Updated 3 minutes ago
Live Shared Portfolio
Shared portfolio, current state.
Holdings, orders, and performance are all here — each position links back to the reasoning that produced it.
+0.0% since inception
100% of the portfolio is still undeployed.
0 recent orders across a 10-coin public universe.
Locked at $9,998.37 so the path has a clear first line.
No live holdings are carrying risk yet. The lab is still waiting for a setup worth funding.
+0.0% during Mar 9–Mar 15, across 0 orders.
How the experiment is going.
Performance comes after state and traceability. The curve shows the broad direction, while the daily and weekly ledgers show how rough or disciplined the path has been.
Equity curve
Portfolio value
The equity curve appears once at least two daily snapshots are recorded.
Latest days
Daily moves
Daily rows appear once the snapshot history has at least two points.
Shared ledger
Weekly gains and losses
| Week | Starting Value | Ending Value | P&L | P&L % | Orders |
|---|---|---|---|---|---|
| Mar 9–Mar 15 | $9,998.37 | $9,998.37 | $0.00 | +0.0% | 0 |
How the lab gets to a decision.
These steps are intentionally narrow. AI interprets the setup, but it does not get to ignore rules, current exposure, or the option to do nothing.
Indicators and rules are calculated first.
The raw setup is built before any model reads it. Trend, regime, levels, and recent context enter the room before language does.
The model reads a bounded market snapshot.
The AI explains the action inside a fixed structure instead of inventing its own playground. It is there to interpret, not to freestyle.
Cash, exposure, and limits stay visible.
Current holdings, available cash, and risk caps all constrain the action. The lab should be able to say HOLD as honestly as it says BUY or SELL.
Orders are paper trades on Binance demo.
The order path is real for the demo environment, which means positions and P&L can be inspected in public without pretending this is live capital.
The lessons sit beside the ledger.
The portfolio shows the current state. The lessons explain what changed, what went wrong, and what the lab learned from it.
The AI got greedy.
A fast move looked attractive, but the lesson was that 4-hour setups still need confirmation before capital gets deployed.
Cash is also a position.
A quiet week reminded the lab that preserving reserve cash is often the right response when the board is noisy and overextended.
A HOLD can be the most honest call.
Not every chart deserves action. The public feed should teach restraint as clearly as it teaches conviction.
Keep following the experiment
The point is to make the lab inspectable.
You should be able to watch the portfolio, see how and why decisions are made, learn from it, and understand when I got something wrong.
If you spot wrong data or want to suggest an improvement, send feedback here.
If having your own personal lab sounds useful, leave your email on the waitlist. If enough people are interested, it is worth building.
This is a public paper portfolio. Past performance does not guarantee future results. Hugo's Trading Lab publishes rules-based analysis with AI-assisted decision summaries for informational purposes only, not financial advice.