def next(self):
if len(self.data.Volume) > LOOK_BACK:
hasBuySignal = jModel.isBullishHarami(
self.data.Open, self.data.Close, self.data.High, self.data.Low,
self.data.Body, self.data.Height, self.data.UpShadow,
self.data.LowerShadow)
hasSellSignal = jModel.isBearishHarami(
self.data.Open, self.data.Close, self.data.High, self.data.Low,
self.data.Body, self.data.Height, self.data.UpShadow,
self.data.LowerShadow)
# if np.datetime64(self.data.Date[-1]) == np.datetime64('2018-07-12T00:00:00.000000000'):
# t4 = jModel.isMorningStarsPattern(self.data.Open, self.data.Close, self.data.High, self.data.Low, self.data.Body, self.data.Height, self.data.UpShadow, self.data.LowerShadow)
# print('today - isMorningStarsPattern - ' + str(t4))
# print(jModel.isBlackCandlestick(self.data.Open[-3], self.data.Close[-3]))
# print(jModel.isBodyOver45(self.data.Body[-3], self.data.Height[-3]))
# print(jModel.isBodyLess35(self.data.Body[-2], self.data.Height[-2]))
# print(jModel.isWhiteCandlestick(self.data.Open[-1], self.data.Close[-1]))
# exit()
if hasBuySignal is not False and self.orderPending is False:
self.buy()
self.orderPending = True
if hasSellSignal is not False and self.orderPending is True:
self.position.close()
self.orderPending = False
def next(self):
if len(self.data.Volume) > LOOK_BACK:
prices = self.data.Close
# if np.datetime64(self.data.Date[-1]) == np.datetime64('2018-01-29T00:00:00.000000000'):
# t4 = jModel.isBearishEngulfing(self.data.Open, self.data.Close, self.data.High, self.data.Low, self.data.Body, self.data.Height, self.data.UpShadow, self.data.LowerShadow)
# print('today - isBearishEngulfing - ' + str(t4))
# exit()
the1stDayIsBlack = jModel.isBlackCandlestick(
self.data.Open[-3], self.data.Close[-3])
isDownTrend = jModel.isDownTrendV1(self.data.Open, self.data.Close,
self.data.High, self.data.Low,
self.data.Body,
self.data.Height,
self.data.UpShadow,
self.data.LowerShadow)
the2ndDayIsDoji = jModel.isDoji(self.data.Body[-2],
self.data.Height[-2])
todayIsShavenHead = jModel.isShavenHead(self.data.Height[-1],
self.data.UpShadow[-1])
todayIsWhite = jModel.isWhiteCandlestick(self.data.Open[-1],
self.data.Close[-1])
if isDownTrend is True and the2ndDayIsDoji is True and todayIsShavenHead is True and todayIsWhite is True:
hasBuySignal = True
else:
hasBuySignal = False
if hasBuySignal is not False:
self.buy(sl=0.9 * prices[-1], tp=1.2 * prices[-1])
def next(self):
if len(self.data.Volume) > 4:
prices = self.data.Close
opens = self.data.Open
bodies = self.data.Body
ups = self.data.UpShadow
lows = self.data.LowerShadow
height = self.data.Height
dates = self.data.Date
current_date = numpy.datetime_as_string(dates[-1], unit="D")
isUmbrellaCandlestick = jModel.isUmbrellaCandlestick(
bodies[-2], height[-2], ups[-2], lows[-2])
isWhiteCandlestick = jModel.isWhiteCandlestick(
opens[-1], prices[-1])
isBlackCandlestick = jModel.isBlackCandlestick(
opens[-1], prices[-1])
isShavenHead = jModel.isShavenHead(height[-1], ups[-1])
if isUmbrellaCandlestick is True and isWhiteCandlestick is True and prices[
-1] > prices[-2] and isShavenHead is True:
self.buy(sl=0.9 * prices[-1], tp=1.2 * prices[-1])
# self.buy(sl=0.9*prices[-1])
# if isUmbrellaCandlestick is True and isBlackCandlestick is True:
# self.position.close()
py_date = datetime.datetime.strptime(current_date, "%Y-%m-%d")
week_day = py_date.weekday()
day = py_date.day
if day > 22 and week_day > 2:
self.position.close()
def next(self):
if len(self.data.Volume) > LOOK_BACK:
prices = self.data.Close
hasBuySignal = jModel.hasBuySignal(
self.data.Open, self.data.Close, self.data.High, self.data.Low,
