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dsyoon
2021-02-18 08:10:56 +09:00
parent 9af08dbee2
commit 2f6b33f8f2
4 changed files with 152 additions and 37 deletions
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84
stockpredictor/analysis/Analyzer.py
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@@ -12,6 +12,8 @@ import sqlite3
from datetime import datetime
from matplotlib import rc
import math
rc('font', family='AppleGothic')
plt.rcParams['axes.unicode_minus'] = False
@@ -71,26 +73,14 @@ class Analyzer:
while result != None:
data = json.loads(result[2])
self.fnguide[result[0]] = True
if (year1 in data):
if (data[year1]['영업이익'] > 0 and data[year1]['당기순이익'] > 0):
self.fnguide[result[0]] = True
if (year2 in data):
if (data[year2]['영업이익'] > 0 and data[year2]['당기순이익'] > 0):
self.fnguide[result[0]] = True
if (year3 in data):
if (data[year3]['영업이익'] > 0 and data[year3]['당기순이익'] > 0):
self.fnguide[result[0]] = True
else:
self.fnguide[result[0]] = False
else:
if (data[year1]['영업이익'] > data[year2]['영업이익']):
self.fnguide[result[0]] = True
else:
self.fnguide[result[0]] = False
else:
if (year1 in data and year2 in data and year3 in data):
if (data[year1]['영업이익'] < 0 and data[year2]['영업이익'] < 0 and data[year3]['영업이익'] < 0):
# 3년 연속 영업이익이 적자이면 매수하지 않는다.
self.fnguide[result[0]] = False
if (data[year1]['영업이익'] < -100):
# 전년 영억적자가 100억 이상이면 매수하지 않는다.
self.fnguide[result[0]] = False
else:
self.fnguide[result[0]] = False
rowid += 1
cursor.execute('SELECT * FROM fnguide WHERE rowid=?', (rowid,))
@@ -314,6 +304,8 @@ class Analyzer:
1) 상향이고 30을 돌파하면 매수,
2) rsi가 상향이고 40을 돌파하면 매수,
3) rsi가 상향이고 70을 돌파하면 단기매수,
시장 보다 강한 종목이란 (https://biz.sbs.co.kr/article/10000976754)
"""
i = last_index
@@ -343,14 +335,30 @@ class Analyzer:
if stochastic_score > 0:
return True, buy_price, stochastic_score
"""
if STOCHASTIC[i]['slow_k'] < 10 and self.common.checkLongYangBongAfterUmBong(STOCK, i):
return 'STOCHASTIC_YANGBONG', buy_price
if STOCHASTIC[i]['slow_k'] < 10:
return 'STOCHASTIC', buy_price
if self.common.checkLongYangBongAfterUmBong(STOCK, i):
return 'YANGBONG', buy_price
return "", buy_price
status = ""
if STOCK[i]['volume'] > 100000 and STOCK[i]['close'] > 1000:
# 거래량이 10만 이상이고, 종가가 1천원 이상인지 체크 (https://happpy-rich.tistory.com/94)
if self.common.check_on_120_daysLine(STOCK, i):
# 특히 종목이 120일선을 뚫은 후 60일선이 상승세인지를 확인한다. (https://biz.sbs.co.kr/article/10000976754)
if STOCHASTIC[i]['slow_k'] < 70:
status += '120_'
if self.common.check_on_60_daysLine(STOCK, i):
if STOCHASTIC[i]['slow_k'] < 70:
status += '60_'
if self.common.check_on_20_daysLine(STOCK, i):
if STOCHASTIC[i]['slow_k'] < 70:
status += '20_'
if STOCHASTIC[i]['slow_k'] < 10:
# 스토캐스틱이 10 이하였다면,
status += 'STOCHASTIC_'
if self.common.checkLongYangBongAfterUmBong(STOCK, i):
# 어제 음봉 이후 장대양봉이었다면,
status += 'YANGBONG_'
return status, buy_price
def analyzeToFile(self, outFileName):
conn = sqlite3.connect(self.inFileName)
@@ -403,14 +411,28 @@ class Analyzer:
while result != None:
item_code = result[0]
item_name = result[1]
"""
if (item_code in self.fnguide and not self.fnguide[item_code]):
# 부실 기업은 매수하지 않고 그냥 넘긴다.
# kospi 지수와 kosdak 지수도 그냥 넘긴다.
if ((item_code in self.fnguide and not self.fnguide[item_code]) or (item_code == "KOSPI" or item_code == "KOSDAK")):
rowid += 1
# 다음 종목을 가져옴
cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,))
result = cursor.fetchone()
continue
"""
stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2]), "MACD": json.loads(result[3]), "STOCHASTIC": json.loads(result[4]), "ICHIMOKU": json.loads(result[5]), "RSI": json.loads(result[6])}
result_3 = result[3]
result_4 = result[4]
result_5 = result[5]
result_6 = result[6]
if result[3] != result[3]: result_3 = result[3].replace("NaN", "0")
if result[4] != result[4]: result_4 = result[4].replace("NaN", "0")
if result[5] != result[5]: result_5 = result[5].replace("NaN", "0")
if result[6] != result[6]: result_6 = result[6].replace("NaN", "0")
if rowid == 2435:
print (1)
stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2]), "MACD": json.loads(result_3), "STOCHASTIC": json.loads(result_4), "ICHIMOKU": json.loads(result_5), "RSI": json.loads(result_6)}
last_index = self.get_last_index(stock)
STOCK = stock['PRICE']
@@ -432,7 +454,7 @@ class Analyzer:
fileName = "%s/%s__%.3f__%.3f__%s.html" % (outPath, state, stochastic_score, rsi_score, item_name.replace(" ", ""))
po.write_html(fig, file=fileName, auto_open=False)
else:
if RSI[last_index]['rsi_buy'] == 1 and STOCK[last_index]['volume'] > 10000:
if RSI[last_index]['rsi_buy'] == 1 and STOCK[last_index]['volume'] > 100000:
fig = self.draw(stock)
title = "%s (%s) buy_price (%d), stochastic(%.3f), rsi(%.3f), macd(%.3f), ichimoku(%d)) 차트"%(item_name, item_code, buy_price, stochastic_score, rsi_score, macd_score, ichimoku_score)
fig['layout'].update(title=title)

