dsyoon/DeepStock
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

init

Browse Source
This commit is contained in:
dosangyoon
2022-08-28 20:59:58 +09:00
parent e7dc327634
commit 956ff3f154
3 changed files with 202 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files

16
Simulation.py
View File

@@ -52,8 +52,7 @@ class Simulation (HTS):
'avg6': 'float',
'avg9': 'float',
'avg12': 'float',
'avg27': 'float',
'avg54': 'float',
'avg20': 'float',
'fast_k': 'float',
'slow_k': 'float',
'slow_d': 'float',
@@ -89,8 +88,7 @@ class Simulation (HTS):
avg6 = go.Scatter(x=data['date'], y=data["avg6"], name="avg6", line_color='#089B5B')
avg9 = go.Scatter(x=data['date'], y=data["avg9"], name="avg9", line_color='#ff00ff')
avg12 = go.Scatter(x=data['date'], y=data["avg12"], name="avg12", line_color='#1469F4')
avg27 = go.Scatter(x=data['date'], y=data["avg27"], name="avg27", line_color='#000000')
avg54 = go.Scatter(x=data['date'], y=data["avg54"], name="avg54", line_color='#008000')
avg20 = go.Scatter(x=data['date'], y=data["avg20"], name="avg20", line_color='#000000')
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')
volume_line = go.Scatter(x=data['date'], y=data["volume"], mode='lines', name='volume')
@@ -106,7 +104,7 @@ class Simulation (HTS):
rsi_line = go.Scatter(x=data['date'], y=data["rsi"], mode='lines', name='rsi')
rsis_line = go.Scatter(x=data['date'], y=data["rsis"], mode='lines', name='rsis')
candle_data = [candle_stick, upper, lower, avg3, avg6, avg9, avg12, avg27, avg54, buy_check, sell_check]
candle_data = [candle_stick, upper, lower, avg3, avg6, avg9, avg12, avg20, buy_check, sell_check]
volume_data = [volume_line]
macd_data = [macd_line, macd_s_line, macd_o_line]
stochastic_data = [slow_k_line, slow_d_line]
@@ -184,12 +182,8 @@ if __name__ == "__main__":
# to check bying
stock_codes = {
"252670": [
'20220510', '20220511', '20220512',
'20220610', '20220613', '20220614',
'20220708', '20220711', '20220712',
'20220810', '20220811', '20220812'],
#"122630": ['20220611', '20220612', '20220613', '20220614'],
"252670": ['20220822', '20220823', '20220824', '20220825', '20220826'],
#"122630": ['20220822', '20220823', '20220824', '20220825', '20220826']
}
method = "rule" # "rule", "ml", "answer"

196
hts/BuySellChecker.py
View File

@@ -183,6 +183,103 @@ class BuySellChecker:
def getBuyPriceAndWeight(self, data, i):
buy, weight = -1, -1
slow_k = 60
START_TIME_INDEX = 0
for c in range(370, len(data.index)):
if data.index[c].strftime("%H:%M:%S") == "09:01:00":
START_TIME_INDEX = c
break
if i > START_TIME_INDEX:
# 매수 분석
valid = True
for c in range(i-10, i+1):
if data["avg20"][c-1] > data["avg20"][c]:
valid = False
if valid:
min_value = min(data["open"][i], data["close"][i])
max_value = max(data["open"][i], data["close"][i])
if min_value < data["avg20"][i] < max_value:
if data["slow_k"][i] < slow_k:
buy = min_value
weight = 1
if data["slow_k"][i] < slow_k:
valid = True
for c in range(i - 5, i + 1):
if data["avg20"][c] >= min(data["avg3"][c], data["avg6"][c], data["avg9"][c], data["avg12"][c]):
valid = False
break
if valid:
valid = False
for c in range(i - 20, i + 1):
if data["avg20"][c] > max(data["avg3"][c], data["avg6"][c], data["avg9"][c], data["avg12"][c]):
valid = True
break
if valid:
buy = max(int(data["open"][i]+data["close"][i])/2, min(data["open"][i], data["close"][i]))
weight = 1
return buy, weight
def getSellPriceAndWeight(self, data, i):
sell, weight = -1, -1
slow_k = 60
START_TIME_INDEX = 0
for c in range(370, len(data.index)):
if data.index[c].strftime("%H:%M:%S") == "09:01:00":
START_TIME_INDEX = c
break
if i > START_TIME_INDEX:
# 매도 분석
# 3분선이 10분 이상 6분선 위에 있다가 6분선 아래로 내려옴
if i >= 381 + 10:
vaild = True
count = 0
for c in range(i-10, i+1):
if data["avg3"][c-1] == data["avg20"][c]:
count += 1
if data["avg3"][c-1] < data["avg20"][c]:
vaild = False
break
if vaild and count < 3:
if data["avg3"][i] < data["avg20"][i]:
if data["slow_k"][i] > slow_k:
sell = int(data["avg3"][i] - data["avg3"][i] % 5)
weight = 1
return sell, weight
# 12분선이 5분 이상 20분선 위에 있다가 20분선 아래로 내려옴
if i >= 381 + 5:
vaild = True
for c in range(1, 6):
if data["avg12"][i - c] < data["avg20"][i - c]:
vaild = False
break
if vaild:
if data["avg12"][i] < data["avg20"][i] and data["avg20"][i-1] < data["avg20"][i]:
if data["slow_k"][i] > slow_k:
sell = data["close"][i]
weight = 1
return sell, weight
if (not (data["avg20"][i-1] > max(data["avg3"][i-1], data["avg6"][i-1], data["avg9"][i-1], data["avg12"][i-1])) and
(data["avg20"][i] > max(data["avg3"][i], data["avg6"][i], data["avg9"][i], data["avg12"][i]))):
if data["slow_k"][i] > slow_k:
sell = data["close"][i]
weight = 1
return sell, weight
return sell, weight
# 곱버스에 해당함
def getBuyPriceAndWeight_252670(self, data, i):
buy, weight = -1, -1
@@ -220,7 +317,6 @@ class BuySellChecker:
weight = 1
return buy, weight
return buy, weight
def getSellPriceAndWeight_252670(self, data, i):
@@ -445,6 +541,96 @@ class BuySellChecker:
vol = result["vol"]
label = result["label"]
# 이동 평균
close_df = pd.DataFrame(close)
avg3_list = close_df.rolling(window=3).mean().fillna(close[0]).values.tolist()
avg3 = [item[0] for item in avg3_list]
avg6_list = close_df.rolling(window=6).mean().fillna(close[0]).values.tolist()
avg6 = [item[0] for item in avg6_list]
avg9_list = close_df.rolling(window=9).mean().fillna(close[0]).values.tolist()
avg9 = [item[0] for item in avg9_list]
avg12_list = close_df.rolling(window=12).mean().fillna(close[0]).values.tolist()
avg12 = [item[0] for item in avg12_list]
avg20_list = close_df.rolling(window=20).mean().fillna(close[0]).values.tolist()
avg20 = [item[0] for item in avg20_list]
# 볼린져 밴드
df = pd.DataFrame(close)
max20 = df.rolling(window=20).mean()
stddev20 = df.rolling(window=20).std()
upper_df = max20 + (stddev20 * 2) # 상단 볼린저 밴드
lower_df = max20 - (stddev20 * 2) # 하단 볼린저 밴드