self.data.Body, self.data.Height, self.data.UpShadow,
self.data.LowerShadow, self.data.Volume, self.data.Date)
hasSellSignal = jModel.hasSellSignal(
self.data.Open, self.data.Close, self.data.High, self.data.Low,
self.data.Body, self.data.Height, self.data.UpShadow,
self.data.LowerShadow, self.data.Volume, self.data.Date)
# if np.datetime64(self.data.Date[-1]) == np.datetime64('2021-01-29T00:00:00.000000000'):
# t4 = jModel.isBullishEngulfing(self.data.Open, self.data.Close, self.data.High, self.data.Low, self.data.Body, self.data.Height, self.data.UpShadow, self.data.LowerShadow)
# print('today - isBullishEngulfing - ' + str(t4))
# print('today - isDoji - ' + str(jModel.isDoji(self.data.Body[-2], self.data.Height[-2])))
# print('today - isWhiteCandlestick - ' + str(jModel.isWhiteCandlestick(self.data.Open[-1], self.data.Close[-1])))
# print('today - isDownTrendV1 - ' + str(jModel.isDownTrendV1(self.data.Open, self.data.Close, self.data.High, self.data.Low, self.data.Body, self.data.Height, self.data.UpShadow, self.data.LowerShadow)))
# exit()
if hasBuySignal is not False and self.orderPending is False:
self.buy()
self.orderIndex = self.orderIndex + 1
print(
str(self.orderIndex) + ". Buy at " +
str(self.data.Date[-1]) + " by signal: " + hasBuySignal)
self.orderPending = True
if hasSellSignal is not False and self.orderPending is True:
self.position.close()
print("----------- Sell at " + str(self.data.Date[-1]) +
" by signal: " + hasSellSignal)
self.orderPending = False
def next(self):
if len(self.data.Volume) > LOOK_BACK:
prices = self.data.Close
hasBuySignal = jModel.hasCustomBuySignal(
self.data.Open, self.data.Close, self.data.High, self.data.Low,
self.data.Body, self.data.Height, self.data.UpShadow,
self.data.LowerShadow)
hasSellSignal = jModel.hasCustomSellSignal(
self.data.Open, self.data.Close, self.data.High, self.data.Low,
self.data.Body, self.data.Height, self.data.UpShadow,
self.data.LowerShadow)
# if np.datetime64(self.data.Date[-1]) == np.datetime64('2018-01-29T00:00:00.000000000'):
# t4 = jModel.isBearishEngulfing(self.data.Open, self.data.Close, self.data.High, self.data.Low, self.data.Body, self.data.Height, self.data.UpShadow, self.data.LowerShadow)
# print('today - isBearishEngulfing - ' + str(t4))
# exit()
if hasBuySignal is not False and self.orderPending is False:
self.buy()
self.orderIndex = self.orderIndex + 1
print(
str(self.orderIndex) + ". Buy at " +
str(self.data.Date[-1]) + " by signal: " +
str(hasBuySignal))
self.orderPending = True
if hasSellSignal is not False and self.orderPending is True:
self.position.close()
print("----------- Sell at " + str(self.data.Date[-1]) +
" by signal: " + str(hasSellSignal))
self.orderPending = False
def next(self):
if len(self.data.Volume) > LOOK_BACK:
hasHammerSignal = jModel.isHammerModel(self.data.Open, self.data.Close, self.data.High, self.data.Low,
self.data.Body, self.data.Height, self.data.UpShadow,
self.data.LowerShadow)
hasHangingManSignal = jModel.isHangingManModel(self.data.Open, self.data.Close, self.data.High, self.data.Low,
self.data.Body, self.data.Height, self.data.UpShadow,
self.data.LowerShadow)
if hasHammerSignal is not False and self.orderPending is False:
self.buy()
self.orderPending = True
if hasHangingManSignal is not False and self.orderPending is True:
self.position.close()
self.orderPending = False
def next(self):
if len(self.data.Volume) > LOOK_BACK:
hasBuySignal = jModel.isBullishEngulfing(self.data.Open, self.data.Close, self.data.High, self.data.Low,
self.data.Body, self.data.Height, self.data.UpShadow,
