feat(strategy): 为order_target_percent添加整手调整并支持按标的取消订单

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "akquant"
-version = "0.1.35"
+version = "0.1.36"
 edition = "2024"
 description = "High-performance quantitative trading framework based on Rust and Python"
 license = "MIT"

examples/01_quickstart.py

@@ -1,41 +1,112 @@
+from typing import Any
+
 import akquant as aq
 import akshare as ak
 import pandas as pd
 from akquant import Bar, Strategy
+from akquant.config import BacktestConfig, RiskConfig, StrategyConfig
 
-# 1. 准备数据
-# 使用 akshare 获取 A 股历史数据 (需安装: pip install akshare)
-df = ak.stock_zh_a_daily(symbol="sh600000", start_date="20230101", end_date="20231231")
+df_1 = ak.stock_zh_a_daily(
+    symbol="sh600000", start_date="20000101", end_date="20261231"
+)
+df_1["symbol"] = "600000"
+df_2 = ak.stock_zh_a_daily(
+    symbol="sh600004", start_date="20000101", end_date="20261231"
+)
+df_2["symbol"] = "600004"
+df_3 = ak.stock_zh_a_daily(
+    symbol="sh600006", start_date="20000101", end_date="20261231"
+)
+df_3["symbol"] = "600006"
+df = {"600000": df_1, "600004": df_2, "600006": df_3}
 
 
 class MyStrategy(Strategy):
-    """Simple demo strategy."""
+    """
+    Example strategy for testing broker execution.
+
+    This strategy buys on the first bar and holds for 100 bars or until 10% profit.
+    """
+
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        """Initialize strategy state."""
+        super().__init__()
+        self.bars_held: dict[str, int] = {}
+        self.entry_prices: dict[str, float] = {}
 
     def on_bar(self, bar: Bar) -> None:
-        """Execute on every bar."""
-        # 简单策略示例:
-        # 当收盘价 > 开盘价 (阳线) -> 买入
-        # 当收盘价 < 开盘价 (阴线) -> 卖出
+        """
+        Handle bar data event.
 
-        # 获取当前持仓
-        current_pos = self.get_position(bar.symbol)
+        :param bar: The current bar data
+        """
+        symbol = bar.symbol
+        pos = self.get_position(symbol)
 
-        if current_pos == 0 and bar.close > bar.open:
-            self.buy(bar.symbol, 100)
-            # print(f"[{bar.timestamp_str}] Buy 100 at {bar.close:.2f}")
+        # 维护持仓计数
+        if pos > 0:
+            if symbol not in self.bars_held:
+                self.bars_held[symbol] = 0
+            self.bars_held[symbol] += 1
+        else:
+            # 如果没有持仓，清理状态
+            if symbol in self.bars_held:
+                del self.bars_held[symbol]
+            if symbol in self.entry_prices:
+                del self.entry_prices[symbol]
 
-        elif current_pos > 0 and bar.close < bar.open:
-            self.close_position(bar.symbol)
-            # print(f"[{bar.timestamp_str}] Sell 100 at {bar.close:.2f}")
+        # 交易逻辑
+        if pos == 0:
+            # 简单示例：每个标的买入 33% 仓位
+            self.order_target_percent(target_percent=0.33, symbol=symbol)
+            # 初始化计数器 (虽然会在下个 bar 的 pos>0 分支中自增，但这里先占位)
+            self.bars_held[symbol] = 0
+            self.entry_prices[symbol] = bar.close
 
+        elif pos > 0:
+            entry_price = self.entry_prices.get(symbol, bar.close)
+            current_bars_held = self.bars_held.get(symbol, 0)
 
-# 运行回测
-result = aq.run_backtest(
-    data=df, strategy=MyStrategy, symbol="sh600000", initial_cash=100000
+            # 计算收益率
+            pnl_pct = (bar.close - entry_price) / entry_price
+
+            # 止盈条件：收益率 >= 10%
+            if pnl_pct >= 0.10:
+                self.sell(symbol, pos)
+                print(
+                    f"Take Profit Triggered for {symbol}: Entry={entry_price}, "
+                    f"Current={bar.close}, PnL={pnl_pct:.2%}"
+                )
+            # 持仓时间条件：持有满 100 个 Bar
+            elif current_bars_held >= 100:
+                self.close_position()
+
+
+# 配置风险参数：safety_margin
+risk_config = RiskConfig(safety_margin=0.0001)
+strategy_config = StrategyConfig(risk=risk_config)
+backtest_config = BacktestConfig(
+    strategy_config=strategy_config,
 )
 
