Volatile instruments
- Add XAGUSD (SI=F, silver lease rate as r_f), BTCUSD and ETHUSD end to end:
pair metadata, live rates/OHLC/signals, CFTC positioning mappings
- Asset-class calendars: crypto annualised on 365 days, FX/metals on 252,
threaded through the signal engine
- Pair switch loads a typical ATM vol, rescales legs by moneyness, and
strategy templates use a ~1%-of-spot strike step
Vol Lab tab
- /api/vol/crypto/{BTC,ETH}: Deribit book summaries -> raw SVI fit per
expiry with Durrleman butterfly-arbitrage check, ATM / 25d RR / 25d BF
(Black-76 forward delta), DVOL, 30d constant-maturity IV, realised vol
and vol risk premium; cached 60s, 503 when Deribit is unreachable
- /api/vol/cone/{pair}: Burghardt-Lane realised-vol cone on the asset's
calendar
- UI: KPIs, cone with implied term-structure overlay, per-expiry smile
(market vs SVI), term-structure table with 'Use' to load T/sigma/RR/BF
into pricing and the Vol Smile tab
Fixes in the signal engine
- OU half-life divided by 252 twice; stationary sd used sqrt(252k) not sqrt(2k)
- Fallback realised vol returned decimals under *_pct keys
Tests: backend/tests (pytest) validate SVI recovery, exact 25d strikes,
cone calibration on both calendars and the endpoints with mocked feeds.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FpiqUMAyo4RL5DdQHMWbwE
Builds the implied-vol smile from the three standard FX market quotes
(ATM delta-neutral straddle, 25-delta risk reversal, 25-delta butterfly)
using Castagna & Mercurio's second-order Vanna-Volga approximation, and
reprices each portfolio leg off the smile vs the flat vol.
- backend: core/vanna_volga.py (delta->strike, DNS ATM, VV smile) and
POST /api/smile
- frontend: new "Vol Smile" dashboard tab with quote inputs, smile
chart, pillar table and smile-vs-flat leg repricing
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FpiqUMAyo4RL5DdQHMWbwE
gs-quant not compatible with Python 3.14 on Render.
try/except in quant_analysis.py already handles missing import
with pure numpy/pandas fallback implementations.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Added gs-quant to backend/requirements.txt
- All gs_quant calls now conditional on GS_QUANT_AVAILABLE flag
- Pure numpy/pandas fallbacks for volatility, RSI, MACD, Bollinger, z-score
- Fixes ModuleNotFoundError crash on Render deployment
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- API base URL now reads from VITE_API_URL env var (frontend)
- WorldMap localhost URLs replaced with env-aware API constant
- Added httpx to backend requirements (live data proxy)
- Added Procfile for Koyeb backend deployment
- Added vercel.json for frontend SPA routing
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude