release: v0.5.0

examples/03_multi_asset_momentum_backup.py

@@ -0,0 +1,69 @@
+"""Multi-Asset Momentum -- relative strength across 5 assets.
+
+Demonstrates:
+  - Multi-asset universe (5 symbols)
+  - Momentum via smoothed ROC on 12h bars
+  - Volatility-adjusted sizing
+
+Usage:
+    python examples/03_multi_asset_momentum.py
+"""
+import os
+import time
+import manifoldbt as mbt
+from manifoldbt.indicators import close, ema, roc, high, low
+from manifoldbt.helpers import time_range, Slippage, Interval
+
+# -- Indicators ---------------------------------------------------------------
+mom = ema(roc(close, 14), 6)                       # 7-day momentum, smoothed
+avg_range = (high - low).rolling_mean(14)
+norm_vol = avg_range / (close + mbt.lit(1e-12))    # normalized volatility
+safe_vol = mbt.when(norm_vol > 0.0005, norm_vol, 0.0005)
+
+# -- Strategy -----------------------------------------------------------------
+signal = mbt.when(mom > 0.0, mom / safe_vol, 0.0)
+
+strategy = (
+    mbt.Strategy.create("multi_momentum")
+    .signal("momentum", mom)
+    .signal("norm_vol", norm_vol)
+    .size(signal * 0.01)
+    .describe("Multi-asset momentum with volatility-adjusted sizing")
+)
+
+# -- Config -------------------------------------------------------------------
+start, end = time_range("2022-01-01", "2025-01-01")
+
+config = mbt.BacktestConfig(
+    universe=[1, 2, 3, 4, 5],
+    time_range_start=start,
+    time_range_end=end,
+    bar_interval=Interval.hours(12),
+    initial_capital=10_000,
+    execution=mbt.ExecutionConfig(
+        signal_delay=1,
+        max_position_pct=0.3,
+        allow_short=False,
+    ),
+    fees=mbt.FeeConfig.binance_perps(),
+    slippage=Slippage.fixed_bps(2),
+    warmup_bars=25,
+)
+
+# -- Run ----------------------------------------------------------------------
+if __name__ == "__main__":
+    root = os.path.join(os.path.dirname(__file__), "..")
+    data_root = os.path.abspath(os.path.join(root, "data"))
+    store = mbt.DataStore(
+        data_root=data_root,
+        metadata_db=os.path.abspath(os.path.join(root, "metadata", "metadata.sqlite")),
+        arrow_dir=os.path.join(data_root, "mega"),
+    )
+
+    t0 = time.perf_counter()
+    result = mbt.run(strategy, config, store)
+    elapsed = time.perf_counter() - t0
+
+    print(result.summary())
+    print(f"\nElapsed: {elapsed:.3f}s")
+    mbt.plot.summary(result, show=True)

examples/15_cross_exchange.py

@@ -4,6 +4,8 @@ Simple RSI mean-reversion:
 - RSI computed on Binance BTC perp data
 - Trades executed at dYdX BTC-USD prices
 - Both loaded via universe dict — no special config needed
+- Per-venue fees: each symbol is charged its own exchange's fee schedule
+  (see FeeConfig.multi_venue below)
 
 Prerequisite:
     Binance perp data (bars_1m/201.arrow) + dYdX data (dydx/1h/BTC-USD.arrow)
@@ -59,7 +61,21 @@ config = mbt.BacktestConfig(
     initial_capital=10_000,
     warmup_bars=30,
     execution=mbt.ExecutionConfig(signal_delay=1),
-    fees=mbt.FeeConfig(maker_fee_bps=1.0, taker_fee_bps=2.5),
+    # Per-venue fees: each symbol pays the fee schedule of the exchange it
+    # executes on. Fills happen on dYdX (the execution venue), so the dYdX
+    # taker fee is what actually hits this strategy; the Binance entry is
+    # signal-only. Symbols without a mapping fall back to `default`.
+    fees=mbt.FeeConfig.multi_venue(
+        default=mbt.VenueFees(maker_fee_bps=1.0, taker_fee_bps=2.5),
+        venues={
+            "dydx": mbt.VenueFees(maker_fee_bps=2.0, taker_fee_bps=5.0),
+            "binance": mbt.VenueFees(maker_fee_bps=1.0, taker_fee_bps=2.5),
+        },
+        symbol_venue={
+            "dydx:BTC-USD:perp": "dydx",        # execution venue (fills here)
+            "binance:BTC-USDT:perp": "binance",  # signal source only
+        },
+    ),
     slippage=Slippage.fixed_bps(2),
 )
 

