Initial commit: manifoldbt public repo

Python DSL, examples, docs, benchmarks, and tests.
Rust engine distributed as pre-compiled wheel via PyPI.

README.md

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+# ManifoldBT
+
+**Rust-powered backtesting engine for quantitative research.**
+
+ManifoldBT is a high-performance backtesting framework with a Python DSL that compiles strategies into an optimized Rust expression graph. It is designed for speed, correctness, and ergonomics.
+
+## Highlights
+
+- **Rust core** — vectorized engine handles 1-minute resolution across years of data
+- **Python DSL** — fluent strategy builder with indicators, signals, and sizing
+- **Monte Carlo** — permutation-based simulation for robustness testing
+- **Walk-Forward** — out-of-sample validation with rolling windows
+- **Parameter Sweeps** — 2D heatmaps and 3D surface plots
+- **Portfolio** — multi-strategy portfolio with risk rules and rebalancing
+
+## Installation
+
+```bash
+pip install manifoldbt
+```
+
+With plotting support:
+
+```bash
+pip install manifoldbt[all]
+```
+
+## Quick Start
+
+```python
+import manifoldbt as mbt
+from manifoldbt.indicators import close, ema
+from manifoldbt.helpers import time_range, Interval, Slippage
+
+# Define indicators
+fast = ema(close, 12)
+slow = ema(close, 26)
+
+# Build strategy
+strategy = (
+    mbt.Strategy.create("ema_crossover")
+    .signal("fast", fast)
+    .signal("slow", slow)
+    .signal("signal", mbt.when(fast > slow, mbt.lit(1.0), mbt.lit(-1.0)))
+    .size(mbt.col("signal") * mbt.lit(0.25))
+)
+
+# Configure backtest
+start, end = time_range("2022-01-01", "2025-01-01")
+config = mbt.BacktestConfig(
+    universe=[1],
+    time_range_start=start,
+    time_range_end=end,
+    bar_interval=Interval.hours(12),
+    initial_capital=10_000,
+    execution=mbt.ExecutionConfig(allow_short=True, max_position_pct=0.5),
+    fees=mbt.FeeConfig.binance_perps(),
+    slippage=Slippage.fixed_bps(2),
+    warmup_bars=30,
+)
+
+# Run
+store = mbt.DataStore(data_root="data", metadata_db="metadata/metadata.sqlite")
+result = mbt.run(strategy, config, store)
+print(result.summary())
+```
+
+## Examples
+
+See the [examples/](examples/) directory for complete runnable strategies:
+
+| # | Example | Description |
+|---|---------|-------------|
+| 00 | [Template](examples/00_template.py) | Minimal starting point |
+| 01 | [Trend Following](examples/01_trend_following.py) | EMA crossover with stop-loss and volume filter |
+| 02 | [Mean Reversion](examples/02_mean_reversion.py) | EMA crossover with parameter sweep |
+| 03 | [Multi-Asset Momentum](examples/03_multi_asset_momentum.py) | Cross-asset momentum signals |
+| 04 | [Linear Regression](examples/04_linear_regression.py) | Regression-based signal |
+| 05 | [Statistical Arbitrage](examples/05_stat_arb.py) | Pairs trading with spread z-score |
+| 06 | [Full Visualization](examples/06_full_visualization.py) | Complete tearsheet and charts |
+| 07 | [Walk-Forward](examples/07_walk_forward.py) | Out-of-sample validation |
+| 08 | [2D Sweep Heatmap](examples/08_sweep_2d_heatmap.py) | Parameter grid search |
+| 09 | [3D Surface](examples/09_surface_3d.py) | 3D parameter surface plot |
+| 10 | [Monte Carlo](examples/10_monte_carlo.py) | Permutation-based robustness |
+| 11 | [Portfolio](examples/11_portfolio.py) | Multi-strategy portfolio |
+
+## Documentation
+
+- [Strategy Authoring Guide](docs/strategy-authoring.md) — full DSL reference
+
+## Performance
+
+ManifoldBT's Rust engine is orders of magnitude faster than pure-Python alternatives:
+
+| Engine | 500K bars | 5M bars |
+|--------|-----------|---------|
+| **ManifoldBT** | ~0.02s | ~0.15s |
+| vectorbt | ~0.8s | ~8s |
+| backtrader | ~12s | ~120s+ |
+
+Run `python benchmarks/bench_vs_competitors.py` to reproduce.
+
+## License
+
+MIT