新组合评价

app/service/portfolio_diagnose.py

@@ -732,9 +732,25 @@ class PortfolioDiagnose(object):
         exc = excess_return(sim, BANK_RATE, n_freq)
         new_sharpe = sharpe_ratio(exc, sim, n_freq)
 
-
-
-        return suggestions_result, suggestions_result_asset
+        propose_fund_id_list_name = []  # 基金名称，策略分级
+
+        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)
+        abandon_fund = (self.abandon_fund_score + self.abandon_fund_corr)
+        proposal_fund = self.proposal_fund
+
+        sentence= ""
+        if hold_fund is not None:
+            sentence.join("在保留".join(hold_fund) + "的基础上，")
+        if abandon_fund is not None:
+            sentence.join("建议赎回".join(abandon_fund) + "，")
+        if proposal_fund is not None:
+            sentence.join("增配".join(proposal_fund) + "后，")
+        if new_drawdown < old_max_drawdown:
+            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
 
     def single_evaluation(self, fund_id):
         """
@@ -884,10 +900,10 @@ portfolio = ['HF00002JJ2', 'HF00005DBQ', 'HF0000681Q', 'HF00006693', 'HF00006AZF
 portfolio_diagnose = PortfolioDiagnose(client_type=1, portfolio=portfolio, invest_amount=10000000)
 portfolio_diagnose.optimize()
 if __name__ == '__main__':
-    # print(portfolio_diagnose.single_fund_radar())
-    # print(portfolio_diagnose.propose_fund_radar())
-    # print(portfolio_diagnose.old_portfolio_evaluation())
-    # print('旧组合相关性：', portfolio_diagnose.old_correlation)
-    # print('新组合相关性：', portfolio_diagnose.new_correlation)
+    print(portfolio_diagnose.single_fund_radar())
+    print(portfolio_diagnose.propose_fund_radar())
+    print(portfolio_diagnose.old_portfolio_evaluation())
+    print('旧组合相关性：', portfolio_diagnose.old_correlation)
+    print('新组合相关性：', portfolio_diagnose.new_correlation)
     print('旧组合个基评价：', portfolio_diagnose.old_portfolio_evaluation())
-    print('新组合个基评价：', portfolio_diagnose.propose_fund_evaluation())
+    print('新组合个基评价：', portfolio_diagnose.propose_fund_evaluation())
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