#Financial-engineering
Showing 40 of 40 repositories tagged #financial-engineering, ranked by stars
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
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)
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.
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.
applications for risk management through computational portfolio construction methods
Discover how to leverage MATLAB for quantitative finance modeling
Open-source Python research library for DeFi strategies. Compose protocol-agnostic entities (lending, perps, DEX and LP) into typed strategies - backtest, simulate, track experiments.
This project is a Python-based trading simulator that allows users to simulate trading strategies, manage an order book, and interact with a mock trading environment using various algorithmic traders. The simulator includes a FIX (Financial Information eXchange) protocol handler, a market-making algorithm, and synthetic liquidity generation.
It is a Jupyter notebook that compares different trading strategies using technical analysis, machine learning, and deep learning methods.
using the Inverse-Transform method to speed up options pricing simulations in R
A community-curated vault of openly available resources that replicates the rigorous syllabus of top MFE / Quant Finance programs
MFE admission prediction — GPBoost model (AUC 0.723) on 12,800+ records, 29 programs, 930 LinkedIn profiles. Pure data-driven, no manual tuning.
Machine Learning for Quantitative Finance
'Portfolio Analysis, methods for portfolio optimization'
Undergraduate thesis, Seoul National University Dept. of Economics — "Modeling Volatility and Risk Spillover Between the Financial Markets of US and China Using GARCH Value-at-Risk Forecasting and Granger Causality."
Moody's Bond Rating Classifier and USPHCI Economic Activity Forecast Modeling
Quantitative Analysis & Trading of the Electricity Market
Quant finance Portal based on project BearAlpha. This project contains strategy back test framework with backtrader, database construct with BearAlpha, factor analyze based on BearAlpha, and financial researches on paper or report with research
Portfolio optimization package in Python.
Financial Engineering in R
Yahoo Finance Python Interface
Functions built on material from Columbia's Coursera courses on Financial Engineering and Risk Management (I & II).
XQRiskCore is a governance-grade risk control engine for trading — with unified trade approval, structured audit logging, role-based access control, and multi-layer enforcement.
exotx provides a simple and user-friendly interface for pricing and analyzing financial derivatives using QuantLib's advanced numerical methods.
options market making engine in C++20 — SVI vol surface, Black-Scholes pricing, lock-free SPSC queues, delta hedging, and real-time PnL attribution.
This project develops and fine-tunes a TimeSeriesTransformer model to forecast EURUSD 5-minute closing prices, serving as a modern counterpart to a baseline LSTM model
Neural network framework for volatility surface approximation and calibration. Supports rough Heston/Bergomi, random grids, multi-regime architectures.
Financial Machine Learning Repository
A lightweight RESTful simulator for option chains that evolves over time with each API request. Useful for testing trading algorithms, visualizations, and analytics pipelines without relying on real-time market data. NO PRODUCTION READY YET
Distributed market-making system. Avellaneda-Stoikov strategy with sub-microsecond C++ hot-path (431ns), event-sourced architecture, VPIN toxicity detection, QUIC mesh transport, real-time dashboard. Rust + C++17 FFI.
An options trading bot