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dosangyoon
2021-10-24 23:35:08 +09:00
parent c9e8f662e8
commit 52285278b6
3 changed files with 70 additions and 65 deletions
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94
hts/BuySellChecker.py
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@@ -187,40 +187,40 @@ class BuySellChecker:
### sell 분석 ###
################
# 1. 볼린져밴드 상단이 최고와 종가 사이 아래에 있는 경우 매도한다.
if (data["High"][i] - data["Close"][i]) / 2 + data["Close"][i] > data["upper"][i]:
sell = data["High"][i]
if (data["high"][i] - data["close"][i]) / 2 + data["close"][i] > data["upper"][i]:
sell = data["high"][i]
"""
# 2. slow_k가 90이 넘으면 매도한다.
if data["slow_k"][i] >= 90:
sell = data["High"][i]
sell = data["high"][i]
"""
if data["slow_k"][i] >= 85:
if data["slow_d"][i-1] < data["slow_k"][i-1] and data["slow_k"][i] < data["slow_d"][i]:
sell = data["High"][i]
sell = data["high"][i]
# 3. 2시 이후에는 최고가가 볼린져밴드 상단 위에 있으면 매도한다.
if i > 300 and data["High"][i] > data["upper"][i]:
sell = data["High"][i]
if i > 300 and data["high"][i] > data["upper"][i]:
sell = data["high"][i]
##########################
### STOCHASTIC buy 분석 ###
##########################
if i < 40:
if data["Low"][i] - 3 < data["lower"][i]:
if data["low"][i] - 3 < data["lower"][i]:
if data["slow_k"][i] <= 20:
if data["slow_k"][i - 2] < data["slow_d"][i - 2] and data["slow_k"][i - 1] < data["slow_d"][i - 1] and data["slow_d"][i] < data["slow_k"][i]:
if data["Close"][i] < data["avg5"][i]:
buy = data["Close"][i]
if data["close"][i] < data["avg5"][i]:
buy = data["close"][i]
else:
buy = data["Low"][i]
buy = data["low"][i]
else:
if data["Low"][i] - 3 < data["lower"][i]:
if data["low"][i] - 3 < data["lower"][i]:
if data["slow_k"][i] <= 35:
if data["slow_k"][i-2] < data["slow_d"][i-2] and data["slow_k"][i-1] < data["slow_d"][i-1] and data["slow_d"][i] < data["slow_k"][i]:
if data["Close"][i] < data["avg5"][i]:
buy = data["Close"][i]
if data["close"][i] < data["avg5"][i]:
buy = data["close"][i]
else:
buy = data["Low"][i]
buy = data["low"][i]
#############################
### STOCHASTIC weight 분석 ###
@@ -239,10 +239,10 @@ class BuySellChecker:
###################
if data["rsi"][i] < 25:
if data["rsi"][i - 2] < data["rsis"][i - 2] and data["rsi"][i - 1] < data["rsis"][i - 1] and data["rsis"][i] < data["rsi"][i]:
if data["Close"][i] < data["avg5"][i]:
buy = data["Close"][i]
if data["close"][i] < data["avg5"][i]:
buy = data["close"][i]
else:
buy = data["Low"][i]
buy = data["low"][i]
weight = 1
return buy, weight, sell
@@ -254,16 +254,16 @@ class BuySellChecker:
### sell 분석 ###
################
# 1. 볼린져밴드 상단이 최고와 종가 사이 아래에 있는 경우 매도한다.
if (data["High"][i] - data["Close"][i]) / 2 + data["Close"][i] > data["upper"][i]:
sell = data["High"][i]
if (data["high"][i] - data["close"][i]) / 2 + data["close"][i] > data["upper"][i]:
sell = data["high"][i]
if data["slow_k"][i] >= 85:
if data["slow_d"][i - 1] < data["slow_k"][i - 1] and data["slow_k"][i] < data["slow_d"][i]:
sell = data["High"][i]
sell = data["high"][i]