+result = aq.run_backtest(
+    strategy=MyStrategy,
+    data=df,
+    initial_cash=5000000,
+    commission_rate=0.0,
+    stamp_tax_rate=0.0,
+    transfer_fee_rate=0.0,
+    min_commission=5.0,
+    lot_size=1,
+    execution_mode=aq.ExecutionMode.NextAverage,
+    config=backtest_config,
+    start_time="20250101",
+    end_time="20250105",
+    symbol=["600000", "600004", "600006"],
+)
 
-pd.set_option("display.max_columns", None)  # 显示所有行
-# 打印回测结果
-print("\n=== Backtest Result ===")
+pd.set_option("display.max_columns", None)
+pd.set_option("display.max_rows", None)
 print(result)
+print(result.orders_df)
+# print(result.equity_curve)

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "maturin"
 
 [project]
 name = "akquant"
-version = "0.1.35"
+version = "0.1.36"
 description = "High-performance quantitative trading framework based on Rust and Python"
 readme = "README.md"
 license = {text = "MIT License"}

python/akquant/strategy.py

@@ -904,9 +904,14 @@ def cancel_order(self, order_id: str) -> None:
         if self.ctx:
             self.ctx.cancel_order(order_id)
 
-    def cancel_all_orders(self) -> None:
-        """取消当前所有未完成的订单."""
-        for order in self.get_open_orders():
+    def cancel_all_orders(self, symbol: Optional[str] = None) -> None:
+        """
+        取消当前所有未完成的订单.
+
+        Args:
+            symbol: 标的代码 (如果不填, 取消所有标的订单)
+        """
+        for order in self.get_open_orders(symbol=symbol):
             self.cancel_order(order.id)
 
     def buy(
@@ -1171,7 +1176,7 @@ def order_target_value(
 
         # 1. Cancel existing open orders for this symbol
         # This prevents "stacking" orders and ensures we target the net exposure
-        self.cancel_all_orders()
+        self.cancel_all_orders(symbol=symbol)
 
         # 2. Get Price
         if price is not None:
@@ -1200,6 +1205,20 @@ def order_target_value(
         target_qty = target_value / current_price
         delta_qty = target_qty - current_qty
 
+        # 3. 整手调整 (向下取整到 lot_size 倍数)
+        current_lot_size = 1
+        if isinstance(self.lot_size, int):
+            current_lot_size = self.lot_size
+        elif isinstance(self.lot_size, dict):
+            val = self.lot_size.get(symbol, self.lot_size.get("DEFAULT", 1))
+            current_lot_size = int(val) if val is not None else 1
+
+        if current_lot_size > 0:
+            if delta_qty > 0:
+                delta_qty = (delta_qty // current_lot_size) * current_lot_size
+            elif delta_qty < 0:
+                delta_qty = -((abs(delta_qty) // current_lot_size) * current_lot_size)
+
         # 自动调整买入数量，防止资金不足
         if delta_qty > 0 and self.ctx:
             max_buy_qty = self._calculate_max_buy_qty(

src/execution.rs

@@ -480,15 +480,15 @@ impl ExecutionClient for RealtimeExecutionClient {
         true
     }
 
-    fn on_order(&mut self, order: Order) {
+    fn on_order(&mut self, _order: Order) {
         // println!(
         //     "[Realtime] Sending Order to Broker: {} {:?} {}",
         //     order.symbol, order.side, order.quantity
         // );
         // In real impl, send to broker API
     }
 
-    fn on_cancel(&mut self, order_id: &str) {
+    fn on_cancel(&mut self, _order_id: &str) {
         // println!("[Realtime] Cancelling Order: {}", order_id);
     }