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dsyoon
2023-01-24 20:42:30 +09:00
parent 74365b7d37
commit cdd2adfd31
3 changed files with 42 additions and 206 deletions
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1
HTS_daily.py
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@@ -141,6 +141,7 @@ class HTS_DAILY (HTS):
if bsLine['sell'][last_index] > 0: if bsLine['sell'][last_index] > 0:
bs_sell_price = bsLine['sell'][last_index] bs_sell_price = bsLine['sell'][last_index]
orderNum = self.getSellingPrice(THIS_TIME, self.stock_code, bs_sell_price) orderNum = self.getSellingPrice(THIS_TIME, self.stock_code, bs_sell_price)
self.orderChecker.delete(today, stock_code)
# 로그 출력 # 로그 출력
print("SELL", THIS_TIME.strftime('%Y%m%d %H%M%S'), orderNum, stock_code, stock_name, bs_sell_price) print("SELL", THIS_TIME.strftime('%Y%m%d %H%M%S'), orderNum, stock_code, stock_name, bs_sell_price)

233
hts/BuySellChecker.py
View File

@@ -943,68 +943,27 @@ class BuySellChecker:
size = len(data["close"]) size = len(data["close"])
bsLine['buy'] = [-1 for i in range(size)] bsLine['buy'] = [-1 for i in range(size)]
bsLine['buy_weight'] = [-1 for i in range(size)] bsLine['buy_weight'] = [-1.0 for i in range(size)]
bsLine['sell'] = [-1 for i in range(size)] bsLine['sell'] = [-1 for i in range(size)]
bsLine['sell_weight'] = [-1 for i in range(size)] bsLine['sell_weight'] = [-1.0 for i in range(size)]
for i in range(size): for i in range(size):
if isRealTime: if isRealTime:
if i < size - 1: if i < size - 1:
continue continue
"""
# 이전에 산 가격보다 지금 5원이상 떨어졌다면 매도 한다.
price = data['close'][i] if data['close'][i] >= data['open'][i] else data['open'][i]
if self.checkBelow5WonFromPreviousBuyPrice(i, data, price):
data['sell'][i] = price
bsLine['sell'][i] = price
bsLine['sell_weight'][i] = 50
return bsLine, data
"""
"""
# middle line에 맞다은 적 없이, low line에 붙었거나 아래에 있었던 캔들의 높은 가격을 얻어옴
buy, buy_weight = self.getBuyPriceAndWeight_Envelope(i, data)
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = buy_weight
return bsLine, data
"""
if 0 < data['gradients_avg60'][i] < 0.001:
if data['high'][i] < data['envelope_middle'][i]:
if -0.015 < data['gradients_avg5'][i] and -0.007 < data['gradients_avg20'][i]:
buy = data['low'][i]
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 10
if i > 10: if i > 10:
if ( if data['avg5'][i-1] < data['avg20'][i-1] and data['avg20'][i] < data['avg5'][i]:
data['gradients_avg60'][i - 10] > 0 and data['gradients_avg60'][i - 9] > 0 and data['gradients_avg60'][i - 8] > 0 and buy = data['close'][i]
data['gradients_avg60'][i - 7] > 0 and data['gradients_avg60'][i - 6] > 0 and data['gradients_avg60'][i - 5] > 0 and
data['gradients_avg60'][i - 4] > 0 and data['gradients_avg60'][i - 3] > 0 and data['gradients_avg60'][i - 2] > 0 and
data['gradients_avg60'][i - 1] > 0 and data['gradients_avg60'][i] < 0
):
if data['disparity'][i] < 3:
buy = data['low'][i]
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 10
if i > 10:
if data['disparity_avg60'][i] < 65:
buy = data['low'][i]
data['buy'][i] = buy data['buy'][i] = buy
bsLine['buy'][i] = buy bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 20 bsLine['buy_weight'][i] = 5.0
if data['slow_k'][i] < 3: if data['slow_k'][i] < 3:
buy = data['low'][i] sell = data['close'][i]
data['buy'][i] = buy data['sell'][i] = sell
bsLine['buy'][i] = buy bsLine['sell'][i] = sell
bsLine['buy_weight'][i] = 10 bsLine['sell_weight'][i] = 100.0
return bsLine, data return bsLine, data
@@ -1015,9 +974,9 @@ class BuySellChecker:
size = len(data["close"]) size = len(data["close"])
