init

2023-10-08 15:52:20 +09:00
parent d993ebc3f0
commit 9da290b220
2 changed files with 82 additions and 63 deletions
--- a/Simulation.py
+++ b/Simulation.py
@@ -50,9 +50,14 @@ class Simulation (HTS):
                            'volume': 'int',
                            'avg5': 'float',
                            'avg20': 'float',
-                            'avg30': 'float',
                            'avg60': 'float',
                            'avg120': 'float',
+                            'avg200': 'float',
+                            'disparity_avg5': 'float',
+                            'disparity_avg20': 'float',
+                            'disparity_avg60': 'float',
+                            'disparity_avg120': 'float',
+                            'disparity_avg200': 'float',
                            'fast_k': 'float',
                            'slow_k': 'float',
                            'slow_d': 'float',
@@ -84,11 +89,11 @@ class Simulation (HTS):
        sell_check = go.Scatter(x=data['date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0))
        upper = go.Scatter(x=data['date'], y=data["upper"], name="upper", line_color='#000000')
        lower = go.Scatter(x=data['date'], y=data["lower"], name="lower", line_color='#000000')
-        avg5 = go.Scatter(x=data['date'], y=data["avg5"], name="avg5", line_color='#8F8203')
-        avg20 = go.Scatter(x=data['date'], y=data["avg20"], name="avg20", line_color='#089B5B')
-        avg30 = go.Scatter(x=data['date'], y=data["avg30"], name="avg30", line_color='#ff00ff')
-        avg60 = go.Scatter(x=data['date'], y=data["avg60"], name="avg60", line_color='#1469F4')
-        avg120 = go.Scatter(x=data['date'], y=data["avg120"], name="avg120", line_color='#000000')
+        avg5 = go.Scatter(x=data['date'], y=data["avg5"], name="avg5", line_color='#F81191')
+        avg20 = go.Scatter(x=data['date'], y=data["avg20"], name="avg20", line_color='#097F19')
+        avg60 = go.Scatter(x=data['date'], y=data["avg60"], name="avg60", line_color='#671BEA')
+        avg120 = go.Scatter(x=data['date'], y=data["avg120"], name="avg120", line_color='#DFB809')
+        avg200 = go.Scatter(x=data['date'], y=data["avg200"], name="avg200", line_color='#000000')
        laggingSpan = go.Scatter(x=data['date'], y=data["laggingSpan"], name='laggingSpan', line_color='#B50ABB')
        changeLine = go.Scatter(x=data['date'], y=data["changeLine"], name='changeLine', line_color='#14A200')
        baseLine = go.Scatter(x=data['date'], y=data["baseLine"], name='baseLine', line_color='#CF6E0D')
@@ -97,11 +102,11 @@ class Simulation (HTS):
        #volume_line = go.Scatter(x=data['date'], y=data["volume"], mode='lines', name='volume')
        volume_line = go.Bar(x=data['date'], y=data["volume"], marker_color='red', name='volume')

-        disparity_avg5 = go.Scatter(x=data['date'], y=data["disparity_avg5"], name="disparity_avg5", line_color='#8F8203')
-        disparity_avg10 = go.Scatter(x=data['date'], y=data["disparity_avg10"], name="disparity_avg10", line_color='#089B5B')
-        disparity_avg20 = go.Scatter(x=data['date'], y=data["disparity_avg20"], name="disparity_avg20", line_color='#ff00ff')
-        disparity_avg60 = go.Scatter(x=data['date'], y=data["disparity_avg60"], name="disparity_avg60", line_color='#1469F4')
-        disparity_avg120 = go.Scatter(x=data['date'], y=data["disparity_avg120"], name="disparity_avg120", line_color='#000000')
+        disparity_avg5 = go.Scatter(x=data['date'], y=data["disparity_avg5"], name="disparity_avg5", line_color='#F81191')
+        disparity_avg20 = go.Scatter(x=data['date'], y=data["disparity_avg20"], name="disparity_avg20", line_color='#097F19')
+        disparity_avg60 = go.Scatter(x=data['date'], y=data["disparity_avg60"], name="disparity_avg60", line_color='#671BEA')
+        disparity_avg120 = go.Scatter(x=data['date'], y=data["disparity_avg120"], name="disparity_avg120", line_color='#DFB809')
+        disparity_avg200 = go.Scatter(x=data['date'], y=data["disparity_avg200"], name="disparity_avg200", line_color='#000000')

        macd_line = go.Scatter(x=data['date'], y=data["macd"], line=dict(color='red', width=2), name='macd')
        macd_s_line = go.Scatter(x=data['date'], y=data["macds"], line=dict(dash='dashdot', color='black', width=2), name='macds')
@@ -114,9 +119,9 @@ class Simulation (HTS):
        rsi_line = go.Scatter(x=data['date'], y=data["rsi"], line=dict(color='red', width=2), name='rsi')
        rsis_line = go.Scatter(x=data['date'], y=data["rsis"], line=dict(dash='dashdot', color='black', width=2), name='rsis')

-        candle_data = [candle_stick, upper, lower, avg5, avg20, avg30, avg60, avg120, buy_check, sell_check, laggingSpan, changeLine, baseLine]
+        candle_data = [candle_stick, upper, lower, avg5, avg20, avg60, avg120, avg200, buy_check, sell_check, laggingSpan, changeLine, baseLine]
        volume_data = [volume_line]
-        disparity_data = [disparity_avg5, disparity_avg10, disparity_avg20, disparity_avg60, disparity_avg120]
+        disparity_data = [disparity_avg5, disparity_avg20, disparity_avg60, disparity_avg120, disparity_avg200]
        macd_data = [macd_line, macd_s_line, macd_o_line]
        stochastic_data = [slow_k_line, slow_d_line]
        rsi_data = [rsi_line, rsis_line]
@@ -191,23 +196,24 @@ class Simulation (HTS):
                for given_day in stock_codes[stock_code]:
                    LAST_DATA = self.stock2Vector.getLastData(stock_code, given_day)
                    result = self.stock2Vector.getRealTime(stock_code, given_day, LAST_DATA)
-                    result_5 = self.makeTickData(result, mins=5)
-                    result_30 = self.makeTickData(result, mins=30)
+                    #result_5 = self.makeTickData(result, mins=5)
+                    #result_30 = self.makeTickData(result, mins=30)

                    data = self.buySellChecker.analyze(result)
                    data.drop(data.index[:len(data) - analyzed_day], inplace=True)

                    # 이동평균, RSI, MACD, 일목균형, 볼린저밴드 상/하단을 계산한다.
-                    data_5 = self.buySellChecker.analyze(result_5)
+                    #data_5 = self.buySellChecker.analyze(result_5)
                    # 분석일 데이터만 활용한다 (이전 데이터는 제거)
-                    data_5.drop(data_5.index[:len(data_5) - analyzed_day], inplace=True)
+                    #data_5.drop(data_5.index[:len(data_5) - analyzed_day], inplace=True)

-                    data_30 = self.buySellChecker.analyze(result_30)
+                    #data_30 = self.buySellChecker.analyze(result_30)
                    # 분석일 데이터만 활용한다 (이전 데이터는 제거)
-                    data_30.drop(data_30.index[:len(data_30) - analyzed_day], inplace=True)
+                    #data_30.drop(data_30.index[:len(data_30) - analyzed_day], inplace=True)

                    # 사야 할 시점과 팔아야 할 시점을 체크한다.
-                    bsLine = self.buySellChecker.checkTransaction(stock_code, data, data_5, data_30, isRealTime=False)
+                    #bsLine = self.buySellChecker.checkTransaction(stock_code, data, data_5, data_30, isRealTime=False)
+                    bsLine = self.buySellChecker.checkTransaction(stock_code, data, None, None, isRealTime=False)

                    # 그래프를 그린다.
                    self.draw(stock_code, given_day, data, bsLine)
@@ -227,10 +233,10 @@ if __name__ == "__main__":
    # to check bying
    stock_codes = {
        "252670": [
-            '20220901', '20220902', '20220905', '20220906', '20220907', '20220908','20220913','20220914','20220915','20220916'
+            '20220901', '20220902', '20220905', '20220906'
        ],
        "122630": [
-            '20220901', '20220902', '20220905', '20220906', '20220907', '20220908', '20220913', '20220914', '20220915', '20220916'
+            '20220901', '20220902', '20220905', '20220906'
        ]
    }
    #simulation.simulate(stock_codes)
--- a/hts/BuySellChecker.py
+++ b/hts/BuySellChecker.py
@@ -109,53 +109,64 @@ class BuySellChecker:
            return -1
        return 0

-    def getBuyPriceAndWeight(self, data, data_5, data_30, i):
+    def getBuyPriceAndWeight(self, i, data, data_5=None, data_30=None):
        buy, weight = -1, -1

-        if len(data_5['slow_k']) <= i or len(data_30['slow_k']) <= i:
-            return buy, weight
+        if data_5 is not None and data_30 is not None:
+            if len(data_5['slow_k']) <= i or len(data_30['slow_k']) <= i:
+                return buy, weight

-        if data_5['slow_k'][i] < 20:
-            if data_5['slow_k'][i - 1] < data_5['slow_d'][i - 1] and data_5['slow_d'][i] < data_5['slow_k'][i]:
-                buy = data['low'][i]
-                weight = 0.3
+            if data_5['slow_k'][i] < 20:
+                if data_5['slow_k'][i - 1] < data_5['slow_d'][i - 1] and data_5['slow_d'][i] < data_5['slow_k'][i]:
+                    buy = data['low'][i]
+                    weight = 0.3

-        if data_30['slow_k'][i] < 30 and data_5['slow_k'][i] < 30:
-            if data_5['slow_k'][i - 1] < data_5['slow_d'][i - 1] and data_5['slow_d'][i] < data_30['slow_k'][i]:
-                buy = data['close'][i]
-                weight = 0.3
-
-        if data_30['slow_k'][i] < 30:
-            if data_5['slow_k'][i] < 30:
-                if data_5['avg5'][i] < data_5['close'][i]:
+            if data_30['slow_k'][i] < 30 and data_5['slow_k'][i] < 30:
+                if data_5['slow_k'][i - 1] < data_5['slow_d'][i - 1] and data_5['slow_d'][i] < data_30['slow_k'][i]:
                    buy = data['close'][i]
-                    weight = 0.2
+                    weight = 0.3

-            if data_5['slow_k'][i - 1] < data_5['slow_d'][i - 1] and data_5['slow_d'][i] < data_30['slow_k'][i]:
-                buy = data['close'][i]
-                weight = 0.3
+            if data_30['slow_k'][i] < 30:
+                if data_5['slow_k'][i] < 30:
+                    if data_5['avg5'][i] < data_5['close'][i]:
+                        buy = data['close'][i]
+                        weight = 0.2
+
+                if data_5['slow_k'][i - 1] < data_5['slow_d'][i - 1] and data_5['slow_d'][i] < data_30['slow_k'][i]:
+                    buy = data['close'][i]
+                    weight = 0.3
+        else:
+            if data['avg5'][i-1] < data['avg200'][i-1] and data['avg200'][i] < data['avg5'][i]:
+                if data['avg60'][i]<data['avg20'][i]<data['avg5'][i]:
+                    buy = data['close'][i]
+                    weight = 0.3

        return buy, weight

-    def getSellPriceAndWeight(self, data, data_5, data_30, i):
+    def getSellPriceAndWeight(self, i, data, data_5=None, data_30=None):
        sell, weight = -1, -1

-        if len(data_5['slow_k']) <= i or len(data_30['slow_k']) <= i:
-            return sell, weight
+        if data_5 is not None and data_30 is not None:
+            if len(data_5['slow_k']) <= i or len(data_30['slow_k']) <= i:
+                return sell, weight

-        if data_30['slow_k'][i] > 90:
-            if (data_5['slow_d'][i-1] < data_5['slow_k'][i-1] and data_5['slow_k'][i] < data_5['slow_d'][i]):
+            if data_30['slow_k'][i] > 90:
+                if (data_5['slow_d'][i-1] < data_5['slow_k'][i-1] and data_5['slow_k'][i] < data_5['slow_d'][i]):
+                    sell = data['close'][i]
+                    weight = 100
+
+                if data_5['slow_k'][i] > 95 and data_5['slow_k'][i] < data_5['slow_d'][i]:
+                    sell = data['close'][i]
+                    weight = 100
+
+            if data_30['slow_k'][i] > 98 and data_5['slow_k'][i] > 98:
                sell = data['close'][i]
                weight = 100
-
-            if data_5['slow_k'][i] > 95 and data_5['slow_k'][i] < data_5['slow_d'][i]:
+        else:
+            if data['avg200'][i-1] < data['avg5'][i-1] and data['avg5'][i] < data['avg200'][i]:
                sell = data['close'][i]
                weight = 100

-        if data_30['slow_k'][i] > 98 and data_5['slow_k'][i] > 98:
-            sell = data['close'][i]
-            weight = 100
-
        return sell, weight


