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dosangyoon
2021-10-07 21:00:44 +09:00
parent af3676dea4
commit c6254cbe12
3 changed files with 129 additions and 82 deletions
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110
hts/HTS.py
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@@ -1,10 +1,10 @@
import win32com.client
#import win32com.client
import time
import os
from datetime import datetime, timedelta
import pandas as pd
from enum import Enum
#import plotly.graph_objects as go
import plotly.graph_objects as go
from stockpredictor.analysis.Common import Common
# enum 주문 상태 세팅용
@@ -517,16 +517,24 @@ class HTS:
vol = result["vol"]
close_df = pd.DataFrame(close)
avg5_list = close_df.rolling(window=3).mean().fillna(close[0]).values.tolist()
avg1_list = close_df.rolling(window=1).mean().fillna(close[0]).values.tolist()
avg1 = [item[0] for item in avg1_list]
avg2_list = close_df.rolling(window=2).mean().fillna(close[0]).values.tolist()
avg2 = [item[0] for item in avg2_list]
avg5_list = close_df.rolling(window=5).mean().fillna(close[0]).values.tolist()
avg5 = [item[0] for item in avg5_list]
avg20_list = close_df.rolling(window=10).mean().fillna(close[0]).values.tolist()
avg10_list = close_df.rolling(window=10).mean().fillna(close[0]).values.tolist()
avg10 = [item[0] for item in avg10_list]
avg20_list = close_df.rolling(window=20).mean().fillna(close[0]).values.tolist()
avg20 = [item[0] for item in avg20_list]
avg60_list = close_df.rolling(window=20).mean().fillna(close[0]).values.tolist()
avg30_list = close_df.rolling(window=30).mean().fillna(close[0]).values.tolist()
avg30 = [item[0] for item in avg30_list]
avg40_list = close_df.rolling(window=40).mean().fillna(close[0]).values.tolist()
avg40 = [item[0] for item in avg40_list]
avg50_list = close_df.rolling(window=50).mean().fillna(close[0]).values.tolist()
avg50 = [item[0] for item in avg50_list]
avg60_list = close_df.rolling(window=60).mean().fillna(close[0]).values.tolist()
avg60 = [item[0] for item in avg60_list]
avg120_list = close_df.rolling(window=30).mean().fillna(close[0]).values.tolist()
avg120 = [item[0] for item in avg120_list]
avg240_list = close_df.rolling(window=40).mean().fillna(close[0]).values.tolist()
avg240 = [item[0] for item in avg240_list]
upper, lower = [], []
for i in range(len(upper_df)):
@@ -539,7 +547,7 @@ class HTS:
point_temp = result["time"]
temp = {"Date": point_temp, "Open": open, "High": high, "Low": low, "Close": close, "Volume": vol, "avg5": avg5, "avg20": avg20, "avg60": avg60, "avg120": avg120, "avg240": avg240}
temp = {"Date": point_temp, "Open": open, "High": high, "Low": low, "Close": close, "Volume": vol, "avg1": avg1, "avg2": avg2, "avg5": avg5, "avg10": avg10, "avg20": avg20, "avg30": avg30, "avg40": avg40, "avg50": avg50, "avg60": avg60}
data = pd.DataFrame(temp)
df_final_time = pd.DatetimeIndex(point_temp)
data.index = df_final_time
@@ -556,11 +564,15 @@ class HTS:
data['Low'] = pd.to_numeric(data['Low'])
data['Close'] = pd.to_numeric(data['Close'])
data['Volume'] = pd.to_numeric(data['Volume'])
data['avg1'] = pd.to_numeric(data['avg1'])
data['avg2'] = pd.to_numeric(data['avg2'])
data['avg5'] = pd.to_numeric(data['avg5'])
data['avg10'] = pd.to_numeric(data['avg10'])
data['avg20'] = pd.to_numeric(data['avg20'])
data['avg30'] = pd.to_numeric(data['avg30'])
data['avg40'] = pd.to_numeric(data['avg40'])
data['avg50'] = pd.to_numeric(data['avg50'])
data['avg60'] = pd.to_numeric(data['avg60'])
data['avg120'] = pd.to_numeric(data['avg120'])
data['avg240'] = pd.to_numeric(data['avg240'])
buy_colors = []
for i in range(len(buy_line)):
@@ -582,17 +594,21 @@ 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))
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')
avg5 = go.Scatter(x=data['Date'], y=data['avg5'], name="avg5", line_color='#FF0000')
avg20 = go.Scatter(x=data['Date'], y=data['avg20'], name="avg20", line_color='#F43B86')
avg60 = go.Scatter(x=data['Date'], y=data['avg60'], name="avg60", line_color='#F0A500')
avg120 = go.Scatter(x=data['Date'], y=data['avg120'], name="avg120", line_color='#14279B')
avg240 = go.Scatter(x=data['Date'], y=data['avg240'], name="avg240", line_color='#000000')
avg1 = go.Scatter(x=data['Date'], y=data['avg1'], name="avg1", line_color='#FF0000')
avg2 = go.Scatter(x=data['Date'], y=data['avg2'], name="avg2", line_color='#A200FF')
avg5 = go.Scatter(x=data['Date'], y=data['avg5'], name="avg5", line_color='#0800FF')
avg10 = go.Scatter(x=data['Date'], y=data['avg10'], name="avg10", line_color='#FF7C00')
avg20 = go.Scatter(x=data['Date'], y=data['avg20'], name="avg20", line_color='#00AAFF')
avg30 = go.Scatter(x=data['Date'], y=data['avg30'], name="avg30", line_color='#FFD100')
avg40 = go.Scatter(x=data['Date'], y=data['avg40'], name="avg40", line_color='#A600FF')
avg50 = go.Scatter(x=data['Date'], y=data['avg50'], name="avg50", line_color='#FF00E0')
avg60 = go.Scatter(x=data['Date'], y=data['avg60'], name="avg60", 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')
