Renamed all "VIP N" to "Tier N" in config, server, and HTML dropdowns.
Added recalc_equity_curve() that rebuilds the equity curve with new
fee rates. Previously the equity curve was passed through unchanged
when switching tiers, so the chart visually stayed identical even
though PnL numbers changed. Now each tier produces its own curve.
Example OBI historical: Tier 0 equity ends at 141.5, Tier 6 at 149.7 —
the chart visibly shifts up as fees drop from 4.5bp to 2.4bp taker.
Server: recalc endpoint now checks HISTORICAL_DIR as fallback
when file not found in BACKTEST_DIR. Previously historical backtests
returned "not found" on recalc.
Frontend: renderBTDetail now accepts pnl_net/pnl_net_pct from
recalc response (the endpoint returns pnl_net not pnl).
Verified: VIP 0 → VIP 6 on OBI historical backtest changes
net PnL from 54.31% to 66.57% with fees dropping $18.10 → $5.85.
backtests/historical_runner.py: Fetches real 1h candles from Hyperliquid
mainnet API (candleSnapshot endpoint). Runs all 7 strategies against
actual BTC price history (721 candles, 30 days, $63,024→$63,605).
Each strategy's signal logic operates on real OHLCV data with
configurable fee tiers. Saves to backtests/results/historical/.
Results on 30d BTC data at VIP0:
Mean Reversion: +93.87% net (Sharpe 0.94)
Order Book Imbalance: +54.31% net (Sharpe 1.03)
Avellaneda-Stoikov: -1.02% net (Sharpe -0.13)
Iceberg Detection: -33.20% net
Momentum Breakout: -54.72% net
Server: Added /api/backtests/historical (list) and
/api/backtest/historical/{name} (full data) endpoints.
Dashboard: Added "Historical" tab with "Real Data" badge. Cards show
coin + mainnet source. Click opens the same detail panel with fee
tier dropdown and equity chart.
config/fee_tiers.py: complete Hyperliquid fee schedule with perps and spot
base rates plus staking discount multipliers. effective_rate() computes
the actual fee after staking discount. get_perp_fees() returns the
effective rate for a given VIP tier, staking tier, and fee model.
Backtest runner: added --fee-tier (0-6) and --staking-tier flags.
Regenerated all 12 backtests at VIP 0 baseline. Runner now shows fee tier
info at startup.
Server: /api/backtest/{name}/recalc endpoint accepts ?fee_tier=X&staking_tier=Y
and returns recalculated PnL with the new fee structure. On-the-fly
recalculation — no need to re-run the backtest.
Dashboard: VIP tier dropdown (VIP 0-6) and staking tier dropdown
(None/Wood/Bronze/Silver/Gold/Platinum/Diamond) in backtest detail panel.
Changing either instantly recalculates PnL via the API.
Key finding: Cartea-Jaimungal goes from -5.58% net at VIP0 to +2.39% net
at VIP6+Diamond (maker rebate: exchange pays YOU -0.0024% to provide
liquidity). Fee structure completely changes strategy viability assessment.
Backtest runner: added per-trade fee simulation (maker 2bps, taker 5bps).
Each trade now records pnl_gross, pnl_net, and fee. New --no-fees flag
excludes fees from PnL. Output includes pnl_gross/pnl_gross_pct and
fees_total alongside existing pnl (net). Regenerated all 12 backtests.
Server: added /api/backtest/{name}/csv endpoint — returns trades as CSV
with columns time,side,size,price,pnl_gross,pnl_net,fee.
Content-Disposition: attachment triggers browser download.
Dashboard: added "Inc. fees" checkbox toggle in backtest detail panel.
Unchecking shows gross PnL (before fees). "↓ CSV" button downloads
the trade history. Both hidden when detail is closed.
Backtest detail: openDetail() now fetches full backtest JSON from the API
instead of showing "Full trade data not in summary". Renders equity curve
chart + full trade history table with 100 rows.
Backtest reproducibility: replaced hash(key) with fixed per-strategy seeds.
Python's hash() is randomized per process (PYTHONHASHSEED), causing wildly
different results for same strategy across runs. Now deterministic.
Server: added total_trades and sortino to /api/backtests summary response.
Paper trader: fixed Avellaneda-Stoikov simulate using TAKER_FEE instead of
MAKER_FEE. Lowered OBI signal threshold from 5bps to 1.5bps for flat markets.
Live node: added None-guard in get_mark_prices — Hyperliquid testnet API
sometimes returns null, crashing the node. Wrapped in try/except.
Tab IDs now match JavaScript: tab-backtest instead of tab-bt.
Paper trading increased to $100,000 ($10K per strategy, $30K reserve).
Server default paper metrics updated to $100K.
New paper trading engine (live/paper_trader.py):
- Pulls real mainnet prices, orderbooks, funding rates every 2s
- Runs all 7 strategies in simulation without placing orders
- Simulates fills at market with realistic taker fees (0.05%) and slip (1bp)
- Avellaneda-Stoikov: simulates spread capture with 15%/tick fill probability
- Tracks virtual positions and PnL per strategy
- $5,000 capital ($1,000 per strategy, $1,000 reserve)
- Writes to /tmp/ftdt-paper-metrics.json
Dashboard updated with 3 tabs:
- Live Trading (Testnet) — real orders on testnet
- Paper Trading (Mainnet) — simulated fills on real mainnet data
- Backtesting — 30-day simulated results
Server.py: added /ws/paper WebSocket endpoint, paper_clients set,
paper metrics reader and broadcast loop.
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%
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.
ramseshk