# 3. 2시 이후에는 최고가가 볼린져밴드 상단 위에 있으면 매도한다.
if i > 300 and data["High"][i] > data["upper"][i]:
sell = data["High"][i]
if i > 300 and data["high"][i] > data["upper"][i]:
sell = data["high"][i]
##########################
### STOCHASTIC buy 분석 ###
@@ -273,23 +273,23 @@ class BuySellChecker:
now_slow = data["slow_k"][i] / data["slow_d"][i] - 1
if pre_slow < 0 and 0 < now_slow:
if data["slow_k"][i] <= 20:
if (data["Close"][i] - data["lower"][i]) / (data["upper"][i] - data["lower"][i]) < 0.1:
if (data["close"][i] - data["lower"][i]) / (data["upper"][i] - data["lower"][i]) < 0.1:
if data["slow_k"][i - 1] < data["slow_d"][i - 1] and data["slow_d"][i] < data["slow_k"][i]:
if data["Close"][i] < data["avg5"][i]:
buy = data["Close"][i]
if data["close"][i] < data["avg5"][i]:
buy = data["close"][i]
else:
buy = data["Low"][i]
buy = data["low"][i]
else:
pre_slow = data["slow_k"][i - 1] / data["slow_d"][i - 1] - 1
now_slow = data["slow_k"][i] / data["slow_d"][i] - 1
if pre_slow < 0 and pre_slow < now_slow and -0.15 < now_slow:
if data["slow_k"][i] <= 20:
if (data["Close"][i] - data["lower"][i]) / (data["upper"][i] - data["lower"][i]) < 0.35:
if (data["close"][i] - data["lower"][i]) / (data["upper"][i] - data["lower"][i]) < 0.35:
if data["slow_k"][i - 1] < data["slow_d"][i - 1] and data["slow_d"][i] < data["slow_k"][i]:
if data["Close"][i] < data["avg5"][i]:
buy = data["Close"][i]
if data["close"][i] < data["avg5"][i]:
buy = data["close"][i]
else:
buy = data["Low"][i]
buy = data["low"][i]
#############################
### STOCHASTIC weight 분석 ###
@@ -312,16 +312,16 @@ class BuySellChecker:
### sell 분석 ###
################
# 1. 볼린져밴드 상단이 최고와 종가 사이 아래에 있는 경우 매도한다.
if (data["High"][i] - data["Close"][i]) / 2 + data["Close"][i] > data["upper"][i]:
sell = data["High"][i]
if (data["high"][i] - data["close"][i]) / 2 + data["close"][i] > data["upper"][i]:
sell = data["high"][i]
if data["slow_k"][i] >= 85:
if data["slow_d"][i - 1] < data["slow_k"][i - 1] and data["slow_k"][i] < data["slow_d"][i]:
sell = data["High"][i]
sell = data["high"][i]
# 3. 2시 이후에는 최고가가 볼린져밴드 상단 위에 있으면 매도한다.
if i > 300 and data["High"][i] > data["upper"][i]:
sell = data["High"][i]
if i > 300 and data["high"][i] > data["upper"][i]:
sell = data["high"][i]
##########################
### STOCHASTIC buy 분석 ###
@@ -332,17 +332,17 @@ class BuySellChecker:
if data["slow_d"][i - 2] > data["slow_d"][i - 1] and data["slow_d"][i - 1] < data["slow_d"][i]:
if abs(data["slow_d"][i]-data["slow_k"][i]) < abs(data["slow_d"][i-1]-data["slow_k"][i-1]):
if now_slow < 0.15:
if data["Close"][i] < data["avg5"][i]:
buy = data["Close"][i]
if data["close"][i] < data["avg5"][i]:
buy = data["close"][i]
else:
buy = data["Low"][i]
buy = data["low"][i]
if data["slow_k"][i-1] < data["slow_d"][i-1] and data["slow_d"][i] < data["slow_k"][i]:
if abs(now_slow) < 0.001:
if now_slow < 0.15:
if data["Close"][i] < data["avg5"][i]:
buy = data["Close"][i]
if data["close"][i] < data["avg5"][i]:
buy = data["close"][i]
else:
buy = data["Low"][i]
buy = data["low"][i]
else:
if i > 60:
print (1)
@@ -350,11 +350,11 @@ class BuySellChecker:
now_slow = data["slow_k"][i] / data["slow_d"][i] - 1
if pre_slow < 0 and pre_slow < now_slow and -0.15 < now_slow:
if data["slow_k"][i] <= 20:
if (data["Close"][i] - data["lower"][i]) / (data["upper"][i] - data["lower"][i]) < 0.35:
if data["Close"][i] < data["avg5"][i]:
buy = data["Close"][i]
if (data["close"][i] - data["lower"][i]) / (data["upper"][i] - data["lower"][i]) < 0.35:
if data["close"][i] < data["avg5"][i]:
buy = data["close"][i]
else:
buy = data["Low"][i]
buy = data["low"][i]
#############################
### STOCHASTIC weight 분석 ###
@@ -437,8 +437,8 @@ class BuySellChecker:
rsi = rsi_df['rsi'].values.tolist()
rsis = rsi_df['rsis'].values.tolist()
temp = {"Date": point_temp,
"Open": open, "High": high, "Low": low, "Close": close, "Volume": vol,
temp = {"date": point_temp,
"open": open, "high": high, "low": low, "close": close, "volume": vol,
"upper": upper, "lower": lower,
"avg1": avg1, "avg2": avg2, "avg5": avg5, "avg10": avg10, "avg20": avg20, "avg30": avg30, "avg40": avg40, "avg50": avg50, "avg60": avg60,
"fast_k": fast_k, "slow_k": slow_k, "slow_d": slow_d,

37
hts/Simulation.py
View File

@@ -42,7 +42,7 @@ class Simulation:
return
def checkTransaction(self, data):
size = len(data["Close"])
size = len(data["close"])
bsLine = {}
bsLine['buy'] = [-1 for i in range(size)]
@@ -62,11 +62,11 @@ class Simulation:
sell_line = bsLine['sell']
