def on_bar_per_minute(self, time: datetime, protfolio: Portfolio):
"""
市场开市后的每分钟。
"""
#每天两点半的后尝试去做交易。
if time.hour == 14 and time.minute == 30:
self.__history_bar100 = self.market.getHistory().getKbars(
self.code, 100)
assert len(self.__history_bar100) == 100
bars = self.__history_bar100
todayBar = self.market.getRealTime().getKBar(self.code)
indicator = Indicator(40)
indicator.update_bar(bars)
dif, dea, macd_bar = indicator.macd(fast_period=12,
slow_period=26,
signal_period=9,
array=True)
if (not self.today_has_buy):
# 预测金叉
todayBar.close_price = todayBar.close_price * 1.01
indicator.update_bar(todayBar)
dif, dea, predict_macd_bar = indicator.macd(fast_period=12,
slow_period=26,
signal_period=9,
array=True)
print(
f"[{self.market.getToday()}]:bar={macd_bar[-1]},predic_bar={predict_macd_bar[-1]}"
)
if (predict_macd_bar[-1] > 0 and macd_bar[-1] <= 0):
targetPrice = todayBar.close_price # 上一个交易日的收盘价作为买如价
print(f" gold cross!!!")
if protfolio.buy(self.code, targetPrice, 100):
self.today_has_buy = True
elif (not self.today_has_sell):
todayBar.close_price = todayBar.close_price * 0.99
indicator.update_bar(todayBar)
dif, dea, predict_macd_bar = indicator.macd(fast_period=12,
slow_period=26,
signal_period=9,
array=True)
print(
f"[{self.market.getToday()}]:bar={macd_bar[-1]},predic_bar={predict_macd_bar[-1]}"
)
if (predict_macd_bar[-1] <= 0 and macd_bar[-1] > 0):
targetPrice = todayBar.close_price
print(f" dead cross!!!")
if protfolio.sell(self.code, targetPrice, 100):
self.today_has_sell = True
def getValues(self, indicator: Indicator,bar:BarData,signal:Signal) -> Map:
values = {}
count = 30
if indicator.count >= count:
dif, dea, macd_bar = indicator.macd(fast_period=12, slow_period=26, signal_period=9, array=True);
##金叉出现
if (macd_bar[-1] >= 0 and macd_bar[-2] <= 0):
if not signal.hasBuy:
signal.buy = True
##死叉出现
if (macd_bar[-1] <= 0 and macd_bar[-2] >= 0):
if signal.hasBuy:
signal.sell = True
return values
def computeAndPrint(bars: []) -> AnalysisData:
data = AnalysisData()
total_count = len(bars)
previous_macd = -1
previouc_kdj = -1
indicator = Indicator(50)
for i in range(0, total_count):
bar: BarData = bars[i]
indicator.update_bar(bar)
k_large_than_d = False
if indicator.count >= 13:
k, d, j = indicator.kdj(fast_period=9, slow_period=3, array=True)
k_large_than_d = k[-1] >= d[-1]
##金叉出现
if (k[-1] >= d[-1] and k[-2] <= d[-2]):
previouc_kdj = i
if indicator.count >= 30:
dif, dea, macd_bar = indicator.macd(fast_period=12,
slow_period=26,
signal_period=9,
array=True)
##金叉出现
if (macd_bar[-1] >= 0 and macd_bar[-2] <= 0):
previous_macd = i
if previouc_kdj > 0:
data.count = data.count + 1
if k_large_than_d:
data.k_large_than_d_count = data.k_large_than_d_count + 1
dis = previous_macd - previouc_kdj
if (dis >= 0 and dis < KDJ_DIS_SIZE):
data.kdj_dis[dis] = data.kdj_dis[dis] + 1
return data
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)
dif, dea, macd_bar = indicator.macd(fast_period=12, slow_period=26, signal_period=9, array=True);
##金叉出现
if (macd_bar[-1] >= 0 and macd_bar[-2] <= 0):
