Alex Zhong: How to Build Quant Trading Strategies From Scratch

Alex Zhong joins The Sophron® Network to discuss how quantitative traders build systematic strategies from scratch — from signal discovery and model validation to portfolio construction across dozens of uncorrelated strategies. The conversation covers what separates alphas that survive out-of-sample from those that don't, why crypto markets offer unique advantages for smaller systematic traders, and how to manage a portfolio of 50+ strategies in a 24/7 market.Alex Zhong is a quantitative trader focused on systematic strategies in crypto markets. At WorldQuant, one of the largest quantitative investment firms in the world, he ranked #27 globally and #2 in China on the Alpha Creation Engine (ACE), and was a Top-5 global out-of-sample performer. His experience includes research with Trexquant Investment, where he built a Sharpe 2 equity earnings prediction strategy that went live, and participation in DRW's Crypto Prediction Challenge, where he ranked in the global Top 50. Alex holds an MSc in Quantitative Finance from the University of Amsterdam and a BSc in Applied Physics from South China University of Technology. He currently runs his own systematic crypto trading desk, managing over 50 strategies in a risk parity framework.We examine how to build a trading strategy from a simple baseline and iterate toward a mature system, covering the full pipeline from data collection and feature engineering to ML modeling and position management. Alex explains why economic intuition matters more than raw backtest performance, how indirect overfitting through multiple testing can fool even experienced researchers, and why studying your losers is one of the best ways to improve a system. The conversation then shifts to crypto markets — why they offer a more level playing field for small players, how sentiment and momentum dynamics differ from value-driven equity markets, and how to manage extreme volatility and tail risk. We conclude with practical advice for students and aspiring quants on breaking into the industry.Follow Alex Zhong on LinkedIn: linkedin.com/in/alex-zhongs/Core Timestamps00:44 – Introduction to Alex Zhong and his background03:20 – Differences between building strategies independently vs. at a professional firm04:46 – How out-of-sample overfitting happens indirectly06:10 – Building a Sharpe 2 strategy from scratch: feature design to position management09:21 – Distinguishing real alpha from overfitting11:44 – Why Alex transitioned from equities to crypto14:30 – The DRW Crypto Prediction Challenge approach18:25 – Red flags that signal a strategy will fail20:17 – Managing thinning margins in high-frequency trading22:57 – Building and managing a portfolio of 50+ strategies28:35 – Managing correlation between strategies in tail-risk scenarios31:17 – Position sizing framework: volatility targeting vs. Kelly criterion36:21 – Biggest lesson from going live: when backtests don't translate38:33 – Advice for students breaking into quantitative finance42:08 – Predictions for crypto markets in the next 3–5 years46:39 – Rapid fire: book recommendation, programming language, best adviceMain Topics Covered• Building quantitative strategies from scratch using iterative improvement• Out-of-sample validation and the dangers of indirect overfitting• Economic intuition vs. data mining in strategy development• Why crypto markets are more accessible for small systematic traders• Managing a portfolio of 50+ strategies in a risk parity framework• Position sizing and volatility targeting in 24/7 crypto markets• Detecting bad strategies early through parameter sensitivity testing• The transition from paper trading to live execution• Career advice for aspiring quantitative tradersConnect With UsInstagramLinkedInXSubscribe for more conversations at the intersection of markets, research, and technology.