Resources to Prepare for Quant Developers/ Quantitative Researcher/ Quantitative Trader/ Quant Analyst/ Software Engineers in Quant Trading Firms, HFTs and Hedge Funds
FinnewsHunter: Multi-agent financial intelligence platform powered by AgenticX. Real-time news analysis, sentiment fusion, and alpha factor mining.
A collection of scripts and notebooks to help you get started quickly.
Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader
This is my github repository where I post trading strategies, tutorials and research on quantitative finance with R, C++ and Python. Some of the topics explored include: machine learning, high frequency trading, NLP, technical analysis and more. Hope you enjoy it!
Python Market Simulation Engine Built on top of Generative AI
Quantitative Finance & Statistics Projects. Topics including multiple linear regression, variance and instability estimates, display methodology.
IB Gateway in a headless docker container.
The official example scripts for the Numerai Signals Data Science Tournament
MFE admission prediction & program ranking — logistic regression on 6,984 records across 28 programs
High-performance C++ Trading Engine
Streamlit IV surface visualizer (Yahoo Finance + Black–Scholes). Explore IV vs expiry and strike/log-moneyness.
I did this project as one of the parts from a Python test for my Master's degree. The objective was to practice the treatment of financial time series.
RustyQlib: A quant library for derivative pricing and quantitative finance
High-Performance Automatic Differentiation for Python
Engine and UI for tracking trading performance across stocks and derivatives (options, futures, & future options).
The open-source, fault-tolerant trading kernel behind XaiAlgo. Features separate strategy logic, ghost-order detection, and auto-backfilling. Built for rock-solid stability on Linux.
This project aims to construct the Equity Implied Volatility surface under the Stochastic Volatility Inspired (SVI) model.
Technical analysis in R: indicators, candlestick pattern detection, and interactive trading charts.
Trading Evolved book code
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