import time import os import math import sqlite3 from datetime import datetime, timedelta from hts.HTS import HTS from hts.OrderType import OrderType from hts.BuySellChecker import BuySellChecker from hts.OrderChecker import OrderChecker from stock.util.LabelChecker import LabelChecker from stock.util.TelegramBot import TelegramBot from stock.analysis.StockStatus import StockStatus class HTS_etf (HTS): RESOURCE_PATH = None stock_code = None buy_count = None orderChecker = None buySellChecker = None labelChecker = None bot = None stockStatus = None def __init__(self, RESOURCE_PATH): super().__init__(RESOURCE_PATH) self.RESOURCE_PATH = RESOURCE_PATH self.orderChecker = OrderChecker(self.RESOURCE_PATH, "ETF") self.buySellChecker = BuySellChecker() self.labelChecker = LabelChecker(RESOURCE_PATH) self.bot = TelegramBot() self.stockStatus = StockStatus(RESOURCE_PATH) return def connect2StockDB(self): self.conn_stock = sqlite3.connect(os.path.join(self.RESOURCE_PATH, "resources/stock.db")) self.cursor_stock = self.conn_stock.cursor() return def disconnectStockDB(self): self.cursor_stock.close() self.conn_stock.close() return def sellStocks(self, stock_code=None, bs_sell_price=None): check = False jangoDic = self.requstJango() if jangoDic and len(jangoDic.keys()) > 0: for code in jangoDic: if stock_code is not None: if code == "A"+stock_code and bs_sell_price is not None: if jangoDic[code]['매도가능'] > 0: if 2 < jangoDic[code]['평가손익']: self.requestOrder(OrderType.sell, code[1:], jangoDic[code]['매도가능'], bs_sell_price) self.bot.post(code, jangoDic[code]['종목명'], "SELL", bs_sell_price, jangoDic[code]['매도가능']) check = True else: continue else: if jangoDic[code]['매도가능'] > 0: if 3 < jangoDic[code]['평가손익']: # 3% 이상 시 수익 매도 currentStock = self.currentStock(code[1:]) self.requestOrder(OrderType.sell, code[1:], jangoDic[code]['매도가능'], currentStock['close']) self.bot.post(code, jangoDic[code]['종목명'], "SELL", currentStock['close'], jangoDic[code]['매도가능']) check = True return check def getSellingPrice(self, log_time, stock_code, final_price, without_loss=False): # final_price와 diff를 받으면, 해당 가격으로 그냥 매도한다는 의미 # final_price와 diff가 None이면 장부가와 final 중 max로 팔겠다는 의미 # final_price가 0이고 diff가 None이면 장부가로 팔겠다는 의미임 orderNum = None jangoDic = self.requstJango() if jangoDic and len(jangoDic.keys()) > 0: for code in jangoDic: if jangoDic[code]['매도가능'] > 0: if without_loss: if jangoDic[code]['장부가']*0.07 < jangoDic[code]['장부가'] - final_price: sell_price = jangoDic[code]['장부가'] if code == "A" + stock_code: orderNum = self.requestOrder(OrderType.sell, stock_code, jangoDic[code]['매도가능'], sell_price) return orderNum, log_time.strftime('%Y%m%d %H%M%S'), jangoDic[code]['매도가능'], sell_price else: max_price = max(jangoDic[code]['장부가'], final_price) sell_price = (int(max_price) - int(max_price) % 5) + 5 if code == "A"+stock_code: orderNum = self.requestOrder(OrderType.sell, stock_code, jangoDic[code]['매도가능'], sell_price) return orderNum, log_time.strftime('%Y%m%d %H%M%S'), jangoDic[code]['매도가능'], sell_price return orderNum, None, None, None def makeTickData(self, data, mins=30): result = {"check": set(), "time": [], "open": [], "close": [], "high": [], "low": [], "vol": [], "label": []} for i in range(mins, len(data['time'])+1): result["check"].add(data['time'][i-1]) result["time"].append(data['time'][i-1]) result["open"].append(data['open'][i-mins]) result["close"].append(data['close'][i-1]) result["high"].append(max(data['high'][i - mins: i])) result["low"].append(min(data['low'][i - mins: i])) result["vol"].append(sum(data['vol'][i - mins: i])) return result def getStockType(self, stock_code, short=False): slow_k, p_slow_k, slow_k_week, p_slow_k_week, slow_k_month, p_slow_k_month = -1, -1, -1, -1, -1, -1 self.cursor_stock.execute('select stochastic_slow_k, max(ymd) from stock_analysis where code=? group by 1 order by ymd desc',(stock_code,)) items = self.cursor_stock.fetchall() if items is not None and len(items) > 1: for i, item in enumerate(items): if i == 0: slow_k = item[0] elif i == 1: p_slow_k = item[0] else: break self.cursor_stock.execute('select stochastic_slow_k, max(ymd) from stock_analysis_weekly where code=? group by 1 order by ymd desc', (stock_code, )) items = self.cursor_stock.fetchall() if items is not None and len(items) > 1: for i, item in enumerate(items): if i == 0: slow_k_week = item[0] elif i == 1: p_slow_k_week = item[0] else: break self.cursor_stock.execute('select stochastic_slow_k, max(ymd) from stock_analysis_monthly where code=? group by 1 order by ymd desc',(stock_code,)) items = self.cursor_stock.fetchall() if items is not None and len(items) > 1: for i, item in enumerate(items): if i == 0: slow_k_month = item[0] elif i == 1: p_slow_k_month = item[0] else: break if slow_k is None or p_slow_k is None: slow_k , p_slow_k = -1, -1 if slow_k_week is None or p_slow_k_week is None: slow_k_week, p_slow_k_week = -1, -1 if slow_k_month is None or p_slow_k_month is None: slow_k_month, p_slow_k_month = -1, -1 type_stock = {'day':1, 'week':10, 'month':100} if stock_code == "^KS11": if slow_k < 20: type_stock['day'] = 10 if 20 < slow_k < 25: type_stock['day'] = 7.5 if 25 < slow_k < 30: type_stock['day'] = 5 if 30 < slow_k < 35: type_stock['day'] = 2.5 if slow_k_week < 20: type_stock['week'] = 100 if 20 < slow_k_week < 25: type_stock['week'] = 75 if 25 < slow_k_week < 30: type_stock['week'] = 50 if 30 < slow_k_week < 35: type_stock['week'] = 25 if slow_k_month < 20: type_stock['month'] = 1000 if 20 < slow_k_month < 25: type_stock['month'] = 750 if 25 < slow_k_month < 30: type_stock['month'] = 500 if 30 < slow_k_month < 35: type_stock['month'] = 250 else: if slow_k < 10: type_stock['day'] = 10 if 10 < slow_k < 15: type_stock['day'] = 7.5 if 15 < slow_k < 20: type_stock['day'] = 5 if 20 < slow_k < 25: type_stock['day'] = 2.5 if slow_k_week < 10: type_stock['week'] = 100 if 10 < slow_k_week < 15: type_stock['week'] = 75 if 15 < slow_k_week < 20: type_stock['week'] = 50 if 20 < slow_k_week < 25: type_stock['week'] = 25 if slow_k_month < 10: type_stock['month'] = 1000 if 10 < slow_k_month < 15: type_stock['month'] = 750 if 15 < slow_k_month < 20: type_stock['month'] = 500 if 20 < slow_k_month < 25: type_stock['month'] = 250 return type_stock def getBuyCount(self, bs_buy_price, kospi_type, stock_type): base_price = 10000 log_base = 1.2 p_k_m, p_k_w, p_k_d, p_s_m, p_s_w, p_s_d = 0.3, 0.2, 0.05, 0.25, 0.18, 0.02 weight_1, weight_2, weight_3, weight_4, weight_5 = 0.5, 0.3, 0.14, 0.05, 0.01 kospi_weight = weight_5 if kospi_type['day'] == 10: kospi_weight = weight_1 if kospi_type['day'] == 7.5: kospi_weight = weight_2 if kospi_type['day'] == 5: kospi_weight = weight_3 if kospi_type['day'] == 2.5: kospi_weight = weight_4 stock_weight = weight_5 if stock_type['day'] == 10: stock_weight = weight_1 if stock_type['day'] == 7.5: stock_weight = weight_2 if stock_type['day'] == 5: stock_weight = weight_3 if stock_type['day'] == 2.5: stock_weight = weight_4 max_price = math.log( kospi_weight * p_k_m * kospi_type['month'] + kospi_weight * p_k_w * kospi_type['week'] + kospi_weight * p_k_d * kospi_type['day'] + stock_weight * p_s_m * stock_type['month'] + stock_weight * p_s_w * stock_type['week'] + stock_weight * p_s_d * stock_type['day'], log_base) * base_price buy_count = 0 if max_price > 1: buy_count = int(math.floor(max_price / bs_buy_price)) return buy_count def buyRealTime(self, today, stocks, analyzed_day=1000): print ("START...") THIS_TIME = datetime.now() kospi_type = self.getStockType("^KS11", short=False) LAST_DATA = {} for stock in stocks: LAST_DATA[stock['stock_code']] = self.getLastData(stock['stock_code'], today) while datetime.strptime(today + " 070000", '%Y%m%d %H%M%S') < THIS_TIME < datetime.strptime(today + " 153100", '%Y%m%d %H%M%S'): if datetime.strptime(today + " 090000", '%Y%m%d %H%M%S') < THIS_TIME < datetime.strptime(today + " 151500", '%Y%m%d %H%M%S'): # 매도를 체크한다. # self.sellStocks() for idx, stock in enumerate(stocks): time.sleep(0.1) print("%5d: %8s, %-50s"%(idx, stock['stock_code'], stock['stock_name'])) try: # 데이터를 가지고 온다. data = self.getRealTime(stock['stock_code'], today, LAST_DATA[stock['stock_code']]) except: print("#ERROR:", stock['stock_code'], stock['stock_name']) continue # 현재 매수가 bs_buy_price = data["close"][len(data["close"]) - 1] # 미체결 기록을 가져와서 10분 이상 된 매수 주문을 취소 한다. ORDER_LIST = self.requestOrderList() orderListToCancel = self.orderChecker.cancel(today, "A" + stock['stock_code'], ORDER_LIST, mins=10) if len(orderListToCancel) > 0: self.cancelOrderList(orderListToCancel) if bs_buy_price > 1000: if not self.orderChecker.exist(today, "A" + stock['stock_code'], hours=5): stock_type = self.getStockType(stock['stock_code'], short=False) buy_count = self.getBuyCount(bs_buy_price, kospi_type, stock_type) if buy_count > 0: # 매수를 주문한다. orderNum = self.requestOrder(OrderType.buy, stock['stock_code'], buy_count , bs_buy_price) self.orderChecker.buy(today, "A" + stock['stock_code'], buy_count, bs_buy_price, orderNum) # bot에 메시지를 보냄 self.bot.post(stock['stock_code'], stock['stock_name'], "BUY", bs_buy_price, buy_count) # 로그 출력 print("BUY", THIS_TIME.strftime('%Y%m%d %H%M%S'), orderNum, stock['stock_code'], stock['stock_name'], bs_buy_price, buy_count) # 로그 출력 print("TIMECHECK: %s, code: %s, name: %s, buy: %d, avg5: %.2f, avg30: %.2f, open: %d, high: %d, low: %d, slow_k: %.2f" % (str(THIS_TIME), stock['stock_code'], stock['stock_name'], bs_buy_price, data["avg5"][0], data["avg30"][0], data["open"][0], data["high"][0], data["low"][0], data["slow_k"][0])) """ elif datetime.strptime(today + " 151530", '%Y%m%d %H%M%S') < THIS_TIME < datetime.strptime(today + " 151600", '%Y%m%d %H%M%S'): # 3시 15분 30초부터 3시 16분 사이는 잔량을 매도한다. if not final_sell_check: #### # 손해 보지 않는 가격에 매도한다. #### for stock in stocks: # 주문 리스트를 가져온다. orderList = self.requestOrderList() # 15:10:00 이후라면 모든 미체결 취소한다. self.cancelOrderList(orderList) # 매도 가격을 가져온다. result = self.getRealTime(stock['stock_code'], today, LAST_DATA[stock['stock_code']]) final_price = result["close"][len(result["close"]) - 1] orderNum, sell_time, jango, sell_price = self.getSellingPrice(THIS_TIME, stock['stock_code'], final_price, without_loss=True) # 로그 출력 