diff --git a/debug.py b/debug.py
new file mode 100644
index 0000000..5232a39
--- /dev/null
+++ b/debug.py
@@ -0,0 +1,46 @@
+import logging
+import pandas as pd
+from pyecharts import options as opts
+from pyecharts.charts import Pie, ThemeRiver
+
+from xalpha.cons import convert_date, myround, yesterdaydash, yesterdayobj
+from xalpha.evaluate import evaluate
+from xalpha.exceptions import FundTypeError, TradeBehaviorError
+from xalpha.record import record, irecord
+from xalpha.indicator import indicator
+from xalpha.info import cashinfo, fundinfo, mfundinfo, get_fund_holdings
+from xalpha.trade import (
+    bottleneck,
+    trade,
+    turnoverrate,
+    vtradevolume,
+    xirrcal,
+    itrade,
+    vtradecost,
+)
+from xalpha.multiple import mul,mulfix
+from xalpha.universal import get_fund_type, ttjjcode, get_rt, get_industry_fromxq
+import xalpha.universal as xu
+
+#status = pd.DataFrame([
+#    ['2019-12-31',-0.04],
+#    ['2020-06-09',2738.22],
+#    ['2020-08-05',3668.81],
+#    ['2020-08-10',793.97],
+#    ['2020-12-31',83.93],
+#    ['2021-12-16',1271.55],
+#    ['2021-12-31',111.29]
+#],columns=['date','mf'])
+#status["date"] = pd.to_datetime(status['date'])
+#cashobj = cashinfo(start='2019-04-24')
+#trade(cashobj,status)
+
+status = pd.DataFrame([
+    ['2012-02-17',100000.0],
+    ['2012-03-15',-0.005],
+    ['2012-03-27',103902.230],
+    ['2012-03-29',-0.005],
+],columns=['date','159915'])
+status["date"] = pd.to_datetime(status['date'])
+infoobj = fundinfo('F159915')
+trade(infoobj,status)
\ No newline at end of file
diff --git a/xalpha/indicator.py b/xalpha/indicator.py
index 79ac9f4..acc0243 100644
--- a/xalpha/indicator.py
+++ b/xalpha/indicator.py
@@ -218,15 +218,14 @@ def max_drawdown(self, date=yesterdayobj()):
         :returns: three elements tuple, the first two are the date obj of
             start and end of the time window, the third one is the drawdown amplitude in unit 1.
         """
-        li = [
-            (row["date"], row["netvalue"])
-            for i, row in self.price[self.price["date"] <= date].iterrows()
-        ]
-        res = []
-        for i, _ in enumerate(li):
-            for j in range(i + 1, len(li)):
-                res.append((li[i][0], li[j][0], (li[j][1] - li[i][1]) / li[i][1]))
-        return min(res, key=lambda x: x[2])
+        tmpprice = self.price.loc[:,:]
+        tmpprice.loc[:,'drawdown'] = (tmpprice['netvalue']-tmpprice['netvalue'].expanding(1).max())/tmpprice['netvalue'].expanding(1).max()
+        tmpprice = tmpprice.loc[tmpprice['date']<=date,:]
+        iid = tmpprice.loc[:,'drawdown'].argmin()
+        lastrow = tmpprice.iloc[iid]
+        newhigh = tmpprice.loc[tmpprice.loc[:,'drawdown']>=-0.0001,:]
+        beginrow = newhigh.loc[newhigh['date']<=lastrow['date'],:].iloc[-1]
+        return beginrow['date'],lastrow['date'],lastrow['drawdown']
 
     ## 以上基本为聚宽提供的整体量化指标，以下是其他短线技术面指标
 
diff --git a/xalpha/info.py b/xalpha/info.py
index 26de273..dbaac74 100644
--- a/xalpha/info.py
+++ b/xalpha/info.py
@@ -935,11 +935,16 @@ def update(self):
         if self.code.startswith("96"):
             return self._hk_update()
         lastdate = self.price.iloc[-1].date
-        diffdays = (yesterdayobj() - lastdate).days
-        if (
-            diffdays == 0
-        ):  ## for some QDII, this value is 1, anyways, trying update is compatible (d+2 update)
-            return None
+        if dt.datetime.today().time()>=dt.time(20,00):
+            # if over 20:00, update today's netvalue
+            # diffdays = (today_obj() - lastdate).days
+            diffdays = 0
+        else:
+            diffdays = (yesterdayobj() - lastdate).days
+            if (
+                diffdays == 0
+            ):  ## for some QDII, this value is 1, anyways, trying update is compatible (d+2 update)
+                return None
         self._updateurl = (
             "http://fund.eastmoney.com/f10/F10DataApi.aspx?type=lsjz&code="
             + self.code
@@ -1004,7 +1009,8 @@ def update(self):
         df = df.iloc[::-1]  ## reverse the time order
         df = df[df["date"].isin(opendate)]
         df = df.reset_index(drop=True)
-        df = df[df["date"] <= yesterdayobj()]
+        #df = df[df["date"] <= yesterdayobj()]
+        df = df[df["date"] <= today_obj()]
         if len(df) != 0:
             self.price = self.price.append(df, ignore_index=True, sort=True)
             return df
diff --git a/xalpha/record.py b/xalpha/record.py
index 6b01f67..c69dc41 100644
--- a/xalpha/record.py
+++ b/xalpha/record.py
@@ -146,7 +146,9 @@ def __init__(self, path="input.csv", **readkwds):
         ]
         if "fee" not in df.columns:
             df = df.assign(fee=[0] * len(df))
-        df = df.sort_values(by="date", ascending=True)
+        # 优先使用date进行排序，date相同的时候，使用index排序，即使用记录的顺序
+        df = df.reset_index()
+        df = df.sort_values(by=["date","index"], ascending=True)
         self.status = df
 
     def filter(self, code, start=None, end=None):
diff --git a/xalpha/universal.py b/xalpha/universal.py
index 02ac624..a07b397 100644
--- a/xalpha/universal.py
+++ b/xalpha/universal.py
@@ -142,7 +142,7 @@ def get_token():
     :return:
     """
     r = rget("https://xueqiu.com", headers={"user-agent": "Mozilla"})
-    return r.cookies["xq_a_token"]
+    return r.cookies["xq_a_token"],r.cookies["u"]
 
 
 def get_historical_fromxq(code, count, type_="before", full=False):
@@ -162,7 +162,7 @@ def get_historical_fromxq(code, count, type_="before", full=False):
         url.format(
             code=code, tomorrow=int(tomorrow_ts() * 1000), count=count, type_=type_
         ),
-        cookies={"xq_a_token": get_token()},
+        cookies={"xq_a_token": get_token()[0],"u":get_token()[1]},
         headers={"user-agent": "Mozilla/5.0"},
     )
     df = pd.DataFrame(data=r["data"]["item"], columns=r["data"]["column"])