From Simulation to Success: +17% Return in TradingView’s 2025 Global Challenge

In April 2025, more than 38,000 traders from around the world joined TradingView’s global trading competition, The Leap. One of them was a Nurp team member — and they delivered big.

Using a simulated $250,000 account, with access to 13 tradable instruments across forex, crypto, indices, and commodities, participants were tasked with navigating real market volatility under strict, structured trading conditions.

Our trader rose to the challenge, generating a +17.69% return and finishing in the top 10% globally.

Proving Performance Under Pressure

This wasn’t just another paper trading contest. Traders had to follow predefined rules, maintain consistency over a month, and adapt to rapidly shifting market conditions — all while competing with thousands of others globally.

A +17% return in this environment doesn’t just represent smart trades – it reflects discipline, timing, and a deep understanding of risk.

Read More: Machine Learning vs Traditional Trading: A Performance Analysis

Why This Matters

Results like this speak for themselves:

  • Top 10% out of 38,000+ global participants 
  • $44,000+ in realized profits (simulated capital) 
  • Consistent strategy execution across volatile market phases 

Whether you’re an active trader, an investor evaluating performance systems, or someone curious about how structured trading performs under pressure — this is proof that strategy beats emotion.

Join the Conversation

Want to learn how strategies like this are built, tested, and executed? Stay tuned for breakdowns, behind-the-scenes insights, and performance reviews from the Nurp team.

For now, we’re proud to celebrate a standout achievement in a truly competitive global environment – and we’re just getting started.

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Abhayjit Anand
Abhayjit | Crypto Trading Insights

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Abhayjit | Crypto Trading Insights

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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.