print("SELL", sell_time, stock['stock_code'], stock['stock_name'], final_price, str(orderNum), jango, sell_price) final_sell_check = True """ time.sleep(3600) THIS_TIME = datetime.now() return True def updteTodayStock(self, stock_code, today_str): bsLine, data = self.labelChecker.makeCandidate(stock_code, today_str) self.labelChecker.updateLabel(stock_code, bsLine, data, today_str) return if __name__ == "__main__": today = datetime.today() PROJECT_HOME = os.getcwd() RESOURCE_PATH = os.path.join(PROJECT_HOME, "resources") # KODEX 인버스 * 2 stocks = [ {"stock_code": "122630", "stock_name": "KODEX 레버리지"}, {"stock_code": "305720", "stock_name": "KODEX 2차전지산업"}, {"stock_code": "102780", "stock_name": "KODEX 삼성그룹"}, {"stock_code": "139260", "stock_name": "TIGER 200 IT"}, {"stock_code": "091180", "stock_name": "KODEX 자동차"}, {"stock_code": "401470", "stock_name": "KODEX K-메타버스액티브"}, {"stock_code": "329200", "stock_name": "TIGER 리츠부동산인프라"}, {"stock_code": "091170", "stock_name": "KODEX 은행"}, {"stock_code": "091160", "stock_name": "KODEX 반도체"}, {"stock_code": "161510", "stock_name": "ARIRANG 고배당주"}, {"stock_code": "228800", "stock_name": "TIGER 여행레저"}, {"stock_code": "150460", "stock_name": "TIGER 중국소비테마"}, {"stock_code": "143860", "stock_name": "TIGER 헬스케어"}, {"stock_code": "228810", "stock_name": "TIGER 미디어컨텐츠"}, {"stock_code": "139220", "stock_name": "TIGER 200 건설"}, {"stock_code": "139280", "stock_name": "TIGER 경기방어"}, {"stock_code": "322400", "stock_name": "HANARO e커머스"}, {"stock_code": "157490", "stock_name": "TIGER 소프트웨어"}, {"stock_code": "228790", "stock_name": "TIGER 화장품"}, {"stock_code": "139230", "stock_name": "TIGER 200 중공업"}, {"stock_code": "396500", "stock_name": "TIGER Fn반도체TOP10"}, {"stock_code": "365000", "stock_name": "TIGER KRX인터넷K-뉴딜"}, {"stock_code": "102970", "stock_name": "KODEX 증권"}, {"stock_code": "117680", "stock_name": "KODEX 철강"}, {"stock_code": "244580", "stock_name": "KODEX 바이오"}, {"stock_code": "266360", "stock_name": "KODEX 미디어&엔터테인먼트"}, {"stock_code": "375770", "stock_name": "KODEX 탄소효율그린뉴딜"}, {"stock_code": "364990", "stock_name": "TIGER KRX게임K-뉴딜"}, {"stock_code": "388420", "stock_name": "KBSTAR 비메모리반도체액티브"}, {"stock_code": "117460", "stock_name": "KODEX 에너지화학"}, {"stock_code": "300950", "stock_name": "KODEX 게임산업"}, {"stock_code": "266410", "stock_name": "KODEX 필수소비재"}, {"stock_code": "140700", "stock_name": "KODEX 보험"}, {"stock_code": "139270", "stock_name": "TIGER 200 금융"}, {"stock_code": "395160", "stock_name": "KODEX Fn시스템반도체"}, {"stock_code": "140710", "stock_name": "KODEX 운송"}, {"stock_code": "139240", "stock_name": "TIGER 200 철강소재"}, {"stock_code": "395150", "stock_name": "KODEX Fn웹툰&드라마"}, {"stock_code": "307510", "stock_name": "TIGER 의료기기"}, {"stock_code": "315270", "stock_name": "TIGER 200커뮤니케이션서비스"}, {"stock_code": "132030", "stock_name": "KODEX 골드선물(H)"}, {"stock_code": "144600", "stock_name": "KODEX 은선물(H)"}, {"stock_code": "261220", "stock_name": "KODEX WTI원유선물(H)"}, {"stock_code": "271050", "stock_name": "KODEX WTI원유선물인버스(H)"}, {"stock_code": "138910", "stock_name": "KODEX 구리선물(H)"} ] hts = HTS_etf(RESOURCE_PATH) hts.connect2DB("hts.db") hts.connect2StockDB() today_str = today.strftime('%Y%m%d') hts.buyRealTime(today_str, stocks, analyzed_day=1000) db_filename = os.path.join(RESOURCE_PATH, "hts.db") hts.insertStockData(stocks, today) hts.disconnectStockDB() hts.disconnect() print ("done...")