# 그래프를 그린다.
fig = go.Figure(data=[candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check, avg5, avg20, avg60, avg120, avg240])
fig = go.Figure(data=[candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check, avg1, avg2, avg5, avg10, avg20, avg30, avg40, avg50, avg60])
fig.update_layout(title=stock_code + "_" + given_day)
fig.show()
return
@@ -772,6 +788,7 @@ class HTS:
bsLine['sell'] = [-1 for i in range(size)]
i = size - 1
"""
status = self.checkStatus(STOCK, i)
count_1 = 0
# if "GOLDEN#2_" in status: count_1 += 1
@@ -816,7 +833,12 @@ class HTS:
if count_0 > 0:
bsLine['buy'][i] = 0
bsLine['sell'][i] = STOCK[i]['close'] + 5
"""
if STOCK[i]['low'] < lower[i]:
bsLine['buy'][i] = STOCK[i]['close'] - 5
if STOCK[i]['close'] > upper[i]:
bsLine['sell'][i] = STOCK[i]['close'] + 5
return bsLine['buy'][i], bsLine['sell'][i]
@@ -824,13 +846,14 @@ class HTS:
size = len(data["Close"])
STOCK = []
for i in range(size):
STOCK.append({'volume': data['Volume'][i], 'close': data["Close"][i], 'open': data["Open"][i], 'high': data["High"][i], 'low': data["Low"][i], 'avg5': data["avg5"][i], 'avg20': data["avg20"][i], 'avg60': data["avg60"][i], 'avg120': data["avg120"][i], 'avg240': data["avg240"][i]})
STOCK.append({'volume': data['Volume'][i], 'close': data["Close"][i], 'open': data["Open"][i], 'high': data["High"][i], 'low': data["Low"][i], 'avg5': data["avg2"][i], 'avg20': data["avg5"][i], 'avg60': data["avg10"][i], 'avg120': data["avg20"][i], 'avg240': data["avg30"][i]})
bsLine = {}
bsLine['buy'] = [-1 for i in range(len(lower))]
bsLine['sell'] = [-1 for i in range(len(lower))]
for i in range(5, size-5):
"""
status = self.checkStatus(STOCK, i)
count_1 = 0
#if "GOLDEN#2_" in status: count_1 += 1
@@ -876,7 +899,12 @@ class HTS:
# bsLine['sell'][i + 2] = STOCK[i]['close'] + 5
if data["avg60"][i - 1] > data["avg60"][i]:
bsLine['sell'][i] = STOCK[i]['close']
"""
if STOCK[i]['low'] < lower[i]:
bsLine['buy'][i] = STOCK[i]['close'] - 5
if STOCK[i]['close'] > upper[i]:
bsLine['sell'][i] = STOCK[i]['close'] + 5
return bsLine
@@ -911,7 +939,7 @@ class HTS:
def buyRealTime(self, stock_code, given_day):
PREVIOUS_PRICE = 0
BUY_COUNT = 200
BUY_COUNT = 100
TOTAL_BUY_AMT = 0
logFp = open(given_day+".log", "w")
@@ -927,13 +955,12 @@ class HTS:
"low": [],
"vol": []}
avg60_1 = 0
avg60_2 = 0
final_price = 0
print ("START...")
