def on_market_prepare_open(self, protfolio: Portfolio, today: datetime):
"""
市场准备开始（比如：竞价）.
"""
indicator = Indicator(40)
for code in self.codes:
bars = self.market.getHistory().getKbars(code, 100)
indicator.update_bar(bars)
count = 20
aroon_down, aroon_up = indicator.aroon(count)
need_hold = aroon_up > 50 and aroon_up > aroon_down
position = protfolio.getLongPosition(code)
if need_hold:
if position.pos_total < 1:
targetPrice = bars[-1].close_price * 1.05 # 上一个交易日的收盘价作为买如价
ok = protfolio.buyAtPercentage(code, targetPrice, 1)
print(f"buy: price = {targetPrice} , {ok}")
else:
if position.pos_total > 0:
targetPrice = bars[-1].close_price * 0.92 # 上一个交易日的收盘价作为买如价
ok = protfolio.sellAll(code, targetPrice)
print(f"sell: price = {targetPrice} , {ok}")
pass
def getValues(self, indicator: Indicator,bar:BarData,signal:Signal) -> Map:
values = {}
count = 15
if indicator.count >= count:
aroon_down,aroon_up = indicator.aroon(count,True)
values["arron_up_25"] = aroon_up[-1]
values["arron_down_25"] = aroon_down[-1]
need_hold = aroon_up[-1] > 50 and aroon_up[-1] > aroon_down[-1]
if need_hold:
if not signal.hasBuy:
signal.buy = True
# print(f"{bar.datetime}： 买: price:{bar.close_price * 1.01}")
else:
if( signal.hasBuy):
signal.sell = True
#print(f"{bar.datetime}： 卖: price:{bar.close_price * 0.99}")
else:
values["arron_up_25"] = 50
values["arron_down_25"] = 50
return values
def getValues(self, indicator: Indicator, bar: BarData,
signal: Signal) -> Map:
values = {}
if indicator.count >= 25:
aroon_down, aroon_up = indicator.aroon(25, True)
values["arron_up_25"] = aroon_up[-1]
values["arron_down_25"] = aroon_down[-1]
need_hold = aroon_up[-1] > 50 and aroon_up[-1] > aroon_down[-1]
if need_hold:
if self.has_bug == False:
signal.buy = True
self.has_bug = True
else:
if (self.has_bug == True):
signal.sell = True
self.has_bug = False
else:
values["arron_up_25"] = 50
values["arron_down_25"] = 50
return values
class KDJMovementEngineModel(CoreEngineModel):
def __init__(self):
self.lasted15Bar = np.array([
None, None, None, None, None, None, None, None, None, None, None,
None, None, None, None
])
self.lasted3BarKdj = np.array([None, None, None])
self.lasted3BarMacd = np.array([None, None, None])
self.lasted3BarArron = np.array([None, None])
self.kdjEncoder = FloatEncoder([15, 30, 45, 60, 75, 90])
self.mDateOccurCountMap = {} ##统计产生收集个数的次数
self.sw = SWImpl()
def onCollectStart(self, code: str) -> bool:
from earnmi.chart.Indicator import Indicator
self.indicator = Indicator(34)
self.code = code
return True
def onCollectTrace(self, bar: BarData) -> CollectData:
self.indicator.update_bar(bar)
self.lasted15Bar[:-1] = self.lasted15Bar[1:]
self.lasted3BarKdj[:-1] = self.lasted3BarKdj[1:]
self.lasted3BarMacd[:-1] = self.lasted3BarMacd[1:]
self.lasted3BarArron[:-1] = self.lasted3BarArron[1:]
k, d, j = self.indicator.kdj(fast_period=9, slow_period=3)
dif, dea, mBar = self.indicator.macd(fast_period=12,
slow_period=26,
signal_period=9)
aroon_down, aroon_up = self.indicator.aroon(n=14)
self.lasted15Bar[-1] = bar
self.lasted3BarKdj[-1] = [k, d, j]
self.lasted3BarMacd[-1] = [dif, dea, mBar]
self.lasted3BarArron[-1] = [aroon_down, aroon_up]
