diff --git a/README.md b/README.md
index 4a203ec..5287ca1 100644
--- a/README.md
+++ b/README.md
@@ -295,8 +295,13 @@ easy-tdx backtest SZ 300308 --strategy-file strategies/expma_cross.py --count 20
```bash
python -X utf8 run_all_strategies.py SZ 300308 --count 2000 --cash 1000000 --adjust QFQ
+
+# 加 --show 自动弹出最佳策略的资金曲线 vs 股价对比图
+python -X utf8 run_all_strategies.py SZ 300308 --count 2000 --cash 1000000 --adjust QFQ --show
```
+`--show` 会用 matplotlib 弹出一个双轴对比窗口：左轴蓝色线是归一化股价，右轴红色线是最佳策略的资金曲线，绿三角=买入、黄三角=卖出，标题显示股票名称和关键绩效指标。需要 `pip install matplotlib`。
+
输出示例（以 SZ 300308 为例）：
```
@@ -345,6 +350,25 @@ python -X utf8 run_all_strategies.py SZ 300308 --count 2000 --cash 1000000 --adj
python -X utf8 run_all_strategies.py SH 600519 --count 2000 --cash 1000000 --adjust QFQ
```
+#### `--show` 可视化效果
+
+
+ 
+ SH601088 中国神华 — bollinger_breakout 策略 | 收益 1281.8%
+
+
+
+ 
+ SH600522 中天科技 — kdj_golden 策略 | 收益 568.6%
+
+
+
+ 
+ SH601179 中国西电 — expma_cross 策略 | 收益 168.0%
+
+
+> **⚠️ Demo 展示，不作为操作依据。** 历史回测收益不代表未来表现，策略参数未经过样本外验证。
+
#### 自带策略示例
`strategies/` 目录下有 9 个开箱即用的策略文件，可直接用于 `--strategy-file`：
diff --git a/run_all_strategies.py b/run_all_strategies.py
index 5b8d08e..2037cdc 100644
--- a/run_all_strategies.py
+++ b/run_all_strategies.py
@@ -9,7 +9,6 @@
from __future__ import annotations
-import json
import sys
import time
from pathlib import Path
@@ -21,6 +20,128 @@ sys.path.insert(0, str(Path(__file__).parent / "src"))
import click
+def _setup_chinese_font() -> None:
+ """配置 matplotlib 中文字体，按平台自动选择。"""
+ import platform
+
+ import matplotlib
+
+ system = platform.system()
+ if system == "Windows":
+ candidates = ["Microsoft YaHei", "SimHei", "KaiTi", "FangSong"]
+ elif system == "Darwin":
+ candidates = ["PingFang SC", "Heiti SC", "STHeiti"]
+ else:
+ candidates = ["WenQuanYi Micro Hei", "Noto Sans CJK SC", "Droid Sans Fallback"]
+
+ import matplotlib.font_manager as fm
+
+ available = {f.name for f in fm.fontManager.ttflist}
+ for font in candidates:
+ if font in available:
+ matplotlib.rcParams["font.sans-serif"] = [font, "DejaVu Sans"]
+ break
+ matplotlib.rcParams["axes.unicode_minus"] = False
+
+
+def _map_trade_values(trades_df: Any, equity: Any, initial_cash: float) -> list[float]:
+ """将交易的 datetime 映射到 equity_curve 对应的归一化值。"""
+ eq_dt = equity["datetime"].values
+ eq_norm = equity["total"].values / initial_cash
+ result_vals: list[float] = []
+ for dt in trades_df["datetime"].values:
+ idx = eq_dt.searchsorted(dt, side="right") - 1
+ if idx < 0:
+ idx = 0
+ if idx >= len(eq_norm):
+ idx = len(eq_norm) - 1
+ result_vals.append(float(eq_norm[idx]))
+ return result_vals
+
+
+def _show_best_chart(
+ df: Any,
+ result: Any,
+ strategy_name: str,
+ stock_label: str,
+ stock_name: str,
+ initial_cash: float,
+) -> None:
+ """展示最佳策略资金曲线与股价归一化对比图。"""
+ try:
+ import matplotlib.pyplot as plt
+ except ImportError:
+ click.echo("[!] 需要 matplotlib 才能展示图表: pip install matplotlib")
+ return
+
+ _setup_chinese_font()
+
+ equity = result.equity_curve
+ if equity.empty:
+ click.echo("[!] 最佳策略无资金曲线数据，跳过绘图")
+ return
+
+ fig, ax1 = plt.subplots(figsize=(14, 7))
+
+ # 归一化股价（以第一天收盘价为基准）
+ close_prices = df["close"].values
+ norm_price = close_prices / close_prices[0]
+ dates = df["datetime"] if "datetime" in df.columns else df.index
+ ax1.plot(dates, norm_price, color="steelblue", linewidth=1.2, label="股价 (归一化)")
