整理 course 目录：原课程归入同名文件夹，新增学习资料/动手练习分类

2026-09-28 11:52:44 +08:00
parent 5629d57ea7
commit cb211da473
51 changed files with 398 additions and 32 deletions
@@ -0,0 +1,48 @@
+"""量化练习公共库：数据获取(带缓存+重试) + 常用指标 + 回测指标。"""
+import os, time, pandas as pd, numpy as np
+
+CACHE = os.path.join(os.path.dirname(__file__), "..", "data", "cache")
+os.makedirs(CACHE, exist_ok=True)
+
+def _fetch(symbol, start, end, adjust, retries=6, wait=2.0):
+    import akshare as ak
+    last = None
+    for i in range(retries):
+        try:
+            return ak.stock_zh_a_hist(symbol=symbol, period="daily",
+                                      start_date=start, end_date=end, adjust=adjust)
+        except Exception as e:                       # 网络间歇性抽风，重试
+            last = e
+            time.sleep(wait * (i + 1))
+    raise last
+
+def get_daily(symbol="000001", start="20200101", end="20241231", adjust="qfq"):
+    """拉单只A股日线(前复权)，带本地缓存与自动重试。"""
+    f = os.path.join(CACHE, f"{symbol}_{start}_{end}_{adjust}.csv")
+    if os.path.exists(f):
+        return pd.read_csv(f, parse_dates=["日期"])
+    df = _fetch(symbol, start, end, adjust)
+    df.to_csv(f, index=False, encoding="utf-8-sig")
+    return df
+
+def add_returns(df, price_col="收盘"):
+    df = df.copy()
+    df["ret"] = df[price_col].pct_change().fillna(0.0)
+    return df
+
+def net_value(ret):
+    return (1 + pd.Series(ret).fillna(0.0)).cumprod()
+
+def stats(ret, periods=252):
+    ret = pd.Series(ret).fillna(0.0)
+    nv = net_value(ret); total = nv.iloc[-1] - 1
+    ann = (1 + total) ** (periods / max(len(ret), 1)) - 1
+    vol = ret.std() * np.sqrt(periods)
+    sharpe = (ret.mean() * periods) / vol if vol > 0 else np.nan
+    dd = (nv / nv.cummax() - 1).min()
+    calmar = ann / abs(dd) if dd < 0 else np.nan
+    return {"总收益": f"{total:.2%}", "年化": f"{ann:.2%}", "年化波动": f"{vol:.2%}",
+            "夏普": f"{sharpe:.2f}", "最大回撤": f"{dd:.2%}", "卡玛": f"{calmar:.2f}"}
+
+def max_drawdown(nv):
+    return (nv / nv.cummax() - 1).min()