📊 The headline number
Compound equity of the Kraken bots vs. passively holding BTC over the same period, computed directly from the published CSV. Switch between all-time and the last 90 days.
🧠 Why this happened (spoiler: fees + time off the market)
The bots bought and sold spot BTC. That means each individual trade tracked the BTC price perfectly — per-trade alpha vs. BTC in the same hold window was effectively zero. So the losses are not "bad picks". They are structural:
- Transaction fees. Kraken round-trip ~0.5% (85% of our orders were takers). 682 round-trips × 0.5% ≈ ~350 percentage points eaten by fees alone, before compounding.
- Time out of the market. Between trades the capital sat in USD. When BTC rallied during those gaps, the bot didn't participate.
- Compounding works both ways. 682 trades of −0.4% average (after fees) compound to −94%, not to 682 × −0.4% = −273%. The compounding floor is −100%; the reality lands just above it.
- Win rate ≠ profitability. 73% win rate with 4× asymmetric losses (wins avg +0.96%, losses avg −3.84%) is mathematically worse than a 50/50 coin flip with symmetric payoffs.
🎯 The trust-score paradox
We also stress-tested one of the core assumptions — that "high trust" wallets (exchanges, institutions, labelled whales) are better signals. In our data they are the worst signals.
| Trust bin | N | 6h return | Win rate |
|---|---|---|---|
| New (<0.1) | 342 | +0.438% | 56.1% |
| Low (0.1–0.3) | 43 | +0.340% | 60.5% |
| Mid (0.3–0.8) | 952 | +0.136% | 56.4% |
| High (0.8+) | 383 | −0.089% | 46.5% |
Interpretation: trust correlates with being known, not with being profitable. Labelled institutional flow is already priced in by the time it hits the public mempool. The signal — if there is any — comes from new wallets that nobody has labelled yet.
🧬 What we changed as a result
The 2025 experiment killed the "trading bot" hypothesis for us. We kept the infrastructure we had built (local Bitcoin full-node, mempool watcher, 835K watchlist addresses, 711 hand-curated entity labels, 7.68M indexed whale transactions) and repurposed it as an information product:
- Intelligence, not signals. We publish real-time data — exchange flows, SOPR, HODL waves, miner balances, entity labels — so you can form your own thesis.
- No suggested entries or exits. Our customer is an analyst, a researcher, a treasurer, a journalist. Not a retail copy-trader.
- Swiss informational service, not a financial-services licence. We have no custody, no brokerage, no asset-management mandate. This is explicitly scoped in our imprint.
- Kept this archive public. Deleting an honest loss feels worse than publishing it. Bitcoin is supposed to be about open data.
📁 The raw data
Every number above is derived from these two CSV files. Schema is stable; new rows append, existing rows never change.
📥 latest_all.csv (full period) 🔐 SHA256📥 latest_90d.csv (rolling) 🔐 SHA256
📁 Browse weekly archive 📄 metadata.json
🔒 Verify a download
Pick the CSV you just downloaded — your browser computes SHA256 locally (no upload) and compares to the published hash.
Command-line equivalent:
curl -s https://btcwhalealerts.com/ledger/latest_all.csv.sha256
⚠️ Caveats
- This archive is read-only since 2026-04-24. The experiment is closed; no new trades are appended.
- Percentage returns only. No absolute position sizes (privacy).
- Not all listed strategies ran continuously. Some were disabled mid-period after being identified as loss-makers (documented in the archive change-log).
- This is not investment advice and not a recommendation of any strategy. It is a post-mortem of a closed experiment, published so our reasoning is verifiable.
📨 Questions?
Academic, journalistic or research use is welcome. The data is openly licensable for citation. See our imprint for contact details.