调仓建议，指标对比

app/service/portfolio_diagnose.py

@@ -702,12 +702,14 @@ class PortfolioDiagnose(object):
                 suggestions["before_optimization"] = 0
                 suggestions["after_optimization"] = value["asset"]
                 suggestions_result[key][suggestions["fund_name"]] = suggestions
+        for key, value in suggestions_result.items():
+            suggestions_result[key] = list(value.values())
         suggestions_result_asset = {"before": total_asset, "after": total_asset}
 
-        # 旧组合累积收益
+        # 旧组合累积收益df
         old_return_df = group_result_data["return_df"]
         old_return_df["cum_return_ratio"] = old_return_df["cum_return_ratio"] - 1
-        # 新组合累积收益
+        # 新组合累积收益df
         propose_fund_return_limit_data = propose_fund_return[propose_fund_return.index >= group_order_start_date]
         start_return = propose_fund_return_limit_data['return'].values[0]
         propose_fund_return_limit_data["new_return"] = (propose_fund_return_limit_data["return"] - start_return)/(1+start_return)
@@ -716,13 +718,15 @@ class PortfolioDiagnose(object):
         start_index_return = index_return[" close"].values[0]
         index_return["new_index_return"] = (index_return[" close"] - start_index_return) / (1 + start_index_return)
 
+        # 新组合累积收益
+        new_return_ratio = propose_fund_return_limit_data["new_return"].values[-1]
         # 新组合区间年化收益率
         freq_max = group_order_df["freq"].max()
         n_freq = freq_days(int(freq_max))
         new_return_ratio_year = annual_return(propose_fund_return_limit_data["new_return"].values[-1], propose_fund_return_limit_data, n_freq)
 
         # 新组合波动率
-        new_volatility_ = volatility(propose_fund_return_limit_data["new_return"]+1, n_freq)
+        new_volatility = volatility(propose_fund_return_limit_data["new_return"]+1, n_freq)
 
         # 新组合最大回撤
         new_drawdown = max_drawdown(propose_fund_return_limit_data["new_return"]+1)
@@ -732,7 +736,13 @@ class PortfolioDiagnose(object):
         exc = excess_return(sim, BANK_RATE, n_freq)
         new_sharpe = sharpe_ratio(exc, sim, n_freq)
 
-        propose_fund_id_list_name = []  # 基金名称，策略分级
+        # 指标对比
+        odl_indicator = {"group_name": "现有持仓组合", "return_ratio": round((old_return-1)*100, 2), "return_ratio_year": round(old_return_ratio_year*100,2),
+                         "volatility": round(old_volatility*100, 2), "max_drawdown": round(old_max_drawdown[0]*100, 2), "sharpe": round(old_sharpe, 2)}
+        new_indicator = {"group_name": "建议优化组合", "return_ratio": round(new_return_ratio*100, 2), "return_ratio_year": round(new_return_ratio_year*100, 2),
+                         "volatility": round(new_volatility*100, 2), "max_drawdown": round(new_drawdown[0]*100, 2), "sharpe": round(new_sharpe, 2)}
+        indicator_compare = [new_indicator, odl_indicator]
+
 
         sentence = "在保留{}的基础上，建议赎回{}，并增配{}后，整体组合波动率大幅降低，最大回撤从{}降到不足{}，年化收益率提升{}个点"
         hold_fund = set(self.portfolio) - set(self.abandon_fund_score + self.abandon_fund_corr)
@@ -750,7 +760,7 @@ class PortfolioDiagnose(object):
             sentence.join("整体组合波动率大幅降低，")
         if new_return_ratio_year > old_return_ratio_year:
             sentence.join("年化收益率提升{}个点。".format(round(new_return_ratio_year-old_return_ratio_year, 1)))
-        return suggestions_result, suggestions_result_asset, sentence
+        return suggestions_result, suggestions_result_asset, indicator_compare, sentence
 
     def single_evaluation(self, fund_id):
         """