tradePrice = bars[-1].close_price * 1.01 # 上一个交易日的收盘价作为买如价
protfolio.buy(code, tradePrice, 1)
protfolio.cover(code,tradePrice,1) ##平仓做空
##死叉出现
if (macd_bar[-1] <= 0 and macd_bar[-2] >=0):
targetPrice = bars[-1].close_price * 0.99 # 上一个交易日的收盘价作为买如价
protfolio.sell(code, targetPrice, 1)
protfolio.short(code, targetPrice, 1) ##开仓做空
pass
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
def generateSWTrainData(kPatterns: [], start: datetime,
end: datetime) -> pd.DataFrame:
sw = SWImpl()
lists = sw.getSW2List()
cloumns = [
"code", "name", "kPattern", "k", "d", "dif", "dea", "macd", "open",
"short", "long"
]
datas = []
kPatternMap = {}
for kPatternValues in kPatterns:
kPatternMap[kPatternValues] = True
macd_list = []
for code in lists:
# for code in lists:
name = sw.getSw2Name(code)
barList = sw.getSW2Daily(code, start, end)
indicator = Indicator(34)
preBar = None
for bar in barList:
##先识别形态
kEncodeValue = None
if indicator.inited:
tmpKEncodeValue = KPattern.encode3KAgo1(indicator)
if kPatternMap.__contains__(tmpKEncodeValue):
kEncodeValue = tmpKEncodeValue
if kEncodeValue is None:
indicator.update_bar(bar)
preBar = bar
continue
##昨天的kdj
k, d, j = indicator.kdj(array=False)
dif, dea, macd = indicator.macd(fast_period=12,
slow_period=26,
signal_period=9,
array=False)
##第二天的收益
short_pct = 100 * ((bar.high_price + bar.close_price) / 2 -
preBar.close_price) / preBar.close_price
long_pct = 100 * ((bar.low_price + bar.close_price) / 2 -
preBar.close_price) / preBar.close_price
open_pct = 100 * (bar.open_price -
preBar.close_price) / preBar.close_price
item = []
item.append(code)
item.append(name)
item.append(kEncodeValue)
item.append(k)
item.append(d)
item.append(dif)
item.append(dea)
item.append(macd)
#下个k线数据
item.append(open_pct)
item.append(short_pct)
item.append(long_pct)
datas.append(item)
macd_list.append(macd)
indicator.update_bar(bar)
preBar = bar
macd_list = np.array(macd_list)
print(
f"total size : {len(datas)},mean ={macd_list.mean()},max={macd_list.max()},min={macd_list.min()}"
)
wxl = pd.DataFrame(datas, columns=cloumns)
return wxl
标准化的步骤就是： macd值处于最后一天的收盘价。
这里统计下中证500的macd标准化之后的数据统计情况
"""
if __name__ == "__main__":
start = datetime(2015, 10, 1)
end = datetime(2020, 9, 30)
souces = ZZ500DataSource(start, end)
bars,code = souces.nextBars()
dif_list = []
dea_list = []
while not bars is None:
indicator = Indicator(40)
for bar in bars:
indicator.update_bar(bar)
if indicator.count > 33:
dif, dea, macd_bar = indicator.macd(fast_period=12, slow_period=26, signal_period=9, array=False)
dif_value = dif/bar.close_price * 100
dea_value = dea / bar.close_price * 100
dif_list.append(dif_value)
dea_list.append(dea_value)
if abs(dif_value) > 20:
print(f"dif:{dif_value},code={code},bar = {bar}")
if abs(dea_value) > 20:
print(f"dea:{dea_value},code={code},bar = {bar}")
bars, code = souces.nextBars()
dif_list = np.array(dif_list)
dea_list = np.array(dea_list)
def_min,def_max = [dea_list.min(),dea_list.max()]
dif_min,dif_max = [dif_list.min(),dif_list.max()]
print(f"dif_max:{dif_max},dif_min:{dif_min},count:{len(dif_list)}")