while datetime.strptime(given_day + " 083000", '%Y%m%d %H%M%S') < datetime.now() < datetime.strptime(given_day + " 151600", '%Y%m%d %H%M%S'):
while datetime.strptime(given_day + " 083000", '%Y%m%d %H%M%S') < datetime.now() < datetime.strptime(given_day + " 15200", '%Y%m%d %H%M%S'):
second = datetime.now().strftime('%Y%m%d %H%M%S')
if datetime.now() < datetime.strptime(given_day + " 144000", '%Y%m%d %H%M%S'):
if second in timecheck and not timecheck[second]:
print("TIMECHECK", second)
logFp.write("%s,%s,\n" %("TIMECHECK", second))
@@ -944,8 +971,6 @@ class HTS:
# 분석을 통해서 볼린저밴드 상/하단을 계산한다.
data, upper, lower = self.analyze(result)
avg60_2 = data['avg60'][len(data['avg60']) - 2]
avg60_1 = data['avg60'][len(data['avg60']) - 1]
final_price = data["Close"][len(data["Close"])- 1]
# 사야 할 시점/가격과 팔아야 할 시점/가격을 체크한다.
bs_buy_price, bs_sell_price = self.checkTransaction_Realtime(data, upper, lower)
@@ -953,16 +978,16 @@ class HTS:
if bs_buy_price > 0:
if PREVIOUS_PRICE > 0:
if PREVIOUS_PRICE > bs_buy_price:
if BUY_COUNT > 240:
BUY_COUNT = 240
if BUY_COUNT <= 140:
if BUY_COUNT > 140:
BUY_COUNT = 140
if BUY_COUNT <= 40:
BUY_COUNT = 40
BUY_COUNT += 10
elif PREVIOUS_PRICE < bs_buy_price:
if BUY_COUNT > 250:
BUY_COUNT = 260
if BUY_COUNT <= 150:
if BUY_COUNT > 150:
BUY_COUNT = 160
if BUY_COUNT <= 50:
BUY_COUNT = 60
BUY_COUNT -= 10
PREVIOUS_PRICE = bs_buy_price
@@ -972,15 +997,17 @@ class HTS:
if TOTAL_BUY_AMT < 7000000:
self.requestOrder("2", stock_code, BUY_COUNT , bs_buy_price)
## 매도 주문 (아래 잔고를 체크해서 매도를 호출하는 것으로 시도한다.)
#time.sleep(60)
#self.requestOrder("1", stock_code, BUY_COUNT , price + 5)
print("BUY", second, bs_buy_price)
logFp.write("%s,%s, %d\n" % ("BUY", second, bs_buy_price))
logFp.flush()
# 가져온 만큼 데이터를 누적해서 파일로 작성한다.
self.write(given_day, result)
if bs_sell_price > 0:
jangoDic = self.requstJango()
if jangoDic and len(jangoDic.keys()) > 0:
for code in jangoDic:
TOTAL_BUY_AMT = jangoDic[code]['매입금액']
if jangoDic[code]['매도가능'] > 0:
self.requestOrder("1", stock_code, jangoDic[code]['매도가능'], bs_sell_price)
timecheck[second] = True
else:
@@ -988,11 +1015,7 @@ class HTS:
logFp.write("%s,%s,\n" % ("NONE", second))
logFp.flush()
# 60일 선이 꺾여서 하락 중일 경우만 바로 매도를 한다.
if (((avg60_1 != 0 and avg60_2 != 0) and avg60_2 > avg60_1) or
(datetime.now() >= datetime.strptime(given_day + " 151500", '%Y%m%d %H%M%S')) or
(datetime.now() < datetime.strptime(given_day + " 090503", '%Y%m%d %H%M%S'))):
else:
# 만약 잔고가 있으면 장부가보다 5원 높게 매도한다.
jangoDic = self.requstJango()
if jangoDic and len(jangoDic.keys()) > 0:
@@ -1015,6 +1038,7 @@ class HTS:
else:
# 장부가의 마지막 자리수가 7,8,9 라면 (2097, 2098, 2099 -> 2105 에 매도)
self.requestOrder("1", stock_code, jangoDic[code]['매도가능'], sell_price + 15)
break
time.sleep(0.9)
@@ -1038,11 +1062,13 @@ if __name__ == "__main__":
#hts.getChartData(stock_codes)
#hts.currentStock(stock_codes)
#for given_day in given_days:
#hts.writeStockData(stock_codes, given_day)
#for stock_code in stock_codes:
#hts.simulate(stock_code, given_day)
given_day = datetime.today().strftime('%Y%m%d')
hts.writeStockData(stock_codes, given_day)
#hts.writeStockData(stock_codes, given_day)
hts.simulate(stock_codes[0], given_day)
#hts.buyRealTime(stock_codes[0], given_day)
print ("done...")

