework.

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