diff --git a/.gitignore b/.gitignore index 441bc37..b234107 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,5 @@ # ---> Python - +.idea *.json *.html resources/stock*.db diff --git a/HTS_252670_daily.py b/HTS_252670_daily.py new file mode 100644 index 0000000..daeb7c2 --- /dev/null +++ b/HTS_252670_daily.py @@ -0,0 +1,195 @@ +import time +import os +from datetime import datetime + +from hts.DailyStatus import DailyStatus +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 + +class HTS_252670_DAILY (HTS): + + RESOURCE_PATH = None + stock_code = None + buy_count = None + orderChecker = None + buySellChecker = None + labelChecker = None + dailyStatus = None + + def __init__(self, RESOURCE_PATH, stock_code, buy_count): + super().__init__(RESOURCE_PATH) + + self.RESOURCE_PATH = RESOURCE_PATH + self.stock_code = stock_code + self.buy_count = buy_count + + self.orderChecker = OrderChecker(self.RESOURCE_PATH, self.stock_code) + self.buySellChecker = BuySellChecker() + self.labelChecker = LabelChecker(RESOURCE_PATH) + self.dailyStatus = DailyStatus(RESOURCE_PATH) + return + + def getSellingPrice(self, log_time, stock_code, final_price, check=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 + + sell_price = -1 + jangoDic = self.requstJango() + if jangoDic and len(jangoDic.keys()) > 0: + for code in jangoDic: + if jangoDic[code]['매도가능'] > 0: + if check: + if jangoDic[code]['장부가']*0.05 < 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) + print("ORDER_SELL", stock_code, 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) + print("ORDER_SELL", stock_code, log_time.strftime('%Y%m%d %H%M%S'), jangoDic[code]['매도가능'], sell_price) + return + + def buyRealTime(self, today): + + print ("START...") + THIS_TIME = datetime.now() + final_sell_check = False + LAST_DATA = self.dailyStatus.getLastData(self.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'): + # 3시 까지만 매수를 시도한다. + + if THIS_TIME < datetime.strptime(today + " 145000", '%Y%m%d %H%M%S'): + if THIS_TIME.strftime('%S') in ("06", "16", "26", "36", "46", "56"): + # 데이터를 가지고 온다. + result = self.getRealTime(self.stock_code, today, LAST_DATA) + final_price = result["close"][len(result["close"])-1] + + # 10초마다 체크하여 체결된 내역이 있으면 50원 높게 매도를 주문한다. + self.getSellingPrice(THIS_TIME, self.stock_code, final_price, check=True) + + if THIS_TIME.strftime('%S') == "03": + # 매분 3초마다 실행한다. + + # 데이터를 가지고 온다. + result = self.getRealTime(self.stock_code, today, LAST_DATA) + + # 규칙 기반의 분석을 통해서 볼린저밴드 상/하단을 계산한다. + data = self.buySellChecker.analyze(result) + + # 만약 미체결 내역이 있는데, 지표가 꺽여 내려온다면, 매수 주문을 취소 시킨다. + last_index = len(data['close']) - 1 + if data['slow_k'][last_index-1]>=80 and data['slow_k'][last_index-1] > data['slow_k'][last_index]: + # 미체결 기록을 가져온다. + ORDER_LIST = self.requestOrderList() + orderListToCancel = self.orderChecker.remove(self.stock_code, OrderType.sell, ORDER_LIST) + self.cancelOrderList(orderListToCancel) + print("CANCEL", THIS_TIME.strftime('%Y%m%d %H%M%S'), len(orderListToCancel), len(ORDER_LIST)) + + + # 사야 할 시점/가격과 팔아야 할 시점/가격을 체크한다. + bsLine, data = self.buySellChecker.checkTransaction(data, self.stock_code, isRealTime=True) + bs_buy_price = bsLine['buy'][0] + bs_buy_weight = bsLine['buy_weight'][0] + bs_sell_price = bsLine['sell'][0] + + data_size = len(data["close"]) + final_price = data["close"][data_size-1] + + if bs_buy_price > 0: + # 기본 100 주에 가중치를 추가해서 매수한다. + BUY_COUNT = int(self.buy_count * bs_buy_weight) + + # 매수를 주문한다. + orderNum = self.requestOrder(OrderType.buy, self.stock_code, BUY_COUNT , bs_buy_price) + + # 미체결 기록을 가져온다. + ORDER_LIST = self.requestOrderList() + # 매수 주문을 기록한다. + orderListToCancel = self.orderChecker.add(self.stock_code, OrderType.buy, orderNum, BUY_COUNT, bs_buy_price, ORDER_LIST) + # 1 시간 이전 미체결을 모두 취소한다. + self.cancelOrderList(orderListToCancel) + # 로그 출력 + print("BUY", THIS_TIME.strftime('%Y%m%d %H%M%S'), BUY_COUNT, bs_buy_price, len(orderListToCancel), len(ORDER_LIST)) + + + if bs_sell_price > 0: + # 미체결 기록을 가져온다. + ORDER_LIST = self.requestOrderList() + # 매도 주문을 기록을 가져온다. + orderListToCancel = self.orderChecker.remove(self.stock_code, OrderType.sell, ORDER_LIST) + # 매도 미체결을 모두 취소한다. + self.cancelOrderList(orderListToCancel) + + # 매도한다. + self.getSellingPrice(THIS_TIME, self.stock_code, final_price) + + # 로그 출력 + print("TIMECHECK: %s, price: %d, avg3: %.2f, avg5: %.2f, avg10: %.2f, slow_k: %.2f, open: %d, high: %d, low: %d" % + (str(THIS_TIME), final_price, + data["avg3"][data_size - 1], data["avg6"][data_size - 1], data["avg9"][data_size - 1], data["slow_k"][data_size - 2], + data["open"][data_size - 1], data["high"][data_size - 1], data["low"][data_size - 1],)) + 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. + #### + + # 주문 리스트를 가져온다. + orderList = self.requestOrderList() + # 15:10:00 이후라면 모든 미체결 취소한다. + self.cancelOrderList(orderList) + + # 매도 가격을 가져온다. + result = self.getRealTime(self.stock_code, today, LAST_DATA) + final_price = result["close"][len(result["close"]) - 1] + + self.getSellingPrice(THIS_TIME, self.stock_code, final_price) + + final_sell_check = True + + time.sleep(0.9) + THIS_TIME = datetime.now() + + return + + def updteTodayStock(self, db_filename, stock_code, today_str): + bsLine, data = self.labelChecker.makeCandidate(stock_code, today_str) + self.labelChecker.updateLabel(db_filename, 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 + stock_code = "252670" + stock_name = "KODEX 200선물인버스2X" + buy_count = 900 + + hts = HTS_252670_DAILY(RESOURCE_PATH, stock_code, buy_count) + today_str = today.strftime('%Y%m%d') + #today_str = "20220916" + hts.buyRealTime(today_str) + + db_filename = os.path.join(RESOURCE_PATH, "hts.db") + hts.insertStockData(db_filename, stock_code, stock_name, today_str) + #hts.updteTodayStock(db_filename, stock_code, today_str) + + print ("done...") diff --git a/Simulation_Daily.py b/Simulation_Daily.py new file mode 100644 index 0000000..e515f47 --- /dev/null +++ b/Simulation_Daily.py @@ -0,0 +1,164 @@ +import numpy as np +from math import nan +import pandas as pd +import plotly.graph_objects as go +from plotly import subplots +import os +from datetime import datetime + +from hts.HTS import HTS +from hts.DailyStatus import DailyStatus +from hts.BuySellChecker import BuySellChecker + +class Simulation (HTS): + buySellChecker = None + stockPredictor = None + dailyStatus = None + + def __init__(self, RESOURCE_PATH): + super().__init__(RESOURCE_PATH) + + self.RESOURCE_PATH = RESOURCE_PATH + + self.buySellChecker = BuySellChecker() + + self.dailyStatus = DailyStatus(RESOURCE_PATH) + return + + def draw(self, stock_code, given_day, data, bsLine): + if bsLine is None: + return + + # 어제 데이터는 지운다. + buy_line = bsLine['buy'] + buy_weight_line = bsLine['buy_weight'] + sell_line = bsLine['sell'] + + # 그래프 설정을 위한 변수를 생성한다. + data = data.astype( + { + 'open': 'int', + 'high': 'int', + 'low': 'int', + 'close': 'int', + 'slow_k': 'float', + 'slow_d': 'float', + 'macd': 'float', + 'macds': 'float', + 'envelope_upper': 