新版本持仓月报

app/service/data_service_v2_1.py

@@ -32,17 +32,17 @@ class UserCustomerDataAdaptor:
     all_fund_distribution = {}
     all_fund_performance = {}
 
-    def __init__(self, user_id, customer_id, end_date=str(datetime.date.today()), index_id="IN0000007M"):
+    def __init__(self, user_id, customer_id, end_date=str("2020-12-31"), index_id="IN0000007M"):
         self.user_id = user_id
         self.customer_id = customer_id
         self.compare_index_id = index_id
         p_end_date = pd.to_datetime(end_date).date()
         p_end_date = datetime.date(year=p_end_date.year, month=p_end_date.month, day=1) - datetime.timedelta(days=1)
         self.end_date = pd.to_datetime(str(p_end_date))
-        self.end_date = pd.to_datetime("2020-12-18")
+        # self.end_date = pd.to_datetime("2020-12-25")
         p_start_date = datetime.date(year=p_end_date.year, month=p_end_date.month, day=1)
         self.month_start_date = p_start_date
-        self.month_start_date = pd.to_datetime("2020-12-01")
+        # self.month_start_date = pd.to_datetime("2020-12-01")
         self.user_customer_order_df = self.get_user_customer_order_data()
         self.fund_nav_total, self.fund_cnav_total = self.get_customer_fund_nav_data()
         self.index_df = self.get_customer_index_nav_data()
@@ -256,8 +256,8 @@ class UserCustomerDataAdaptor:
 
             # 根据确认净值日查看是否含有累积净值的数据，如果没有按照前后差值推算当天累积净值
             if pd.isnull(p_nav_df.loc[confirm_share_date, cur_fund_id]):
-                last_nav_data = p_nav_df[p_nav_df.index < confirm_share_date][cur_fund_id].dropna().tail(1)
-                last_cnav_data = p_cnav_df[p_cnav_df.index < confirm_share_date][cur_fund_id].dropna().tail(1)
+                last_nav_data = p_nav_df[p_nav_df.index > confirm_share_date][cur_fund_id].dropna().head(1)
+                last_cnav_data = p_cnav_df[p_cnav_df.index > confirm_share_date][cur_fund_id].dropna().head(1)
                 # 判断上个净值日和当前确认日之中是否存在分红日
                 """need add judge"""
 
@@ -351,8 +351,8 @@ class UserCustomerDataAdaptor:
 
             # 根据确认净值日查看是否含有累积净值的数据，如果没有按照前后差值推算当天累积净值
             if pd.isnull(p_nav_df.loc[confirm_share_date, cur_fund_id]):
-                last_nav_data = p_nav_df[p_nav_df.index < confirm_share_date][cur_fund_id].dropna().tail(1)
-                last_cnav_data = p_cnav_df[p_cnav_df.index < confirm_share_date][cur_fund_id].dropna().tail(1)
+                last_nav_data = p_nav_df[p_nav_df.index > confirm_share_date][cur_fund_id].dropna().head(1)
+                last_cnav_data = p_cnav_df[p_cnav_df.index > confirm_share_date][cur_fund_id].dropna().head(1)
                 # 判断上个净值日和当前确认日之中是否存在分红日
                 """need add judge"""
 

app/service/portfolio_diagnose.py

@@ -873,12 +873,12 @@ class PortfolioDiagnose(object):
         index_return["new_index_return"] = (index_return["index"] - start_index_return) / (1 + start_index_return)
         index_return_ratio = index_return["new_index_return"].values[-1]
         index_return_ratio_year = annual_return(index_return["new_index_return"].values[-1],
-                                                index_return["new_index_return"], n_freq)
-        index_volatility = volatility(index_return["new_index_return"] + 1, n_freq)
+                                                index_return["new_index_return"], 250)
+        index_volatility = volatility(index_return["new_index_return"] + 1, 250)
         index_drawdown = max_drawdown(index_return["new_index_return"] + 1)
         index_sim = simple_return(index_return["new_index_return"]+1)
-        index_exc = excess_return(index_sim, BANK_RATE, n_freq)
-        index_sharpe = sharpe_ratio(index_exc, index_sim, n_freq)
+        index_exc = excess_return(index_sim, BANK_RATE, 250)
+        index_sharpe = sharpe_ratio(index_exc, index_sim, 250)
 
