Engine default + both bot configs + backtest set to 0 (cap logic stays, opt-in
via risk.max_per_event). June backfill without the cap: +465%, 237 resolved
(202W/35L), 22 missed, $170 fees.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Engine records every blocked OPEN (no free cash, event cap, price guard) with
its would-be stake; settle_resolved marks them won/lost at CLOB resolution with
hypothetical P&L (fee-inclusive) - the live counterpart of the backtest's
Missed table. Feed gains missed[] + missed_pnl.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- engine (copytrade): stake_usd() = bankroll_pct x current equity (cash + open
cost basis) - Kelly-style compounding both directions - halved while equity
sits below 80% of its high-water mark; new risk.max_per_event (default 2)
blocks stacking correlated markets on one real-world event (dated-slug prefix
grouping; LSB1 once put 6 conviction bets on a single match).
- copybot: feed/summary report the dynamic stake, stake_pct, event_cap, hwm.
- portfolio backtest mirrors the exact same rule (PCT 4%, clamp $5-$150,
EVENT_CAP 2, brake 80%/half), with per-bet stakes in every table row and a
persistent CLOB slug cache for event grouping. June backfill: +426% vs +168%
flat - compounding amplifies the in-sample month; July live is the test.
Misses fell 62 -> 19 cash-missed (+26 deliberate event-cap skips): smaller
early stakes capture more signals.
- configs: bankroll_pct 0.04, max_trade/max_position 150 (runaway guards),
max_per_event 2.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Moved the 8 tested-and-failed strategy tools into archive/ (copytrade, backtest,
edge_research, lookback, table_77, lp_screener, lp_paper, xarb) with an
archive/README explaining each. Root now holds the keepers: insider.py (made
self-sufficient — dropped the copytrade load_json dependency) and smart_money.py
(data foundation). New FINDINGS.md is the honest scorecard: six systematic
public-data edges all efficient/illusory, the win-rate survivorship-bias
finding, and the one real signal (z-score improbability + funding clustering).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
jaxperro