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dosangyoon
2021-09-30 11:54:15 +09:00
parent 06c5dfd4e1
commit 4ec61a4694
1 changed files with 29 additions and 16 deletions
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hts/HTS.py
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@@ -1,10 +1,10 @@
import win32com.client #import win32com.client
import time import time
import os import os
from datetime import datetime, timedelta from datetime import datetime, timedelta
import pandas as pd import pandas as pd
from enum import Enum from enum import Enum
#import plotly.graph_objects as go import plotly.graph_objects as go
# enum 주문 상태 세팅용 # enum 주문 상태 세팅용
@@ -514,8 +514,8 @@ class HTS:
vol = [sum(result["vol"][i:i+window]) for i in range(0, size, window)] vol = [sum(result["vol"][i:i+window]) for i in range(0, size, window)]
close_df = pd.DataFrame(close) close_df = pd.DataFrame(close)
ma3_list = close_df.rolling(window=3).mean().fillna(close[0]).values.tolist() ma2_list = close_df.rolling(window=2).mean().fillna(close[0]).values.tolist()
ma3 = [item[0] for item in ma3_list] ma2 = [item[0] for item in ma2_list]
ma5_list = close_df.rolling(window=5).mean().fillna(close[0]).values.tolist() ma5_list = close_df.rolling(window=5).mean().fillna(close[0]).values.tolist()
ma5 = [item[0] for item in ma5_list] ma5 = [item[0] for item in ma5_list]
ma10_list = close_df.rolling(window=10).mean().fillna(close[0]).values.tolist() ma10_list = close_df.rolling(window=10).mean().fillna(close[0]).values.tolist()
@@ -538,7 +538,7 @@ class HTS:
upper_temp = [upper[i] for i in range(size) if i % window == 0] upper_temp = [upper[i] for i in range(size) if i % window == 0]
lower_temp = [lower[i] for i in range(size) if i % window == 0] lower_temp = [lower[i] for i in range(size) if i % window == 0]
temp = {"Date": point_temp, "Open": open, "High": high, "Low": low, "Close": close, "Volume": vol, "ma3": ma3, "ma5": ma5, "ma10": ma10, "ma15": ma15, "ma20": ma20} temp = {"Date": point_temp, "Open": open, "High": high, "Low": low, "Close": close, "Volume": vol, "ma2": ma2, "ma5": ma5, "ma10": ma10, "ma15": ma15, "ma20": ma20}
data = pd.DataFrame(temp) data = pd.DataFrame(temp)
df_final_time = pd.DatetimeIndex(point_temp) df_final_time = pd.DatetimeIndex(point_temp)
data.index = df_final_time data.index = df_final_time
@@ -552,7 +552,7 @@ class HTS:
data['Low'] = pd.to_numeric(data['Low']) data['Low'] = pd.to_numeric(data['Low'])
data['Close'] = pd.to_numeric(data['Close']) data['Close'] = pd.to_numeric(data['Close'])
data['Volume'] = pd.to_numeric(data['Volume']) data['Volume'] = pd.to_numeric(data['Volume'])
data['ma3'] = pd.to_numeric(data['ma3']) data['ma2'] = pd.to_numeric(data['ma2'])
data['ma5'] = pd.to_numeric(data['ma5']) data['ma5'] = pd.to_numeric(data['ma5'])
data['ma10'] = pd.to_numeric(data['ma10']) data['ma10'] = pd.to_numeric(data['ma10'])
data['ma15'] = pd.to_numeric(data['ma15']) data['ma15'] = pd.to_numeric(data['ma15'])
@@ -578,17 +578,17 @@ class HTS:
sell_check = go.Scatter(x=data['Date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_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=upper, name="upper", line_color='#8B4513') bolinger_upper = go.Scatter(x=data['Date'], y=upper, name="upper", line_color='#8B4513')
bolinger_lower = go.Scatter(x=data['Date'], y=lower, name="lower", line_color='#8B4513') bolinger_lower = go.Scatter(x=data['Date'], y=lower, name="lower", line_color='#8B4513')
ma3 = go.Scatter(x=data['Date'], y=data['ma3'], name="ma3", line_color='#F43B86') ma2 = go.Scatter(x=data['Date'], y=data['ma2'], name="ma2", line_color='#FF0000')
ma5 = go.Scatter(x=data['Date'], y=data['ma5'], name="ma5", line_color='#6D9886') ma5 = go.Scatter(x=data['Date'], y=data['ma5'], name="ma5", line_color='#F43B86')
ma10 = go.Scatter(x=data['Date'], y=data['ma10'], name="ma10", line_color='#406343') ma10 = go.Scatter(x=data['Date'], y=data['ma10'], name="ma10", line_color='#F0A500')
ma15 = go.Scatter(x=data['Date'], y=data['ma15'], name="ma15", line_color='#14279B') ma15 = go.Scatter(x=data['Date'], y=data['ma15'], name="ma15", line_color='#14279B')
ma20 = go.Scatter(x=data['Date'], y=data['ma20'], name="ma20", line_color='#212121') ma20 = go.Scatter(x=data['Date'], y=data['ma20'], name="ma20", 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') 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')
