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dsyoon
2023-10-16 10:52:44 +09:00
parent 8bb8e8b09a
commit 90b3327716
4 changed files with 62 additions and 37 deletions
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2
HTS_etf_122630.py
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@@ -144,7 +144,7 @@ class HTS_etf(HTS):
# 미체결 기록을 가져와서 10분 이상 된 매수 주문을 취소 한다. # 미체결 기록을 가져와서 10분 이상 된 매수 주문을 취소 한다.
ORDER_LIST = self.requestOrderList() ORDER_LIST = self.requestOrderList()
orderListToCancel = self.orderChecker.cancel(today, "A" + stock_code, ORDER_LIST, mins=10) orderListToCancel = self.orderChecker.cancel(today, "A" + stock_code, ORDER_LIST, mins=30)
if len(orderListToCancel) > 0: if len(orderListToCancel) > 0:
self.cancelOrderList(orderListToCancel) self.cancelOrderList(orderListToCancel)

2
HTS_etf_252670.py
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@@ -145,7 +145,7 @@ class HTS_etf(HTS):
# 미체결 기록을 가져와서 10분 이상 된 매수 주문을 취소 한다. # 미체결 기록을 가져와서 10분 이상 된 매수 주문을 취소 한다.
ORDER_LIST = self.requestOrderList() ORDER_LIST = self.requestOrderList()
orderListToCancel = self.orderChecker.cancel(today, "A" + stock_code, ORDER_LIST, mins=10) orderListToCancel = self.orderChecker.cancel(today, "A" + stock_code, ORDER_LIST, mins=30)
if len(orderListToCancel) > 0: if len(orderListToCancel) > 0:
self.cancelOrderList(orderListToCancel) self.cancelOrderList(orderListToCancel)

45
Simulation.py
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@@ -37,7 +37,8 @@ class Simulation (HTS):
data = data.loc[pd.DatetimeIndex(data.index).day == int(given_day[6:])] data = data.loc[pd.DatetimeIndex(data.index).day == int(given_day[6:])]
buy_line = bsLine['buy'][len(bsLine['buy'])-len(data):] buy_line = bsLine['buy'][len(bsLine['buy'])-len(data):]
buy_weight_line = bsLine['buy_weight'][len(bsLine['buy'])-len(data):] buy_weight_line = bsLine['buy_weight'][len(bsLine['buy'])-len(data):]
sell_line = bsLine['sell'][len(bsLine['buy'])-len(data):] sell_line = bsLine['sell'][len(bsLine['sell'])-len(data):]
sell_weight_line = bsLine['sell_weight'][len(bsLine['sell']) - len(data):]
# 그래프 설정을 위한 변수를 생성한다. # 그래프 설정을 위한 변수를 생성한다.
data = data.astype({'open': 'int', data = data.astype({'open': 'int',
@@ -73,13 +74,25 @@ class Simulation (HTS):
buy_colors.append("#0C752E") buy_colors.append("#0C752E")
buy_size.append(10 + (5 * buy_weight_line[i])) buy_size.append(10 + (5 * buy_weight_line[i]))
sell_size = []
sell_colors = [] sell_colors = []
for i in range(len(sell_line)): for i in range(len(sell_line)):
if sell_line[i] < 0: if sell_line[i] < 0:
sell_colors.append("#ffffff") sell_colors.append("#ffffff")
sell_line[i] = nan sell_line[i] = nan
sell_size.append(0)
else: else:
sell_colors.append("#00ced1") sell_colors.append("#00ced1")
sell_size.append(10 + (5 * sell_weight_line[i]))
volume_colors = []
for i in range(len(buy_line)):
if data['open'][i] > data['close'][i]:
volume_colors.append("#0000FF")
elif data['open'][i] < data['close'][i]:
volume_colors.append("#FF0000")
else:
volume_colors.append("#000000")