27
stockpredictor/analysis/Common.py
View File

@@ -131,4 +131,31 @@ class Common:
if stock[i]['open'] < stock[i]['close'] and stock[i]['close'] == stock[i]['high']: # 오늘 장대양봉인지 체크
if stock[i-1]['volume']*2 < stock[i]['volume']: # 어제 거래량 보다 두배 이상일 때
return True
return False
def check_on_20_daysLine(self, stock, i):
# 20일선 돌파를 체크할 때는 5일선 < 20일선 < 120일선 < 60일선 이어야 하며, 5일선은 상승중이어야 한다. (삼성전자 2020년 4월 6일)
if i > 0:
if stock[i-1]['avg20'] > stock[i-1]['close'] and stock[i]['avg20'] < stock[i]['close']:
if stock[i]['avg5'] < stock[i]['avg20'] < stock[i]['avg120'] < stock[i]['avg60']:
if stock[i-1]['avg5'] < stock[i]['avg5']:
return True
return False
def check_on_60_daysLine(self, stock, i):
# 60일선 돌파를 체크할 때는 20일선 < 5일선 < 60일 < 120일선 이어야 하며, 5일선과 20일선은 상승중이어야 한다. (삼성전자 2020년 5월 27일)
if i > 0:
if stock[i-1]['avg60'] > stock[i-1]['close'] and stock[i]['avg60'] < stock[i]['close']:
if stock[i]['avg20'] < stock[i]['avg5'] < stock[i]['avg60'] < stock[i]['avg120']:
if stock[i-1]['avg5'] < stock[i]['avg5'] and stock[i-1]['avg20'] < stock[i]['avg20']:
return True
return False
def check_on_120_daysLine(self, stock, i):
# 120일선 돌파를 체크할 때는 60일선이 상승 중이어야 한다.
if i > 0:
if stock[i-1]['avg120'] > stock[i-1]['close'] and stock[i]['avg120'] < stock[i]['close']:
if stock[i-1]['avg5'] < stock[i]['avg5'] and stock[i-1]['avg20'] < stock[i]['avg20'] and stock[i-1]['avg60'] < stock[i]['avg60']:
return True
return False

