I am a 21 y/o Economics student from Germany.
Got pulled into systematic trading and quant finance during my degree.
Before this I traded discretionary for 2 years. Mostly ICT.
I knew the theory — risk management, HTF bias, psychology… Stayed around breakeven the whole way, couldn't really make it work.
I still believe discretionary trading works. But honestly?
Most "traders" online are larping. One winning streak, big flex, no proof of an actual long-term track record or edge.
What can they show? A few payouts. Over what horizon? Markets carry enough noise that anyone can win for a while. Very few sustain it for years — way less than you see online.
Why I fell in love with systematic trading:
→ I can backtest decades of data
→ I can define exactly what and where my edge is
→ I know with higher probability which regimes will hurt me and which will feed me
→ I don't need to be 100% psychologically resilient every single day to follow the rules
→ No cap on how many systems I can run in parallel
Over time I built — with my own research, experience + Claude — 3 ready-to-deploy MT5 algo EAs, each running on its own CFD prop firm account:
Portfolio A → 6 strategies
Portfolio B → 5 strategies
Portfolio C → 6 strategies
11 unique strategies, 8 assets (some overlap across portfolios).
Mainly momentum / trend-following. A few mean-reversion plays sprinkled in.
Everything purely technical, fully rule-based, no discretion.
Backtested 2018 → today. Each portfolio sized for its own 100k prop firm account → 300k combined reference. Metrics across the full portfolio:
• Sharpe ~3.0
• Profit Factor ~1.4
• Max DD <10% on every single account
• Annual vol ~5%
• Zero blowups
Yes, 5% annual vol looks low. That's the point.
Each EA is sized for its own 100k account. Drop all 3 onto a 300k view → vol drops further.
Boring on purpose. Prop firms reward consistency, not heroics. And of course I can just increase the global risk 2x if I have a 200k account...
Past results never guarantee future ones. I know that. But the edge is defined, repeatable, falsifiable. That's the difference.
Your favorite guru can laugh at 2%/month. I'd rather scale across multiple prop firms with consistent gains than chase 10%+ / month and blow up once a year.
Everything is still theory.
My goal: scale aggressively across prop firms now, while I keep refining systems, learning more technical skills, and finishing my degree.
I'm gonna share more insights into how I build, my workflow, research, strategy evaluation.
You can follow me on this journey for free.
We build in public from here!
I chose algo because I want to scale beyond my own attention span.
Not because discretionary is fake.
If you trade discretionary and you've got multiple years of consistent live results — respect.
If you trade algo and you laugh at every discretionary trader by default — you're flexing your tools, not your understanding.
Build edge. Measure it as honestly as your medium allows. That's the whole game.
The quant corner of Twitter loves to dunk on discretionary traders.
"No backtest. No edge. Just vibes."
I get it. I went algo for a reason. But the take is lazy.
Discretionary traders absolutely can make money. The reason most quants don't see it has nothing to do with whether the edge exists. 🧵
The actual goal — for both sides — is the same:
A defined system that produces positive expected value with the lowest vol you can manage.
The discretionary trader's "system" is just stored in their head + reps instead of in code. If they can't articulate it, they don't have one. Same standard as a quant.
Edge is edge. Process is process. The medium doesn't matter.
Rough thresholds I use:
• Return Spearman < 0.3 → useful diversifier
• DD Pearson < 0.4 → ok on same account
• λ_L < 0.2 → low tail co-crash risk
Most unexperienced algo guys backtest 8 EAs, dump them on one account, call it a portfolio.
They built one strategy in 8 files.
A portfolio is a correlation structure. Not a list.
"Diversification is the only free lunch in investing."
— Harry Markowitz, Nobel Prize 1990
Sounds like textbook filler. It's the most concrete edge I have.
Stack 3 mediocre strategies and you get a portfolio that beats every one of them.
Same trades. Same risk. Higher Sharpe. For free.
The catch — only if you measure correlation the right way. And most don't. 🧵
One correlation number isn't enough. I look at three:
→ Returns — Spearman on daily P&L. Rank-based, robust to outliers, catches non-linear co-movement.
→ Drawdowns — Pearson on daily DD series. Here magnitude matters: I want to know if A is down 10% when B is down 12%. Ranks would blur that.
→ Tails — Lower Tail Dependence (λ_L). The probability that B has a worst-5% day WHEN A has a worst-5% day. This is what actually blows up accounts