# 그래프를 설정한다. # 그래프를 설정한다.
buy_check = go.Scatter(x=data['date'], y=buy_line, mode='markers', name="buy", marker=dict(size=buy_size, color=buy_colors, line_width=0)) buy_check = go.Scatter(x=data['date'], y=buy_line, mode='markers', name="buy", marker=dict(size=buy_size, color=buy_colors, line_width=0))
@@ -98,7 +111,7 @@ class Simulation (HTS):
candle_stick = go.Candlestick(x=data['date'], open=data['open'], high=data['high'], low=data['low'], close=data['close'], increasing_line_color='red', decreasing_line_color='blue', showlegend=False) candle_stick = go.Candlestick(x=data['date'], open=data['open'], high=data['high'], low=data['low'], close=data['close'], increasing_line_color='red', decreasing_line_color='blue', showlegend=False)
#volume_line = go.Scatter(x=data['date'], y=data["volume"], mode='lines', name='volume') #volume_line = go.Scatter(x=data['date'], y=data["volume"], mode='lines', name='volume')
volume_line = go.Bar(x=data['date'], y=data["volume"], marker_color='red', name='volume') volume_line = go.Bar(x=data['date'], y=data["volume"], marker_color=volume_colors, name='volume')
disparity_avg5 = go.Scatter(x=data['date'], y=data["disparity_avg5"], name="disparity_avg5", line_color='#F81191') disparity_avg5 = go.Scatter(x=data['date'], y=data["disparity_avg5"], name="disparity_avg5", line_color='#F81191')
disparity_avg20 = go.Scatter(x=data['date'], y=data["disparity_avg20"], name="disparity_avg20", line_color='#097F19') disparity_avg20 = go.Scatter(x=data['date'], y=data["disparity_avg20"], name="disparity_avg20", line_color='#097F19')
@@ -118,9 +131,9 @@ class Simulation (HTS):
rsi_line = go.Scatter(x=data['date'], y=data["rsi"], line=dict(color='red', width=2), name='rsi') rsi_line = go.Scatter(x=data['date'], y=data["rsi"], line=dict(color='red', width=2), name='rsi')
rsis_line = go.Scatter(x=data['date'], y=data["rsis"], line=dict(dash='dashdot', color='black', width=2), name='rsis') rsis_line = go.Scatter(x=data['date'], y=data["rsis"], line=dict(dash='dashdot', color='black', width=2), name='rsis')
candle_data = [candle_stick, upper, lower, avg5, avg20, avg30, avg60, avg120, avg200, buy_check, sell_check, laggingSpan, changeLine, baseLine] #candle_data = [candle_stick, upper, lower, avg5, avg20, avg30, avg60, avg120, avg200, buy_check, sell_check, laggingSpan, changeLine, baseLine]
candle_data = [candle_stick, avg5, avg20, avg30, avg60, avg200, buy_check, sell_check] candle_data = [candle_stick, avg5, avg20, avg30, avg60, avg200, buy_check, sell_check]
candle_data = [candle_stick, avg200, buy_check, sell_check] #candle_data = [candle_stick, avg200, buy_check, sell_check]
volume_data = [volume_line] volume_data = [volume_line]
disparity_data = [disparity_avg5, disparity_avg20, disparity_avg30, disparity_avg60, disparity_avg120, disparity_avg200] disparity_data = [disparity_avg5, disparity_avg20, disparity_avg30, disparity_avg60, disparity_avg120, disparity_avg200]
macd_data = [macd_line, macd_s_line, macd_o_line] macd_data = [macd_line, macd_s_line, macd_o_line]
@@ -136,20 +149,20 @@ class Simulation (HTS):
fig = subplots.make_subplots( fig = subplots.make_subplots(
rows=6, cols=1, rows=6, cols=1,
subplot_titles=("거래량", "이격도", "스토캐스틱", "RSI", "MACD", '캔들'), subplot_titles=("이격도", "스토캐스틱", "RSI", "MACD", "거래량", '캔들'),
#specs=[[{}], [{}], [{}], [{}], [{}], [{}]], #specs=[[{}], [{}], [{}], [{}], [{}], [{}]],
shared_xaxes=True, horizontal_spacing=0.03, vertical_spacing=0.01, shared_xaxes=True, horizontal_spacing=0.03, vertical_spacing=0.01,
row_heights=[200, 200, 200, 200, 200, 700] row_heights=[200, 200, 200, 200, 200, 700]
) )
for trace in volume_data:
fig.append_trace(trace, 1, 1)
for trace in disparity_data: for trace in disparity_data:
fig.append_trace(trace, 2, 1) fig.append_trace(trace, 1, 1)
for trace in stochastic_data: for trace in stochastic_data:
fig.append_trace(trace, 3, 1) fig.append_trace(trace, 2, 1)
for trace in rsi_data: for trace in rsi_data:
fig.append_trace(trace, 4, 1) fig.append_trace(trace, 3, 1)
for trace in macd_data: for trace in macd_data:
fig.append_trace(trace, 4, 1)
for trace in volume_data:
fig.append_trace(trace, 5, 1) fig.append_trace(trace, 5, 1)
for trace in candle_data: for trace in candle_data:
fig.append_trace(trace, 6, 1) fig.append_trace(trace, 6, 1)
@@ -234,12 +247,12 @@ if __name__ == "__main__":
# to check bying # to check bying
stock_codes = { stock_codes = {
"252670": ['20231012'], #"252670": ['20210930'],
"122630": ['20231012'], #"122630": ['20230930'],
#"252670": ['20210901','20210902','20210903','20210906'], #"252670": ['20210903','20210910','20210913'],
#"252670": ['20210901', '20210902', '20210903', '20210906', '20210907', '20210908', '20210909', '20210910', '20210913', '20210914', '20210915', '20210916', '20210917', '20210923', '20210924', '20210927', '20210928', '20210929', '20210930', '20211001', '20211005'], "252670": ['20210901', '20210902', '20210903', '20210906', '20210907', '20210908', '20210909', '20210910', '20210913', '20210914', '20210915', '20210916', '20210917', '20210923', '20210924', '20210927', '20210928', '20210929', '20210930', '20211001', '20211005','20231012','20231013'],
#"122630": ['20220901', '20220902', '20220905', '20220906'] #"122630": ['20210901','20210902','20210903','20210906','20231012','20231013']
#"122630": ['20210901', '20210902', '20210903', '20210906', '20210907', '20210908', '20210909', '20210910', '20210913', '20210914', '20210915', '20210916', '20210917', '20210923', '20210924', '20210927', '20210928', '20210929', '20210930', '20211001', '20211005'], #"122630": ['20210901', '20210902', '20210903', '20210906', '20210907', '20210908', '20210909', '20210910', '20210913', '20210914', '20210915', '20210916', '20210917', '20210923', '20210924', '20210927', '20210928', '20210929', '20210930', '20211001', '20211005','20231012','20231013'],
} }
#simulation.simulate(stock_codes) #simulation.simulate(stock_codes)
simulation.simulate(stock_codes) simulation.simulate(stock_codes)

18
hts/BuySellChecker.py
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@@ -221,6 +221,15 @@ class BuySellChecker:
def getBuyPriceAndWeight(self, i, data): def getBuyPriceAndWeight(self, i, data):
buy, weight = -1, -1 buy, weight = -1, -1
if i < 40:
return buy, weight
max_vol_5 = max(data['volume'].to_list()[i - 4: i + 1])
max_vol_30 = max(data['volume'].to_list()[i - 24: i - 4])
if max_vol_30 < max_vol_5:
if data['open'][i-1] < data['close'][i-1] and data['volume'][i-1] < data['volume'][i]:
#if data['open'][i - 1] < data['close'][i - 1] and data['volume'][i - 1] < data['volume'][i]:
# 1) 스토캐스틱 과매도 # 1) 스토캐스틱 과매도
slow_k_buy = False slow_k_buy = False
for idx in range(i, i-10, -1): for idx in range(i, i-10, -1):
@@ -242,11 +251,14 @@ class BuySellChecker:
if data['rsi'][i-1] < 40 and data['rsi'][i] > 40: if data['rsi'][i-1] < 40 and data['rsi'][i] > 40:
buy, weight = data['close'][i] , 1 buy, weight = data['close'][i] , 1
"""
min_macd = min(data['macd']) min_macd = min(data['macd'])
if i > 30 and data['macd'][i] < min_macd + (-min_macd * 0.5): if i > 30 and data['macd'][i] < min_macd + (-min_macd * 0.4):
buy, weight = data['close'][i], 1
"""
if data['macd'][i] < -4:
if data['open'][i - 1] < data['close'][i - 1] and data['volume'][i - 1] < data['volume'][i]:
buy, weight = data['close'][i], 1 buy, weight = data['close'][i], 1
return buy, weight return buy, weight