10
stockpredictor/crawler/toSQLite/Crawler.py
View File

@@ -19,8 +19,6 @@ print("[KOSPI 상장기업 재무제표 다운로드]")
crawler.crawl_fnguide(inFnguideFileName)
"""
crawler = MetaCrawler()
print("\n[환율 (USD, JPY, EUR, CNY), 원유 (WTI), 국제금]")
inFileName = PROJECT_HOME + '/resources/meta_1.db'
@@ -44,6 +42,14 @@ crawler = StockCrawler()
crawler.crawl_etf_stocks(inFileName)
crawler.crawl_stocks(inFileName)
print("\n[지수 저장]")
kospiFileName = PROJECT_HOME + '/resources/kospi.tsv'
kosdakFileName = PROJECT_HOME + '/resources/kosdak.tsv'
outFileName = PROJECT_HOME + '/resources/stock.db'
crawler = StockCrawler()
crawler.saveIndex("KOSPI", kospiFileName, outFileName)
crawler.saveIndex("KOSDAK", kosdakFileName, outFileName)
print("\n[종목 분석]")
# S: 분석까지 진행
inFileName = PROJECT_HOME + '/resources/stock.db'

68
stockpredictor/crawler/toSQLite/StockCrawler.py
View File

@@ -223,12 +223,10 @@ class StockCrawler:
###print (df.head())
# 한글로 된 컬럼명을 영어로 바꿔줌
df = df.rename(columns={'날짜': 'date', '종가': 'close', '전일비': 'diff', '시가': 'open', '고가': 'high', '저가': 'low',
'거래량': 'volume'})
df = df.rename(columns={'날짜': 'date', '종가': 'close', '전일비': 'diff', '시가': 'open', '고가': 'high', '저가': 'low', '거래량': 'volume'})
# 데이터의 타입을 int형으로 바꿔줌
df[['close', 'diff', 'open', 'high', 'low', 'volume']] = df[
['close', 'diff', 'open', 'high', 'low', 'volume']].astype(int)
df[['close', 'diff', 'open', 'high', 'low', 'volume']] = df[['close', 'diff', 'open', 'high', 'low', 'volume']].astype(int)
# 컬럼명 'date'의 타입을 date로 바꿔줌
df['date'] = pd.to_datetime(df['date'])
@@ -350,3 +348,65 @@ class StockCrawler:
cursor.execute("UPDATE " + tableName + " SET PRICE=? WHERE CODE=?", (text, stock["CODE"]))
return
def saveIndex(self, code, inFileName, outFileName):
tableName = 'stock'
conn = sqlite3.connect(outFileName)
cursor = conn.cursor()
cursor.execute("CREATE TABLE IF NOT EXISTS " + tableName + " (CODE text PRIMARY KEY, NAME text, PRICE text)")
stock = {"NAME": code, "CODE": code, "PRICE": []}
lastDay = ""
cursor.execute('SELECT * FROM ' + tableName + ' WHERE CODE=?', (stock["CODE"],))
result = cursor.fetchone()
if result != None:
stock["PRICE"] = json.loads(result[2])
lastDay = stock["PRICE"][len(stock["PRICE"]) - 1]["DATE"]
with open(inFileName, "r", encoding="utf-8") as inFp:
for line in inFp:
line = line.strip()
if line[0] == "#":
continue
arr = line.split("\t")
if arr[0] == lastDay:
cursor.close()
conn.close()
return
price = {"DATE": arr[0], "close": float(arr[1]), "diff": float(arr[6].replace("%", "")), "open": float(arr[2]), "high": float(arr[3]), "low": float(arr[4]), "volume": 0}
price['avg3'] = 0
price['avg5'] = 0
price['avg7'] = 0
price['avg10'] = 0
price['avg20'] = 0
price['avg30'] = 0
price['avg60'] = 0
price['avg90'] = 0
price['avg100'] = 0
price['avg120'] = 0
price['avg150'] = 0
price['avg180'] = 0
price['avg200'] = 0
price['avg240'] = 0
stock["PRICE"].append(price)
stock["PRICE"] = sorted(stock["PRICE"], key=lambda x: x['DATE'])
self.get_moving_avg(stock)
text = json.dumps(stock['PRICE'], ensure_ascii=False)
cursor.execute('SELECT * FROM ' + tableName + ' WHERE CODE=?', (stock["CODE"],))
result = cursor.fetchone()
if result == None:
cursor.execute("INSERT INTO " + tableName + "(CODE, NAME, PRICE, MACD, STOCHASTIC, ICHIMOKU, RSI) VALUES(?, ?, ?, ?, ?, ?, ?)", (stock["CODE"], stock["NAME"], text, "[{}]", "[{}]", "[{}]", "[{}]"))
else:
cursor.execute("UPDATE " + tableName + " SET PRICE=?, MACD=?, STOCHASTIC=?, ICHIMOKU=?, RSI=? WHERE CODE=?", (text, "[{}]", "[{}]", "[{}]", "[{}]", stock["CODE"]))
conn.commit()
cursor.close()
conn.close()
return