upper, lower = [], []
for i in range(len(upper_df)):
if i < 10:
upper.append(upper_df.values[0][0])
lower.append(lower_df.values[0][0])
else:
upper.append(upper_df.values[i][0])
lower.append(lower_df.values[i][0])
point_temp = result["time"]
STOCK = []
for i in range(len(open)):
STOCK.append({'volume': vol[i], 'close': close[i], 'open': open[i], 'high': high[i], 'low': low[i],
'avg20': avg20[i]})
# stochastic
stochastic_df = self.stochastic.apply(STOCK, n=30, m=5, t=5)
fast_k = stochastic_df['fast_k'].values.tolist()
slow_k = stochastic_df['slow_k'].values.tolist()
slow_d = stochastic_df['slow_d'].values.tolist()
# macd
macd_df = self.macd.apply(STOCK, short=12, long=26, t=9)
macd = macd_df['macd'].values.tolist()
macds = macd_df['macds'].values.tolist()
macdo = macd_df['macdo'].values.tolist()
# rsi
rsi_df = self.rsi.apply(STOCK, period=30, window=5)
rsi = rsi_df['rsi'].values.tolist()
rsis = rsi_df['rsis'].values.tolist()
# ichimokuCloud
ichimokuCloud_df = self.ichimokuCloud.apply(STOCK, c=9, b=26, l=52)
ichimokuCloud_df = ichimokuCloud_df[:len(ichimokuCloud_df) - 51]
changeLine = ichimokuCloud_df['changeLine'].values.tolist()
baseLine = ichimokuCloud_df['baseLine'].values.tolist()
leadingSpan1 = ichimokuCloud_df['leadingSpan1'].values.tolist()
leadingSpan2 = ichimokuCloud_df['leadingSpan2'].values.tolist()
# 결과
temp = {
"date": point_temp,
"open": open, "high": high, "low": low, "close": close, "volume": vol,
"avg3": avg3,"avg6": avg6,"avg9": avg9,"avg12": avg12, "avg20": avg20,
"upper": upper, "lower": lower,
"macd": macd, "macds": macds, "macdo": macdo,
"fast_k": fast_k, "slow_k": slow_k, "slow_d": slow_d,
"rsi": rsi, "rsis": rsis,
"changeLine": changeLine, "baseLine": baseLine, "leadingSpan1": leadingSpan1, "leadingSpan2": leadingSpan2,
"label": label
}
data = pd.DataFrame(temp)
df_final_time = pd.DatetimeIndex(point_temp)
data.index = df_final_time
data = data.fillna(close[0])
return data
def analyze1(self, result):
# 기본 캔들 정보
open = result["open"]
close = result["close"]
high = result["high"]
low = result["low"]
vol = result["vol"]
label = result["label"]
# 캔들 정보 연산
height = [close[i] - open[i] for i in range(0, len(close))]
top_tail_height = [high[i] - max(open[i], close[i]) for i in range(0, len(close))]
@@ -839,12 +1025,16 @@ class BuySellChecker:
# isRealTime=True, 실시간 적용
last_index = size - 1
buy, buy_weight = self.getBuyPriceAndWeight(data, last_index)
sell, sell_weight = self.getSellPriceAndWeight(data, last_index)
"""
if stock_code == "252670":
sell, sell_weight = self.getSellPriceAndWeight_252670(data, last_index)
buy, buy_weight = self.getBuyPriceAndWeight_252670(data, last_index)
else:
sell, sell_weight = self.getSellPriceAndWeight_122630(data, last_index)
buy, buy_weight = self.getBuyPriceAndWeight_122630(data, last_index)
"""
bsLine['buy'] = [buy]
bsLine['buy_weight'] = [buy_weight]
@@ -858,12 +1048,16 @@ class BuySellChecker:
bsLine['sell_weight'] = [-1 for i in range(size)]
for i in range(size):
buy, buy_weight = self.getBuyPriceAndWeight(data, i)
sell, sell_weight = self.getSellPriceAndWeight(data, i)
"""
if stock_code == "252670":
sell, sell_weight = self.getSellPriceAndWeight_252670(data, i)
buy, buy_weight = self.getBuyPriceAndWeight_252670(data, i)
else:
sell, sell_weight = self.getSellPriceAndWeight_122630(data, i)
buy, buy_weight = self.getBuyPriceAndWeight_122630(data, i)
"""
bsLine['buy'][i] = buy
bsLine['buy_weight'][i] = buy_weight
bsLine['sell'][i] = sell

3
requirements.txt
View File

@@ -3,7 +3,8 @@ plotly
matplotlib
pandas_datareader
bs4
pywin32
datasets
#pywin32
ipywidgets==7.0.0
#keras