import json import os import time import shutil from stockpredictor.analysis.Common import Common from stockpredictor.analysis.Stochastic import Stochastic from stockpredictor.analysis.BolingerBand import BolingerBand import matplotlib.pyplot as plt import datetime import sqlite3 from datetime import datetime from matplotlib import rc rc('font', family='AppleGothic') plt.rcParams['axes.unicode_minus'] = False import pandas as pd import plotly.graph_objs as go from plotly import tools, subplots import plotly.io as po class Analyzer: tableName = 'stock' PROJECT_HOME = None stocks = None candidate = None stochastic = None common = None inFileName = None fnguideFileName = None fnguide = {} def __init__(self, PROJECT_HOME, inFileName, fnguideFileName): self.PROJECT_HOME = PROJECT_HOME self.inFileName = inFileName self.fnguideFileName = fnguideFileName self.stocks = [] self.candidate = [] self.common = Common() self.stochastic = Stochastic() self.bolingerBand = BolingerBand() self.readFnguide() return def readFnguide(self): conn = sqlite3.connect(self.fnguideFileName) cursor = conn.cursor() today = datetime.today() year1 = str(today.year - 1) + ".12.01" year2 = str(today.year - 2) + ".12.01" year3 = str(today.year - 3) + ".12.01" rowid = 1 cursor.execute('SELECT * FROM fnguide WHERE rowid=?', (rowid,)) result = cursor.fetchone() while result != None: if result[2] == "227950": print (1) data = json.loads(result[2]) self.fnguide[result[0]] = True if (year1 in data and year2 in data and year3 in data): if (data[year1]['영업이익'] < 0 or data[year2]['영업이익'] < 0 or data[year3]['영업이익'] < 0): # and 3년 연속 영업이익이 적자이면 매수하지 않는다. # or: 3년 중 1번이라도 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 rowid += 1 cursor.execute('SELECT * FROM fnguide WHERE rowid=?', (rowid,)) result = cursor.fetchone() cursor.close() conn.close() return def draw(self, stock): last_index = self.get_last_index(stock) if last_index > 300: index = 300 # 최대 300일치 그래프 확인 df_stock = pd.DataFrame(stock["PRICE"][len(stock["PRICE"]) - index:]) df_stochastic = pd.DataFrame(stock["STOCHASTIC"][len(stock["STOCHASTIC"]) - index:last_index+1]) else: index = last_index df_stock = pd.DataFrame(stock["PRICE"][:index+1]) df_stochastic = pd.DataFrame(stock["STOCHASTIC"][:index+1]) # general volume = go.Bar(x=df_stock.DATE, y=df_stock['volume'], name="volume") volume_data = [volume] # stochastic slow_k = go.Scatter(x=df_stochastic.DATE, y=df_stochastic['slow_k'], name="Slow%K", line_color='#8B4513') slow_d = go.Scatter(x=df_stochastic.DATE, y=df_stochastic['slow_d'], name="Slow%D", line_color='#4169E1') stochastic_data = [slow_k, slow_d] fig = subplots.make_subplots(rows=2, cols=1, subplot_titles=('거래량', 'Stochastic')) for trace in volume_data: fig.append_trace(trace, 1, 1) for trace in stochastic_data: fig.append_trace(trace, 2, 1) fig.update_layout(height=800) return fig def get_last_index(self, stock): for i in range(0, len(stock['PRICE'])): if (stock['PRICE'][i]['close'] == 0 and stock['PRICE'][i]['open'] == 0 and stock['PRICE'][i]['volume'] == 0): return i-1 return len(stock['PRICE']) - 1 def analyzeStochastic(self): conn = sqlite3.connect(self.inFileName) cursor = conn.cursor() # 기존 분석 데이터를 모두 지움 cursor.execute('update ' + self.tableName + ' set STOCHASTIC = ""') rowid = 1 cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,)) result = cursor.fetchone() while result != None: stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2])} results = self.stochastic.analyze(stock) text = json.dumps(results, ensure_ascii=False) cursor.execute("UPDATE " + self.tableName + " SET STOCHASTIC=? WHERE CODE=?", (text, stock["CODE"])) print("#analyzeStochastic", rowid, stock['NAME']) rowid += 1 cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,)) result = cursor.fetchone() conn.commit() cursor.close() conn.close() return def analyzeFinalScore(self, last_index, STOCK, STOCHASTIC): """ 매수 조건 #0. 최소 매수 조건은 거래량은 20만건, 종가는 2천원 이상인 종목이어야 한다. #1. 골든크로스: 5일선, 20일선, 60일선, 120일선이 순서대로 나열되는 순간 """ i = last_index buy_price = 0 count = 0 for idx in range(i, i-5, -1): if idx-1 < 0: break buy_price += STOCK[idx-1]['close'] - STOCK[idx]['low'] count += 1 if count == 0: buy_price = STOCK[i]['close'] else: # 종가 - 최저가의 최근 3일 평균 가격을 산정한다. buy_price = round(STOCK[i]['close'] - (buy_price/count)) status = "" if STOCK[i]['volume'] > 100000 and STOCK[i]['close'] > 2000: # 거래량이 100만 이상이고, 종가가 1천원 이상인지 체크 (https://happpy-rich.tistory.com/94) # 정배열 체크 temp_status = self.common.check_RightArrange(STOCK, i) if temp_status != "": status += temp_status # 20일선 돌파 temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '20') if temp_status != "": status += temp_status # 60일선 돌파 temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '60') if temp_status != "": status += temp_status # 120일선 돌파 temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '120') if temp_status != "": status += temp_status # 240일선 돌파 temp_status = self.common.check_Dolpa_Jiji(STOCK, i, '240') if temp_status != "": status += temp_status # 20일선 지지 매수가 추천 temp_status = self.common.check_Dolpa_Jiji_20(STOCK, i) if temp_status != "": status += temp_status # 음봉인데 어제보다 종가가 더 높은 경우 # 이 경우 정배열 상태인지도 함께 체크를 한다. higher_umbong_status = self.common.checkHigherUmbong(STOCK, i) if higher_umbong_status != "": status += higher_umbong_status """ # 단타 #1 temp_status = self.common.check_Danta1(STOCK, i) if temp_status != "": status += temp_status # 단타 #2 temp_status = self.common.check_Danta2(STOCK, i) if temp_status != "": status += temp_status all_upper_cross_status = self.common.checkAllUpperCross(STOCK, i) if all_upper_cross_status != "": status += all_upper_cross_status # 1주일 동안 몇 10% 이상 오른 종목 W1Rise = self.common.check_W1Rise(STOCK, i, 0.1) if W1Rise != "": status += W1Rise # 1일 동안 몇 10% 이상 내린 종목 W1Fall = self.common.check_D1Fall(STOCK, i, -0.1) if W1Fall != "": status += W1Fall """ # GOLDENCROSS#1은 바로 매수하지 않고, 이 시점 이후로 5일선이 20일선을 하방으로 뚫었다가 다시 20일선을 상방으로 뚫는 순간 매수를 시도한다. # GOLDENCROSS#2은 바로 매수 가능 # GOLDENCROSS#3은 바로 매수 가능 golden_cross_status = self.common.check_golded_cross(STOCK, i) if golden_cross_status != "": status += golden_cross_status """ # BUYINGBEARMARKET#1은 바로 매수 가능 # BUYINGBEARMARKET#2은 바로 매수 가능 bearmarket_buying_status = self.common.check_bearmarket_buying(STOCK, STOCHASTIC, i) if bearmarket_buying_status != "": status += bearmarket_buying_status """ # STOCHASTIC stochastic_status = self.common.check_stochastic(STOCK, STOCHASTIC, i) if stochastic_status != "": status += stochastic_status # YANGBONG """ longYangBongAfterUmBong_status = self.common.checkLongYangBongAfterUmBong(STOCK, i) # 어제 음봉 이후 장대양봉이었다면, if longYangBongAfterUmBong_status != "": status += longYangBongAfterUmBong_status """ # Doji doji_status = self.common.checkDoji(STOCK, i) # 하락 추세에서 도지가 나오면 매수 if doji_status != "": status += doji_status """--------------------------------- # Gravestone gravestone_status = self.common.checkGravestone(STOCK, i) # 상승 추세에서 그레이브스톤이 나오면 매도 if gravestone_status != "": status += gravestone_status ---------------------------------""" """ # Dragonfly dragonfly_status = self.common.checkDragonfly(STOCK, i) # 하락 추세에서 드레곤플라이가 나오면 매수 if dragonfly_status != "": status += dragonfly_status # Hammer hammer_status = self.common.checkHammer(STOCK, i) # 하락 추세에서 해머가 나오면 매수 if hammer_status != "": status += hammer_status """ """--------------------------------- # Hangingman hangingman_status = self.common.checkHangingman(STOCK, i) # 상승 추세에서 행잉맨이 나오면 매도 if hangingman_status != "": status += hangingman_status ---------------------------------""" """ # 상승장악형 (Engulfing) - 다음 날도 양봉이라면 매수 engulfing_status = self.common.checkEngulfingHigh(STOCK, i) # 하락 추세에서 상승장악형이 나오면 매수 if engulfing_status != "": status += engulfing_status """ """--------------------------------- # 하락장악형 (Engulfing) engulfing_status = self.common.checkEngulfingLow(STOCK, i) # 상승 추세에서 하락장악형이 나오면 매도 if engulfing_status != "": status += engulfing_status ---------------------------------""" """ # 상승 포아형 (Harami) harami_status = self.common.checkHaramiHigh(STOCK, i) # 하락 추세에서 상승포아형이 나오면 매수 if harami_status != "": status += harami_status """ """--------------------------------- # 하락 포아형 (Harami) harami_status = self.common.checkHaramiLow(STOCK, i) # 상승 추세에서 하락포아형이 나오면 매도 if harami_status != "": status += harami_status ---------------------------------""" """ # 관통형 (piercing) piercing_status = self.common.checkPiercing(STOCK, i) # 하락 추세에서 관통형이 나오면 매수 if piercing_status != "": status += piercing_status """ """--------------------------------- # 흑운형 (Dark-cloud) darkcloud_status = self.common.checkDarkCloud(STOCK, i) # 상승 추세에서 흑운형이 나오면 매도 if darkcloud_status != "": status += darkcloud_status ---------------------------------""" """ # 샛별 (Morning start) morningstar_status = self.common.checkMorningstar(STOCK, i) # 하락 추세에서 샛별형이 나오면 매수 if morningstar_status != "": status += morningstar_status """ """--------------------------------- # 저녁별 (Evening start) eveningstar_status = self.common.checkEveningstar(STOCK, i) # 상승 추세에서 저녁별형이 나오면 매도 if eveningstar_status != "": status += eveningstar_status ---------------------------------""" return status, buy_price def getPositionalEnergy(self, stock, i): # 350일 중 가장 찾은 금액과 가장 높았던 금액 중 현재가의 위치 계산 top = stock[i]['close'] bottom = stock[i]['close'] price = stock[i]['close'] for i in range(8, 540): if i > len(stock) or not stock[-i]: break if top < stock[-i]["close"]: top = stock[-i]["close"] if stock[-i]["close"] < bottom: bottom = stock[-i]["close"] if top - bottom == 0: energy = 100 else: energy = round(((price - bottom) / (top - bottom)), 2) return energy def writeFile(self, fig, state, isbuy, buy_price, bolingerband_score, stochastic_score, positionalEnergy, item_name, item_code): if state != "": fileName = self.status_path fileName = "%s/%d__%s__p(%.2f)__b(%.2f)__s(%.2f)__%d__%s_%s.html" % (fileName, isbuy, state, positionalEnergy, bolingerband_score, stochastic_score, buy_price, item_name.replace(" ", ""), item_code) po.write_html(fig, file=fileName, auto_open=False) if bolingerband_score < 0.15: fileName = self.bolingerband_path fileName = "%s/%d__b(%.2f)__p(%.2f)__s(%.2f)__%s__%d__%s_%s.html" % (fileName, isbuy, bolingerband_score, positionalEnergy, stochastic_score, state, buy_price, item_name.replace(" ", ""), item_code) po.write_html(fig, file=fileName, auto_open=False) if stochastic_score < 15: fileName = self.stochastic_path fileName = "%s/%d__s(%.2f)__b(%.2f)__p(%.2f)__%s__%d__%s_%s.html" % (fileName, isbuy, stochastic_score, bolingerband_score, positionalEnergy, state, buy_price, item_name.replace(" ", ""), item_code) po.write_html(fig, file=fileName, auto_open=False) if positionalEnergy < 0.15: fileName = self.positionalEnergy_path fileName = "%s/%d__p(%.2f)__b(%.2f)__s(%.2f)__%s__%d__%s_%s.html" % (fileName, isbuy, positionalEnergy, bolingerband_score, stochastic_score, state, buy_price, item_name.replace(" ", ""), item_code) po.write_html(fig, file=fileName, auto_open=False) if isbuy > 0: fileName = self.outPath fileName = "%s/%d__p(%.2f)__b(%.2f)__s(%.2f)__%s__%d__%s_%s.html" % (fileName, isbuy, positionalEnergy, bolingerband_score, stochastic_score, state, buy_price, item_name.replace(" ", ""), item_code) po.write_html(fig, file=fileName, auto_open=False) return def makeDirectory(self, outPath): self.outPath = outPath if os.path.isdir(outPath): shutil.rmtree(outPath) os.mkdir(outPath) self.stochastic_path = outPath + "/stochastic" if os.path.isdir(self.stochastic_path): os.rmdir(self.stochastic_path) os.mkdir(self.stochastic_path) self.bolingerband_path = outPath + "/bolingerband" if os.path.isdir(self.bolingerband_path): os.rmdir(self.bolingerband_path) os.mkdir(self.bolingerband_path) self.positionalEnergy_path = outPath + "/positionalEnergy" if os.path.isdir(self.positionalEnergy_path): os.rmdir(self.positionalEnergy_path) os.mkdir(self.positionalEnergy_path) self.status_path = outPath + "/status" if os.path.isdir(self.status_path): os.rmdir(self.status_path) os.mkdir(self.status_path) return # 그래프 출력 def analyzeToHtml(self, outPath): self.makeDirectory(outPath) conn = sqlite3.connect(self.inFileName) cursor = conn.cursor() rowid = 1 cursor.execute('SELECT CODE, NAME, PRICE, STOCHASTIC, BOLINGERBAND FROM ' + self.tableName + ' WHERE rowid=?', (rowid,)) result = cursor.fetchone() # 최근 20일간 +-종목 개수 체크 inde_check = [] for check_index in range(365): inde_check.append([0,0]) while result != None: item_code = result[0] item_name = result[1] print("#html", rowid, item_name) # 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") or result[3] == ''): 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 