self.data.LowerShadow)
hasSellSignal = jModel.isBearishEngulfing(self.data.Open, self.data.Close, self.data.High, self.data.Low,
self.data.Body, self.data.Height, self.data.UpShadow,
self.data.LowerShadow)
if hasBuySignal is not False and self.orderPending is False:
self.buy()
self.orderPending = True
if hasSellSignal is not False and self.orderPending is True:
self.position.close()
self.orderPending = False
def next(self):
if len(self.data.Volume) > 4:
prices = self.data.Close
opens = self.data.Open
bodies = self.data.Body
ups = self.data.UpShadow
lows = self.data.LowerShadow
height = self.data.Height
dates = self.data.Date
prevDayIsSpinningTopCandlestick = jModel.isSpinningTopCandlestick(
bodies[-2], height[-2], ups[-2], lows[-2])
prevDayIsBlackCandlestick = jModel.isBlackCandlestick(
opens[-2], prices[-2])
prevDayIsWhiteCandlestick = jModel.isWhiteCandlestick(
opens[-2], prices[-2])
prevDayMaxOpenClose = opens[
-2] if opens[-2] > prices[-2] else prices[-2]
prevDayMinOpenClose = opens[
-2] if opens[-2] < prices[-2] else prices[-2]
todayIsWhiteCandlestick = jModel.isWhiteCandlestick(
opens[-1], prices[-1])
todayIsBlackCandlestick = jModel.isBlackCandlestick(
opens[-1], prices[-1])
todayMaxOpenClose = opens[
-1] if opens[-1] > prices[-1] else prices[-1]
todayMinOpenClose = opens[
-1] if opens[-1] < prices[-1] else prices[-1]
if prevDayIsBlackCandlestick is True \
and prices[-1] >= opens[-2] \
and opens[-1] <= prices[-2] \
and todayIsWhiteCandlestick is True:
# self.buy(sl=0.9*prices[-1], tp=1.2 * prices[-1])
self.buy(sl=0.9 * prices[-1])
if prevDayIsWhiteCandlestick is True \
and prices[-1] <= opens[-2] \
and opens[-1] >= prices[-2] \
and todayIsBlackCandlestick is True:
self.position.close()
if prevDayIsBlackCandlestick is True \
and ((prices[-1] <= opens[-2] and opens[-1] <= prices[-2] and todayIsBlackCandlestick is True) \
or prevDayMinOpenClose > todayMaxOpenClose):
self.position.close()
def next(self):
if len(self.data.Volume) > LOOK_BACK:
prices = self.data.Close
# if np.datetime64(self.data.Date[-1]) == np.datetime64('2020-04-03T00:00:00.000000000'):
# print('yesterday - isShavenBottom - ' + str(jModel.isShavenBottom(self.data.Height[-2], self.data.LowerShadow[-2])))
# print('today - isShavenHead - ' + str(jModel.isShavenHead(self.data.Height[-1], self.data.UpShadow[-1])))
# print('today - isWhiteCandlestick - ' + str(jModel.isWhiteCandlestick(self.data.Open[-1], self.data.Close[-1])))
# exit()
hasBuySignal = jModel.hasCustomBuySignal(self.data.Open, self.data.Close, self.data.High, self.data.Low,
self.data.Body, self.data.Height, self.data.UpShadow,
self.data.LowerShadow, 3)
if hasBuySignal is not False:
self.buy(sl=0.9 * prices[-1], tp=1.2 * prices[-1])
close = ticker_data['matchedPrice']
highest = ticker_data['highest']
lowest = ticker_data['lowest']
total_height = highest - lowest
body = abs(close - open)
head = _upf(close, open, highest)
tail = _botf(close, open, lowest)
price = close / 1000
if open == close:
""" Today is a doji candlestick """
ch = datetime.now().strftime("%H")
if int(ch) < 14:
continue
history_ticker_data = stockHistory.getStockHistoryData(ticker)
htd = jModel.convertToJapanCandle(history_ticker_data)
_close = htd.Close.to_numpy()
isDownTrend = jModel.isDownTrendV2ByRSI(_close)
if isDownTrend is True:
selectedTickers.append(ticker)
message += ticker + "(" + str(price) + ")\n"
elif open < close:
""" Today is a white candlestick """
go_pass = False
# ----------------------------------------------------------------------------------------------
isHammer = jModel.isHammer(body, total_height, head, tail)
