client success story
Executive Summary
Richard is a retired software and auto-retail founder who sold his businesses in 2016 and wanted more than his bank’s 3% yield, without sitting in front of a screen all day. Eighteen months after adopting Nurp’s Intelligent Trader suite and running additional test capital on the Argos trading algorithm, he now manages more than USD 3.5 million, checks the dashboard for only 15 minutes daily, and sees a steady 3–5% monthly return, with small 2x risk test accounts occasionally topping 10% in a single month.
Retired Entrepreneur
18 months
Intelligent Trader portfolio with Argos
(one test account at 2x risk)
~ $3.5 million
The Challenge
After exiting two companies – including the largest independent used-car dealer in the U.S. – Richard needed his nest egg to compound meaningfully yet leave time for family. Eight-hour trading sessions were unsustainable, and parking cash at 3% interest risked erosion by spending and inflation.
A web search for “smart algorithmic trading” led him to Nurp’s third-party-verified MyFXBook data. One short onboarding call linked his brokerage to the master accounts; since then, daily involvement has dropped to a quick connectivity and balance check.
3-5%
~ 10%
~ $3.5 million
Recovered roughly half of a self-induced $600k drawdown within weeks
15 minutes
Argos
Qualitative benefits
Those published results showed a robust, patient strategy – and that’s exactly what I’m experiencing
– Richard
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.