+ ax1.set_ylabel("股价归一化", color="steelblue", fontsize=11)
+ ax1.tick_params(axis="y", labelcolor="steelblue")
+
+ # 归一化资金曲线（以初始资金为基准）
+ eq_dates = equity["datetime"]
+ eq_values = equity["total"].values / initial_cash
+ ax2 = ax1.twinx()
+ ax2.plot(eq_dates, eq_values, color="crimson", linewidth=1.5,
+ label=f"策略: {strategy_name}")
+ ax2.set_ylabel("资金曲线 (归一化)", color="crimson", fontsize=11)
+ ax2.tick_params(axis="y", labelcolor="crimson")
+
+ # 标记买卖点
+ trades = result.trades
+ if not trades.empty:
+ buy_trades = trades[trades["direction"] == "BUY"]
+ sell_trades = trades[trades["direction"] == "SELL"]
+ if not buy_trades.empty:
+ ax2.scatter(
+ buy_trades["datetime"].values,
+ _map_trade_values(buy_trades, equity, initial_cash),
+ marker="^", color="green", s=30, alpha=0.7, zorder=5, label="买入",
+ )
+ if not sell_trades.empty:
+ ax2.scatter(
+ sell_trades["datetime"].values,
+ _map_trade_values(sell_trades, equity, initial_cash),
+ marker="v", color="orange", s=30, alpha=0.7, zorder=5, label="卖出",
+ )
+
+ # 标题：股票代码 + 名称 + 策略绩效
+ title = f"{stock_label}"
+ if stock_name:
+ title += f" {stock_name}"
+ perf = result.performance
+ ret_str = f"{perf.get('total_return', 0):.1%}"
+ dd_str = f"{perf.get('max_drawdown', 0):.1%}"
+ sharpe_str = f"{perf.get('sharpe', 0):.2f}"
+ title += f" | 最佳策略: {strategy_name} | 收益 {ret_str} 回撤 {dd_str} 夏普 {sharpe_str}"
+
+ ax1.set_title(title, fontsize=12, pad=15)
+ ax1.set_xlabel("日期", fontsize=11)
+
+ # 合并两个轴的图例
+ lines1, labels1 = ax1.get_legend_handles_labels()
+ lines2, labels2 = ax2.get_legend_handles_labels()
+ ax1.legend(lines1 + lines2, labels1 + labels2, loc="upper left", fontsize=9)
+
+ fig.autofmt_xdate()
+ plt.tight_layout()
+ click.echo("\n正在显示图表，关闭窗口后继续...")
+ plt.show()
+
+
@click.command()
@click.argument("market")
@click.argument("code")
@@ -29,6 +150,7 @@ import click
@click.option("--commission", default=0.0003, type=float, help="佣金率")
@click.option("--adjust", default="QFQ", help="复权: NONE/QFQ/HFQ")
@click.option("--period", default="DAILY", help="K线周期")
+@click.option("--show", "show_chart", is_flag=True, help="显示最佳策略资金曲线 vs 股价对比图")
def run_all(
market: str,
code: str,
@@ -37,6 +159,7 @@ def run_all(
commission: float,
adjust: str,
period: str,
+ show_chart: bool,
) -> None:
"""批量运行 strategies/ 目录下所有策略并比较结果。"""
from easy_tdx.backtest.engine import BacktestEngine
@@ -60,6 +183,7 @@ def run_all(
click.echo("正在获取行情数据...")
client = MacClient.from_best_host()
client.connect()
+ stock_name = ""
try:
df = client.get_stock_kline(
mkt,
@@ -69,6 +193,14 @@ def run_all(
count=count,
adjust=parse_adjust(adjust),
)
+ # 获取股票名称
+ if show_chart:
+ try:
+ quotes_df = client.get_stock_quotes([(mkt, code)])
+ if not quotes_df.empty and "name" in quotes_df.columns:
+ stock_name = str(quotes_df.iloc[0]["name"])
+ except Exception:
+ pass
finally:
client.close()
click.echo(f"获取到 {len(df)} 条K线数据")
@@ -268,6 +400,19 @@ def run_all(
for r in errored:
click.echo(f" {r['strategy']}: {r['error']}")
+ # 5. 展示最佳策略曲线图
+ if show_chart and valid:
+ best_name = valid[0]["strategy"]
+ if best_name in backtest_results:
+ _show_best_chart(
+ df=df,
+ result=backtest_results[best_name],
+ strategy_name=best_name,
+ stock_label=f"{market}{code}",
+ stock_name=stock_name,
+ initial_cash=cash,
+ )
+
if __name__ == "__main__":
run_all()
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