isSpinningTopCandlestick = jModel.isSpinningTopCandlestick(
body, total_height, head, tail)
isShavenHead = jModel.isShavenHead(total_height, head)
isShavenBottom = jModel.isShavenBottom(total_height, tail)
isBigBody = jModel.isBigBody(body, total_height, open, close)
self.data.LowerShadow)
# if np.datetime64(self.data.Date[-1]) == np.datetime64('2018-07-12T00:00:00.000000000'):
# t4 = jModel.isMorningStarsPattern(self.data.Open, self.data.Close, self.data.High, self.data.Low, self.data.Body, self.data.Height, self.data.UpShadow, self.data.LowerShadow)
# print('today - isMorningStarsPattern - ' + str(t4))
# print(jModel.isBlackCandlestick(self.data.Open[-3], self.data.Close[-3]))
# print(jModel.isBodyOver45(self.data.Body[-3], self.data.Height[-3]))
# print(jModel.isBodyLess35(self.data.Body[-2], self.data.Height[-2]))
# print(jModel.isWhiteCandlestick(self.data.Open[-1], self.data.Close[-1]))
# exit()
if hasBuySignal is not False and self.orderPending is False:
self.buy()
self.orderPending = True
if hasSellSignal is not False and self.orderPending is True:
self.position.close()
self.orderPending = False
DATA_PATH = os.path.abspath('../../vn-stock-data/VNX/')
ticker_id = 'VRE'
ticker_data = _af.get_pricing_by_path(DATA_PATH + '/' + ticker_id + '.csv',
'2018-01-01')
new_data = jModel.convertToJapanCandle(ticker_data)
bt = Backtest(ticker_data, Harami, commission=.005, exclusive_orders=False)
stats = bt.run()
print(stats)
# print(stats['_trades'])
bt.plot()
import os
import sys
METHOD_MODULE_PATH = os.path.abspath('../..')
sys.path.insert(1, METHOD_MODULE_PATH)
import method.algofuncs as _af
import method.JavCan as jModel
DATA_PATH = os.path.abspath('../../vn-stock-data/VNX/')
# vn30_ticker = _af.getListVN30()
vnx_file = os.path.abspath('../../vn-stock-data/VNX.csv')
hose_ticker = _af.getHOSETickers(vnx_file)
for ticker_id in hose_ticker:
ticker_data = _af.get_pricing_by_path(DATA_PATH + '/' + ticker_id + '.csv',
'2021-07-01')
_1hit_data = ticker_data.tail(3)
new_data = jModel.convertToJapanCandle(_1hit_data)
prices = new_data.Close
opens = new_data.Open
bodies = new_data.Body
ups = new_data.UpShadow
lows = new_data.LowerShadow
height = new_data.Height
isUmbrellaCandlestick = jModel.isUmbrellaCandlestick(
bodies[-2], height[-2], ups[-2], lows[-2])
isWhiteCandlestick = jModel.isWhiteCandlestick(opens[-1], prices[-1])
if isUmbrellaCandlestick is True and isWhiteCandlestick is True and prices[
-1] > prices[-2]:
print(ticker_id)
if len(ticker) != 3:
continue
_volume = ticker_data['nmTotalTradedQty']
_minVol = getMinVolumeByTime()
if type(_volume) is not int or _volume < _minVol:
continue
open = ticker_data['openPrice']
close = ticker_data['matchedPrice']
highest = ticker_data['highest']
lowest = ticker_data['lowest']
total_height = highest - lowest
body = abs(close - open)
head = _upf(close, open, highest)
tail = _botf(close, open, lowest)
condition1 = True if tail > 0.65 * total_height else False
condition2 = True if total_height > 0.05 * close else False
# today has a long tail
if condition1 is True:
# print(ticker)
if condition2 is True:
# print(ticker)
history_ticker_data = stockHistory.getStockHistoryData(
ticker) # not include today data
# # print(history_ticker_data)
htd = jModel.convertToJapanCandle(history_ticker_data)
_close = htd.Close.to_numpy()
isDownTrend = jModel.isDownTrendV2ByRSI(_close)
if isDownTrend is True:
# print(ticker)
sendTelegramMessage(ticker)
import warnings
warnings.filterwarnings('ignore')
import os
import sys
METHOD_MODULE_PATH = os.path.abspath('../..')
