bugfix

portfolios/holder.py

@@ -81,19 +81,14 @@ class DividendPortfoliosHolder(PortfoliosHolder):
         weight = {int(x[0]): x[1] for x in json.loads(signal['portfolio']).items()}
         if last_nav:
             share = {int(x): y for x, y in json.loads(last_nav['portfolios'])['share'].items()}
-            share_nav = {int(x): y for x, y in json.loads(last_nav['portfolios'])['share'].items()}
             fund_div_tuple = self.get_navs_and_div(fund_ids=tuple(set(weight) | set(share)), day=day)
             navs = fund_div_tuple[0]
             fund_dividend = fund_div_tuple[1]
-            # 配息当天配股
-            for k in share_nav.keys():
-                if k in fund_dividend:
-                    share_nav[k] = (share_nav[k] * fund_dividend[k]) / (share_nav[k] * navs[k]) + share_nav[k]
             fund_dividend = sum(
                 map(lambda k: share[k] * fund_dividend[k], filter(lambda k: k in fund_dividend, share.keys())))
-            dividend_acc = last_nav['div_acc']
+            dividend_acc = last_nav['div_acc'] + fund_dividend
             fund_av = round(sum([navs[x] * y for x, y in share.items()]), 4)
-            fund_nav = round(sum([navs[x] * y for x, y in share_nav.items()]), 4)
+            fund_nav = fund_av + dividend_acc
             cash = last_nav['cash'] + fund_dividend
             div_forecast = last_nav['div_forecast']
             #     每年的首个季度调整配息
@@ -245,19 +240,14 @@ class InvTrustPortfoliosHolder(DividendPortfoliosHolder):
         if last_nav:
             # 若非首次配息
             share = {int(x): y for x, y in json.loads(last_nav['portfolios'])['share'].items()}
-            share_nav = {int(x): y for x, y in json.loads(last_nav['portfolios'])['share_nav'].items()}
             fund_div_tuple = self.get_navs_and_div(fund_ids=tuple(set(weight) | set(share)), day=day)
             navs = fund_div_tuple[0]
             fund_dividend = fund_div_tuple[1]
-            # 配息当天配股
-            for k in share_nav.keys():
-                if k in fund_dividend:
-                    share_nav[k] = (share_nav[k] * fund_dividend[k]) / (share_nav[k] * navs[k]) + share_nav[k]
             fund_dividend = sum(
                 map(lambda k: share[k] * fund_dividend[k], filter(lambda k: k in fund_dividend, share.keys())))
             dividend_acc = last_nav['div_acc'] + fund_dividend
             fund_av = round(sum([navs[x] * y for x, y in share.items()]), 4)
-            fund_nav = round(sum([navs[x] * y for x, y in share_nav.items()]), 4)
+            fund_nav = fund_av + dividend_acc
             asset_nav = fund_av
             share = {x: fund_av * w / navs[x] for x, w in weight.items()}
             #  若调仓当日，有基金产生配息
@@ -385,8 +375,10 @@ class DivHoldReportor(RoboReportor):
         if not holds.empty:
             holds['signal_type'] = 'INIT'
             holds['real_av'] = holds['asset_nav']
+            holds['nav'] = holds['acc_av']
             holds = holds[
-                ['date', 'signal_type', 'fund_av', 'fund_div', 'cash', 'real_av', 'port_div', 'acc_av', 'nav']]
+                ['date', 'signal_type', 'fund_av', 'fund_nav', 'fund_div', 'cash', 'real_av', 'port_div', 'div_acc',
+                 'acc_av', 'nav']]
             return holds.to_dict('records')
         return []
 

reports/combo_datas.py

@@ -23,7 +23,7 @@ class DivAlligamComboDatasReportor(RoboReportor):
         holds = pd.DataFrame(self._hold_reportor.load_report(max_date=max_date, min_date=min_date))
         if not holds.empty:
             holds.set_index('date', inplace=True)
-            holds = holds[['real_av', 'acc_av', 'nav']]
+            holds = holds[['real_av', 'acc_av', 'nav', 'fund_nav']]
             holds.rename(columns={'real_av': 'av', 'acc_av': 'acc'}, inplace=True)
 
             benchmark = pd.DataFrame(self._benchmark.load_report(max_date=max_date, min_date=min_date))

web/robo_controller.py

@@ -51,7 +51,8 @@ async def root():
                          funds.items()]
         data['creat_date'] = portfolio['create_time'].strftime('%Y-%m-%d %H:%M:%S')
         # todo 补全
-        data['cp'] = 0.81
+        # returns = round(datas.pct_change(), 5)
+        # data['cp'] = sharpe_ratio(returns, risk_free=0, period='daily', annualization=None),
         data['rr'] = 0.81
         data['roi'] = 0.81
         data['risk'] = round(sum([id_ticker_map[key]['risk'] * weight for key, weight in funds.items()]), 2)