https://www.tapd.cn/59187493/documents/show/1159187493001000730

依照文档进行模型优化

asset_pool/asset_optimize.py

@@ -2,6 +2,7 @@ import json
 from abc import ABC, abstractmethod
 from sys import exception
 
+import numpy as np
 import pandas as pd
 from dateutil.relativedelta import relativedelta
 from empyrical import sortino_ratio, annual_volatility
@@ -117,14 +118,15 @@ class FundDividendSortinoAssetOptimize(SortinoAssetOptimize):
         sortino = sortino.T
         sortino['score'] = sortino.apply(lambda r: sum([x['weight'] * r[x['name']] for x in self._config]), axis=1)
         sortino.sort_values('score', ascending=False, inplace=True)
-        records = sortino.to_dict(orient='records')
-        data = {key: record for record in records for key in fund_ids}
+        records = sortino.to_dict(orient='index')
+        data = {fund_ids[k]: v for k, v in records.items()}
         self.save_sortino(day, data)
         # 取得分数高的前optimize_count个
         return pct_change.columns[sortino.index[0:self.optimize_count]].values, sortino['score']
 
     def save_sortino(self, day, datas):
         for key, record in datas.items():
+            record = {k: v for k, v in record.items() if not (np.isnan(v) or np.isinf(v))}
             robo_indicator.update_sortino(key, day, json.dumps(record))
 
     def get_optimize_pool(self, day):
@@ -143,6 +145,8 @@ class FundDividendSortinoAssetOptimize(SortinoAssetOptimize):
                     pool.extend(self.find_optimize(tuple(fund_group), day)[0])
                 elif len(fund_group) <= self.optimize_count:
                     pool.extend(fund_group)
+            if len(pool) < get_config('portfolios.solver.asset-count')[0]:
+                raise ValueError(f"基金优选个数小于{get_config('portfolios.solver.asset-count')[0]}，请调整参数")
             rop.insert(day, AssetPoolType.OPTIMIZE, sorted(pool))
             last_one = rop.get_last_one(day=day, type=AssetPoolType.OPTIMIZE)
         return json.loads(last_one['asset_ids'])
@@ -156,10 +160,12 @@ class FundDividendSortinoAssetOptimize(SortinoAssetOptimize):
         fund_ids = [fund['id'] for fund in funds]
         pct_change = pd.DataFrame(self.get_pct_change(fund_ids, day))
         pct_change.set_index('date', inplace=True)
-        ratio = annual_volatility(
-            pct_change.truncate(before=(day - relativedelta(**self.annual_volatility_section[0]))))
+        pct_change = pct_change.truncate(before=(day - relativedelta(**self.annual_volatility_section[0])))
+        # 时间未够计算年化波动的直接剔除
+        funds = [fund for fund in funds if fund['id'] in pct_change.columns]
+        ratio = annual_volatility(pct_change)
         ratio = pd.Series(ratio).to_dict()
-        annual = {fund_id: value for fund_id in fund_ids for value in ratio.values()}
+        annual = dict(zip(pct_change.columns, ratio.values()))
         self.save_annual(day, annual)
         filters = self.annual_volatility_filter
         for f in filters:
@@ -167,12 +173,14 @@ class FundDividendSortinoAssetOptimize(SortinoAssetOptimize):
             exclude = f.get('exclude')
             volatility = f.get('volatility')
             records = [fund for fund in funds if fund['customType'] == customType and fund['id'] in annual.keys()]
-            if exclude:
+            if exclude is not None:
                 exclude = exclude if len(records) > exclude else len(records)
-                records = records[0:-exclude]
-            if volatility:
-                records = [record for record in records if annual.get(record['id']) > volatility]
-            filtered.extend(records)
+                filtered.extend(records[-exclude:])
+            if volatility is not None:
+                records = [record for record in records[0:exclude] if annual.get(record['id']) > volatility]
+                filtered.extend(records)
+        for f in filtered:
+            funds.remove(f)
         return funds
 
     def save_annual(self, day, annual):
@@ -230,6 +238,7 @@ class FundDividendSortinoAssetOptimize(SortinoAssetOptimize):
             fund_navs.sort_values('nav_date', inplace=True)
             fund_navs = fund_navs.pivot_table(index='nav_date', columns='fund_id', values='nav_cal')
             fund_navs.fillna(method='ffill', inplace=True)
+            fund_navs.dropna(axis=1, inplace=True)
             result = round(fund_navs.pct_change().dropna(), 4)
             result.reset_index(inplace=True)
             result.rename(columns={'nav_date': 'date'}, inplace=True)

config-svrobo_Mdiv_PRR3.yml

@@ -80,11 +80,14 @@ asset-pool: # 资产池模块
     optimize-count: 3 #基金优选个数
     annual-volatility-filter: #1各资产年化波动率末exclude位 2各资产年化波动率大于volatility
       - customType: 1
-        exclude: 2
-        volatility: 0
-      - customType: 2
         exclude: 1
         volatility: 0
+      - customType: 2
+        exclude: 3
+        volatility: 0.05
+      - customType: 3
+        exclude: 2
+        volatility: 0.001
     annual-volatility-section:  # 波动率时间区间
       - years: 3
 portfolios: # 投组模块
@@ -249,7 +252,7 @@ robo-executor: # 执行器相关
   use: ${ROBO_EXECUTOR:backtest} # 执行哪个执行器，优先取系统环境变量ROBO_EXECUTOR的值，默认backtest
   sync-data: ${SYNC_DATA:off} # 是否开启同步资料数据
   backtest: # 回测执行器相关
-    start-date: 2023-01-02 # 回测起始日期
+    start-date: 2013-01-02 # 回测起始日期
     end-date: 2023-10-31 # 回测截止日期
     sealing-period: 10 #调仓封闭期
     start-step: ${BACKTEST_START_STEP:1} # 回测从哪一步开始执行 1:计算资产池；2:计算最优投组：3:计算再平衡信号以及持仓投组