app/templates/monthReport.html

@@ -2561,26 +2561,26 @@
                 <th>优化前(万元）</th>
                 <th>优化后(万元）</th>
               </tr>
+
+<!--              <dl>-->
+                {% for key, value in suggestions_result.items()   %}
+               {% for i in range(value|length) %}
               <tr>
-                <td rowspan="3">宏观策略</td>
-                <td>半夏宏观对冲</td>
-                <td class="font_red">200</td>
-                <td class="font_green">1000</td>
-              </tr>
-              <tr>
-                <td>半夏宏观对冲</td>
-                <td class="font_red">200</td>
-                <td class="font_green">1000</td>
-              </tr>
-              <tr>
-                <td>半夏宏观对冲</td>
-                <td class="font_red">200</td>
-                <td class="font_green">1000</td>
+                {% if i == 0%}
+                <td rowspan={{value|length }}>{{key}}</td>
+                {% endif %}
+                <td> {{value[i]["fund_name"]}}</td>
+                <td class="font_red">{{value[i]["before_optimization"]}}</td>
+                <td class="font_green">{{value[i]["after_optimization"]}}</td>
               </tr>
+              {% endfor %}
+                {% endfor %}
+
+
               <tr>
                 <td colspan="2" class="back_gray font_bold">总市值(万元）</td>
-                <td class="font_bold">1200</td>
-                <td class="font_bold">1000</td>
+                <td class="font_bold">{{suggestions_result_asset["before"]}}</td>
+                <td class="font_bold">{{suggestions_result_asset["after"]}}</td>
               </tr>
             </table>
 
@@ -2721,30 +2721,23 @@
                 <th>最大回撤(%)</th>
                 <th>夏普比率</th>
               </tr>
+              {%for i in range(indicator_compare|length)%}
+              {%if i<(indicator_compare|length)-1%}
+              {%if i%2==0 %}
               <tr class="back_yellow1">
-                <td>建议优化组合</td>
-                <td>5.75</td>
-                <td>0.40</td>
-                <td>2.29</td>
-                <td>2.15</td>
-                <td>3.05</td>
-              </tr>
+                {%endif%}
+                {%if i%2==1 %}
               <tr class="back_yellow2">
-                <td>建议优化组合</td>
-                <td>5.75</td>
-                <td>0.40</td>
-                <td>2.29</td>
-                <td>2.15</td>
-                <td>3.05</td>
-              </tr>
-              <tr>
-                <td>现有持仓组合</td>
-                <td>5.75</td>
-                <td>0.40</td>
-                <td>2.29</td>
-                <td>2.15</td>
-                <td>3.05</td>
+                {%endif%}
+              {%endif%}
+                <td>{{indicator_compare[i]["group_name"]}}</td>
+                <td>{{indicator_compare[i]["return_ratio"]}}</td>
+                <td>{{indicator_compare[i]["return_ratio_year"]}}</td>
+                <td>{{indicator_compare[i]["volatility"]}}</td>
+                <td>{{indicator_compare[i]["max_drawdown"]}}</td>
+                <td>{{indicator_compare[i]["sharpe"]}}</td>
               </tr>
+              {%endfor%}
             </table>
 
             <div class="aim_foot">
@@ -2761,7 +2754,7 @@
               <div class="all_item">
                 <div class="all_dot"></div>
                 <div class="all_text">
-                  在保留综合性基金（富国创新，鹏华匠心，汇添富中盘）并增配申毅套利基金后，整体组合的波动率大幅降低，最大回撤从26%降到不足4%，年化收益提升1个点。
+                  {{new_group_evaluation}}
                 </div>
               </div>
             </div>

app/utils/jinjia2html.py

@@ -76,7 +76,8 @@ class DataIntegrate:
 
 # 调仓建议
     def get_transfer_suggestions(self):
-        self.suggestions_result, self.suggestions_result_asset = portfolio_diagnose.new_evaluation("default", self.d, self.user_customer)
+        self.suggestions_result, self.suggestions_result_asset, \
+        self.indicator_compare, self.new_group_evaluation = portfolio_diagnose.new_evaluation("default", self.d, self.user_customer)
 
 # 收益比较
 
@@ -161,7 +162,10 @@ class DataIntegrate:
                 'old_correlation': self.old_correlation,
                 'propose_fund_data_list': self.propose_fund_data_list,
                 'suggestions_result': self.suggestions_result,
-                'suggestions_result_asset': self.suggestions_result_asset
+                'suggestions_result_asset': self.suggestions_result_asset,
+                'indicator_compare': self.indicator_compare,
+                'new_group_evaluation': self.new_group_evaluation
+
                 }
         # 开始渲染html模板
         env = Environment(loader=PackageLoader('app', 'templates'))  # 创建一个包加载器对象