financial-engineering

Collection of notebooks about quantitative finance, with interactive python code.

C++ DataFrame for statistical, financial, and ML analysis in modern C++

Various Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau

Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

A Deep Graph-based Toolbox for Fraud Detection

Applications of Monte Carlo methods to financial engineering projects, in Python.

Robust and flexible Python implementation of the willow tree lattice for derivatives pricing.

Machine learning models for time series analysis

A collection of methods for solving Finance/Accounting equations, implemented in C#.

OptionStratLib is a comprehensive Rust library for options trading and strategy development across multiple asset classes.

Python Financial ENGineering (PyFENG package in PyPI.org)

Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio (Sangadiev et al., 2020), etc.

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.

A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X

C++ Matrix -- High performance and accurate (e.g. edge cases) matrix math library with expression template arithmetic operators

Collection of notebooks and scripts related to financial engineering, quant-research and algo-trading.

😲🤑Method for Investors and Traders to make Buying and Selling Decisions. 😄Fundamental hare Market Analysis is about using Real data to evaluate a Stock's Value📊 📈 📉

Demeter is a blockchain backtesting tool that supports trading types such as swaps, liquidity provider, lending, and options. It is compatible with markets including Uniswap, GMX, Aave, Deribit, and Squeeth.

Markowitz portfolio optimization on synthetic and real stocks

applications for risk management through computational portfolio construction methods