feat(data): EUR/USD M1 fetch + daily realized-vol prep (toy slice, #2/#11)

fetch_data.py politely pulls EUR/USD M1 from histdata.com (maintained package
handles the anti-hotlink token; per-year, spaced). prepare_data.py (LOCKED per
Phase-1 contract) parses M1 -> daily series with realized_vol = the val_vol_r2
target (sqrt sum of squared intraday returns). Verified on 2019-2021: 937 days,
March-2020 COVID RV spike 5.1x over 2019 median — real signal, target works.
Data gitignored (DVC/MinIO = #10).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

requirements.txt

@@ -1,6 +1,8 @@
-# Python deps for the autoresearch loop (train.py + scripts). The Go side
-# (data pipeline, eval harness) is separate. Install torch from the cu130 index:
+# Python deps for the autoresearch loop (train.py + scripts). Install torch from
+# the cu130 index FIRST (koala Blackwell sm_120, torch 2.12.1+cu130 verified):
 #   pip install torch --index-url https://download.pytorch.org/whl/cu130
 #   pip install -r requirements.txt
-# koala = Blackwell sm_120, driver R610; torch 2.12.1+cu130 verified 2026-06-23.
 numpy>=2.0
+pandas>=2.2
+pyarrow>=16
+histdata>=1.3        # histdata.com downloader (handles the tk token politely)