CODE, NAME, PRICE, STOCHASTIC, BOLINGERBAND FROM ' + self.tableName + ' WHERE rowid=?', (rowid,)) result = cursor.fetchone() continue result_3 = result[3] if result[3] != result[3]: result_3 = result[3].replace("NaN", "0") if result[3]==None: rowid += 1 cursor.execute('SELECT CODE, NAME, PRICE, STOCHASTIC, BOLINGERBAND FROM ' + self.tableName + ' WHERE rowid=?', (rowid,)) result = cursor.fetchone() continue stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2]), "STOCHASTIC": json.loads(result_3), "BOLINGERBAND": json.loads(result[4])} last_index = self.get_last_index(stock) STOCK = stock['PRICE'] STOCHASTIC = stock['STOCHASTIC'] BOLINGERBAND = stock['BOLINGERBAND'] stochastic_score = STOCHASTIC[last_index]['slow_k'] # upper: 20, lower: 10 # 14 = (14-10) / (20-10) = 0.4 # 18 = (18-10) / (20-10) = 0.8 # 5 = (5-10) / (20-10) = -0.5 if BOLINGERBAND[last_index]['upper'] == BOLINGERBAND[last_index]['lower']: bolingerband_score = 0 else: bolingerband_score = round(((STOCK[last_index]['close']-BOLINGERBAND[last_index]['lower'])/(BOLINGERBAND[last_index]['upper']-BOLINGERBAND[last_index]['lower'])), 2) # 위치 에너지 positionalEnergy = self.getPositionalEnergy(STOCK, last_index) if STOCK[last_index]['volume'] > 100000 and STOCK[last_index]['close'] > 1000: # 종목 상태 체크 분석 state, buy_price = self.analyzeFinalScore(last_index, STOCK, STOCHASTIC) isbuy = 0 # 스토케스틱이 20이하이어야 하며, 볼린저밴드 0.3 보다 작으며, 위치에너지도 0.2보다 낮다면, if stochastic_score < 30 and bolingerband_score < 0.3 and positionalEnergy < 0.3: isbuy = 1 # 위치에너지가 낮거나 240일선 아래에 있는 상태에서 상태값을 갖는 경우 매수한다. if state != "": isbuy = 2 # 종가가 240일선 아래라면 매수한다. if STOCK[last_index]['close'] < STOCK[last_index]['avg240']: if state == "": isbuy = 3 else: isbuy = 4 if len(STOCK) > 5: # 볼린저밴드 하단에 부딪혔다면, """ if (STOCK[last_index-2]['low'] <= BOLINGERBAND[last_index-2]['lower'] <= STOCK[last_index-2]['high'] or STOCK[last_index-3]['low'] <= BOLINGERBAND[last_index-3]['lower'] <= STOCK[last_index-3]['high'] or STOCK[last_index-4]['low'] <= BOLINGERBAND[last_index-4]['lower'] <= STOCK[last_index-4]['high']): """ if (STOCK[last_index - 2]['low'] <= BOLINGERBAND[last_index - 2]['lower'] <= STOCK[last_index - 2]['high'] or STOCK[last_index - 3]['low'] <= BOLINGERBAND[last_index - 3]['lower'] <= STOCK[last_index - 3]['high']): # 어제 양봉이거나 # 음봉이라면 그저깨 종가보다 어제 시가가 높거나 같고 그저깨 시가보다 어제 종가가 높다. # 음봉이라면 그저깨 시가보다 어제 시가가 높거나 같고 그저깨 종가보다 어제 종가가 높다. if STOCK[last_index-1]['open'] < STOCK[last_index-1]['close'] or ( (STOCK[last_index-2]['close'] <= STOCK[last_index-1]['open'] and STOCK[last_index-2]['open'] < STOCK[last_index-1]['close']) or (STOCK[last_index-2]['open'] <= STOCK[last_index-1]['open'] and STOCK[last_index-2]['close'] < STOCK[last_index-1]['close'])): # (KOSPI: 2011년 8월 11일) # 오늘 양봉이어야 한다. if STOCK[last_index]['open'] < STOCK[last_index]['close']: isbuy = 5 # (KOSPI: 2011년 9월 26일) # 오늘 음봉이라면, 오늘 시가는 어제 종가보다 높아야 하고, 오늘 종가는 어제 시가보다 높아야 한다. if (STOCK[last_index]['close'] < STOCK[last_index]['open']) and (STOCK[last_index-1]['close'] < STOCK[last_index]['open'] and STOCK[last_index-1]['open'] < STOCK[last_index]['close']): isbuy = 5 if isbuy==4 and stochastic_score < 30 and bolingerband_score < 0.3 and positionalEnergy < 0.3: isbuy = 9 fig = self.draw(stock) title = "%s (%s), %s, buy_price (%d), stochastic(%.2f), bolingerband(%.2f), positionalEnergy(%.2f) 차트" % (item_name, item_code, state, buy_price, stochastic_score, bolingerband_score, positionalEnergy) fig['layout'].update(title=title) self.writeFile(fig, state, isbuy, buy_price, bolingerband_score, stochastic_score, positionalEnergy, item_name, item_code) for check_index in range(365): if len(STOCK) > check_index and STOCK[last_index-check_index]['open'] < STOCK[last_index-check_index]['close']: inde_check[check_index][0] += 1 else: inde_check[check_index][1] += 1 rowid += 1 cursor.execute('SELECT CODE, NAME, PRICE, STOCHASTIC, BOLINGERBAND FROM ' + self.tableName + ' WHERE rowid=?', (rowid,)) result = cursor.fetchone() outFp = open("inout.cvs", mode='w') for check_index in range(365): idx = 365 - check_index - 1 outFp.write("%d,%d,%d,%4.2f\n" % (idx, inde_check[idx][0], inde_check[idx][1], inde_check[idx][0]*100/(inde_check[idx][0]+inde_check[idx][1]))) outFp.close() cursor.close() conn.close() return def analyze(self): conn = sqlite3.connect(self.inFileName) cursor = conn.cursor() # 기존 분석 데이터를 모두 지움 cursor.execute('update ' + self.tableName + ' set STOCHASTIC = "", BOLINGERBAND = ""') rowid = 1 cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,)) result = cursor.fetchone() while result != None: stock = {"CODE": result[0], "NAME": result[1], "PRICE": json.loads(result[2])} try: results_STOCHASTIC = self.stochastic.analyze(stock) text_STOCHASTIC = json.dumps(results_STOCHASTIC, ensure_ascii=False) results_BolingerBand = self.bolingerBand.analyze(stock) text_BOLINGERBAND = json.dumps(results_BolingerBand, ensure_ascii=False) except: print("#", rowid, stock['NAME']) rowid += 1 cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,)) result = cursor.fetchone() continue cursor.execute("UPDATE " + self.tableName + " SET STOCHASTIC=?, BOLINGERBAND=? WHERE CODE=?", (text_STOCHASTIC, text_BOLINGERBAND, stock["CODE"])) print("#", rowid, stock['NAME']) rowid += 1 cursor.execute('SELECT * FROM ' + self.tableName + ' WHERE rowid=?', (rowid,)) result = cursor.fetchone() conn.commit() cursor.close() conn.close() return if __name__ == "__main__": start = time.time() PROJECT_HOME = os.path.join(os.path.dirname(os.path.join(os.path.dirname(os.path.join(os.path.dirname(__file__)))))) inFileName = PROJECT_HOME + '/resources/stock.db' inFnguideFileName = PROJECT_HOME + '/resources/fnguide.db' analyzer = Analyzer(PROJECT_HOME, inFileName, inFnguideFileName) # 분석 & update DB """ #print ("analyze Stochastic...") analyzer.analyzeStochastic() """ ####### # analyzer.analyze() ####### day = datetime.today().strftime("%Y%m%d") # HTML 출력 outPath = PROJECT_HOME + "/resources/analysis/"+day if os.path.isdir(outPath): shutil.rmtree(outPath) os.mkdir(outPath) print("print to Html...") analyzer.analyzeToHtml(outPath) # 파일 출력 #print("print to File...") #outFileName = PROJECT_HOME + '/resources/analysis/'+day+'.json' #analyzer.analyzeToFile(outFileName) print("time : %6.2f 초" % (time.time() - start)) print("done...")