# 그래프 설정을 위한 변수를 생성한다.
data['Open'] = pd.to_numeric(data['Open'])
data['High'] = pd.to_numeric(data['High'])
data['Low'] = pd.to_numeric(data['Low'])
data['Close'] = pd.to_numeric(data['Close'])
data['Volume'] = pd.to_numeric(data['Volume'])
data['open'] = pd.to_numeric(data['open'])
data['high'] = pd.to_numeric(data['high'])
data['low'] = pd.to_numeric(data['low'])
data['close'] = pd.to_numeric(data['close'])
data['volume'] = pd.to_numeric(data['volume'])
data['avg5'] = pd.to_numeric(data['avg5'])
data["fast_k"] = pd.to_numeric(data['fast_k'])
data["slow_k"] = pd.to_numeric(data['slow_k'])
@@ -90,19 +90,19 @@ class Simulation:
sell_colors.append("#00ced1")
# 그래프를 설정한다.
buy_check = go.Scatter(x=data['Date'], y=buy_line, mode='markers', name="buy", marker=dict(size=14, color=buy_colors, line_width=0))
sell_check = go.Scatter(x=data['Date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0))
bolinger_upper = go.Scatter(x=data['Date'], y=data["upper"], name="upper", line_color='#8B4513')
bolinger_lower = go.Scatter(x=data['Date'], y=data["lower"], name="lower", line_color='#8B4513')
avg5 = go.Scatter(x=data['Date'], y=data["avg5"], name="avg5", line_color='#000000')
buy_check = go.Scatter(x=data['date'], y=buy_line, mode='markers', name="buy", marker=dict(size=14, color=buy_colors, line_width=0))
sell_check = go.Scatter(x=data['date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0))
bolinger_upper = go.Scatter(x=data['date'], y=data["upper"], name="upper", line_color='#8B4513')
bolinger_lower = go.Scatter(x=data['date'], y=data["lower"], name="lower", line_color='#8B4513')
avg5 = go.Scatter(x=data['date'], y=data["avg5"], name="avg5", 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')
fast_k_line = go.Scatter(x=data['Date'], y=data["fast_k"], mode='lines', name='fast_k')
slow_k_line = go.Scatter(x=data['Date'], y=data["slow_k"], mode='lines', name='slow_k')
slow_d_line = go.Scatter(x=data['Date'], y=data["slow_d"], mode='lines', name='slow_d')
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_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')
fast_k_line = go.Scatter(x=data['date'], y=data["fast_k"], mode='lines', name='fast_k')
slow_k_line = go.Scatter(x=data['date'], y=data["slow_k"], mode='lines', name='slow_k')
slow_d_line = go.Scatter(x=data['date'], y=data["slow_d"], mode='lines', name='slow_d')
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, bolinger_upper, bolinger_lower, buy_check, sell_check, avg1, avg2, avg5, avg10, avg20, avg30, avg40, avg50, avg60]
candle_data = [candle_stick, bolinger_upper, bolinger_lower, avg5, buy_check, sell_check]
@@ -174,6 +174,7 @@ if __name__ == "__main__":
'20210914','20210915','20210916','20210917','20210923','20210924','20210927','20210928','20210929',
'20210930','20211001','20211005','20211006','20211007','20211008','20211012','20211013','20211014',
'20211018', '20211019','20211020','20211021','20211022']
given_days = ['20211022']
simulation = Simulation()

4
hts/data/sample.csv Normal file
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@@ -0,0 +1,4 @@
LABEL,DATETIME,index,open,high,low,close,volume,upper,lower,avg1,avg2,avg5,avg10,avg20,avg30,avg40,avg50,avg60,fast_k,slow_k,slow_d,rsi,rsis
NONE,,,,,,,,,,,,,,,,,,,,,,,
BUY,,,,,,,,,,,,,,,,,,,,,,,
SELL,,,,,,,,,,,,,,,,,,,,,,,
1 LABEL DATETIME index open high low close volume upper lower avg1 avg2 avg5 avg10 avg20 avg30 avg40 avg50 avg60 fast_k slow_k slow_d rsi rsis
2 NONE
3 BUY
4 SELL