diff --git a/tests/fetch_3033.py b/tests/fetch_3033.py
new file mode 100644
index 0000000..3369b55
--- /dev/null
+++ b/tests/fetch_3033.py
@@ -0,0 +1,100 @@
+"""
+获取 3033.HK 最新10条数据
+对比复权和不复权价格
+"""
+
+import yfinance as yf
+import pandas as pd
+from typing import Optional
+import os
+
+
+def fetch_3033(period: str = "10d", proxy: Optional[str] = None) -> None:
+    """
+    获取 3033.HK 数据，对比复权和不复权价格
+    
+    Args:
+        period: 获取周期，默认10天
+        proxy: 代理地址，如 "socks5://127.0.0.1:1080"
+    """
+    # 设置代理
+    if proxy:
+        os.environ['HTTP_PROXY'] = proxy
+        os.environ['HTTPS_PROXY'] = proxy
+        print(f"使用代理: {proxy}")
+    
+    code = "3033.HK"
+    ticker = yf.Ticker(code)
+    
+    print(f"\n{'='*80}")
+    print(f"获取 {code} 最新数据")
+    print(f"{'='*80}\n")
+    
+    # 1. 不复权价格 (auto_adjust=False)
+    print("【1. 不复权价格】(auto_adjust=False)")
+    print("-" * 80)
+    data_raw = ticker.history(period=period, auto_adjust=False)
+    if not data_raw.empty:
+        print(f"{'日期':<12} {'开盘':>10} {'收盘':>10} {'最高':>10} {'最低':>10} {'成交量':>12}")
+        print("-" * 80)
+        for date, row in data_raw.tail(10).iterrows():
+            date_str = date.strftime('%Y-%m-%d')
+            print(f"{date_str:<12} {row['Open']:>10.3f} {row['Close']:>10.3f} {row['High']:>10.3f} {row['Low']:>10.3f} {row['Volume']:>12.0f}")
+        print(f"\n最新收盘价: {data_raw['Close'].iloc[-1]:.3f}")
+    else:
+        print("无数据")
+    
+    # 2. 前复权价格 (auto_adjust=True，默认)
+    print(f"\n{'='*80}")
+    print("【2. 前复权价格】(auto_adjust=True，默认)")
+    print("-" * 80)
+    data_adj = ticker.history(period=period, auto_adjust=True)
+    if not data_adj.empty:
+        print(f"{'日期':<12} {'开盘':>10} {'收盘':>10} {'最高':>10} {'最低':>10} {'成交量':>12}")
+        print("-" * 80)
+        for date, row in data_adj.tail(10).iterrows():
+            date_str = date.strftime('%Y-%m-%d')
+            print(f"{date_str:<12} {row['Open']:>10.3f} {row['Close']:>10.3f} {row['High']:>10.3f} {row['Low']:>10.3f} {row['Volume']:>12.0f}")
+        print(f"\n最新收盘价: {data_adj['Close'].iloc[-1]:.3f}")
+    else:
+        print("无数据")
+    
+    # 3. 对比
+    if not data_raw.empty and not data_adj.empty:
+        print(f"\n{'='*80}")
+        print("【3. 价格对比】")
+        print("-" * 80)
+        latest_raw = data_raw['Close'].iloc[-1]
+        latest_adj = data_adj['Close'].iloc[-1]
+        print(f"不复权最新价: {latest_raw:.3f}")
+        print(f"前复权最新价: {latest_adj:.3f}")
+        print(f"差异: {abs(latest_raw - latest_adj):.3f} ({abs(latest_raw - latest_adj)/latest_raw*100:.2f}%)")
+    
+    print(f"\n{'='*80}")
+
+
+def main():
+    """主函数"""
+    # 检查是否需要使用代理
+    # 如果 Clash 开启，使用 Clash HTTP 代理
+    # 如果 SSH 隧道开启，使用 SOCKS5 代理
+    
+    # 使用 Clash HTTP 代理
+    proxy = "http://127.0.0.1:7890"
+    
+    # 如果 Clash 不可用，尝试 SOCKS5 代理（SSH 隧道）
+    # proxy = "socks5://127.0.0.1:1080"
+    
+    try:
+        fetch_3033(period="10d", proxy=proxy)
+    except Exception as e:
+        print(f"使用代理 {proxy} 失败: {e}")
+        print("\n尝试不使用代理...")
