The Ultimate Tech Dictionary

Tech terms, made simple.
The Ultimate Tech Dictionary is your go-to guide for understanding the often confusing world of modern technology. Whether you’re diving into algorithmic trading, exploring machine learning, or just trying to keep up with fintech jargon, this eBook delivers clear, concise definitions for every essential term.

What You’ll Learn:

  • Easy-to-understand definitions of 100+ essential tech and finance terms

  • Key concepts in algorithmic trading, AI trading bots, and machine learning

  • Explanations of tools and platforms used in forex trading and crypto investing

  • A quick-reference resource ideal for both beginners and professionals

  • The language of innovation — decoded and demystified

Who It’s For:

  • New traders navigating complex systems and strategies

  • Investors researching trading algorithms and autonomous trading platforms

  • Financial professionals staying current on fintech and trading tech

  • Anyone confused by terms like “backtesting,” “latency,” or “quantitative model”

Why It Matters:

Understanding the terminology behind today’s most powerful technologies is the first step to using them effectively. This eBook ensures you speak the language of innovation — whether you’re building a system or evaluating one.

Download The Ultimate Tech Dictionary
Demystify trading and tech terms so you can move forward with clarity and confidence.

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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.