         # 收益对比数据
         return_compare_df = pd.merge(index_return[["new_index_return"]], old_return_df[["cum_return_ratio"]],

app/service/result_service_v2.py

@@ -178,7 +178,7 @@ class UserCustomerResultAdaptor(UserCustomerDataAdaptor):
                  "return_ratio_year": "%.2f" % round(return_ratio_year*100, 2)}
 
             # 对应指数数据
-            index_df = self.get_customer_index_nav_data()
+            index_df = self.get_customer_index_nav_data().dropna()
             index_result = self.signal_fund_profit_result(index_df[index_df.index >= pd.to_datetime(first_trade_date)],
                                                           "index")
             folio_report_data["index_result"] = index_result
@@ -317,7 +317,7 @@ class UserCustomerResultAdaptor(UserCustomerDataAdaptor):
 
         # 月度回报表格数据
         start_year = self.start_date.year
-        now_year = datetime.datetime.now().year
+        now_year = self.end_date.year
         month_return_data_dict = {}
         for i in range(now_year-start_year+1):
             month_return_data_dict[start_year+i] = {j+1: {"profit": "-", "net_amount": "-"} for j in range(12)}
@@ -340,7 +340,7 @@ class UserCustomerResultAdaptor(UserCustomerDataAdaptor):
         report_data["cumulative_return"] = float(cumulative_return)
 
         # 对应指数数据
-        index_df = self.get_customer_index_nav_data()
+        index_df = self.get_customer_index_nav_data().dropna()
         index_result = self.signal_fund_profit_result(index_df[index_df.index >= pd.to_datetime(first_trade_date)], "index")
         report_data["index_result"] = index_result
 
@@ -415,7 +415,10 @@ class UserCustomerResultAdaptor(UserCustomerDataAdaptor):
 
             # 基金持仓数据
             total_market_values = p_sum_profit + p_total_amount #   月末总市值
-            fund_hoding_info = {"fund_strategy_name": dict_substrategy[int(row["substrategy"])], "fund_name": row["fund_name"]}
+            fund_strategy_name = dict_substrategy[int(row["substrategy"])]
+            if "长富" in row["fund_name"] or "盈沛" in row["fund_name"] :
+                fund_strategy_name = "FOF"
+            fund_hoding_info = {"fund_strategy_name": fund_strategy_name, "fund_name": row["fund_name"]}
             fund_hoding_info["confirm_date"] = row["confirm_share_date"].strftime("%Y-%m-%d")
             fund_hoding_info["hold_year"] = "%.2f" % round((self.end_date - pd.to_datetime(row["confirm_share_date"])).days/365.0, 2)    # 存续年数
             fund_hoding_info["market_values"] = round((float(row["confirm_share"]) * (fund_basic_info["cur_cnav"] - confirm_cnav) + float(row["confirm_amount"]))/10000, 2)

app/templates/v2/monthReportV2.1.html

@@ -466,7 +466,7 @@
     }
 
     .par .par_item .par_content.relative_chart table td {
-      padding: 14px 0 14px 0;
+      padding: 7px 0 7px 0;
       text-align: center;
     }
 

app/utils/jinjia2html_v2.py

@@ -318,9 +318,9 @@ class DataIntegrate:
         template = env.get_template('/v2/monthReportV2.1.html')  # 获取一个模板文件
         monthReport_html = template.render(data)  # 渲染
         # 保存 monthReport_html
-        # save_file = "app/html/monthReport.html"
-        # with open(save_file, 'w', encoding="utf-8") as f:
-        #     f.write(monthReport_html)
+        save_file = "app/html/monthReport.html"
+        with open(save_file, 'w', encoding="utf-8") as f:
+            f.write(monthReport_html)
 
         # save_file = "app/html/v2/monthReportV2.html"
         # with open(save_file, 'w', encoding="utf-8") as f: