init

Simulation.py

@@ -52,8 +52,7 @@ class Simulation (HTS):
                             'avg6': 'float',
                             'avg9': 'float',
                             'avg12': 'float',
-                            'avg27': 'float',
+                            'avg20': 'float',
-                            'avg54': 'float',
                             'fast_k': 'float',
                             'slow_k': 'float',
                             'slow_d': 'float',
@@ -89,8 +88,7 @@ class Simulation (HTS):
         avg6 = go.Scatter(x=data['date'], y=data["avg6"], name="avg6", line_color='#089B5B')
         avg9 = go.Scatter(x=data['date'], y=data["avg9"], name="avg9", line_color='#ff00ff')
         avg12 = go.Scatter(x=data['date'], y=data["avg12"], name="avg12", line_color='#1469F4')
-        avg27 = go.Scatter(x=data['date'], y=data["avg27"], name="avg27", line_color='#000000')
+        avg20 = go.Scatter(x=data['date'], y=data["avg20"], name="avg20", line_color='#000000')
-        avg54 = go.Scatter(x=data['date'], y=data["avg54"], name="avg54", line_color='#008000')
 
         candle_stick = go.Candlestick(x=data['date'], open=data['open'], high=data['high'], low=data['low'], close=data['close'], increasing_line_color='red', decreasing_line_color='blue')
         volume_line = go.Scatter(x=data['date'], y=data["volume"], mode='lines', name='volume')
@@ -106,7 +104,7 @@ class Simulation (HTS):
         rsi_line = go.Scatter(x=data['date'], y=data["rsi"], mode='lines', name='rsi')
         rsis_line = go.Scatter(x=data['date'], y=data["rsis"], mode='lines', name='rsis')
 
-        candle_data = [candle_stick, upper, lower, avg3, avg6, avg9, avg12, avg27, avg54, buy_check, sell_check]
+        candle_data = [candle_stick, upper, lower, avg3, avg6, avg9, avg12, avg20, buy_check, sell_check]
         volume_data = [volume_line]
         macd_data = [macd_line, macd_s_line, macd_o_line]
         stochastic_data = [slow_k_line, slow_d_line]
@@ -184,12 +182,8 @@ if __name__ == "__main__":
 
     # to check bying
     stock_codes = {
-        "252670": [
+        "252670": ['20220822', '20220823', '20220824', '20220825', '20220826'],
-            '20220510', '20220511', '20220512',
+        #"122630": ['20220822', '20220823', '20220824', '20220825', '20220826']
-            '20220610', '20220613', '20220614',
-            '20220708', '20220711', '20220712',
-            '20220810', '20220811', '20220812'],
-        #"122630": ['20220611', '20220612', '20220613', '20220614'],
     }
 
     method = "rule" # "rule", "ml", "answer"

hts/BuySellChecker.py

@@ -183,6 +183,103 @@ class BuySellChecker:
 
 
 
+    def getBuyPriceAndWeight(self, data, i):
+        buy, weight = -1, -1
+        slow_k = 60
+
+        START_TIME_INDEX = 0
+        for c in range(370, len(data.index)):
+            if data.index[c].strftime("%H:%M:%S") == "09:01:00":
+                START_TIME_INDEX = c
+                break
+
+        if i > START_TIME_INDEX:
+            # 매수 분석
+
+            valid = True
+            for c in range(i-10, i+1):
+                if data["avg20"][c-1] > data["avg20"][c]:
+                    valid = False
+            if valid:
+                min_value = min(data["open"][i], data["close"][i])
+                max_value = max(data["open"][i], data["close"][i])
+                if min_value < data["avg20"][i] < max_value:
+                    if data["slow_k"][i] < slow_k:
+                        buy = min_value
+                        weight = 1
+
+            if data["slow_k"][i] < slow_k:
+                valid = True
+                for c in range(i - 5, i + 1):
+                    if data["avg20"][c] >= min(data["avg3"][c], data["avg6"][c], data["avg9"][c], data["avg12"][c]):
+                        valid = False
+                        break
+                if valid:
+                    valid = False
+                    for c in range(i - 20, i + 1):
+                        if data["avg20"][c] > max(data["avg3"][c], data["avg6"][c], data["avg9"][c], data["avg12"][c]):
+                            valid = True
+                            break
+                    if valid:
+                        buy = max(int(data["open"][i]+data["close"][i])/2, min(data["open"][i], data["close"][i]))
+                        weight = 1
+
+        return buy, weight
+
+    def getSellPriceAndWeight(self, data, i):
+        sell, weight = -1, -1
+        slow_k = 60
+
+        START_TIME_INDEX = 0
+        for c in range(370, len(data.index)):
+            if data.index[c].strftime("%H:%M:%S") == "09:01:00":
+                START_TIME_INDEX = c
+                break
+
+        if i > START_TIME_INDEX:
+            # 매도 분석
+
+            # 3분선이 10분 이상 6분선 위에 있다가 6분선 아래로 내려옴
+            if i >= 381 + 10:
+                vaild = True
+                count = 0
+                for c in range(i-10, i+1):
+                    if data["avg3"][c-1] == data["avg20"][c]:
+                        count += 1
+                    if data["avg3"][c-1] < data["avg20"][c]:
+                        vaild = False
+                        break
+                if vaild and count < 3:
+                    if data["avg3"][i] < data["avg20"][i]:
+                        if data["slow_k"][i] > slow_k:
+                            sell = int(data["avg3"][i] - data["avg3"][i] % 5)
+                            weight = 1
+                            return sell, weight
+
+            # 12분선이 5분 이상 20분선 위에 있다가 20분선 아래로 내려옴
+            if i >= 381 + 5:
+                vaild = True
+                for c in range(1, 6):
+                    if data["avg12"][i - c] < data["avg20"][i - c]:
+                        vaild = False
+                        break
+                if vaild:
+                    if data["avg12"][i] < data["avg20"][i] and data["avg20"][i-1] < data["avg20"][i]:
+                        if data["slow_k"][i] > slow_k:
+                            sell = data["close"][i]
+                            weight = 1
+                            return sell, weight
+
+            if (not (data["avg20"][i-1] > max(data["avg3"][i-1], data["avg6"][i-1], data["avg9"][i-1], data["avg12"][i-1])) and
+                    (data["avg20"][i] > max(data["avg3"][i], data["avg6"][i], data["avg9"][i], data["avg12"][i]))):
+                if data["slow_k"][i] > slow_k:
+                    sell = data["close"][i]
+                    weight = 1
+                    return sell, weight
+
+        return sell, weight
+
+
     # 곱버스에 해당함
     def getBuyPriceAndWeight_252670(self, data, i):
         buy, weight = -1, -1
@@ -220,7 +317,6 @@ class BuySellChecker:
                     weight = 1
                     return buy, weight
 
-
         return buy, weight
 
     def getSellPriceAndWeight_252670(self, data, i):
@@ -445,6 +541,96 @@ class BuySellChecker:
         vol = result["vol"]
         label = result["label"]
 
