The programming languages most widely used for automated and algo trading are Python, C++, Java, C#, and increasingly Rust, with
The three most widely deployed forex automated trading strategies are trend-following systems on major currency pairs, mean-reversion systems on range-bound
The five best algo trading books to read are “Advances in Financial Machine Learning” by Marcos Lopez de Prado, “Algorithmic
Backtesting is necessary but not sufficient for automated trading because backtests systematically overstate live performance through overfitting, look-ahead bias, idealized
Quant trading strategies for beginners include trend following, mean reversion, momentum, breakout strategies, and pairs trading. These five strategy categories
Gold trading is the practice of buying and selling gold through physical, paper, or derivative instruments to profit from changes
The top short-term trading instruments for algo trading bots are major forex pairs, cryptocurrency markets, liquid equity ETFs, index futures,
Market data analysis is the foundation of every quantitative trading strategy. Without clean, well-structured market data, no model, however sophisticated,
AI Quantitative
Researcher
Bingham Zhou
Bingham Zhou, CFA, has over 15 years of experience as a quantitative researcher. His expertise spans systematic equity strategies, CTA trend-following, and interest rate proprietary trading in both U.S. and Asian markets. He holds advanced degrees from MIT, Carnegie Mellon, and Yale.
Greg Doscher was a CFO for many years who built out many quantitative strategies and investment tools to manage and enhance risk adjusted returns in the company’s pension plan. Prior to joining Nurp, he consolidated his skills in coding and discretionary trading to develop a comprehensive and fully automated algorithmic trading system deployed across 200+ futures markets and cryptocurrencies that encompassed all of the trading strategies he had honed over the last 22 years in finance
Marcin was Head of Quant IT at the USD 4bn+ CERN Pension Fund, where he spent nearly a decade building quantitative asset allocation systems and implementing algorithmic investment strategies for a multi-asset institutional portfolio.Before joining Nurp Marcin was also Senior Quant Strategist at Evooq, a Swiss-based fund managing four strategies across equities, gold, and equity derivatives.Marcin holds a degree in Computer Science an MBA from the University of Geneva and the Certificate in Quantitative Finance (CQF).
Abhayjit Anand
Abhay has worked with Nurp since 2022. As a Product Strategist, he focuses on building, refining, and commercializing algorithmic trading strategies. He brings seven years of experience in financial trading – combining macro research, technical analysis, quantitative strategy development, and market psychology. Alongside his work at Nurp, Abhay also serves as an Investment Analyst at Orca Capital. Before entering financial markets professionally, he spent eight years at IBM, including three years in the AI & data division as a Delivery Lead managing complex implementation projects.
