generated from mathias/template-go-web
485fdaa9f9fb7a870d1896a974d04b2863c09bb6
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>
hostexecutor
Generated from
mathias/template-go-web.
Bootstrap
After creating from template, run:
go mod tidy # regenerate go.sum with real module path
task generate # generate templ files
task build # build the binary
Description
JEPA-based latent representation learning for FX trading risk management — research project
370 KiB
Languages
Python
76.4%
Go
18.4%
Shell
4.3%
templ
0.6%
Dockerfile
0.3%