35
hts/HTS_5min.py
View File

@@ -520,10 +520,16 @@ class HTS:
ma5 = [item[0] for item in ma5_list]
ma10_list = close_df.rolling(window=10).mean().fillna(close[0]).values.tolist()
ma10 = [item[0] for item in ma10_list]
ma15_list = close_df.rolling(window=15).mean().fillna(close[0]).values.tolist()
ma15 = [item[0] for item in ma15_list]
ma20_list = close_df.rolling(window=20).mean().fillna(close[0]).values.tolist()
ma20 = [item[0] for item in ma20_list]
ma30_list = close_df.rolling(window=30).mean().fillna(close[0]).values.tolist()
ma30 = [item[0] for item in ma30_list]
ma40_list = close_df.rolling(window=40).mean().fillna(close[0]).values.tolist()
ma40 = [item[0] for item in ma40_list]
ma50_list = close_df.rolling(window=50).mean().fillna(close[0]).values.tolist()
ma50 = [item[0] for item in ma50_list]
ma60_list = close_df.rolling(window=60).mean().fillna(close[0]).values.tolist()
ma60 = [item[0] for item in ma60_list]
upper, lower = [], []
for i in range(len(upper_df)):
@@ -538,7 +544,7 @@ class HTS:
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]
temp = {"Date": point_temp, "Open": open, "High": high, "Low": low, "Close": close, "Volume": vol, "ma2": ma2, "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, "ma20": ma20, "ma30": ma30, "ma40": ma40, "ma50": ma50, "ma60": ma60}
data = pd.DataFrame(temp)
df_final_time = pd.DatetimeIndex(point_temp)
data.index = df_final_time
@@ -558,8 +564,11 @@ class HTS:
data['ma2'] = pd.to_numeric(data['ma2'])
data['ma5'] = pd.to_numeric(data['ma5'])
data['ma10'] = pd.to_numeric(data['ma10'])
data['ma15'] = pd.to_numeric(data['ma15'])
data['ma20'] = pd.to_numeric(data['ma20'])
data['ma30'] = pd.to_numeric(data['ma30'])
data['ma40'] = pd.to_numeric(data['ma40'])
data['ma50'] = pd.to_numeric(data['ma50'])
data['ma60'] = pd.to_numeric(data['ma60'])
buy_colors = []
for i in range(len(buy_line)):
@@ -584,14 +593,17 @@ class HTS:
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='#F43B86')
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')
ma20 = go.Scatter(x=data['Date'], y=data['ma20'], name="ma20", line_color='#000000')
ma30 = go.Scatter(x=data['Date'], y=data['ma30'], name="ma30", line_color='#14279B')
ma40 = go.Scatter(x=data['Date'], y=data['ma40'], name="ma40", line_color='#14279B')
ma50 = go.Scatter(x=data['Date'], y=data['ma50'], name="ma50", line_color='#14279B')
ma60 = go.Scatter(x=data['Date'], y=data['ma60'], name="ma60", line_color='#14279B')
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.
fig = go.Figure(data=[candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check, ma2, ma10, ma15, ma20])
fig = go.Figure(data=[candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check, ma2, ma10, ma20, ma30, ma40, ma50, ma60])
fig.update_layout(title=given_day + "_2x")
fig.show()
return
@@ -602,9 +614,13 @@ class HTS:
close = data["Close"]
open = data["Open"]
ma2 = data["ma2"]
ma5 = data["ma5"]
ma10 = data["ma10"]
ma15 = data["ma15"]
ma20 = data["ma20"]
ma30 = data["ma30"]
ma40 = data["ma40"]
ma50 = data["ma50"]
ma60 = data["ma60"]
bsLine = {}
bsLine['buy'] = [-1 for i in range(len(lower))]
@@ -823,8 +839,11 @@ class HTS:
ma2 = data["ma2"]
ma5 = data["ma5"]
ma10 = data["ma10"]
ma15 = data["ma15"]
ma20 = data["ma20"]
ma30 = data["ma30"]
ma40 = data["ma40"]
ma50 = data["ma50"]
ma60 = data["ma60"]
# 살 시점인지 체크
# 볼린저밴드 하단에 연속으로 같은 가격이 왔을 때,

2
hts/timecheck.csv
View File

@@ -1,4 +1,6 @@
time, check
090303,False
090403,False
090503,False
090603,False
090703,False
1 time check
2 090303 False
3 090403 False
4 090503 False
5 090603 False
6 090703 False