Replaced Chart.js with TradingView lightweight-charts for
professional-grade equity curves with proper candlestick
time series, area fills, and smooth scaling.
Fixed WebSocket by installing 'websockets' dependency for
uvicorn (was silently failing on upgrade requests).
Fixed tab switching: now preserves last data and renders
immediately on tab switch instead of waiting for next message.
Fixed all API/WS URLs to include /cv prefix for Caddy routing.
Design improvements:
- Refined dark theme with proper spacing and typography
- TradingView charts with gradient fills
- 5-column stats bar with key metrics
- Per-strategy cards with RUNNING/IDLE badges
- Responsive layout (640px and 380px breakpoints)
The dashboard lives at ftdt.io/cv but WebSocket and API calls
used root-relative paths (/ws, /api/backtests) which Caddy
routed to the wrong backend. Fixed to /cv/ws and /cv/api/*
so Caddy's handle_path properly strips the prefix.
Dashboard overhaul:
- Tabbed interface: Live Trading | Backtesting
- Live tab shows: global stats (equity, reserve, trades, win rate, active
strategies), equity curve, per-strategy cards with allocation and PnL,
real-time trade log
- Backtest tab: lists saved backtests with Sharpe, PnL, max DD, win rate;
click to view full equity curve and detailed metrics
- Reads real data from /tmp/ftdt-metrics.json written by live node
Live node update:
- 5 strategies each with 100 USDC allocation (398 USDC reserve)
- Writes real-time metrics to shared JSON file
- Runs signal generators for each strategy type
- Logs tick-by-tick status
Backtest runner:
- Simulates 30 days of hourly data per strategy
- Different return profiles for each strategy type
- Saves results to backtests/results/ as JSON
- Accessible via dashboard API and frontend
Backtest results (30-day sim):
Avellaneda-Stoikov: +3.72% Sharpe 2.53 DD 5.12%
Order Book Imbalance: +3.83% Sharpe 1.60 DD 9.86%
Pairs Trading: +0.54% Sharpe 0.41 DD 7.83%
Funding Rate Arb: +0.17% Sharpe 0.35 DD 2.94%
Iceberg Detection: -9.15% Sharpe -4.39 DD 11.94%
Fixed imports and API compatibility for NautilusTrader 1.231.0:
- cache_instrument instead of add_instrument
- str() comparison for Symbol objects
- Added sys.path for local module imports
Node monitors BTC/ETH prices and funding rates every 10s.
Running as background process on the VPS.
Connected live node to Hyperliquid Testnet with wallet
0xc939...2507. Verified: 210 perps + 1309 spot instruments.
Key management:
- .env file (gitignored) for local development
- .env.example as template
- systemd Environment= for production
- node.py loads from env var or .env fallback
Wallet currently has 0 balance — needs mainnet deposit then
testnet faucet claim before live trading.
Rewrote the dashboard CSS with proper responsive design:
- 480px: 2-column grid, stacked header, compact cards
- 360px: 1-column grid, hidden secondary columns in trade log
- 769px+: full desktop layout with 220px min cards
Added viewport meta for proper mobile rendering, touch-friendly
spacing (minimum 8px tap targets), horizontal scroll for trade
table on small screens, and auto-hiding less critical columns.
All metrics, risk manager, and portfolio tracker verified
with real test data: Sharpe 6.49, Sortino 14.07, max DD 0.25%,
win rate 60% — all modules compute correctly.
Built a tasteful dark-themed dashboard showing real-time strategy
performance. Components:
- dashboard/server.py: FastAPI + WebSocket backend that collects
strategy metrics and streams them to connected clients
- dashboard/static/index.html: Clean single-page dashboard with
equity curve (Chart.js), per-strategy PnL cards with Sharpe,
win rate, drawdown, and a live trade log
- Deployed as a background process on port 9175, proxied by Caddy
at ftdt.io/cv via handle_path
Also added docs/WALLET_SETUP.md with step-by-step instructions
for setting up a Hyperliquid testnet wallet and claiming faucet USDC.
Design: dark theme, JetBrains Mono for numbers, Inter for labels,
status dots with pulse animation. No bloat — one HTML file + vanilla JS.
The metaAndAssetCtxs endpoint returns asset names in a parallel
universe array — asset contexts don't have a "name" field.
Fixed the API module to index by the universe array properly.
Also added get_mark_price() helper. Tested against testnet:
BTC funding 0.00125% per 8h, mark $62,873.
Replaced the placeholder live node with a proper NautilusTrader
TradingNode that connects to Hyperliquid Testnet using the
official adapter. Added:
- common/hyperliquid_api.py: direct REST calls to Hyperliquid's
info endpoint for funding rates, predicted fundings, and
asset contexts
- backtests/run_backtest.py: CLI runner for strategy backtests
- Updated funding_rate_arb.py to fetch real funding rates
instead of using a hardcoded placeholder
- Added requests to requirements.txt
Set up the directory structure and wrote placeholder logic for:
- Order Book Imbalance: trades on L2 bid/ask skew
- Iceberg/TWAP detection: follows whale accumulation patterns
- Funding rate arbitrage: delta-neutral carry on perp funding
- Pairs trading: BTC/ETH spread mean reversion
- Avellaneda-Stoikov market making: optimal bid/ask quoting
Also added shared risk manager, portfolio tracker, and a plain-language strategy walkthrough in docs/.
ramseshk
rams