init

hts/BS.py

@@ -16,58 +16,6 @@ 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()
 
@@ -232,6 +180,57 @@ class BS:
 
         return status
 
+    def getPriceAndWeight1(self, data, i):
+        buy, weight, sell = -1, -1, -1
+
+        ################
+        ### sell 분석 ###
+        ################
+        # 1. 볼린져밴드 상단이 최고와 종가 사이 아래에 있는 경우 매도한다.
+        if (data["High"][i] - data["Close"][i]) / 2 + data["Close"][i] > data["upper"][i]:
+            sell = data["High"][i]
+        # 2. slow_k가 90이 넘으면 매도한다.
+        if data["slow_k"][i] >= 90:
+            sell = data["High"][i]
+        # 3. 2시 이후에는 최고가가 볼린져밴드 상단 위에 있으면 매도한다.
+        if i > 300 and data["High"][i] > data["upper"][i]:
+                sell = data["High"][i]
+
+        ################
+        ### buy 분석 ###
+        ################
+        # 1. slow_k가 25 아래 있으면 매수한다.
+        if data["slow_k"][i] <= 20:
+            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 = 3
+        if data["rsi"][i] < 10:
+            weight = 3
+
+        if data["slow_k"][i] in (1, 2, 3, 4, 5, 6, 7, 8, 9, 10):
+            weight = 2
+        elif data["slow_k"][i] in (11, 12, 13, 14, 15, 16):
+            weight = 1.5
+        elif data["slow_k"][i] in (17, 18, 19, 20, 21, 22, 23, 24, 25):
+            weight = 1
+
+        return buy, weight, sell
+
+    def getPriceAndWeight2(self, data, i):
+        buy, weight, sell = -1, -1, -1
+
+        if data["slow_k"][i] < 25:
+            buy = data["Low"][i]
+        if data["slow_k"][i] > 90:
+            sell = data["High"][i]
+
+        return buy, weight, sell
+
+
     def analyze(self, result):
         df = pd.DataFrame(result["close"])
 

hts/HTS.py

@@ -531,10 +531,10 @@ class HTS:
         bsLine['sell'] = [-1 for i in range(size)]
 
         i = size - 1
-        if i <= 20:
+        if i < 5:
             return -1, -1, -1
 
-        buy, weight, sell = self.bs.getPriceAndWeight(data, i)
+        buy, weight, sell = self.bs.getPriceAndWeight1(data, i)
         return buy, weight, sell
 
     def getSellingPrice(self, final_price):

hts/Simulation.py

@@ -49,8 +49,8 @@ class Simulation:
         bsLine['weight'] = [-1 for i in range(size)]
         bsLine['sell'] = [-1 for i in range(size)]
 
-        for i in range(21, size-5):
+        for i in range(6, size-5):
-            buy, weight, sell = self.bs.getPriceAndWeight(data, i)
+            buy, weight, sell = self.bs.getPriceAndWeight1(data, i)
             bsLine['buy'][i] = buy
             bsLine['weight'][i] = weight
             bsLine['sell'][i] = sell
@@ -163,7 +163,6 @@ if __name__ == "__main__":
     given_days = ['20210901','20210902','20210903','20210906','20210907','20210908','20210909','20210910','20210913',
                   '20210914','20210915','20210916','20210917','20210923','20210924','20210927','20210928','20210929',
                   '20210930','20211001', '20211005','20211006', '20211007','20211008', '20211012','20211013', '20211014']
-
     simulation = Simulation()
 
     for given_day in given_days:

stockpredictor/analysis/Stochastic.py

@@ -15,7 +15,7 @@ class Stochastic:
 
     # 일자(n,m,t)에 따른 Stochastic(KDJ)의 값을 구하기 위해 함수형태로 만듬
     # n=15 (%k), m=5 (%d), t=3
-    def apply(self, df, n=10, m=6, t=6):
+    def apply(self, df, n=5, m=3, t=3):
         # 입력받은 값이 dataframe이라는 것을 정의해줌
         df = pd.DataFrame(df)