6258

basic/sync.py

 import logging
 from abc import ABC, abstractmethod
 from datetime import datetime as dt
+from dateutil.relativedelta import relativedelta
 from typing import List
 from urllib.parse import quote
 
@@ -68,6 +69,10 @@ class JDCDataSync(DataSync, ABC):
 @component(bean_name='index-sync')
 class IndexSync(JDCDataSync):
 
+    @property
+    def start_date(self):
+        return super(IndexSync, self).start_date - relativedelta(years=4)
+
     @property
     def datum_type(self) -> DatumType:
         return DatumType.INDEX
@@ -98,6 +103,10 @@ class IndexSync(JDCDataSync):
 @component(bean_name='eco-sync')
 class EcoSync(JDCDataSync):
 
+    @property
+    def start_date(self):
+        return super(EcoSync, self).start_date - relativedelta(years=4)
+
     @property
     def datum_type(self) -> DatumType:
         return DatumType.ECO

config.yml

@@ -151,7 +151,7 @@ rebalance: # 再平衡模块
         fed-threshold: -0.75 # fed判断阀值
     right-side: # 市场右侧相关
       rtn-days: 5 # 计算spx回报率滚动天数，交易日
-      min-threshold: -0.03 # spx回报率跌破阀值
+      min-threshold: -0.05 # spx回报率跌破阀值
       coef: 0.95 # 计算cvar的系数
       cvar-min-volume: 30 # 计算cvar至少需要多少交易日数据
     high-low-buy: # 高低买入相关
@@ -226,7 +226,7 @@ robo-executor: # 执行器相关
   backtest: # 回测执行器相关
     start-date: 2008-01-02 # 回测起始日期
     end-date: 2022-11-01 # 回测截止日期
-    start-step: ${BACKTEST_START_STEP:1} # 回测从哪一步开始执行 1:计算资产ewma；2:计算资产池；3:计算最优投组：4:计算再平衡信号以及持仓投组
+    start-step: ${BACKTEST_START_STEP:4} # 回测从哪一步开始执行 1:计算资产ewma；2:计算资产池；3:计算最优投组：4:计算再平衡信号以及持仓投组
     end-step: ${BACKTEST_END_STEP:4} # 回测从哪一步执行完成后结束执行 1:计算资产ewma；2:计算资产池；3:计算最优投组：4:计算再平衡信号以及持仓投组
     clean-up: on
   real: # 实盘执行器

rebalance/drift_solver.py

@@ -21,7 +21,7 @@ class DateCurve(DriftSolver):
     def get_drift(self, day, risk: PortfoliosRisk):
         last_re = rrs.get_last_one(max_date=day, risk=risk, effective=True)
         result = self.diff_threshold - self.init_factor * (day - last_re['date']).days ** 4
-        return max(0, result)
+        return result
 
 
 @component(bean_name='high-weight')

rebalance/signals/curve_drift.py

@@ -22,15 +22,16 @@ class CurveDrift(BaseRebalanceSignal):
             SignalType.CRISIS_ONE,
             SignalType.CRISIS_TWO,
             SignalType.MARKET_RIGHT,
-            SignalType.INIT
+            SignalType.INIT,
+            SignalType.LOW_BUY
         ]
 
     def is_trigger(self, day, risk: PortfoliosRisk) -> bool:
         last_re = rrs.get_last_one(max_date=day, risk=risk, effective=True)
         if last_re is None or SignalType(last_re['type']) in self.exclude_last_type:
             return False
-        if last_re['date'] + relativedelta(days=120) <= day:
-            return True
+        # if last_re['date'] + relativedelta(days=120) <= day:
+        #     return True
         hr_datums = self._datum.get_high_risk_datums(risk)
         datum_ids = [x['id'] for x in hr_datums]
         normal_portfolio = self._builder.get_portfolios(day, risk)

rebalance/test_case.py

@@ -13,7 +13,7 @@ class RebalanceTest(unittest.TestCase):
 
     @autowired(names={'builder': 'crisis_one'})
     def test_crisis_one(self, builder: RebalanceSignal = None):
-        start = parse_date('2018-07-06')
+        start = parse_date('2008-01-07')
         end = start + relativedelta(years=3)
         while start < end:
             signal = builder.is_trigger(start, PortfoliosRisk.FT9)
@@ -33,7 +33,7 @@ class RebalanceTest(unittest.TestCase):
 
     @autowired(names={'builder': 'market-right'})
     def test_market_right(self, builder: RebalanceSignal = None):
-        signal = builder.get_signal(parse_date('2022-02-22'), PortfoliosRisk.FT9)
+        signal = builder.get_signal(parse_date('2008-01-07'), PortfoliosRisk.FT9)
         logger.info(signal)
 
     @autowired(names={'builder': 'curve-drift'})

robo_executor.py

@@ -119,10 +119,10 @@ class BacktestExecutor(RoboExecutor):
             now = dt.now()
             wait([self.async_build_hold(x) for x in PortfoliosRisk])
             logger.info(f"build hold portfolios success, use[{(dt.now() - now).seconds}s]")
-        logger.info("start to export report".center(50, '-'))
-        now = dt.now()
-        file = self._export.export(max_date=self.end_date)
-        logger.info(f"report file[{os.path.basename(file)}] exported successfully. use[{(dt.now() - now).seconds}s].")
+        # logger.info("start to export report".center(50, '-'))
+        # now = dt.now()
+        # file = self._export.export(max_date=self.end_date)
+        # logger.info(f"report file[{os.path.basename(file)}] exported successfully. use[{(dt.now() - now).seconds}s].")
 
     @asynchronized(isolate=True)
     def async_build_risk_date(self, asset_id):