Fact vs. Fiction – Quantitative Trading Myths Busted

Think you know quantitative trading? Think again.
This eye-opening guide breaks down the most common myths about quantitative trading, exposing false assumptions with real data, proven strategies, and expert analysis. Whether you’re skeptical or curious, this eBook will change the way you think about the future of trading.

What You’ll Learn:

  • The top misconceptions about quantitative and algorithmic trading

  • Why many traders misunderstand how trading algorithms work

  • Evidence-based insights into performance, risk, and accessibility

  • Real-world examples that separate hype from reality

  • How machine learning trading systems actually operate

  • What it takes to succeed with automated trading bots and quantitative strategies

Who It’s For:

  • Retail and institutional traders unsure if quant trading is “too complex”

  • Manual traders questioning whether automation can deliver real results

  • Investors researching alternative investments and forex trading algorithms

  • Anyone looking to make informed, fact-based trading decisions

Why It Matters:

In a space full of misinformation, clarity is power. This guide helps you cut through the noise and understand the true nature, potential, and limitations of quantitative trading — so you can invest with confidence.

Download Fact vs. Fiction – Quantitative Trading Myths Busted
Learn what’s real, what’s hype, and how to leverage the facts to your advantage.

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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.