client success story
Executive Summary
Rohan is an experienced cloud engineer who used to trade futures manually after work but found emotions kept erasing his gains. Two months ago he funded an $85,000 account running Nurp’s Odyssey algorithm at a 2x risk multiplier.
The account briefly touched a ~10 % drawdown, then climbed back to break-even while he did nothing more than glance at MetaTrader during his daily hikes. Watching the strategy respect its long-term 4.9 % max drawdown (per 1x risk) has given him confidence to let the trading algorithm run unattended.
Cloud engineer & former manual
futures trader
2 months
Intelligent Trader portfolio with Odyssey algorithm (85k live account, 2x risk)
$85,000
The Challenge
Manual futures trading demanded constant attention and led to impulsive stop-loss changes that wiped out profits. Rohan wanted a probability-based system that could enforce strict risk limits without his supervision.
Rohan chose Odyssey after seeing its four-year MyFXBook record cap losses at just 4.9 %, a level that matched his risk appetite. During a single onboarding call the Nurp team linked his new Forex.com account to the master strategy, and he immediately doubled the default risk multiplier to 2× on his USD 85 000 balance. Since then the bot has run entirely unattended; Rohan’s “management” consists of a quick glance at MetaTrader on his phone—often mid-hike—simply to watch his automated “employee” at work.
“It is like having an employee that trades full-time for you – emotionless and precise.”
— Rohan
3-5%
~ 10%
~ $3.5 million
Recovered roughly half of a self-induced $600k drawdown within weeks
15 minutes
Argos
Qualitative benefits
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.
