async def test_load_bars_batch(self):
codes = ["000001.XSHE", "000001.XSHG"]
# end = arrow.now(tz=cfg.tz).datetime
# async for code, bars in Security.load_bars_batch(codes, end, 10,
# FrameType.MIN30):
# print(bars[-2:])
# self.assertEqual(10, len(bars))
#
# codes = ['000001.XSHE', '000001.XSHG']
end = arrow.get("2020-08-27").datetime
async for code, bars in Security.load_bars_batch(
codes, end, 5, FrameType.DAY):
print(code, bars[-2:])
self.assertEqual(5, len(bars))
self.assertEqual(bars[-1]["frame"], end.date())
if code == "000001.XSHG":
self.assertAlmostEqual(3350.11, bars[-1]["close"], places=2)
async def distribution(self):
# 涨停、跌停
zt, dt = 0, 0
codes = Securities().choose(['stock'])
end = arrow.now(cfg.tz).floor('minute').datetime
pct = []
async for code, bars in Security.load_bars_batch(
codes, end, 2, FrameType.DAY):
c1, c0 = bars[-2:]['close']
if (c0 + 0.01) / c1 - 1 > 0.1:
zt += 1
if (c0 - 0.01) / c1 - 1 < -0.1:
dt += 1
pct.append(c0 / c1 - 1)
# 分布
cuts = np.histogram(
pct, bins=[-0.2, -0.1, -0.07, -0.03, 0, 0.03, 0.07, 0.1, 0.2])
self.price_change_history.append((zt, dt, cuts))
if len(self.price_change_history) == 8:
self.price_change_history.pop(0)
now = arrow.now(tz=cfg.tz)
if now.hour >= 15:
dt = tf.date2int(now)
await cache.sys.hset(
f"glance{dt}", "distribution",
json.dumps({
"zt": zt,
"dt": dt,
"cuts": cuts
}))
return zt, dt, cuts
async def scan(self,
frame_type: Union[str, FrameType] = FrameType.DAY,
end: Frame = None,
codes: List[str] = None):
logger.info("running momentum scan at %s level", frame_type)
if end is None:
end = arrow.now(cfg.tz).datetime
assert type(end) in (datetime.date, datetime.datetime)
frame_type = FrameType(frame_type)
ft = frame_type.value
codes = codes or Securities().choose(['stock'])
day_bars = {}
async for code, bars in Security.load_bars_batch(
codes, end, 2, FrameType.DAY):
day_bars[code] = bars
if len(day_bars) == 0:
return
async for code, bars in Security.load_bars_batch(
codes, end, 11, frame_type):
if len(bars) < 11:
continue
fired = bars[-1]['frame']
day_bar = day_bars.get(code)
if day_bar is None:
continue
c1, c0 = day_bars.get(code)[-2:]['close']
cmin = min(bars['close'])
# 还处在下跌状态、或者涨太多
if c0 == cmin or (c0 / c1 - 1) > self.baseline(f"up_limit"):
continue
ma5 = signal.moving_average(bars['close'], 5)
err, (a, b, c), (vx, _) = signal.polyfit(ma5[-7:] / ma5[-7])
# 无法拟合，或者动能不足
if err > self.baseline(f"ma5:{ft}:err") or a < self.baseline(
f"ma5:{ft}:a"):
continue
# 时间周期上应该是信号刚出现，还在窗口期内
vx_range = self.baseline(f"ma5:{ft}:vx")
if not vx_range[0] < vx < vx_range[1]:
continue
p = np.poly1d((a, b, c))
y = p(9) / p(6) - 1
# 如果预测未来三周期ma5上涨幅度不够
if y < self.baseline(f"ma5:{ft}:y"):
continue
sec = Security(code)
if frame_type == FrameType.DAY:
start = tf.shift(tf.floor(end, frame_type), -249, frame_type)
bars250 = await sec.load_bars(start, end, frame_type)
ma60 = signal.moving_average(bars250['close'], 60)
ma120 = signal.moving_average(bars250['close'], 120)
ma250 = signal.moving_average(bars250['close'], 250)
# 上方无均线压制
if (c0 > ma60[-1]) and (c0 > ma120[-1]) and (c0 > ma250[-1]):
logger.info("%s, %s, %s, %s, %s, %s", sec, round(a, 4),
round(b, 4), round(vx, 1),
round(c0 / c1 - 1, 3), round(y, 3))
await self.enter_stock_pool(code,
fired,
frame_type,
a=a,
b=b,
err=err,
y=y,
vx=self.fit_win - vx)
elif frame_type == FrameType.WEEK:
await self.enter_stock_pool(code,
fired,
frame_type,
a=a,
b=b,
err=err,
y=y,
vx=self.fit_win - vx)
elif frame_type == FrameType.MIN30:
await self.fire_trade_signal('long',
code,
fired,
frame_type,
a=a,
b=b,
err=err,
y=y,
vx=self.fit_win - vx)
async def test_something(self):
end = arrow.get('2020-8-27 10:00:00').datetime
async for code, bars in Security.load_bars_batch(['300589.XSHE'], end,
26, FrameType.DAY):
print(code, bars[-1])