Quantitative Investing.
Simple & Beautiful.
Quant Strategy Lab offers easy access to institutional-grade quantitative investment education. Learn how to build and test strategies step by step — with a clear process, plain language, and no false promises. Use our validated strategy library as your blueprint.
Build Real Strategies. Based on Evidence, Not Hope.
Get Early AccessEarly access. No cost. No credit card. Your input shapes what we build.
Why This Exists
Most investment education is built on noise.
You see bold claims — but no proof.
You hear complex terms — but no clear explanation.
You're told strategies work — but never shown how they are built.
And when you try to go deeper, it gets technical fast.
The result: most serious investors are left guessing. Following tips. Trusting backtests they can't evaluate. Taking on risk they don't fully understand.
QS Lab was built to change that, because with the right tools and guidance you can reach amazing places.
What You Get
A structured path from curious investor to serious strategy builder.
Structured Courses
From zero to systematic strategy builder, step by step. Every concept is explained before it is applied. No prior coding experience assumed.
Validated Strategies
Every strategy in the QS Lab library has been reviewed through our 8-step validation framework before it reaches you. You see the logic, the testing, and the limits — not just the backtest chart.
Build and Test Yourself
Apply what you learn immediately. Design, test, and refine your own strategies using the same structured workflow that professional researchers use.
Community
Share ideas, discuss strategies, and get peer review from serious practitioners. No noise. No tips. Just structured discussion from people doing the work.
Built on professional-grade tools and guided workflows. You do not need to be a programmer to begin.
What you won't
find here.
Just a clear, structured process you can understand, apply, and build on.
Strategy Lab Testing
Every strategy gets tested beyond a simple backtest.
Most strategies you find online are presented without proper testing. A backtest that looks great is not the same as a strategy that works. We filter out weak ideas early, by performing multiple testing like it is a parachute you can rely on.
We call this the 8 Levels of Validation — a structured process used by professional asset managers to evaluate strategies before committing capital.
Level 1: Enough Data
Do we have enough history to trust the numbers?
A strategy that looks brilliant after 6 months of testing might simply have been lucky. Level 1 sets a minimum threshold — we need enough independent data points before any result is meaningful.
Level 1: Enough Data
Do we have enough history to trust the numbers?
A strategy that looks brilliant after 6 months of testing might simply have been lucky. Level 1 sets a minimum threshold — we need enough independent data points before any result is meaningful.
Level 2: Real Costs
Does it still work when you add trading fees?
Every time you buy or sell, you pay a cost. A strategy that trades frequently can look great before costs and terrible after. Level 2 applies realistic transaction costs to every trade and asks: is there still a profit left?
Level 2: Real Costs
Does it still work when you add trading fees?
Every time you buy or sell, you pay a cost. A strategy that trades frequently can look great before costs and terrible after. Level 2 applies realistic transaction costs to every trade and asks: is there still a profit left?
Level 3: Proven Signal
Is there genuine statistical evidence the strategy works?
Even positive returns after costs might just be luck. Level 3 applies a statistical test — if the same result could plausibly appear by chance, the strategy has no proven edge.
Level 3: Proven Signal
Is there genuine statistical evidence the strategy works?
Even positive returns after costs might just be luck. Level 3 applies a statistical test — if the same result could plausibly appear by chance, the strategy has no proven edge.
Level 4: Consistent Over Time
Did it work in multiple periods — not just one?
A strategy that only worked from 2017 to 2022 is not a strategy — it is a lucky era. Level 4 tests across rolling five-year windows. At least 60% must show a profit.
Level 4: Consistent Over Time
Did it work in multiple periods — not just one?
A strategy that only worked from 2017 to 2022 is not a strategy — it is a lucky era. Level 4 tests across rolling five-year windows. At least 60% must show a profit.
Level 5: Beats Random
Does it outperform a purely random trading strategy?
We compare the strategy against 1,000 randomly generated signals on the same data. If the real strategy doesn't rank in the top 5%, the signal is not adding value — the returns could be explained by luck alone.
Level 5: Beats Random
Does it outperform a purely random trading strategy?
We compare the strategy against 1,000 randomly generated signals on the same data. If the real strategy doesn't rank in the top 5%, the signal is not adding value — the returns could be explained by luck alone.
Level 6: Works in All Markets
Does it hold up in rising, falling, and sideways markets?
A strategy that only makes money in bull markets is not a strategy — it is leveraged exposure. Level 6 tests across bull, bear, and sideways environments. At least two of three must show positive performance.
Level 6: Works in All Markets
Does it hold up in rising, falling, and sideways markets?
A strategy that only makes money in bull markets is not a strategy — it is leveraged exposure. Level 6 tests across bull, bear, and sideways environments. At least two of three must show positive performance.
Level 7: Risk Is Acceptable
Are the returns good enough and the losses manageable?
A strategy that doubles your money over five years sounds great — until it also cut your account in half along the way. Level 7 evaluates Sharpe ratio, Calmar ratio, CVaR, and a Monte Carlo stress test simulating thousands of possible futures.
Level 7: Risk Is Acceptable
Are the returns good enough and the losses manageable?
A strategy that doubles your money over five years sounds great — until it also cut your account in half along the way. Level 7 evaluates Sharpe ratio, Calmar ratio, CVaR, and a Monte Carlo stress test simulating thousands of possible futures.
Level 8: Passes the Future Test
Does it work on data it has never been tested on?
We split historical data into training and testing periods. The strategy is built on training data only, then evaluated on data it has never seen. Performance on unseen data must be at least 50% as strong as on training data. This is how we catch overfitting.
Level 8: Passes the Future Test
Does it work on data it has never been tested on?
We split historical data into training and testing periods. The strategy is built on training data only, then evaluated on data it has never seen. Performance on unseen data must be at least 50% as strong as on training data. This is how we catch overfitting.
Who Built This
Built by former institutional equity derivatives professionals.
QS Lab was built by two former institutional equity derivatives professionals who spent 30+ years with JPMorgan, Lehman Brothers, Nomura, Morgan Stanley and other investment banks advising financial institutions, investment funds and family offices on risk management.
Marcus Di Prima
Managing Director
JPMorgan, Lehman Brothers & Zurich Insurance Group. 20+ years in institutional equity derivatives with a passion for flying, sailing, skydiving, kitesurfing, landscapes and trading.
Martin Bertsch
Managing Director
Nomura, Lehman Brothers, JPMorgan Chase, Morgan Stanley. 20+ years of experience in equity and fixed income derivatives, with a passion for travelling, hiking, and photography.
Marcus and Martin met at JPMorgan in 1999, working together in the Equity Derivatives division. Within their first year they executed one of the largest equity derivatives transactions in Europe that year. Many more followed.
What they discovered early was simple: complementary skills and shared focus produce better results than either person working alone. That principle has shaped everything they have built since.
Both retired from institutional finance at an early age. For most of their careers, working inside investment banking meant being restricted from making investment decisions in their own accounts — a standard condition for anyone operating close to material non-public information. When they left, that constraint lifted. They began building their own quantitative investment infrastructure from scratch.
QS Lab grew from that experience. The tools, frameworks, and validation processes that institutional investors use to evaluate strategies are not complicated — but they have always been inaccessible. Recent advances in technology and AI have changed that. Every serious investor can now work with the same rigour that professionals apply, with the right guidance.
This is our passion — and we want to share it with you.
Get Early Access.
We are opening QS Lab to the first 100 subscribers before public launch. Go through the course, explore our first validated strategies, and tell us what works and what doesn't.
Full access. No cost. No credit card.