sys.path.insert(1, METHOD_MODULE_PATH)
import method.algofuncs as _af
import method.JavCan as jModel
DATA_PATH = os.path.abspath('../../vn-stock-data/VNX/')
hold_tickers = ['ABB', 'ACB', 'BSR', 'FPT', 'GMD', 'OCB', 'PVS', 'PVT', 'STB', 'TPB', 'VCI', 'VHG', 'VND', 'VGT']
printedDate = False
for ticker_id2 in hold_tickers:
ticker_data = _af.get_pricing_by_path(DATA_PATH + '/' + ticker_id2 + '.csv', '2021-05-01')
if printedDate == False:
print(ticker_data.Date[-1])
printedDate = True
_1hit_data = ticker_data.tail(10)
new_data = jModel.convertToJapanCandle(_1hit_data)
hasSellSignal = jModel.hasCustomSellSignal(new_data.Open, new_data.Close, new_data.High, new_data.Low,
new_data.Body, new_data.Height, new_data.UpShadow,
new_data.LowerShadow, new_data.Date)
if hasSellSignal is not False:
print(ticker_id2 + ' -- ' + str(hasSellSignal))
# print(jModel.isBlackCandlestick(new_data.Open[-3], new_data.Close[-3]))
# print(jModel.isBlackCandlestick(new_data.Open[-2], new_data.Close[-2]))
# print(jModel.isBlackCandlestick(new_data.Open[-1], new_data.Close[-1]))
ticker = ticker_data['stockSymbol']
if len(ticker) != 3:
continue
_volume = ticker_data['nmTotalTradedQty']
if type(_volume) is not int or _volume < 500000:
continue
# _open = ticker_data['openPrice']
# _close = ticker_data['matchedPrice']
# _highest = ticker_data['highest']
# _lowest = ticker_data['lowest']
# _height = _highest - _lowest
# _body = abs(_close - _open)
# _up = _upf(_close, _open, _highest)
# _bot = _botf(_close, _open, _lowest)
condition = jModel.isWhiteCandlestick(ticker_data['openPrice'],
ticker_data['matchedPrice'])
# today is a white candlestick
if condition is True:
# print(ticker)
history_ticker_data = stockHistory.getStockHistoryData(
ticker) # not include today data
# print(history_ticker_data)
htd = jModel.convertToJapanCandle(history_ticker_data)
_open = htd.Open.to_numpy()
_close = htd.Close.to_numpy()
_highest = htd.High.to_numpy()
_lowest = htd.Low.to_numpy()
_height = htd.Height.to_numpy()
_body = htd.Body.to_numpy()
_up = htd.UpShadow.to_numpy()
_bot = htd.LowerShadow.to_numpy()
import sys
import numpy as np
from datetime import datetime
METHOD_MODULE_PATH = os.path.abspath('../..')
sys.path.insert(1, METHOD_MODULE_PATH)
import method.JavCan as jModel
import vn_realtime_stock_data.stockHistory as stockHistory
ticker = 'HPG'
# print(ticker)
history_ticker_data = stockHistory.getStockHistoryData(ticker) # not include today data
# print(history_ticker_data)
# exit()
# print(history_ticker_data)
htd = jModel.convertToJapanCandle(history_ticker_data)
print(htd)
# _open = htd.Open.to_numpy()
# _close = htd.Close.to_numpy()
# _highest = htd.High.to_numpy()
# _lowest = htd.Low.to_numpy()
# _height = htd.Height.to_numpy()
# _body = htd.Body.to_numpy()
# _up = htd.UpShadow.to_numpy()
# _bot = htd.LowerShadow.to_numpy()
# _time = htd.Time.to_numpy()
#
# for idx, x in np.ndenumerate(_open):
# # _iuc = jModel.isHammer(_body[idx], _height[idx], _up[idx], _bot[idx])
# if _bot[idx] > 0.6 * _height[idx]:
# # if _iuc is True:
import method.JavCan as jModel
ticker_id = 'VRE'
DATA_PATH = os.path.abspath('../vn-stock-data/VNX/')
ticker_data = _af.get_pricing_by_path(DATA_PATH + '/' + ticker_id + '.csv', '2019-01-01')
# print(ticker_data)
# print(len(ticker_data.index))
# print(ticker_data[0:5])
# print(ticker_data.size)
# exit()
d2 = jModel.convertToJapanCandle(ticker_data)
for index, row in d2.iterrows():
# print(row['Open'])
# isHammer = jModel.isHammer(row['Open'], row['Close'], row['Body'], row['Height'], row['UpShadow'], row['LowerShadow'])
# if isHammer is True:
# print(index)
if np.datetime64(row['Date']) == np.datetime64('2019-01-04T00:00:00.000000000'):
isHammer = jModel.isDoji(row['Body'], row['Height'])
print(isHammer)
# last = 0
# np_ticker_data = ticker_data.to_numpy()
# data_len = len(ticker_data.index)
# for i in range(data_len):
# if i > 2: