docs: create/update README.md for all 17 crates

Create 8 missing READMEs (config, ctrader-openapi, market-data, ml-data,
model_loader, risk-data, trading-data, training_uploader). Update 9 existing
READMEs to standard template format.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

crates/backtesting/README.md

@@ -1,48 +1,24 @@
-# Backtesting Crate
+# backtesting
 
-## Overview
+Strategy backtesting engine for simulating trading strategies against historical market data.
 
-The `backtesting` crate provides a robust and configurable engine for simulating trading strategies against historical market data. It enables quantitative analysts and developers to evaluate strategy performance, optimize parameters, and validate hypotheses before live deployment.
+## Key Types
+
+- `Backtester` — main backtesting engine
+- `BacktestConfig` — simulation configuration (time range, instruments, slippage, commissions)
+- `BacktestResults` — performance metrics (Sharpe, max drawdown, alpha, beta, Sortino)
 
 ## Features
 
-*   **Historical Data Replay:** Efficiently replays market data from Parquet files, supporting various data granularities (ticks, order book snapshots, candles).
-*   **Comprehensive Performance Metrics:** Calculates key performance indicators such as Sharpe Ratio, Maximum Drawdown, Alpha, Beta, Sortino Ratio, and more.
-*   **Realistic Slippage Modeling:** Configurable slippage models (e.g., fixed, percentage, volume-based) to accurately reflect real-world execution costs.
-*   **Commission Modeling:** Supports various commission structures (e.g., fixed per trade, percentage of value, per share/contract) for accurate P&L calculation.
-*   **Detailed Trade Analytics:** Generates in-depth reports on individual trades, cumulative P&L, win/loss ratios, and trade duration analysis.
-*   **Pluggable Strategy Interface:** Defines a clear interface for users to implement and integrate their custom trading strategies seamlessly.
+- Historical data replay from Parquet files (ticks, order book snapshots, candles)
+- Configurable slippage models (fixed, percentage, volume-based)
+- Commission modeling (fixed, percentage, per-contract)
+- Pluggable strategy interface
 
 ## Usage
 
 ```rust
 use backtesting::{Backtester, BacktestConfig};
-use common::types::InstrumentId;
-use std::path::PathBuf;
-
-let config = BacktestConfig {
-    start_time: "2023-01-01T00:00:00Z".parse().unwrap(),
-    end_time: "2023-01-02T00:00:00Z".parse().unwrap(),
-    data_path: PathBuf::from("./historical_data/"),
-    instruments: vec![InstrumentId::new("BTCUSD".to_string())],
-    // ... other configuration like slippage, commissions
-};
-
-// let mut backtester = Backtester::new(config);
-// let strategy = MySimpleStrategy::new(); // Initialize your strategy
-// backtester.run(&strategy).expect("Backtest failed");
-
-// let results = backtester.get_results();
-// println!("Sharpe Ratio: {}", results.sharpe_ratio);
-// println!("Max Drawdown: {}", results.max_drawdown);
+let config = BacktestConfig { /* ... */ };
+let results = backtester.run(&strategy)?;
 ```
-
-## Testing
-
-```bash
-cargo test --package backtesting
-```
-
-## Documentation
-
-Full API documentation is available at [docs.rs/backtesting](https://docs.rs/backtesting).