# 그래프를 그린다. # 그래프를 그린다.
fig = go.Figure(data=[candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check, ma3, ma5, ma10, ma15, ma20]) fig = go.Figure(data=[candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check, ma2, ma5, ma10, ma15, ma20])
fig.update_layout(title=given_day + "_2x") fig.update_layout(title=given_day + "_2x")
fig.show() fig.show()
return return
@@ -598,6 +598,11 @@ class HTS:
high = data["High"] high = data["High"]
close = data["Close"] close = data["Close"]
open = data["Open"] open = data["Open"]
ma2 = data["ma2"]
ma5 = data["ma5"]
ma10 = data["ma10"]
ma15 = data["ma15"]
ma20 = data["ma20"]
# 살 시점인지 체크 # 살 시점인지 체크
# 볼린저밴드 하단에 연속으로 같은 가격이 왔을 때, # 볼린저밴드 하단에 연속으로 같은 가격이 왔을 때,
@@ -605,20 +610,28 @@ class HTS:
check = False check = False
buy_line = [-1 for i in range(len(lower))] buy_line = [-1 for i in range(len(lower))]
for i in range(3, len(lower)): for i in range(3, len(lower)):
# 하락 추세에서는 매수하지 않는다.
if ma2[i] < ma5[i] < ma10[i]:
continue
for j in range(i-3, i): for j in range(i-3, i):
if (low[j] < lower[j]) and (low[i] < lower[i] and low[j] == low[i]): if (low[j] < lower[j]) and (low[i] < lower[i] and low[j] == low[i]):
#buy_line[i] = low[i] #buy_line[i] = low[i]
check = True check = True
break break
if check and i < len(lower) - 1: if check and i < len(lower) - 1:
buy_line[i+1] = low[i] + 5 buy_line[i+1] = low[i] + 5
check = False check = False
if low[i-2] < lower[i-2] and low[i-1] < lower[i-1] and low[i] < open[i] == close[i] < high[i] and open[i] - low[i] == high [i] - open[i]: if low[i-2] < lower[i-2] and low[i-1] < lower[i-1] and low[i] < open[i] == close[i] < high[i] and open[i] - low[i] == high [i] - open[i]:
if not (open[i-2] < close[i-2] and open[i-1] < close[i-1]) and not (open[i-2] == close[i-2] or open[i-1] == close[i-1]): if not (open[i-2] < close[i-2] and open[i-1] < close[i-1]) and not (open[i-2] == close[i-2] or open[i-1] == close[i-1]):
buy_line[i+1] = high[i] buy_line[i+1] = high[i]
# 2일과 5일선이 10일 선 위로 올라오면 매수한다.
if (ma2[i-1] < ma10[i-1] and ma5[i-1] < ma10[i-1]) and (ma10[i] < ma5[i] < ma2[i]):
buy_line[i+1] = low[i] + 5
# 팔 시점 체크 # 팔 시점 체크
# 산 가격에 5원 위로 매도를 건다. # 산 가격에 5원 위로 매도를 건다.
sell_line = [-1 for i in range(len(lower))] sell_line = [-1 for i in range(len(lower))]
@@ -799,11 +812,11 @@ if __name__ == "__main__":
#hts.currentStock(stock_code) #hts.currentStock(stock_code)
#hts.printStockData(stock_code, given_day) #hts.printStockData(stock_code, given_day)
#given_days = ['20210909','20210910','20210913','20210914','20210915','20210916','20210917','20210923','20210924','20210927','20210928','20210929'] given_days = ['20210909','20210910','20210913','20210914','20210915','20210916','20210917','20210923','20210924','20210927','20210928','20210929']
#given_days = ['20210929'] #given_days = ['20210929']
#for given_day in given_days: for given_day in given_days:
# hts.simulate(stock_code, given_day) hts.simulate(stock_code, given_day)
hts.buyRealTime(stock_code, given_day) #hts.buyRealTime(stock_code, given_day)
print ("done...") print ("done...")