joungmin
27189b1ad9
feat: add Fear & Greed filter to entry logic
...
- core/fng.py: F&G API wrapper with 1h cache (alternative.me)
- FNG_MIN_ENTRY=41 (env-configurable), blocks entry below threshold
- core/strategy.py: call is_entry_allowed() before volume/regime checks
- daemon/runner.py: log F&G status on every scan cycle
- core/notify.py: include F&G value in buy/signal/status notifications
- core/trader.py: pass current F&G value to notify_buy
Backtest evidence (1y / 18 tickers / 1h candles):
- No filter: 820 trades, 32.7% WR, avg +0.012%, KRW +95k
- F&G >= 41: 372 trades, 39.5% WR, avg +0.462%, KRW +1.72M
- Blocked 452 trades (avg -0.372%, saved ~1.68M KRW loss)
Also add:
- backtest_db.py: Oracle DB storage for backtest runs/results/trades
- fng_1y_backtest.py, fng_adaptive_backtest.py, fng_sim_comparison.py
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-03-03 15:56:17 +09:00
joungmin
673ce08d84
feat: add velocity entry, fast-poll thread, tighten BEAR threshold
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- Add velocity-based entry signal in strategy.py (VELOCITY_THRESHOLD=0.10,
VELOCITY_MIN_MOVE=0.5%, VELOCITY_MIN_AGE_M=5)
- Add fast-poll thread in daemon/runner.py (SIGNAL_POLL_INTERVAL=15s)
for sub-minute velocity event detection
- Add vol_ratio tiered condition and get_active_signals() to strategy.py
- Change BEAR_THRESHOLD -1.0 → -0.5 in market_regime.py to catch
slow downtrends earlier (weighted 2h score)
- Expand sell_reason VARCHAR2(500) in price_db.py DDL
- Add velocity_backtest.py and sim10m.py for strategy experimentation
- Update STRATEGY.md: correct regime algorithm description (weighted 2h
score, not BTC 1h ±5%), add fast-poll/velocity sections, add backtest
section D, add change history table
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-03-03 10:17:08 +09:00
joungmin
16b4c932a2
feat: bear block, trend-continuation entry, partial TP backtest
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1. daemon/runner.py: skip scan entirely in bear regime
- calls get_regime() at start of each scan loop
- logs bear block with score before sleeping
2. core/strategy.py: trend-continuation entry filter
- check_trend_6h(): 6h price trend >= 1% (rejects flash spikes)
- 15-min confirmation watchlist (_watchlist dict)
- should_buy() adds watchlist to existing 12h+regime+momentum logic
- CONFIRM_SECONDS env var (default 900 = 15min)
- TREND_6H_MIN_PCT env var (default 1.0%)
3. backtest.py: partial take-profit scenario comparison (--tp-cmp)
- simulate(): partial_tp_pct / partial_tp_ratio params
- blended pnl = ratio * partial_pnl + (1-ratio) * remaining_pnl
- main_tp_cmp(): 3 scenarios A/B/C (none / +5% 50% / +3% 50%)
- result: partial TP reduces cumulative return (-56% → -63%)
big winners carry the strategy; trimming them hurts expected value
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-03-01 10:51:02 +09:00
joungmin
83bd51117f
feat: initial upbit auto-trader implementation
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Strategy C: volatility breakout (Larry Williams K=0.5) AND momentum
(MA20 + 2x volume surge) must both trigger for a buy signal.
Hard rules:
- Trailing stop: sell when price drops -10% from peak
- Max budget: 1,000,000 KRW total, up to 3 positions (333,333 KRW each)
- Scan top 20 KRW tickers by 24h trading volume every 60s
- Monitor positions every 10s
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-02-28 10:20:02 +09:00
