chore: prepare v1.1.0 release

Update version numbers across Rust, Python, and documentation files to 1.1.0. Enhance the .gitignore to include macOS dSYM files and plans directory. Introduce new dependencies in the Rust core library and update the README to reflect recent performance benchmarks and backtesting engine capabilities. Add new artifacts to the benchmarks manifest and improve documentation for the backtesting engine API.

docs/benchmarks.rst

@@ -13,9 +13,92 @@ The authoritative benchmark workflow lives in ``benchmarks/``:
 - Cross-library speed suite: ``benchmarks/test_speed.py``
 - Cross-library accuracy suite: ``benchmarks/test_accuracy.py``
 - TA-Lib head-to-head script: ``benchmarks/bench_vs_talib.py``
+- Backtesting engine benchmark: ``benchmarks/bench_backtest.py``
 - Table generation from benchmark JSON: ``benchmarks/benchmark_table.py``
 - Perf-contract artifact bundle: ``benchmarks/run_perf_contract.py``
 
+Backtesting engine — competitor comparison
+------------------------------------------
+
+Measured on Apple M-series, Python 3.13, Rust 1.91, using an SMA(20/50)
+crossover strategy with 0.1% commission and 5 bps slippage.  Median of 5 runs.
+
+.. list-table:: Speed vs backtesting libraries (signal → equity curve)
+   :header-rows: 1
+
+   * - Library
+     - 1k bars
+     - 10k bars
+     - 100k bars
+     - vs ferro-ta core (100k)
+   * - **ferro-ta** ``backtest_core``
+     - 0.004 ms
+     - 0.033 ms
+     - 0.286 ms
+     - —
+   * - **ferro-ta** ``backtest_ohlcv_core``
+     - 0.004 ms
+     - 0.037 ms
+     - 0.332 ms
+     - ~same
+   * - NumPy vectorized (manual)
+     - 0.013 ms
+     - 0.042 ms
+     - 0.459 ms
+     - 1.6× slower
+   * - vectorbt 0.28
+     - 1.32 ms
+     - 1.31 ms
+     - 2.90 ms
+     - **10× slower**
+   * - backtesting.py
+     - 10.5 ms
+     - 42.3 ms
+     - 319.6 ms
+     - **1,117× slower**
+   * - backtrader 1.9
+     - 53.9 ms
+     - 518 ms
+     - n/a (skipped)
+     - **>15,000× slower**
+
+Accuracy: ferro-ta positions and bar-returns are **bit-exact** against the NumPy
+reference implementation (max per-bar equity diff = 0.00e+00 with zero
+commission/slippage).
+
+Additional ferro-ta capabilities not present in the libraries above:
+
+.. list-table::
+   :header-rows: 1
+
+   * - Capability
+     - ferro-ta result
+     - NumPy baseline
+     - Speedup
+   * - Monte Carlo 1,000 sims (100k bars)
+     - 50 ms (parallel Rayon + LCG)
+     - 612 ms (Python loop)
+     - **12×**
+   * - 23 performance metrics, single call (100k bars)
+     - 2.8 ms
+     - 0.36 ms (2 metrics only)
+     - 0.12 ms / metric
+   * - Multi-asset 100 assets (100k bars)
+     - 43 ms parallel / 88 ms serial
+     - —
+     - 2× parallel speedup
+   * - Walk-forward fold indices (100k bars)
+     - 0.3 µs
+     - —
+     - —
+
+Reproduce the backtest benchmark:
+
+.. code-block:: bash
+
+   python benchmarks/bench_backtest.py --sizes 10000 100000 \
+       --json benchmarks/artifacts/latest/bench_backtest_results.json
+
 Latest checked-in TA-Lib artifact
 ---------------------------------