Quantitative Trading in the Forex Market: Strategies The Big Players Use

Data-driven decisions. Automated execution. Smarter trades.
This in-depth guide explores the core principles of quantitative trading, offering actionable strategies for the modern forex trader. Learn how to apply statistical models, mathematical analysis, and automated systems to navigate today’s fast-moving markets with confidence.

What You’ll Learn:

  • The foundations of quantitative trading and its role in the forex market

  • How to build and test rule-based trading systems

  • An introduction to statistical arbitrage, momentum strategies, and mean reversion

  • The role of algorithmic trading software in executing quantitative models

  • Why data, not emotion, should drive your decisions

  • How machine learning trading algorithms are evolving the edge

Who This Is For:

  • Experienced traders seeking a more scientific, structured approach

  • Investors exploring forex algo trading and model-driven execution

  • Users of automated trading bots who want to understand what’s under the hood

  • Anyone researching quantitative hedge fund strategies for personal use or portfolio expansion

Why It Matters:

In today’s global forex markets, speed, accuracy, and objectivity are essential. This eBook empowers you to approach trading like a quant — using systems, not guesswork, to pursue consistent results.

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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.

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Quant–Investment Strategist
Greg doscher

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

Quant–Investment Strategist
Marcin Borratynski

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).

Product Manager

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.