init

hts/BS.py

@@ -16,6 +16,58 @@ class BS:
 
         return
 
+    def getPriceAndWeight(self, data, i):
+        buy, weight, sell = -1, -1, -1
+
+        # sell 분석
+        if (data["High"][i] - data["Close"][i]) / 2 + data["Close"][i] > data["upper"][i]:
+            sell = data["High"][i]
+        if i > 300:
+            if data["High"][i] > data["upper"][i]:
+                sell = data["High"][i]
+
+        # buy 분석
+        if data["slow_k"][i] <= 36:
+            if data["Low"][i] < data["lower"][i]:
+                buy = data["Low"][i]
+            if data["slow_k"][i] <= 25:
+                if data["slow_k"][i - 1] < data["slow_d"][i - 1] and data["slow_d"][i] < data["slow_k"][i]:
+                    buy = data["Low"][i]
+
+        if i < 40:
+            if data["slow_k"][i] < 25:
+                buy = data["Low"][i]
+
+        # weight 분석
+        # rsi가 rsis 위로 올라오며 15 이하일 경우 10배로 주문함 (14:30 이전)
+        if data["rsi"][i] < 15 and data["rsis"][i] < 15 and data["rsi"][i - 1] < data["rsis"][i - 1] and data["rsis"][i] < data["rsi"][i]:
+            buy = data["Low"][i]
+            weight = 4
+
+        if data["slow_k"][i] == 1:
+            weight = 4  # 8
+        elif data["slow_k"][i] in (2, 3):
+            weight = 3.5  # 7
+        elif data["slow_k"][i] in (4, 5, 6):
+            weight = 3  # 6
+        elif data["slow_k"][i] in (7, 8, 9, 10):
+            weight = 2.5  # 5
+        elif data["slow_k"][i] in (11, 12, 13, 14, 15):
+            weight = 2  # 4
+        elif data["slow_k"][i] in (16, 17, 18, 19, 20, 21):
+            weight = 1.5  # 3
+        elif data["slow_k"][i] in (22, 23, 24, 25, 26, 27, 28):
+            weight = 1  # 2
+        elif data["slow_k"][i] in (29, 30, 31, 32, 33, 34, 35, 36):
+            weight = 1
+        if data["rsi"][i] < 10:
+            weight = 3  # 8
+
+        if i <= 20:
+            weight = 1
+
+        return buy, weight, sell
+
     def checkStatus(self, STOCK, last_index):
         status = set()
 
@@ -235,7 +287,9 @@ class BS:
 
         # stochastic 계산
         stochastic_df = self.stochastic.apply(pd.DataFrame(STOCK))
-        stochastic_df = stochastic_df.fillna(100)
+        stochastic_df['fast_k'] = stochastic_df['fast_k'].fillna(float(stochastic_df['fast_k'].iloc[9]))
+        stochastic_df['slow_k'] = stochastic_df['slow_k'].fillna(float(stochastic_df['slow_k'].iloc[14]))
+        stochastic_df['slow_d'] = stochastic_df['slow_d'].fillna(float(stochastic_df['slow_d'].iloc[19]))
         fast_k = stochastic_df['fast_k'].values.tolist()
         slow_k = stochastic_df['slow_k'].values.tolist()
         slow_d = stochastic_df['slow_d'].values.tolist()