'float', + 'envelope_lower': 'float', + 'envelope_middle': 'float', + 'rsi': 'float', + 'rsis': 'float' + } + ) + + buy_size = [] + buy_colors = [] + for i in range(len(buy_line)): + if buy_line[i] < 0: + buy_colors.append("#ffffff") + buy_line[i] = nan + buy_size.append(0) + else: + buy_colors.append("#B2028C") + buy_size.append(10 + (5 * buy_weight_line[i])) + + sell_colors = [] + for i in range(len(sell_line)): + if sell_line[i] < 0: + sell_colors.append("#ffffff") + sell_line[i] = nan + else: + sell_colors.append("#00ced1") + + # 그래프를 설정한다. + buy_check = go.Scatter(x=data['ymd'], y=buy_line, mode='markers', name="buy", marker=dict(size=buy_size, color=buy_colors, line_width=0)) + sell_check = go.Scatter(x=data['ymd'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0)) + envelope_upper = go.Scatter(x=data['ymd'], y=data["envelope_upper"], name="upper", line_color='#000000') + envelope_middle = go.Scatter(x=data['ymd'], y=data["envelope_middle"], name="upper", line_color='#927786') + envelope_lower = go.Scatter(x=data['ymd'], y=data["envelope_lower"], name="lower", line_color='#000000') + + candle_stick = go.Candlestick(x=data['ymd'], open=data['open'], high=data['high'], low=data['low'], close=data['close'], increasing_line_color='red', decreasing_line_color='blue', showlegend=False) + + macd_line = go.Scatter(x=data['ymd'], y=data["macd"], line=dict(color='red', width=2), name='macd') + macd_s_line = go.Scatter(x=data['ymd'], y=data["macds"], line=dict(dash='dashdot', color='black', width=2), name='macds') + + # fast_k_line = go.Scatter(x=hts['date'], y=hts["fast_k"], mode='lines', name='fast_k') + slow_k_line = go.Scatter(x=data['ymd'], y=data["slow_k"], line=dict(color='red', width=2), name='slow_k') + slow_d_line = go.Scatter(x=data['ymd'], y=data["slow_d"], line=dict(dash='dashdot', color='black', width=2), name='slow_d') + + rsi_line = go.Scatter(x=data['ymd'], y=data["rsi"], line=dict(color='red', width=2), name='rsi') + rsis_line = go.Scatter(x=data['ymd'], y=data["rsis"], line=dict(dash='dashdot', color='black', width=2), name='rsis') + + candle_data = [candle_stick, envelope_upper, envelope_middle, envelope_lower, buy_check, sell_check] + macd_data = [macd_line, macd_s_line] + stochastic_data = [slow_k_line, slow_d_line] + rsi_data = [rsi_line, rsis_line] + + # 그래프를 그린다. + """ + fig = go.Figure(data=candle_data) + fig.update_layout(title=stock_code + "_" + given_day) + fig.show() + """ + + fig = subplots.make_subplots( + rows=4, cols=1, + subplot_titles=("MACD", "RSI", "스토캐스틱", '캔들'), + #specs=[[{}], [{}], [{}], [{}], [{}], [{}]], + shared_xaxes=True, horizontal_spacing=0.03, vertical_spacing=0.01, + row_heights=[200, 200, 200, 750] + ) + for trace in macd_data: + fig.append_trace(trace, 1, 1) + for trace in rsi_data: + fig.append_trace(trace, 2, 1) + for trace in stochastic_data: + fig.append_trace(trace, 3, 1) + for trace in candle_data: + fig.append_trace(trace, 4, 1) + + + #fig.update_xaxes(nticks=5) + #fig.update_layout(height=1800, title=stock_code + "_" + given_day, xaxis_rangeslider_visible=False) + + df = pd.DataFrame(bsLine) + df = df.fillna(-1) + buy_count = len(df.loc[df["buy"] > 0]) + sell_count = len(df.loc[df["sell"] > 0]) + + fig.update_layout(height=1700, title=stock_code + "_" + given_day + "_" + str(buy_count)+","+str(sell_count)) + #fig.update_layout(title=stock_code + "_" + given_day + "_" + str(buy_count) + "," + str(sell_count)) + fig.show() + + return + + + def simulate(self, stock_code, n=100): + today = datetime.today().strftime('%Y%m%d') + data = self.dailyStatus.getLastData(stock_code, today, n) + + # 사야 할 시점과 팔아야 할 시점을 체크한다. + bsLine, data = self.buySellChecker.checkEnvelopeTiming(data, stock_code, isRealTime=False) + + # 그래프를 그린다. + self.draw(stock_code, today, data, bsLine) + + return + +if __name__ == "__main__": + + PROJECT_HOME = os.getcwd() + RESOURCE_PATH = os.path.join(PROJECT_HOME, "resources") + + # to check bying + stock_codes = ["252670", "122630"] + #stock_codes = ["252670"] + #stock_codes = ["122630"] + + for stock_code in stock_codes: + simulation = Simulation(RESOURCE_PATH) + simulation.simulate(stock_code, 2000) + + print ("done...") diff --git a/hts/BuySellChecker.py b/hts/BuySellChecker.py index e759565..526fdf6 100644 --- a/hts/BuySellChecker.py +++ b/hts/BuySellChecker.py @@ -1,5 +1,4 @@ import pandas as pd -import numpy as np from stock.analysis.Common import Common from stock.analysis.Stochastic import Stochastic from stock.analysis.RSI import RSI @@ -838,4 +837,202 @@ class BuySellChecker: bsLine['buy'][i] = int((data["open"][i] + data["close"][i]) / 2) bsLine['buy_weight'][i] = 1 - return bsLine, data \ No newline at end of file + return bsLine, data + + + + + def getBuyPriceAndWeight_Envelope_trend(self, data, i): + buy, weight, type = -1, -1, -1 + + if data['close'][i-1] < data['envelope_lower'][i-1] and data['envelope_lower'][i] < data['close'][i]: + buy = data["close"][i] + weight = 1 + type = 1 + + if data['close'][i] < data['envelope_lower'][i]: + if data['rsis'][i] < data['rsi'][i]: + buy = data["close"][i] + weight = 1 + type = 2 + + if data['close'][i-1] < data['envelope_middle'][i-1] and data['envelope_middle'][i] < data['close'][i]: + if data['slow_k'][i] < 25: + buy = data["close"][i] + weight = 1 + type = 3 + + check1 = False + check2 = False + if data['slow_k'][i] < 40: + if data['close'][i-1] < data['envelope_middle'][i-1] and data['envelope_middle'][i] < data['close'][i]: + idx = -1 + for t1 in range(i-1, i-10, -1): + if data['close'][t1] < data['envelope_middle'][t1]: + check1 = True + idx = t1 + break + if check1: + for t1 in range(idx-1, i - 10, -1): + if data['envelope_middle'][t1] < data['close'][t1]: + check2 = True + break + if check2: + buy = data["close"][i] + weight = 1 + type = 4 + + if data.index[i].strftime("%Y.%m.%d") == "2021.12.21": + print(1) + + check = True + if data['slow_k'][i] < 40: + if data['close'][i - 1] < data['envelope_middle'][i - 1] and data['envelope_middle'][i] < data['close'][i]: + + for t1 in range(i-1, i-10, -1): + if data['envelope_middle'][t1] < data['close'][t1]: + check = False + if check: + buy = data["close"][i] + weight = 1 + type = 4 + + return buy, weight, type + + def getSellPriceAndWeight_Envelope_trend(self, data, i): + sell, weight, type = -1, -1, -1 + + if data.index[i].strftime("%Y.%m.%d") == "2022.12.01": + print (1) + + # upper lined에서 처리 + if data['close'][i-1] < data['envelope_upper'][i - 1] and data['envelope_upper'][i] < data['close'][i]: + if data['slow_d'][i-1] <= data['slow_k'][i - 1] and data['slow_k'][i] <= data['slow_d'][i]: + sell = data["close"][i] + weight = 1 + type = 1 + if data['envelope_upper'][i-1] < data['close'][i - 1] and data['envelope_upper'][i] < data['close'][i]: + if data['slow_d'][i-1] <= data['slow_k'][i - 1] and data['slow_k'][i] <= data['slow_d'][i]: + sell = data["close"][i] + weight = 1 + type = 2 + if data['envelope_upper'][i-1] < data['close'][i - 1] and data['envelope_upper'][i] < data['close'][i]: + if data['slow_d'][i-1] +2 <= data['slow_k'][i - 1] and data['slow_d'][i]+1 == data['slow_k'][i]: + sell = data["close"][i] + weight = 1 + type = 3 + + if data['envelope_upper'][i] 0: + if bsLine['sell'][i-1] > -1: + bsLine['sell'][i] = -1 + bsLine['sell_weight'][i] = -1 + + return bsLine, data diff --git a/hts/DailyStatus.py b/hts/DailyStatus.py new file mode 100644 index 0000000..9e89e54 --- /dev/null +++ b/hts/DailyStatus.py @@ -0,0 +1,103 @@ +import os.path +import pandas as pd +import platform +if platform.system().lower().find("window") >= 0 and platform.architecture()[0] != "64bit" : + import win32com.client + +import sqlite3 +from datetime import datetime, timedelta + +class DailyStatus: + tableName = None + dbFileName = None + RESOURCE_PATH = None + + def __init__(self, RESOURCE_PATH): + self.RESOURCE_PATH = RESOURCE_PATH + self.tableName = 'stock_analysis' + self.dbFileName = "stock.db" + return + + def getDBData(self, stock_code, day, result): + conn = sqlite3.connect(os.path.join(self.RESOURCE_PATH, self.dbFileName)) + cursor = conn.cursor() + + cursor.execute('SELECT ymd, close, open, high, low, envelope_upper, envelope_lower, envelope_middle, rsi, rsis, macd, macds, stochastic_slow_k, stochastic_slow_d FROM ' + self.tableName + ' WHERE CODE=? and ymd=? order by ymd', (stock_code, day,)) + db_result = cursor.fetchall() + for rows in db_result: + ymd = rows[0] + close = rows[1] + open = rows[2] + high = rows[3] + low = rows[4] + envelope_upper = rows[5] + envelope_lower = rows[6] + envelope_middle = rows[7] + rsi = 0 if rows[8] is None else rows[8] + rsis = 0 if rows[9] is None else rows[9] + macd = rows[10] + macds = rows[11] + stochastic_slow_k = 0 if rows[12] is None else rows[12] + stochastic_slow_d = 0 if rows[13] is None else rows[13] + + result["ymd"].append(ymd) + result["open"].append(int(open)) + result["close"].append(int(close)) + result["high"].append(int(high)) + result["low"].append(int(low)) + result["envelope_upper"].append(int(envelope_upper)) + result["envelope_lower"].append(int(envelope_lower)) + result["envelope_middle"].append(int(envelope_middle)) + result["rsi"].append(int(rsi)) + result["rsis"].append(int(rsis)) + result["macd"].append(int(macd)) + result["macds"].append(int(macds)) + result["slow_k"].append(int(stochastic_slow_k)) + result["slow_d"].append(int(stochastic_slow_d)) + + return + + def isValidYMD(self, stock_code, day): + conn = sqlite3.connect(os.path.join(self.RESOURCE_PATH, self.dbFileName)) + cursor = conn.cursor() + + cursor.execute('SELECT ymd, count(*) as cnt FROM ' + self.tableName + ' WHERE CODE=? and ymd=?', (stock_code, day,)) + db_result = cursor.fetchone() + if db_result[1] > 0: + return True + return False + + def getLastData(self, stock_code, today, n=10): + result = { + "ymd": [], + "open": [], + "close": [], + "high": [], + "low": [], + "envelope_upper": [], + "envelope_lower": [], + "envelope_middle": [], + "rsi": [], + "rsis": [], + "macd": [], + "macds": [], + "slow_k": [], + "slow_d": [] + } + + days = [] + for i in range(1, n): + last_day = (datetime.strptime(today, '%Y%m%d') - timedelta(i)).strftime('%Y.%m.%d') + isValid = self.isValidYMD(stock_code, last_day) + if isValid: + days.append(last_day) + + days = sorted(days) + for day in days: + self.getDBData(stock_code, day, result) + + data = pd.DataFrame(result) + df_final_time = pd.DatetimeIndex(result['ymd']) + data.index = df_final_time + + return data \ No newline at end of file