def getValues(self, indicator: Indicator, bar: BarData,
signal: Signal) -> Map:
values = {}
if indicator.count >= 15:
k, d, j = indicator.kdj(array=False)
values["k"] = k
values["d"] = d
values["j"] = j
else:
values["k"] = 50
values["d"] = 50
values["j"] = 50
return values
def getValues(self, indicator: Indicator,bar:BarData,signal:Signal) -> Map:
values = {}
count = 30
if indicator.count >= count:
k, d, j = indicator.kdj(fast_period=9, slow_period=3, array=True)
##金叉出现
if (k[-1] >= d[-1] and k[-2] <= d[-2]):
if not signal.hasBuy:
signal.buy = True
##死叉出现
if (k[-1] <= d[-1] and k[-2] >= d[-2]):
if signal.hasBuy:
signal.sell = True
return values
def getValues(self, indicator: Indicator, bar: BarData,
signal: Signal) -> Map:
values = {}
if indicator.count > 20:
k, d, j = indicator.kdj(fast_period=9, slow_period=3, array=True)
values["k"] = k[-1]
values["d"] = d[-1]
values["j"] = j[-1]
if k[-2] < d[-2] and k[-1] >= d[-1]:
signal.buy = True
else:
values["k"] = 50
values["d"] = 50
values["j"] = 50
return values
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.kdj()
##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
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
class EngineModel2KAlgo1(CoreEngineModel):
def __init__(self):
self.lasted3Bar = np.array([None, None, None])
self.lasted3BarKdj = np.array([None, None, None])
self.sw = SWImpl()
def onCollectStart(self, code: str) -> bool:
from earnmi.chart.Indicator import Indicator
self.indicator = Indicator(40)
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]
if self.indicator.count >= 15:
from earnmi.chart.KPattern import KPattern
kPatternValue = KPattern.encode2KAgo1(self.indicator)
if not kPatternValue is None:
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
class Find_KPattern_skip1_predit2(KBarCollector):
print_on_destroy = False
def __init__(self, limit_close_pct=1):
self.limit_close_pct = limit_close_pct
self.success_sell_pct = 2
self.collect_k_count = 0 #收集总数
self.k_count = 0 #满足条件的k线形态总数
self.dataSet = {}
pass
def onCreate(self):
pass
def onStart(self, code: str) -> bool:
self.indicator = Indicator(40)
self.code = code
return True
def collect(self, bar: BarData) -> TraceData:
self.indicator.update_bar(bar)
kPatternValue = KPattern.encode2KAgo1(self.indicator)
if not kPatternValue is None and self.indicator.count > 20:
self.collect_k_count += 1
traceData = Skip1_Predict2_TraceData(kPatternValue, bar)
traceData.code = bar.symbol
return traceData
return None
def __between_0_100(self, value: int):
if value > 100:
return 100
elif value < 0:
return 0
return value
def onTrace(self, traceData: Skip1_Predict2_TraceData, bar: BarData):
startBar = traceData.occurBar
if traceData.skipBar is None:
k, d, j = self.indicator.kdj(fast_period=9,
slow_period=3,
array=False)
k = self.__between_0_100(k)
j = self.__between_0_100(d)
traceData.skipBar = bar
traceData.indicator_k = k
traceData.indicator_j = j
close_pct = 100 * (bar.close_price -
startBar.close_price) / startBar.close_price
if abs(close_pct) > self.limit_close_pct:
traceData.isWanted = False
traceData.finished = True
return
sell_pct = 100 * ((bar.high_price + bar.close_price) / 2 -
startBar.close_price) / startBar.close_price
buy_pct = 100 * ((bar.low_price + bar.close_price) / 2 -
startBar.close_price) / startBar.close_price
traceData.sell_pct = max(sell_pct, traceData.sell_pct)
traceData.buy_pct = min(buy_pct, traceData.buy_pct)
traceData.predictBars.append(bar)
if (len(traceData.predictBars) >= 2):
traceData.isWanted = True
traceData.finished = True
pass
def newCountData(self) -> CountData:
dataItem = CountData()
dataItem.count_total = 0
dataItem.pct_total = 0
dataItem.count_earn = 0
dataItem.pct_earn = 0
return dataItem
def onTraceFinish(self, traceData: Skip1_Predict2_TraceData):
if (not traceData.isWanted):
return
dataItem: CountData = self.dataSet.get(traceData.kPatternValue)
if dataItem is None:
dataItem = self.newCountData()
self.dataSet[traceData.kPatternValue] = dataItem
self.doWantedTraceData(traceData, dataItem)
pass
def doWantedTraceData(self, traceData: Skip1_Predict2_TraceData,
countData: CountData):
pct = traceData.sell_pct
self.k_count += 1
countData.count_total += 1
countData.pct_total += pct
isSuccess = pct >= self.success_sell_pct
if isSuccess:
countData.count_earn += 1
countData.pct_earn += pct
def onEnd(self, code: str):
pass
def onDestroy(self):
if not self.print_on_destroy:
return
dataSet = self.dataSet
print(
f"总共收集{self.collect_k_count}个形态，共{self.k_count}个满足条件，识别出{len(dataSet)}类形态，有意义的形态有："
)
max_succ_rate = 0
min_succ_rate = 100
ret_list = []
occur_count = 0
for key, dataItem in dataSet.items():
success_rate = 100 * dataItem.count_earn / dataItem.count_total
if dataItem.count_total < 300:
continue
# if success_rate < 40:
# continue
ret_list.append(key)
if dataItem.count_earn > 0:
earn_pct = dataItem.pct_earn / dataItem.count_earn
else:
earn_pct = 0
avg_pct = dataItem.pct_total / dataItem.count_total
occur_count += dataItem.count_total
occur_rate = 100 * dataItem.count_total / self.collect_k_count
max_succ_rate = max(success_rate, max_succ_rate)
min_succ_rate = min(success_rate, min_succ_rate)
print(
f"{key}： total={dataItem.count_total},suc=%.2f%%,occur_rate=%.2f%%,earn_pct:%.2f%%,avg_pct:%.2f%%)"
% (success_rate, occur_rate, earn_pct, avg_pct))
total_occur_rate = 100 * occur_count / self.collect_k_count
print(
f"总共：occur_rate=%.2f%%, min_succ_rate=%.2f%%, max_succ_rate=%.2f%%"
% (total_occur_rate, min_succ_rate, max_succ_rate))
print(f"{ret_list}")
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
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