+        try:
+            fetch_3033(period="10d", proxy=None)
+        except Exception as e2:
+            print(f"无代理也失败: {e2}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tests/fetch_au9999.py b/tests/fetch_au9999.py
new file mode 100644
index 0000000..2969d44
--- /dev/null
+++ b/tests/fetch_au9999.py
@@ -0,0 +1,119 @@
+"""
+使用 Tushare 获取 AU9999 黄金数据
+"""
+
+import os
+import pandas as pd
+import tushare as ts
+from datetime import datetime, timedelta
+from typing import Optional
+from dotenv import load_dotenv
+
+
+def get_tushare_token() -> str:
+    """从环境变量获取 Tushare token"""
+    load_dotenv()
+    token = os.environ.get('TUSHARE_TOKEN')
+    if not token:
+        raise ValueError("未设置 TUSHARE_TOKEN 环境变量")
+    return token
+
+
+def fetch_au9999(start_date: str, end_date: str) -> Optional[pd.DataFrame]:
+    """
+    获取 AU9999 黄金现货数据（使用上期所黄金主力合约 AU.SHF）
+    
+    Args:
+        start_date: 开始日期 (YYYY-MM-DD)
+        end_date: 结束日期 (YYYY-MM-DD)
+    
+    Returns:
+        DataFrame with columns: date, open, high, low, close, vol
+    """
+    try:
+        # 初始化 Tushare
+        pro = ts.pro_api(get_tushare_token())
+        
+        # 转换日期格式
+        start_str = start_date.replace('-', '')
+        end_str = end_date.replace('-', '')
+        
+        print(f"从 Tushare 获取 AU9999 数据...")
+        print(f"时间范围: {start_date} ~ {end_date}")
+        
+        # 获取黄金期货主力合约数据
+        # ts_code: AU.SHF 表示上海期货交易所黄金主力合约
+        df = pro.fut_daily(ts_code='AU.SHF', start_date=start_str, end_date=end_str)
+        
+        if df is None or df.empty:
+            print("未获取到数据")
+            return None
+        
+        # 标准化列名
+        df = df.rename(columns={
+            'trade_date': 'date',
+            'open': 'open',
+            'high': 'high',
+            'low': 'low',
+            'close': 'close',
+            'vol': 'volume',
+        })
+        
+        # 转换日期格式
+        df['date'] = pd.to_datetime(df['date'])
+        df = df.set_index('date')
+        df = df.sort_index()
+        
+        # 选择需要的列
+        df = df[['open', 'high', 'low', 'close', 'volume']]
+        
+        print(f"✓ 获取成功: {len(df)} 条数据")
+        print(f"时间范围: {df.index[0].strftime('%Y-%m-%d')} ~ {df.index[-1].strftime('%Y-%m-%d')}")
+        
+        return df
+        
+    except Exception as e:
+        print(f"获取数据失败: {e}")
+        return None
+
+
+def print_au9999_data(df: pd.DataFrame):
+    """打印 AU9999 数据"""
+    print("\n" + "="*80)
+    print("AU9999 黄金数据 (上期所主力合约 AU.SHF)")
+    print("="*80)
+    print(f"{'日期':<15} {'开盘价':>12} {'最高价':>12} {'最低价':>12} {'收盘价':>12} {'成交量':>12}")
+    print("-"*80)
+    
+    for date, row in df.iterrows():
+        date_str = date.strftime('%Y-%m-%d')
+        print(f"{date_str:<15} {row['open']:>12.2f} {row['high']:>12.2f} {row['low']:>12.2f} {row['close']:>12.2f} {row['volume']:>12.2f}")
+    
+    print("="*80)
+
+
+def main():
+    """主函数"""
+    # 计算最近30天的日期范围
+    end_date = datetime.now()
+    start_date = end_date - timedelta(days=30)
+    
+    start_str = start_date.strftime('%Y-%m-%d')
+    end_str = end_date.strftime('%Y-%m-%d')
+    
+    # 获取数据
+    df = fetch_au9999(start_str, end_str)
+    
+    if df is not None:
+        print_au9999_data(df)
+        
+        # 保存到CSV
+        output_file = "au9999_data.csv"
+        df.to_csv(output_file)