if self.indicator.count <= 15:
return None
#最近15天之内不含停牌数据
if not BarUtils.isAllOpen(self.lasted15Bar):
return None
#交易日天数间隔超过5天的数据
if BarUtils.getMaxIntervalDay(self.lasted15Bar) >= 5:
return None
timeKey = utils.to_start_date(bar.datetime)
if self.mDateOccurCountMap.get(timeKey) is None:
self.mDateOccurCountMap[timeKey] = 0
if self.indicator.count >= 30:
k0, d0, j0 = self.lasted3BarKdj[-2]
k1, d1, j1 = self.lasted3BarKdj[-1]
#金叉产生
goldCross = k0 < d0 and k1 >= d1
if not goldCross:
return None
kPatternValue = KPattern.encode3KAgo1(self.indicator)
if not kPatternValue is None:
self.mDateOccurCountMap[timeKey] += 1
dimen = Dimension(type=TYPE_2KAGO1, value=kPatternValue)
collectData = CollectData(dimen=dimen)
collectData.occurBars = list(self.lasted15Bar[-3:])
collectData.occurKdj = list(self.lasted3BarKdj)
collectData.occurExtra['lasted3BarMacd'] = self.lasted3BarMacd
collectData.occurExtra[
'lasted3BarArron'] = self.lasted3BarArron
return collectData
return None
def onCollect(self, data: CollectData, newBar: BarData):
#不含停牌数据
if not BarUtils.isOpen(newBar):
data.setValid(False)
return
data.predictBars.append(newBar)
size = len(data.predictBars)
if size >= 5:
data.setFinished()
def getYLabelPct(self, cData: CollectData) -> [float, float]:
if len(cData.predictBars) < 5:
#不能作为y标签。
return None, None
bars: ['BarData'] = cData.predictBars
basePrice = self.getYBasePrice(cData)
highIndex = 0
lowIndex = 0
highBar = cData.predictBars[0]
lowBar = cData.predictBars[0]
sell_pct = 100 * ((highBar.high_price + highBar.close_price) / 2 -
basePrice) / basePrice
buy_pct = 100 * ((lowBar.low_price + lowBar.close_price) / 2 -
basePrice) / basePrice
for i in range(1, len(cData.predictBars)):
bar: BarData = cData.predictBars[i]
_s_pct = 100 * (
(bar.high_price + bar.close_price) / 2 - basePrice) / basePrice
_b_pct = 100 * (
(bar.low_price + bar.close_price) / 2 - basePrice) / basePrice
if _s_pct > sell_pct:
sell_pct = _s_pct
highIndex = i
if _b_pct < buy_pct:
buy_pct = _b_pct
lowIndex = i
return sell_pct, buy_pct
def getYBasePrice(self, cData: CollectData) -> float:
##以金叉发生的当前收盘价作为基准值。
return cData.occurBars[-2].close_price
def generateXFeature(self, cData: CollectData) -> []:
#保证len小于三，要不然就不能作为生成特征值。
if (len(cData.occurBars) < 3):
return None
basePrcie = self.getYBasePrice(cData)
##使用随机森林，所以不需要标准化和归一化
goldCrossBar = cData.occurBars[-2]
god_cross_dif, god_cross_dea, god_cross_macd = cData.occurExtra.get(
'lasted3BarMacd')[-2]
god_cross_dif = 100 * god_cross_dif / basePrcie
god_cross_dea = 100 * god_cross_dea / basePrcie
k, d, j = cData.occurKdj[-2]
def getSellBuyPct(bar: BarData):
s_pct = 100 * (
(bar.high_price + bar.close_price) / 2 - basePrcie) / basePrcie
b_pct = 100 * (
(bar.low_price + bar.close_price) / 2 - basePrcie) / basePrcie
return s_pct, b_pct
s_pct_1, b_pct_1 = getSellBuyPct(cData.occurBars[-3])
s_pct_2, b_pct_2 = getSellBuyPct(cData.occurBars[-2])
s_pct_3, b_pct_3 = getSellBuyPct(cData.occurBars[-1])
data = []
data.append(god_cross_dif)
data.append(god_cross_dea)
data.append(k)
data.append(d)
data.append(s_pct_1)
data.append(b_pct_1)
data.append(s_pct_2)
data.append(b_pct_2)
data.append(s_pct_3)
data.append(b_pct_3)