examples/17_per_venue_fees.py

@@ -0,0 +1,111 @@
+"""Example 17: Per-Venue Fees — charge each symbol its own fee schedule.
+
+Real desks route different assets to different exchanges (or liquidity tiers),
+each with its own maker/taker fees, funding column and borrow rate. ``FeeConfig``
+models this directly: a ``default`` venue plus named ``per_venue`` overrides and a
+``symbol_venue`` map saying which symbol trades where.
+
+Here a 4-asset momentum portfolio executes the majors (BTC, ETH) on a cheap
+venue and the alts (XRP, DOT) on a more expensive one. Single-provider universe,
+so it runs without Pro.
+
+Usage:
+    python examples/17_per_venue_fees.py
+"""
+import os
+import time
+import manifoldbt as mbt
+from manifoldbt.indicators import close, ema, roc, high, low
+from manifoldbt.helpers import time_range, Slippage, Interval
+
+# -- Indicators ---------------------------------------------------------------
+mom = ema(roc(close, 14), 6)
+avg_range = (high - low).rolling_mean(14)
+norm_vol = avg_range / (close + mbt.lit(1e-12))
+safe_vol = mbt.when(norm_vol > 0.0005, norm_vol, 0.0005)
+
+# -- Strategy -----------------------------------------------------------------
+signal = mbt.when(mom > 0.0, mom / safe_vol, 0.0)
+
+strategy = (
+    mbt.Strategy.create("per_venue_momentum")
+    .signal("momentum", mom)
+    .signal("norm_vol", norm_vol)
+    .size(signal * 0.01)
+    .describe("Multi-asset momentum with per-venue fees")
+)
+
+# -- Per-venue fees -----------------------------------------------------------
+# Majors fill on a cheap venue; alts on a pricier one. Symbols absent from
+# `symbol_venue` would fall back to `default`. Keys are symbol names (qualified
+# with the provider), resolved to SymbolIds automatically.
+fees = mbt.FeeConfig.multi_venue(
+    default=mbt.VenueFees(maker_fee_bps=2.0, taker_fee_bps=5.0),
+    venues={
+        "cheap":     mbt.VenueFees(maker_fee_bps=1.0, taker_fee_bps=3.0),
+        "expensive": mbt.VenueFees(maker_fee_bps=5.0, taker_fee_bps=12.0),
+    },
+    symbol_venue={
+        "binance:BTC-USDT:perp": "cheap",
+        "binance:ETH-USDT:perp": "cheap",
+        "binance:XRP-USDT:perp": "expensive",
+        "binance:DOT-USDT:perp": "expensive",
+    },
+)
+
+# -- Config -------------------------------------------------------------------
+start, end = time_range("2022-01-01", "2025-01-01")
+
+config = mbt.BacktestConfig(
+    universe={
+        "binance": ["BTC-USDT:perp", "ETH-USDT:perp",
+                    "XRP-USDT:perp", "DOT-USDT:perp"],
+    },
+    time_range_start=start,
+    time_range_end=end,
+    bar_interval=Interval.hours(12),
+    initial_capital=10_000,
+    execution=mbt.ExecutionConfig(
+        signal_delay=1,
+        max_position_pct=0.3,
+        allow_short=False,
+    ),
+    fees=fees,
+    slippage=Slippage.fixed_bps(2),
+    warmup_bars=25,
+)
+
+# -- Run ----------------------------------------------------------------------
+if __name__ == "__main__":
+    root = os.path.join(os.path.dirname(__file__), "..")
+    data_root = os.path.abspath(os.path.join(root, "data"))
+    store = mbt.DataStore(
+        data_root=data_root,
+        metadata_db=os.path.abspath(os.path.join(root, "metadata", "metadata.sqlite")),
+        arrow_dir=os.path.join(data_root, "mega"),
+    )
+
+    t0 = time.perf_counter()
+    result = mbt.run(strategy, config, store)
+    elapsed = time.perf_counter() - t0
+
+    print(result.summary())
+
+    # Show that fees actually differ by venue: average fee in bps per symbol.
+    trades = result.trades
+    if trades.num_rows > 0:
+        sids = trades.column("symbol_id").to_pylist()
+        fee_vals = trades.column("fees").to_pylist()
+        qty = trades.column("quantity").to_pylist()
+        fill = trades.column("fill_price").to_pylist()
+        agg: dict[int, list[float]] = {}
+        for sid, f, q, p in zip(sids, fee_vals, qty, fill):
+            notional = abs(q) * p
+            if notional > 0:
+                agg.setdefault(sid, []).append(f / notional * 10_000)
+        print("\nRealized fee (bps) by symbol_id:")
+        for sid in sorted(agg):
+            bps = sum(agg[sid]) / len(agg[sid])
+            print(f"  symbol {sid}: {bps:.2f} bps  ({len(agg[sid])} fills)")
+
+    print(f"\nElapsed: {elapsed:.3f}s")

examples/bench_mega_all_symbols.py

@@ -20,9 +20,12 @@ strategy = (
     .size(mbt.when(trend > 0.0, 0.5, 0.0))
 )
 
-# -- Config: 21 crypto symbols, 3 years, 1h bars --------------------------------
-# SOL (3) starts 2024 only — excluded
-universe = [s for s in range(1, 23) if s != 3]
+# -- Config: all available Binance perp symbols, 3 years, 1h bars -----------------
+universe = {"binance": [
+    "BTC-USDT:perp", "ETH-USDT:perp", "LTC-USDT:perp", "BNB-USDT:perp",
+    "DOT-USDT:perp", "XRP-USDT:perp", "ADA-USDT:perp", "LINK-USDT:perp",
+    "DOGE-USDT:perp", "AVAX-USDT:perp",
+]}
 start, end = time_range("2022-01-01", "2025-01-01")
 
 config = mbt.BacktestConfig(
@@ -56,4 +59,4 @@ elapsed = time.perf_counter() - t0
 print(result.profile_summary())
 print(f"\nWall clock: {elapsed:.3f}s")
 print(f"Trades: {result.trade_count}")
-print(f"Symbols: {len(universe)}")
+print(f"Symbols: {len(universe['binance'])}")