+        print(f"\n数据已保存: {output_file}")
+    else:
+        print("获取数据失败")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tests/fetch_btc_okx.py b/tests/fetch_btc_okx.py
new file mode 100644
index 0000000..8afa632
--- /dev/null
+++ b/tests/fetch_btc_okx.py
@@ -0,0 +1,109 @@
+"""
+从 OKX 获取 BTC 日线数据
+使用 CCXT 库，支持本地 Clash HTTP 代理
+"""
+
+import ccxt
+import pandas as pd
+from datetime import datetime, timedelta
+from typing import Optional
+import os
+
+
+def fetch_btc_okx(days: int = 10, http_proxy: str = "http://127.0.0.1:7890") -> Optional[pd.DataFrame]:
+    """
+    从 OKX 获取 BTC/USDT 日线数据
+    
+    Args:
+        days: 获取最近多少天的数据，默认10天
+        http_proxy: HTTP 代理地址，默认使用本地 Clash 代理 http://127.0.0.1:7890
+    
+    Returns:
+        DataFrame with columns: date, open, high, low, close, volume
+    """
+    try:
+        # 配置 CCXT
+        config = {'enableRateLimit': True}
+        
+        # 设置 HTTP 代理
+        if http_proxy:
+            config['proxies'] = {'http': http_proxy, 'https': http_proxy}
+            print(f"使用 HTTP 代理: {http_proxy}")
+        
+        # 创建 OKX 交易所实例
+        exchange = ccxt.okx(config)
+        
+        # 计算时间范围
+        end_date = datetime.now()
+        start_date = end_date - timedelta(days=days + 5)  # 多取几天确保有足够数据
+        
+        since = int(start_date.timestamp() * 1000)
+        
+        print(f"从 OKX 获取 BTC/USDT 最近{days}天数据...")
+        print(f"时间范围: {start_date.strftime('%Y-%m-%d')} ~ {end_date.strftime('%Y-%m-%d')}")
+        
+        # 获取日线数据
+        ohlcv = exchange.fetch_ohlcv('ETH/USDT', '1d', since, limit=100)
+        
+        if not ohlcv:
+            print("未获取到数据")
+            return None
+        
+        # 转换为 DataFrame
+        df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
+        
+        # 转换时间戳为日期索引（UTC -> 北京时间）
+        df['date'] = pd.to_datetime(df['timestamp'], unit='ms', utc=True).dt.tz_convert('Asia/Shanghai')
+        df = df.set_index('date')
+        df = df[['open', 'high', 'low', 'close', 'volume']]
+        
+        # 过滤最近N天
+        df = df.tail(days)
+        
+        print(f"✓ 获取成功: {len(df)} 条数据")
+        print(f"时间范围: {df.index[0].strftime('%Y-%m-%d %H:%M')} ~ {df.index[-1].strftime('%Y-%m-%d %H:%M')}")
+        
+        return df
+        
+    except Exception as e:
+        print(f"获取数据失败: {e}")
+        return None
+
+
+def print_btc_data(df: pd.DataFrame):
+    """打印 BTC 数据"""
+    print("\n" + "="*80)
+    print("BTC/USDT 日线数据 (OKX)")
+    print("="*80)
+    print(f"{'日期':<20} {'开盘价':>12} {'最高价':>12} {'最低价':>12} {'收盘价':>12} {'成交量':>12}")
+    print("-"*80)
+    
+    for date, row in df.iterrows():
+        date_str = date.strftime('%Y-%m-%d %H:%M')
+        print(f"{date_str:<20} {row['open']:>12.2f} {row['high']:>12.2f} {row['low']:>12.2f} {row['close']:>12.2f} {row['volume']:>12.4f}")
+    
+    print("="*80)
+
+
+def main():
+    """主函数"""
+    # 使用本地 Clash HTTP 代理（默认端口 7890）
+    # 如果 Clash 使用其他端口，请修改此处
+    http_proxy = "http://127.0.0.1:7890"
+    
+    # 获取数据
+    df = fetch_btc_okx(days=10, http_proxy=http_proxy)
+    
+    if df is not None:
+        print_btc_data(df)
+        
+        # 保存到CSV
+        output_file = "btc_okx_1d.csv"
+        df.to_csv(output_file)
+        print(f"\n数据已保存: {output_file}")
+    else:
+        print("获取数据失败")
+
+
+if __name__ == "__main__":
+    main()