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Meet the founder · Carl C.G. Eriksson

Built by a trader.
For traders.

Carl C.G. Eriksson has run quantitative algos since 2015. He built them to grow his own and his family's money, then opened them up to other traders. Same algos, same drawdowns, same returns.

2015Public since
10k+Trades placed
30+Countries
Read the full story Our 5 principles
Keynotes · Stockholm
Web Summit Lisbon
Web Summit · Lisbon
IG Trading Summit
IG Trading Summit
The story

Why ProRealAlgos exists.

2015The switch

Done with discretionary trading.

I had traded by hand for years, and I had grown tired of discretionary trading. With a coding background to lean on, I started automating the strategies I had been running manually. Within a year I had left manual trading behind entirely and spent my time on algorithm development and backtesting instead, work I genuinely enjoyed more than the trading itself.

2019The origin

The algos started spreading.

It started informally in 2019. I shared a few of my algorithms with other traders, and after a while I felt compelled to bring more of them along with me. That is really how ProRealAlgos came about, a way to make the systems available beyond my own circle.

2023The mission

The long game.

The goal has stayed the same ever since, to climb the net worth ladder and bring the people using the algos along with me. By 2023 the algos had run roughly 120,000 trades across everyone using them, with gross exposure reaching 15 billion euros.

2026The tooling

The addition of AI.

AI joined the development desk for real. What used to take weeks to code now takes an afternoon. The bar didn’t change: the survivors still get coded, forward-tested and traded with my own money. The difference? We can now test ten times as many strategies.

+1,447%
ALL TIME RETURN
7yrs
LIVE CAPITAL
10,380
NBR OF TRADES
30+
COUNTRIES
Published, not hidden

The losses that shaped our algos.

Seven years of live trading, and three drawdowns we still talk about. The worst single months, the worst peak-to-trough stretches, measured on real capital and net of fees. Each one cost us something. Each one left behind a rule the algos still run today.

APR → SEP 2021 −15.7%

The summer the tape went dead.

Our deepest drawdown on record, and the slowest. Through a low-volatility 2021 summer the market just drifted, with no clean swings to mean-revert against. The algos kept buying shallow dips that kept sliding a little lower, nicking us for one small loss after another. Five months of bleed, no single bad trade to point at.

−€2,659 off a €16,930 account · back to new highs in 1 month
→ The rule it left behind

Doing nothing is a position. We added a volatility floor, so the mean-reversion algos stand down when realised volatility drops below threshold instead of forcing trades into dead tape.

JUL → OCT 2023 −14.8%

When the whole book became one trade.

As ten-year yields marched toward 5% in the autumn of 2023, every equity index sold off together. Our DAX, S&P 500 and Nasdaq algos were all leaning the same way, so a book that looked diversified by market was really one big correlated bet. They fell in lockstep, and so did we.

−€5,598 off a €37,836 account · back to new highs in 1 month
→ The rule it left behind

Different instruments are not different risk if they move together. We further diversified our portfolio with new algorithms for new markets based on completely new market edges. No one macro move should hit every algo at once.

FEB → MAR 2026 −13.3%

Our most expensive month, on purpose.

After a standout +15% February, March handed back 13.3% in a single fast volatility spike. In cash that was roughly €11,098, comfortably the largest euro loss in our history, for one plain reason: the account had never been this big. Same percentage of risk, a much scarier number on the statement.

−€11,098 off an €83,154 account · still climbing back to the high
→ The rule it left behind

The euros scale with the account, the pain of a loss as well. Added new reinvestment of profit code to not scale reinvesting linearly. A 13% month should always feel like 13%, never like a new car.

Figures are peak-to-trough drawdowns on the live results account, net of fees, pulled from the same sheet that powers our public performance page. We publish every month we've ever traded, the red ones included.

See the full track record
The Pact · Parallel signatures
Carl C.G. Eriksson
Founder · ProRealAlgos · 05.2019 ✓Signed

The ProRealAlgos Manifesto.

You already know what this kind of trading is, and what it isn't. No Lamborghinis, no jets, no gurus, just 24 algorithms I built for myself and my family because I wanted time away from the screens. The returns were a side effect.

I believe trading should be mechanical and boring. I believe it shouldn't try to beat the market every month, it should survive the bear years and compound through the bull ones. And I believe in a few of us, not thousands, trading the same algos on the same broker, losing together and winning together. Not a quick win. Net worth, compounded over a decade. This is the Capital Climbing Club.

Signed, Carl C.G. Eriksson · founder, author, trader
Where the algos come from

Built on years of research, not instinct.

Most retail strategies start with a hunch. Ours start with research: 18 papers, 150 years of market data, nine years of synthesis. Everything we ship is built on top of this study.

Research on 150 years of market data.

Every algo we ship traces back to an edge in this study, tested across 150 years of market data.

18
Research
papers
150
Years of
market data
09
Years of
compilation
Read the full study → ~24 min read
↳ Browse all 18 research papers
+1,290% ProRealAlgos strategies +620% S&P 500 2000 2005 2010 2015 2020 2025
↳ The study that ProRealAlgos is built on

What works (and what doesn't)
in the stock market.

A comprehensive synthesis of what 150 years of market history actually teach us. Drawn from 18 research papers; condensed into five principles and 24 algos.

Updated May 2026 Read the study →

Distilled into five principles.

↳ Auditable against the study
01

Risk management is the strategy.

Most retail traders pick "what to buy" and forget "how much." Sizing, drawdown limits, and exposure rules decide whether a 70% win-rate system makes you rich or breaks you.

RP-15 · RP-07 · RP-10
02

Complexity is usually compensation.

When a strategy needs fourteen indicators to work, it's usually compensating for the fact that none of them really do. The robust edges tend to be the simple ones.

RP-04 · RP-11
03

Automatic execution removes ego.

Discretionary trading rewards whoever can manage their own psychology. Automated systems just take the psychology out of the loop entirely — fewer chances to be the weak link.

RP-03 · RP-14
04

Onboarding only one trader at a time.

We onboard new members one at a time, with personal handover. Algo trading without proper onboarding is how people lose money quietly.

RP-17 · RP-06
05

If we don't run it, we don't sell it.

Every algo licensed to a member is running on Carl's own brokerage account, with real capital, in real time. Skin in the same game we ask of you.

RP-18 · RP-09