+        # 이동 평균
+        close_df = pd.DataFrame(close)
+        avg3_list = close_df.rolling(window=3).mean().fillna(close[0]).values.tolist()
+        avg3 = [item[0] for item in avg3_list]
+        avg6_list = close_df.rolling(window=6).mean().fillna(close[0]).values.tolist()
+        avg6 = [item[0] for item in avg6_list]
+        avg9_list = close_df.rolling(window=9).mean().fillna(close[0]).values.tolist()
+        avg9 = [item[0] for item in avg9_list]
+        avg12_list = close_df.rolling(window=12).mean().fillna(close[0]).values.tolist()
+        avg12 = [item[0] for item in avg12_list]
+        avg20_list = close_df.rolling(window=20).mean().fillna(close[0]).values.tolist()
+        avg20 = [item[0] for item in avg20_list]
+
+        # 볼린져 밴드
+        df = pd.DataFrame(close)
+        max20 = df.rolling(window=20).mean()
+        stddev20 = df.rolling(window=20).std()
+        upper_df = max20 + (stddev20 * 2) # 상단 볼린저 밴드
+        lower_df = max20 - (stddev20 * 2) # 하단 볼린저 밴드
+
+        upper, lower = [], []
+        for i in range(len(upper_df)):
+            if i < 10:
+                upper.append(upper_df.values[0][0])
+                lower.append(lower_df.values[0][0])
+            else:
+                upper.append(upper_df.values[i][0])
+                lower.append(lower_df.values[i][0])
+
+        point_temp = result["time"]
+        STOCK = []
+        for i in range(len(open)):
+            STOCK.append({'volume': vol[i], 'close': close[i], 'open': open[i], 'high': high[i], 'low': low[i],
+                          'avg20': avg20[i]})
+
+        # stochastic
+        stochastic_df = self.stochastic.apply(STOCK, n=30, m=5, t=5)
+        fast_k = stochastic_df['fast_k'].values.tolist()
+        slow_k = stochastic_df['slow_k'].values.tolist()
+        slow_d = stochastic_df['slow_d'].values.tolist()
+
+        # macd
+        macd_df = self.macd.apply(STOCK, short=12, long=26, t=9)
+        macd = macd_df['macd'].values.tolist()
+        macds = macd_df['macds'].values.tolist()
+        macdo = macd_df['macdo'].values.tolist()
+
+        # rsi
+        rsi_df = self.rsi.apply(STOCK, period=30, window=5)
+        rsi = rsi_df['rsi'].values.tolist()
+        rsis = rsi_df['rsis'].values.tolist()
+
+        # ichimokuCloud
+        ichimokuCloud_df = self.ichimokuCloud.apply(STOCK, c=9, b=26, l=52)
+        ichimokuCloud_df = ichimokuCloud_df[:len(ichimokuCloud_df) - 51]
+        changeLine = ichimokuCloud_df['changeLine'].values.tolist()
+        baseLine = ichimokuCloud_df['baseLine'].values.tolist()
+        leadingSpan1 = ichimokuCloud_df['leadingSpan1'].values.tolist()
+        leadingSpan2 = ichimokuCloud_df['leadingSpan2'].values.tolist()
+
+        # 결과
+        temp = {
+            "date": point_temp,
+            "open": open, "high": high, "low": low, "close": close, "volume": vol,
+            "avg3": avg3,"avg6": avg6,"avg9": avg9,"avg12": avg12, "avg20": avg20,
+            "upper": upper, "lower": lower,
+            "macd": macd, "macds": macds, "macdo": macdo,
+            "fast_k": fast_k, "slow_k": slow_k, "slow_d": slow_d,
+            "rsi": rsi, "rsis": rsis,
+            "changeLine": changeLine, "baseLine": baseLine, "leadingSpan1": leadingSpan1, "leadingSpan2": leadingSpan2,
+
+            "label": label
+        }
+
+        data = pd.DataFrame(temp)
+        df_final_time = pd.DatetimeIndex(point_temp)
+        data.index = df_final_time
+
+        data = data.fillna(close[0])
+        return data
+
+    def analyze1(self, result):
+        # 기본 캔들 정보
+        open = result["open"]
+        close = result["close"]
+        high = result["high"]
+        low = result["low"]
+        vol = result["vol"]
+        label = result["label"]
+
         # 캔들 정보 연산
         height = [close[i] - open[i] for i in range(0, len(close))]
         top_tail_height = [high[i] - max(open[i], close[i]) for i in range(0, len(close))]
@@ -839,12 +1025,16 @@ class BuySellChecker:
             # isRealTime=True, 실시간 적용
             last_index = size - 1
 
+            buy, buy_weight = self.getBuyPriceAndWeight(data, last_index)
+            sell, sell_weight = self.getSellPriceAndWeight(data, last_index)
+            """
             if stock_code == "252670":
                 sell, sell_weight = self.getSellPriceAndWeight_252670(data, last_index)
                 buy, buy_weight = self.getBuyPriceAndWeight_252670(data, last_index)
             else:
                 sell, sell_weight = self.getSellPriceAndWeight_122630(data, last_index)
                 buy, buy_weight = self.getBuyPriceAndWeight_122630(data, last_index)
+            """
 
             bsLine['buy'] = [buy]
             bsLine['buy_weight'] = [buy_weight]
@@ -858,12 +1048,16 @@ class BuySellChecker:
             bsLine['sell_weight'] = [-1 for i in range(size)]
 
             for i in range(size):
+                buy, buy_weight = self.getBuyPriceAndWeight(data, i)
+                sell, sell_weight = self.getSellPriceAndWeight(data, i)
+                """
                 if  stock_code == "252670":
                     sell, sell_weight = self.getSellPriceAndWeight_252670(data, i)
                     buy, buy_weight = self.getBuyPriceAndWeight_252670(data, i)
                 else:
                     sell, sell_weight = self.getSellPriceAndWeight_122630(data, i)
                     buy, buy_weight = self.getBuyPriceAndWeight_122630(data, i)
+                """
                 bsLine['buy'][i] = buy
                 bsLine['buy_weight'][i] = buy_weight
                 bsLine['sell'][i] = sell

requirements.txt

@@ -3,7 +3,8 @@ plotly
 matplotlib
 pandas_datareader
 bs4
-pywin32
+datasets
+#pywin32
 ipywidgets==7.0.0
 
 #keras