Plain `git stash` only stashes tracked modified files. Scripts like
track_recommendation_performance.py write new untracked files to
data/recommendations/ which block `git pull --rebase`. Adding
--include-untracked captures those files in the stash so the rebase
can proceed cleanly.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The rsi_oversold scanner is a contrarian signal, not a momentum signal —
it fires on short-term panic pullbacks within uptrends and expects a 3-7 day
bounce. Keeping it in the momentum pipeline conflates two fundamentally
different signal types and could cause the ranker to misprice it.
Changes:
- Add mean_reversion pipeline (priority 6, deep_dive_budget 5) to default_config.py
- Move rsi_oversold scanner from pipeline="momentum" to pipeline="mean_reversion"
in both default_config.py and rsi_oversold.py
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The discovery run writes delisted_cache.json which isn't staged, causing
'cannot pull with rebase: You have unstaged changes' on all three commit steps.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- tradingagents/dataflows/universe.py: single source of truth for ticker
universe; all scanners now call load_universe(config) instead of
duplicating the 3-level fallback chain with hardcoded "data/tickers.txt"
- scripts/prefetch_ohlcv.py: nightly script using existing ohlcv_cache.py
incremental logic; first run downloads 1y history, subsequent runs append
only new trading days
- .github/workflows/prefetch.yml: runs at 01:00 UTC daily, before all other
workflows; commits updated parquet to repo
- Updated 6 scanners: minervini, high_52w_breakout, ml_signal, options_flow,
sector_rotation, technical_breakout — removed duplicate DEFAULT_TICKER_FILE
constants and _load_tickers_from_file() functions
- minervini, high_52w_breakout, technical_breakout: replace yf.download()
with download_ohlcv_cached() — reads from prefetched cache instead of
hitting yfinance at discovery time
- default_config.py: added discovery.ohlcv_cache_dir config key
- data/ohlcv_cache/: initial 1y backfill (588 tickers, 5.4MB parquet)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Both scanners were implemented by research PRs but never added to default_config.
Without entries they cannot be disabled or tuned from config and are invisible
to the settings UI. Also updated /research-strategy to make config entry mandatory.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
All WebFetch calls now route through r.jina.ai for JS-rendered, clean markdown.
arXiv uses structured API endpoint for discovery. Reddit threads fetched via
Jina after URL discovery with WebSearch.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Concluded hypotheses already live in concluded/ — keeping them in active.json
causes the registry to grow unboundedly. Runner now removes them at the end
of each cycle. Also cleaned up the existing social_dd concluded entry.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- iterate: CRITICAL note that all writes must use file tools, not narration
- iterate: new Step 5.5 — auto-registers one forward-test hypothesis per run
when a code change needs live-data validation
- research-strategy: cron changed from Monday-only to daily at 07:00 UTC
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Analysis of 25 picks reveals 60% 30d win rate (+2.32%) vs 41.7% 7d (-1.92%).
Score suppression is not the primary issue (avg score 71.5, 22/25 >= 65).
Root cause is evaluation horizon mismatch — ranker calibrated on 7d outcomes.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Statistical hypotheses now conclude immediately on the next runner cycle
without counting toward max_active. Only implementation hypotheses occupy
runner slots. Added conclude_statistical_hypothesis() for instant analysis
against existing performance data with Gemini LLM enrichment.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Implements ShortSqueezeScanner wrapping existing get_short_interest() in finviz_scraper.py.
Research finding: raw high SI predicts negative long-term returns (academic); edge is using
SI as a squeeze-risk flag when combined with earnings_calendar or options_flow catalysts.
Directly addresses earnings_calendar pending hypothesis (APLD 30.6% SI was strongest setup).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Implements ShortSqueezeScanner wrapping existing get_short_interest() in finviz_scraper.py.
Research finding: raw high SI predicts negative long-term returns (academic); edge is using
SI as a squeeze-risk flag when combined with earnings_calendar or options_flow catalysts.
Directly addresses earnings_calendar pending hypothesis (APLD 30.6% SI was strongest setup).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
gh pr create/list/edit were defaulting to TauricResearch (upstream).
Added --repo Aitous/TradingAgents to all gh calls in iterate,
research-strategy workflows and slash commands.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- active.json: updated days_elapsed from hypothesis runner
- hypotheses.py: black formatting applied by pre-commit hook
- .gitignore: local additions
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Youssef Aitousarrah
Aitous
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