bsLine['buy'] = [-1 for i in range(size)] bsLine['buy'] = [-1 for i in range(size)]
bsLine['buy_weight'] = [-1 for i in range(size)] bsLine['buy_weight'] = [-1.0 for i in range(size)]
bsLine['sell'] = [-1 for i in range(size)] bsLine['sell'] = [-1 for i in range(size)]
bsLine['sell_weight'] = [-1 for i in range(size)] bsLine['sell_weight'] = [-1.0 for i in range(size)]
for i in range(size): for i in range(size):
if isRealTime: if isRealTime:
@@ -1025,24 +984,17 @@ class BuySellChecker:
continue continue
if i > 10: if i > 10:
if data['disparity_avg60'][i] < 60: if data['avg5'][i - 1] < data['avg20'][i - 1] and data['avg20'][i] < data['avg5'][i]:
buy = data['low'][i] buy = data['close'][i]
data['buy'][i] = buy data['buy'][i] = buy
bsLine['buy'][i] = buy bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 15 bsLine['buy_weight'][i] = 5.0
if data['macd'][i] < -1000: if data['slow_k'][i] < 3:
buy = data['low'][i] sell = data['close'][i]
data['buy'][i] = buy data['sell'][i] = sell
bsLine['buy'][i] = buy bsLine['sell'][i] = sell
bsLine['buy_weight'][i] = 15 bsLine['sell_weight'][i] = 100.0
if data['slow_k'][i] < 7:
if data['slow_d'][i] < data['slow_k'][i]:
buy = data['low'][i]
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 5
return bsLine, data return bsLine, data
@@ -1071,154 +1023,23 @@ class BuySellChecker:
bsLine['sell'] = [-1 for i in range(size)] bsLine['sell'] = [-1 for i in range(size)]
bsLine['sell_weight'] = [-1 for i in range(size)] bsLine['sell_weight'] = [-1 for i in range(size)]
gap_interval = analyzed_day
gap_state = False
for i in range(size): for i in range(size):
if isRealTime: if isRealTime:
if i < size - 1: if i < size - 1:
continue continue
if i > 10: if i > 10:
# 만약 전일 저가와 오늘 종의 차이가 1만원이 넘으면 향후 60일은 분석하지 않는다. if data['avg5'][i - 1] < data['avg20'][i - 1] and data['avg20'][i] < data['avg5'][i]:
if data['high'][i] < int(data['low'][i-1] * 0.7): buy = data['close'][i]
gap_state = True
gap_interval -= 1
continue
if gap_state:
if gap_interval <= 0:
gap_state = False
gap_interval = 60
else:
gap_interval -= 1
continue
if data['disparity'][i] < 2:
check = True
for l in range(i-3, i):
if (
data['gradients_avg60'][l-1] > data['gradients_avg60'][l] or
data['gradients_avg20'][l-1] > data['gradients_avg20'][l] or
data['gradients_low'][l-1] > data['gradients_low'][l] or
data['disparity_avg5'][l-1] > data['disparity_avg5'][l] or
data['disparity'][l-1] < data['disparity'][l]
):
check = False
break
if check and 99 < sum(data['disparity_avg5'][i-4:i+1])/5 < 100 and 99 < sum(data['disparity_avg60'][i-4:i+1])/5 < 100:
buy = data['low'][i]
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 20
check = True
for l in range(i - 2, i):
if (
data['gradients_avg60'][l - 1] > data['gradients_avg60'][l] or
data['gradients_low'][l - 1] > data['gradients_low'][l]
):
check = False
break
if (
check and
-0.0011 < data['gradients_low'][i] < 0 and -0.007 < data['gradients_avg5'][i] < 0.001 and
-0.0012 < data['gradients_avg60'][i] < 0 and
98.90 < data['disparity_avg5'][i] < 101
):
buy = data['low'][i]
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 20
check = True
for l in range(i - 6, i):
if (
data['gradients_avg60'][l - 1] < data['gradients_avg60'][l] or
data['gradients_avg20'][l - 1] < data['gradients_avg20'][l] or
data['gradients_low'][l - 1] < data['gradients_low'][l] or
-0.039 < data['gradients_low'][l - 1] < -0.35 or
-0.05 < data['gradients_avg20'][l - 1] < -0.30 or
-0.40 < data['gradients_avg60'][l - 1] < -0.30
):
check = False
break
if check and 99 < min (data['disparity_avg5'][i - 6:i]) < max (data['disparity_avg5'][i - 6:i]) < 101:
buy = data['low'][i]
data['buy'][i] = buy data['buy'][i] = buy
bsLine['buy'][i] = buy bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 20 bsLine['buy_weight'][i] = 3.0
check = True
for l in range(i - 3, i):
if (
data['gradients_low'][l - 1] < data['gradients_low'][l] or
data['gradients_avg60'][l - 1] < data['gradients_avg60'][l] or
data['gradients_avg20'][l - 1] < data['gradients_avg20'][l] or
0.01 < data['gradients_low'][l - 1] < 0.21 or
-0.09 < data['gradients_avg20'][l - 1] < -0.002 or
0.01 < data['gradients_avg60'][l - 1] < 0.021
):
check = False
break
if check:
buy = data['low'][i]
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 20
if (data['disparity'][i] < 5 and 99.0 < data['disparity_avg60'][i] < 99.1 and
-0.009 < data['gradients_avg60'][i] < -0.008 and 0.015 < data['gradients_avg20'][i] < 0.016 and
-0.006 < data['gradients_avg5'][i] < -0.005 and -0.009 < data['gradients_low'][i] < -0.008):
check = True
for l in range(i-5, i):
if (
data['gradients_avg60'][l-1] > data['gradients_avg60'][l] or
data['gradients_low'][l-1] > data['gradients_low'][l] or
data['disparity'][l - 1] < data['disparity'][l]
):
check = False
break
if check:
buy = data['low'][i]
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 20
if data['macd'][i] < -4000:
if data['macd'][i-1] < data['macd'][i]:
if not self.notBuy(data, i) and data['slow_k'][i] < 30:
buy = data['low'][i]
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 20
# macd 이전에 없던 바닥인 경우 상승할 찰나 매수
if data['macds'][i-1] < min(data['macds'][:i-1]):
if data['macds'][i-1] < data['macds'][i]:
if not self.notBuy(data, i) and data['slow_k'][i] < 30:
buy = data['low'][i]
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 20
if (
98 < data['disparity_avg5'][i] < 100 and data['disparity_avg20'][i] < 93.5 and data['disparity_avg60'][i] < 89 and
-0.014 < data['gradients_avg60'][i] < -0.013 and -0.03 < data['gradients_avg20'][i] < -0.02 and -0.014 < data['gradients_low'][i] < -0.013 and
data['slow_k'][i] < 11
):
if not self.notBuy(data, i):
buy = data['low'][i]
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 20
if data['slow_k'][i]<20 and data['slow_k'][i-1] < data['slow_d'][i-1] and data['slow_d'][i] < data['slow_k'][i]:
buy = data['low'][i]
data['buy'][i] = buy
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = 30
if data['slow_k'][i] < 3:
sell = data['close'][i]
data['sell'][i] = sell
bsLine['sell'][i] = sell
bsLine['sell_weight'][i] = 100.0
return bsLine, data return bsLine, data

14
hts/OrderChecker.py
View File

@@ -37,6 +37,7 @@ class OrderChecker:
def add(self, ymd, stock_code, type, orderNum, count, price): def add(self, ymd, stock_code, type, orderNum, count, price):
if self.exist(stock_code): if self.exist(stock_code):
return False return False
# 새로운 주문을 추가한다. # 새로운 주문을 추가한다.
self.order_df = self.order_df.append({"stock_code": stock_code, "type": type, "orderNum": orderNum, "count": count, "price": price, "datetime": datetime.now()}, ignore_index=True) self.order_df = self.order_df.append({"stock_code": stock_code, "type": type, "orderNum": orderNum, "count": count, "price": price, "datetime": datetime.now()}, ignore_index=True)
@@ -45,3 +46,16 @@ class OrderChecker:
self.order_df.to_csv(saveFileName) self.order_df.to_csv(saveFileName)
return True return True
def delete(self, ymd, stock_code):
if not self.exist(stock_code):
return False
# 매도 주문을 삭제한다.
self.order_df = self.order_df.loc[(self.order_df["stock_code"] != stock_code)]
# 파일로 기록한다.
saveFileName = os.path.join(self.RESOURCE_PATH, "order", ymd + ".csv")
self.order_df.to_csv(saveFileName)
return True