About the Author
Michael Johnson spent over a decade on institutional trading desks before founding EAFree. As a quantitative analyst at Goldman Sachs and JP Morgan, he architected and ran algorithmic strategies allocating more than $200M across FX, rates, and equity index markets.
In 2019, after watching the retail Expert Advisor market flood with unverified, over-optimized strategies that quietly destroyed trader accounts, Michael founded EAFree with one thesis: every EA listed on the platform must pass institutional-grade vetting for code quality, risk parameters, and live-account performance — before a single retail trader is exposed to it.
Today Michael sets EAFree's product direction, owns the platform's risk and listing standards, and leads partnerships with regulated brokers and MetaQuotes. He still reviews flagged EA submissions personally when the vetting team escalates edge cases.
Outside EAFree he advises early-stage fintech founders on quantitative product design and contributes to open-source backtesting tooling.
Career Timeline
- 2019 — Present
Founder & CEO · EAFree
Built EAFree from zero to 12K+ active traders, 350+ vetted EAs, and operations in 45+ countries. Owns risk policy, listing standards, and broker partnerships.
- 2014 — 2019
Vice President, Quantitative Strategies · JP Morgan
Led a team of five quants designing systematic FX and rates strategies. Managed over $120M in algorithmic exposure across G10 currency pairs.
- 2009 — 2014
Associate, Algorithmic Trading · Goldman Sachs
Developed execution algorithms for the FX e-trading desk. Co-authored Goldman's internal volatility-adjusted position sizing model.
Academic Background
M.Sc. Financial Engineering
Columbia University
2009
B.Sc. Mathematics & Economics
University of Chicago
2007
Topics & Specialisations
Quantitative Trading
Systematic strategy design, factor modelling, and statistical arbitrage on liquid FX and index instruments.
Risk Management
Volatility-adjusted position sizing, drawdown control, and tail-risk hedging frameworks used across institutional and retail EAs.
Algorithmic Strategy
Execution algorithms, slippage modelling, and walk-forward optimisation to expose curve-fitted EAs before they reach live accounts.
Expert Advisor Vetting
EAFree's listing rubric — code review, parameter sensitivity, live-account performance, and broker compatibility — applied to every EA before publication.
In Their Own Words
“Backtests prove what a strategy *could* have done. Live forward-tests prove what it *will* do. We never list an EA on the strength of backtests alone.”
“The riskiest sentence in retail trading is "this EA averaged X% monthly last year." Averages hide the trade that takes your account to zero.”
“A good Expert Advisor is boring. If the equity curve looks exciting, look harder at the risk parameters.”
“Every parameter an EA exposes is a place for a user to hurt themselves. Defaults matter more than features.”