joungmin
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6580cda017
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docs: update STRATEGY.md with F&G filter and project structure changes
- Add F&G filter section: FNG_MIN_ENTRY=41, 1-year backtest proof
(no filter: +95K KRW → F&G>=41: +1.72M KRW over 1 year)
- Add F&G backtest result (section D) with adaptive param findings
- Update section E: rename velocity backtest (was D)
- Split file table into production core vs tests/ scripts
- Update simulation commands to use tests/ path prefix
- Update env config: add FNG_MIN_ENTRY=41
- Add changelog entries for F&G filter, project structure, ecosystem.config.js
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2026-03-03 16:14:50 +09:00 |
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joungmin
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673ce08d84
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feat: add velocity entry, fast-poll thread, tighten BEAR threshold
- 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>
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2026-03-03 10:17:08 +09:00 |
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joungmin
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612055162e
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docs: update backtest results and WF_WINDOW param after tuning
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2026-03-02 15:16:00 +09:00 |
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joungmin
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6a685a7852
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feat: add sim_45m40.py and update STRATEGY.md with 40min backtest results
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2026-03-02 15:02:45 +09:00 |
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joungmin
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c6c6b0020f
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docs: clarify backtest sections with candle unit and data source
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2026-03-02 14:58:26 +09:00 |
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joungmin
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bd802fb896
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docs: update STRATEGY.md to 40min candle strategy
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2026-03-02 14:55:06 +09:00 |
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joungmin
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324d69dde0
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feat: volume-lead strategy with compounding, WF filter, and DB-backed simulation
- core/strategy.py: replace trend strategy with volume-lead accumulation
(vol spike + 2h quiet → signal, +4.8% rise → entry)
- core/trader.py: compound budget adjusts on both profit and loss (floor 30%)
- core/notify.py: add accumulation signal telegram notification
- ohlcv_db.py: Oracle ADB OHLCV cache (insert, load, incremental update)
- sim_365.py: 365-day compounding simulation loading from DB
- krw_sim.py: KRW-based simulation with MAX_POSITIONS constraint
- ticker_sim.py: ticker count expansion comparison
- STRATEGY.md: full strategy documentation
- .gitignore: exclude *.pkl cache files
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2026-03-02 01:46:03 +09:00 |
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