init

stock/analysis/AnalyzerSqlite.py

@@ -472,11 +472,26 @@ class AnalyzerSqlite:
         cursor.close()
         conn.close()
 
+        # 상승 종목 개수
         param = {'bull': [], 'bear': [], 'even': []}
         for i in range(60):
             param['bull'].append(0)
             param['bear'].append(0)
             param['even'].append(0)
+        for idx, item in enumerate(items):
+            CODE = item[0]
+            stock_daily = self.getStockData(stockAnalysisTableName, CODE)
+            for c in range(len(stock_daily['open'])):
+                if c >= 60:
+                    break
+                if stock_daily['open'][c] < stock_daily['close'][c]:
+                    param['bull'][c] += 1
+                elif stock_daily['close'][c] < stock_daily['open'][c]:
+                    param['bear'][c] += 1
+                else:
+                    param['even'][c] += 1
+        self.writeSummary(param)
+
 
         for idx, item in enumerate(items):
             CODE = item[0]
@@ -526,22 +541,11 @@ class AnalyzerSqlite:
                         log = "이전없던거래량_" + log
                         self.writeFile(dir_name, CODE, NAME, top, stock_daily, log)
 
-                    check = self.common.check_optimal_buy_timeing(stock_daily)
+                    check = self.common.check_optimal_buy_timeing(param, stock_daily)
                     if check:
                         dir_name = "daily_최적_타이밍_찾기"
                         log = dir_name + "_"
                         self.writeFile(dir_name, CODE, NAME, top, stock_daily, log)
-
-                for c in range(len(stock_daily['open'])):
-                    if c >= 60:
-                        break
-                    if stock_daily['open'][c] < stock_daily['close'][c]:
-                        param['bull'][c] += 1
-                    elif stock_daily['close'][c] < stock_daily['open'][c]:
-                        param['bear'][c] += 1
-                    else:
-                        param['even'][c] += 1
-        self.writeSummary(param)
         return
 
     def get_moving_average(self, stock):

stock/analysis/Common.py

@@ -572,13 +572,49 @@ class Common:
 
         return False
 
-    def check_optimal_buy_timeing(self, stock):
+    def check_optimal_buy_timeing(self, param, stock):
 
-        if stock['avg120'][0] < stock['avg60'][0] < stock['avg20'][0] < stock['avg5'][0]:
+        if (
-            if stock['avg20'][1] < stock['avg20'][0] and stock['avg5'][1] < stock['avg5'][0]:
+                (stock['macd'][-2] < stock['macd'][-1] and stock['rsi'][-1]) < 80 or
-                if stock['avg240'][0] < stock['avg20'][0] < stock['avg5'][0]:
+                (stock['rsi'][-2] < stock['rsi'][-1] and np.min(stock['rsi'][-3:]) < 35) or
-                    if stock['rsi'][0] < 70:
+                (stock['rsi'][-1:] < 33) or
-                        return True
+                0.9 <= ticker['rise_rate']
+        ):
+            # trend 상승
+            if stock['trend'][i - 1] < stock['trend'][i]:
+                # avg360 상승
+                if stock['avg360'][i - 1] < stock['avg360'][i]:
+                    # avg3 < trend
+                    if stock['avg3'][i] < stock['trend'][i]:
+                        # avg3 이전 3개 봉 위
+                        if np.max(stock['avg3'][i - 3:i]) < stock['avg3'][i]:
+                            buy_type = "trend"
+                            buy_weight = 1  # 8
+                            check = True
+
+            # 상승 추세일 때
+            if (stock['macd'][-2] < stock['macd'][-1] and stock['macds'][-1] < stock['macd'][
+                -1] or
+                    stock['rsi'][-2] < stock['rsi'][-1]):
+
+                # rsi가 50을 상향 돌파할 때
+                if 0.9 <= ticker['rise_rate'] and np.max(stock['rsi'][i - 5:i]) < 50 and 50 < stock['rsi'][i]:
+                    buy_type = "rsi"
+                    buy_weight = 0.5  # 1
+                    check = True
+
+                # golden & 거래량
+                if stock['avg120'][i] < stock['avg30'][i] < stock['avg15'][i] < stock['avg10'][i] < stock['avg3'][i]:
+                    buy_type = "golden"
+                    buy_weight = 0.5  # 6
+                    check = True
+
+            # rsi가 30보다 작은 후에 상승일 때
+            if np.min(stock['rsi'][i - 5:i]) < 30:
+                if stock['rsi'][i - 1] < stock['rsi'][i]:
+                    buy_type = "rsi"
+                    buy_weight = 0.8  # 4
+                    check = True
 
         return False