return data
class TheEngineModel(CoreEngineModel):
def __init__(self):
self.lasted3Bar = np.array([None, None, None])
self.lasted3BarKdj = np.array([None, None, None])
self.kdjEncoder = FloatEncoder([15, 30, 45, 60, 75, 90])
self.mDateOccurCountMap = {} ##统计产生收集个数的次数
self.sw = SWImpl()
def onCollectStart(self, code: str) -> bool:
from earnmi.chart.Indicator import Indicator
self.indicator = Indicator(34)
self.code = code
return True
def onCollectTrace(self, bar: BarData) -> CollectData:
self.indicator.update_bar(bar)
self.lasted3Bar[:-1] = self.lasted3Bar[1:]
self.lasted3BarKdj[:-1] = self.lasted3BarKdj[1:]
k, d, j = self.indicator.kdj(fast_period=9, slow_period=3)
self.lasted3Bar[-1] = bar
self.lasted3BarKdj[-1] = [k, d, j]
timeKey = utils.to_start_date(bar.datetime)
if self.mDateOccurCountMap.get(timeKey) is None:
self.mDateOccurCountMap[timeKey] = 0
if self.indicator.count >= 30:
aroon_down, aroon_up = self.indicator.aroon(n=14, array=False)
from earnmi.chart.KPattern import KPattern
if aroon_up < aroon_down or aroon_up < 50:
return None
kPatternValue = KPattern.encode2KAgo1(self.indicator)
if not kPatternValue is None:
self.mDateOccurCountMap[timeKey] += 1
_kdj_mask = self.kdjEncoder.mask()
kPatternValue = kPatternValue * _kdj_mask * _kdj_mask + self.kdjEncoder.encode(
k) * _kdj_mask + self.kdjEncoder.encode(d)
dimen = Dimension(type=TYPE_2KAGO1, value=kPatternValue)
collectData = CollectData(dimen=dimen)
collectData.occurBars.append(self.lasted3Bar[-2])
collectData.occurBars.append(self.lasted3Bar[-1])
collectData.occurKdj.append(self.lasted3BarKdj[-2])
collectData.occurKdj.append(self.lasted3BarKdj[-1])
return collectData
return None
def onCollect(self, data: CollectData, newBar: BarData) -> bool:
if len(data.occurBars) < 3:
data.occurBars.append(self.lasted3Bar[-1])
data.occurKdj.append(self.lasted3BarKdj[-1])
else:
data.predictBars.append(newBar)
size = len(data.predictBars)
return size >= 2
@abstractmethod
def getYLabelPrice(self, cData: CollectData) -> [float, float, float]:
bars: ['BarData'] = cData.predictBars
if len(bars) > 0:
sell_price = -9999999999
buy_price = -sell_price
for bar in bars:
sell_price = max((bar.high_price + bar.close_price) / 2,
sell_price)
buy_price = min((bar.low_price + bar.close_price) / 2,
buy_price)
return sell_price, buy_price
return None, None
def getYBasePrice(self, cData: CollectData) -> float:
return cData.occurBars[-2].close_price
def generateXFeature(self, cData: CollectData) -> []:
#保证len小于三，要不然就不能作为生成特征值。
if (len(cData.occurBars) < 3):
return None
occurBar = cData.occurBars[-2]
skipBar = cData.occurBars[-1]
kdj = cData.occurKdj[-1]
sell_pct = 100 * ((skipBar.high_price + skipBar.close_price) / 2 -
occurBar.close_price) / occurBar.close_price
buy_pct = 100 * ((skipBar.low_price + skipBar.close_price) / 2 -
occurBar.close_price) / occurBar.close_price
def set_0_between_100(x):
if x > 100:
return 100
if x < 0:
return 0
return x
def percent_to_one(x):
return int(x * 100) / 1000.0
data = []
data.append(percent_to_one(buy_pct))
data.append(percent_to_one(sell_pct))
data.append(set_0_between_100(kdj[0]) / 100)
data.append(set_0_between_100(kdj[2]) / 100)
return data
