Simple, systematic trading strategies that work
Every strategy on EdgeLab is tested on data it has never seen before it gets published — full rules, honest backtests and the code to run them. The rules are plain English, simple enough to run on any platform or code in any language. Most strategies fail our tests. These didn't.
Latest research
-
The RSI 30/40 strategy: buy the Nasdaq at 30, sell at 40 — every trade from 23 years
The strategy from the video, tested honestly: 32 signals since 2003, 28 winners, every trade listed one by one — plus the faster RSI(2) variant and the honest math of what each earns.
-
Buying the dip in QQQ: 23 years of evidence, net of costs
Twenty rule combinations, no cherry-picking: the dip-buying edge is real, robust across settings, and persistent across two decades. It still doesn't do what the meme says it does.
-
How many trading strategies do you need? The portfolio math
One formula decides it, and correlation is the variable that matters. Theory said our two-strategy combo should land at Sharpe 1.04 — the market paid 1.02. The full math, plus the trap that ruins most multi-strategy portfolios.
-
Can a mechanical strategy pass an FTMO challenge? We ran 5,600 of them
62% pass at honest size — but the median pass took 357 trading days, and sizing up feeds the daily-loss rule. The simulation prop firm content never runs.
Download the free strategy
A simple RSI-based strategy with a handful of clear rules. Over the past three years it has taken 32 trades — 25 winners (78%) — with a worst drawdown of -8.2%, net of costs. It's in the market about 8% of the time: one alert does the watching, your capital sits safe between signals, and the markets get minutes of your day instead of owning it.
The free report gives you the exact rules (they fit on a sticky note), every single trade with timestamps, 23 years of long-run evidence for the idea — and the honest caveats. And because one strategy is a tactic rather than a system, subscribers also get a second strategy a few days later, one that trades a completely different market (correlation with the first: -0.04), plus the math of combining them into one calm portfolio. That combination is the whole point of EdgeLab.
Download the free strategy
One PDF: the exact rules, all 32 trades, the long-run evidence — and what it honestly earns.
No spam. Unsubscribe anytime.
How we test
Every strategy published on EdgeLab has passed the same three filters:
- Out-of-sample validation. The most recent 20–30% of price history is locked away during development and used exactly once. If the strategy fails there, it's rejected.
- Sensitivity analysis. Every parameter is shifted ±20–30%. If the edge only exists at one magic setting, it's curve fitting — rejected.
- Monte Carlo simulation. Trade order is randomized across thousands of runs to stress-test drawdowns beyond what the historical sequence happened to produce.
And every backtest pays its way: we charge 0.05% per side in commission and slippage — roughly two to three times what a liquid ETF actually costs to trade at a decent broker. If an edge can't survive costs it will never pay in real life, so we'd rather understate every number on this site than flatter one.
More than 80% of the strategies we develop are rejected. Here's why that rejection rate is the whole point →
Who's behind this
I'm Robin Eriksson. I spent my first five years in the markets losing money on discretionary trading before switching to systematic strategies — and testing everything. EdgeLab is where I publish the research: what works, what doesn't, and the process for telling the difference. More about me and the methodology →
