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

init

Browse Source
This commit is contained in:
dosang.yoon
2022-06-26 23:58:57 +09:00
parent 5c1be31d03
commit c48bde70c8
6 changed files with 231 additions and 1472 deletions
Download Patch File Download Diff File Expand all files Collapse all files

194
hts/BuySellChecker.py
View File

@@ -2,6 +2,7 @@ import pandas as pd
from stockpredictor.analysis.Common import Common
from stockpredictor.analysis.Stochastic import Stochastic
from stockpredictor.analysis.RSI import RSI
from stockpredictor.analysis.MACD import MACD
class BuySellChecker:
@@ -13,6 +14,7 @@ class BuySellChecker:
self.common = Common()
self.stochastic = Stochastic()
self.rsi = RSI()
self.macd = MACD()
return
@@ -20,7 +22,7 @@ class BuySellChecker:
status = set()
# 정배열 체크
temp_status = self.common.check_RightArrange(STOCK, last_index)
temp_status = self.common.check_RightArrange(STOCK)
if temp_status != "":
status.add(temp_status)
@@ -183,60 +185,52 @@ class BuySellChecker:
def getPriceAndWeight1(self, data, i):
buy, weight, sell = -1, -1, -1
################
### 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]
"""
# 2. slow_k가 90이 넘으면 매도한다.
if data["slow_k"][i] >= 90:
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]:
if i >= 3:
################
### 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]
# 2. slow_k가 90이 넘으면 매도한다.
if data["slow_k"][i] > 90:
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 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]
##########################
### STOCHASTIC buy 분석 ###
##########################
if i < 40:
if data["low"][i] < data["lower"][i]+5:
if data["slow_k"][i-1] < 50 and data["slow_k"][i] < 55:
if data["slow_k"][i-1] < data["slow_d"][i-1] and data["slow_d"][i] < data["slow_k"][i] and data["slow_k"][i-1] < data["slow_k"][i]:
buy = data["low"][i]
else:
if data["low"][i] < data["lower"][i] + 5:
# 3. 2시 이후에는 최고가가 볼린져밴드 상단 위에 있으면 매도한다.
if i > 300 and data["high"][i] > data["upper"][i]:
sell = data["high"][i]
##########################
### buy 분석 ###
##########################
if data["low"][i] < data["lower"][i] + 5 and data["open"][i] <= data["close"][i]:
if data["slow_k"][i-1] < 30 and data["slow_k"][i] < 30:
if data["slow_k"][i-1] < data["slow_k"][i]:
buy = data["low"][i]
#############################
### STOCHASTIC weight 분석 ###
#############################
if data["slow_k"][i] in (0, 1, 2, 3):
weight = 1
if data["slow_k"][i] in (4, 5, 6, 7, 8):
weight = 1
elif data["slow_k"][i] in (9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20):
weight = 1
elif data["slow_k"][i] in (21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35):
weight = 1
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]
else:
buy = data["low"][i]
weight = 1
###################
### RSI buy 분석 ###
###################
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]
else:
buy = data["low"][i]
#############################
### STOCHASTIC weight 분석 ###
#############################
if data["slow_k"][i] in (0, 1, 2, 3):
weight = 1
if data["slow_k"][i] in (4, 5, 6, 7, 8):
weight = 1
elif data["slow_k"][i] in (9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20):
weight = 1
elif data["slow_k"][i] in (21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35):
weight = 1
return buy, weight, sell
@@ -301,63 +295,14 @@ class BuySellChecker:
return buy, weight, sell
def getPriceAndWeight_1minute(self, data, i):
def getPriceAndWeight3(self, data, i):
buy, weight, sell = -1, -1, -1
################
### 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["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]
# 3. 2시 이후에는 최고가가 볼린져밴드 상단 위에 있으면 매도한다.
if i > 300 and data["high"][i] > data["upper"][i]:
sell = data["high"][i]
##########################
### STOCHASTIC buy 분석 ###
##########################
if i < 40:
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 0 < now_slow:
if data["slow_k"][i] <= 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['avg3'][i] <= data['avg2'][i]:
if data["open"][i] < data["close"][i]:
buy = data["close"][i]
else:
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] <= 10:
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['avg3'][i] <= data['avg2'][i]:
if data["close"][i] < data["avg5"][i]:
buy = data["close"][i]
else:
buy = data["low"][i]
#############################
### STOCHASTIC weight 분석 ###
#############################
if data["slow_k"][i] in (0, 1, 2, 3):
weight = 1
if data["slow_k"][i] in (4, 5, 6, 7, 8):
weight = 1
elif data["slow_k"][i] in (9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20):
weight = 1
elif data["slow_k"][i] in (21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35):
weight = 1
# 381: 어제 날짜 데이터 개수
if i >= 381 + 5:
if data["macdo"][i] < 0 and data["macd"][i] < -5:
if data["macd"][i-3] > data["macd"][i-2] and data["macd"][i-2] > data["macd"][i-1] and data["macd"][i-1] < data["macd"][i]:
buy = data["close"][i]
return buy, weight, sell
@@ -370,8 +315,8 @@ class BuySellChecker:
vol = result["vol"]
close_df = pd.DataFrame(close)
avg2_list = close_df.rolling(window=2).mean().fillna(close[0]).values.tolist()
avg2 = [item[0] for item in avg2_list]
avg3_list = close_df.rolling(window=3).mean().fillna(close[0]).values.tolist()
avg3 = [item[0] for item in avg3_list]
avg5_list = close_df.rolling(window=5).mean().fillna(close[0]).values.tolist()
avg5 = [item[0] for item in avg5_list]
avg10_list = close_df.rolling(window=10).mean().fillna(close[0]).values.tolist()
@@ -382,8 +327,8 @@ class BuySellChecker:
avg60 = [item[0] for item in avg60_list]
df = pd.DataFrame(close)
max20 = df.rolling(window=10).mean()
stddev20 = df.rolling(window=10).std()
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
@@ -401,7 +346,7 @@ class BuySellChecker:
STOCK = []
for i in range(len(open)):
STOCK.append({'volume': vol[i], 'close': close[i], 'open': open[i], 'high': high[i], 'low': low[i],
'avg2': avg2[i], 'avg5': avg5[i],'avg10': avg10[i],'avg30': avg30[i],'avg60': avg60[i]})
'avg3': avg3[i], 'avg5': avg5[i],'avg10': avg10[i],'avg30': avg30[i],'avg60': avg60[i]})
# stochastic 계산
stochastic_df = self.stochastic.apply(STOCK, n=30, m=5, t=5)
@@ -410,6 +355,13 @@ class BuySellChecker:
slow_k = stochastic_df['slow_k'].values.tolist()
slow_d = stochastic_df['slow_d'].values.tolist()
# macd 계산
macd_df = self.macd.apply(STOCK, short=12, long=26, t=9)
macd_df = macd_df.fillna(100)
macd = macd_df['macd'].values.tolist()
macds = macd_df['macds'].values.tolist()
macdo = macd_df['macdo'].values.tolist()
# rsi 계산
rsi_df = self.rsi.apply(STOCK, period=30, window=5)
rsi_df = rsi_df.fillna(100)
@@ -418,10 +370,32 @@ class BuySellChecker:
temp = {"date": point_temp,
"open": open, "high": high, "low": low, "close": close, "volume": vol, "upper": upper, "lower": lower,
"avg2": avg2, "avg5": avg5, "avg10": avg10, "avg30": avg30, "avg60": avg60,
"fast_k": fast_k, "slow_k": slow_k, "slow_d": slow_d, "rsi": rsi, "rsis": rsis}
"avg3": avg3, "avg5": avg5, "avg10": avg10, "avg30": avg30, "avg60": avg60,
"macd": macd, "macds": macds, "macdo": macdo,
"fast_k": fast_k, "slow_k": slow_k, "slow_d": slow_d,
"rsi": rsi, "rsis": rsis}
data = pd.DataFrame(temp)
df_final_time = pd.DatetimeIndex(point_temp)
data.index = df_final_time
return data
return data
def checkTransaction(self, data, stock_code):
size = len(data["close"])
bsLine = {}
bsLine['buy'] = [-1 for i in range(size)]
bsLine['weight'] = [-1 for i in range(size)]
bsLine['sell'] = [-1 for i in range(size)]
for i in range(size):
if stock_code == "252670":
buy, weight, sell = self.getPriceAndWeight3(data, i)
else:
buy, weight, sell = self.getPriceAndWeight3(data, i)
bsLine['buy'][i] = buy
bsLine['weight'][i] = weight
bsLine['sell'][i] = sell
return bsLine