quantitative-development

Implementation of Trading Strategies for Backtesting in MetaTrader 5 (MT5) Using MQL5 Programming Language – Free Open-Source Trading Bots (Expert Advisors) for MT5

QuantLib implementation in ImGui

Trading platform infrastructure with separate server and client components

📈 A high-frequency trading engine designed to simulate ingesting market data and execute trades with microsecond latency.

Demonstrates applied data science techniques (Jupyter Notebook) for financial or risk reporting, including visualization and statistical inference.

A backtesting and performance analysis package

Fetches market data from the Alpha Vantage API, calculates daily returns for a portfolio of stocks, and computes the Value at Risk (VaR) at a 95% confidence level.

Pro Trader Strategy Script is an automated trading tool designed to help traders analyze market trends and execute strategy rules efficiently. It offers customizable indicator inputs, clear buy/sell signal alerts, and built-in risk management parameters to help optimize your algorithmic trading workflow across various platforms.

Looks like nautilus trader is best for live trading, and bt is good for visualizing

High-performance Limit Order Book (LOB) matching engine in C++20

Universal Trading Bot for automated multi-platform execution. Advanced algorithmic trading framework with seamless API integration for Forex, MetaTrader 5 (MT5), MetaTrader 4 (MT4), Crypto exchanges, and custom broker platforms.

Customer-side copy trading execution agent.

Project 1 of the 2020 Northwestern Financial Technology Bootcamp. We built a functional quantitative trading system that implements strategies researched and tested in Quantopian. Those strategies are then executed in Alpaca- the commission-free stock trading API.

A Python research lab for forex pairs trading using Engle-Granger cointegration, OLS hedge ratios, z-score mean reversion, walk-forward validation, and pair scanning.

Limit and market order book in Java with unit test