@@ -247,18 +258,20 @@ class BuySellChecker:
        avg60 = [item[0] for item in avg60_list]
        avg120_list = close_df.rolling(window=120).mean().fillna(close[0]).values.tolist()
        avg120 = [item[0] for item in avg120_list]
+        avg200_list = close_df.rolling(window=200).mean().fillna(close[0]).values.tolist()
+        avg200 = [item[0] for item in avg120_list]

        open_df = pd.DataFrame(close)
        disparity_avg5_list = (open_df / close_df.rolling(window=5).mean()).values.tolist()
        disparity_avg5 = [item[0] for item in disparity_avg5_list]
-        disparity_avg10_list = (open_df / close_df.rolling(window=10).mean()).values.tolist()
-        disparity_avg10 = [item[0] for item in disparity_avg10_list]
        disparity_avg20_list = (open_df / close_df.rolling(window=20).mean()).values.tolist()
        disparity_avg20 = [item[0] for item in disparity_avg20_list]
        disparity_avg60_list = (open_df / close_df.rolling(window=60).mean()).values.tolist()
        disparity_avg60 = [item[0] for item in disparity_avg60_list]
        disparity_avg120_list = (open_df / close_df.rolling(window=120).mean()).values.tolist()
        disparity_avg120 = [item[0] for item in disparity_avg120_list]
+        disparity_avg200_list = (open_df / close_df.rolling(window=200).mean()).values.tolist()
+        disparity_avg200 = [item[0] for item in disparity_avg200_list]

        # 볼린져 밴드
        df = pd.DataFrame(close)
@@ -280,7 +293,7 @@ class BuySellChecker:
        STOCK = []
        for i in range(len(open)):
            STOCK.append({'volume': vol[i], 'close': close[i], 'open': open[i], 'high': high[i], 'low': low[i],
-                          'avg5': avg5[i], 'avg20': avg20[i], 'avg30': avg30[i], 'avg60': avg60[i], 'avg120': avg120[i]})
+                          'avg5': avg5[i], 'avg20': avg20[i], 'avg60': avg60[i], 'avg120': avg120[i], 'avg200': avg200[i]})

        # stochastic
        stochastic_df = self.stochastic.apply(STOCK, n=30, m=5, t=5)
@@ -312,9 +325,9 @@ class BuySellChecker:
        temp = {
            "date": point_temp,
            "open": open, "high": high, "low": low, "close": close, "volume": vol,
-            "avg5": avg5, "avg20": avg20, "avg30": avg30, "avg60": avg60, "avg120": avg120,
-            "disparity_avg5": disparity_avg5, "disparity_avg10": disparity_avg10, "disparity_avg20": disparity_avg20,
-            "disparity_avg60": disparity_avg60, "disparity_avg120": disparity_avg120,
+            "avg5": avg5, "avg20": avg20, "avg60": avg60, "avg120": avg120, "avg200": avg200,
+            "disparity_avg5": disparity_avg5, "disparity_avg20": disparity_avg20,
+            "disparity_avg60": disparity_avg60, "disparity_avg120": disparity_avg120, "disparity_avg200": disparity_avg200,
            "upper": upper, "lower": lower,
            "macd": macd, "macds": macds, "macdo": macdo,
            "fast_k": fast_k, "slow_k": slow_k, "slow_d": slow_d,
@@ -726,7 +739,7 @@ class BuySellChecker:
        outFp.write(str(df["label"][i]) + "\n")
        return

-    def checkTransaction(self, stock_code, data, data_5, data_30, isRealTime=True):
+    def checkTransaction(self, stock_code, data, data_5=None, data_30=None, isRealTime=True):
        # 어제 오늘 데이터로 분석
        bsLine = {}
        size = len(data["close"])
@@ -735,8 +748,8 @@ class BuySellChecker:
            # isRealTime=True, 실시간 적용
            last_index = size - 1

-            buy, buy_weight = self.getBuyPriceAndWeight(data, data_5, data_30, last_index)
-            sell, sell_weight = self.getSellPriceAndWeight(data, data_5, data_30, last_index)
+            buy, buy_weight = self.getBuyPriceAndWeight(last_index, data, data_5, data_30)
+            sell, sell_weight = self.getSellPriceAndWeight(last_index, data, data_5, data_30)

            bsLine['buy'] = [buy]
            bsLine['buy_weight'] = [buy_weight]
@@ -751,8 +764,8 @@ class BuySellChecker:
            bsLine['sell_weight'] = [-1 for i in range(size)]

            for i in range(size):
-                buy, buy_weight = self.getBuyPriceAndWeight(data, data_5, data_30, i)
-                sell, sell_weight = self.getSellPriceAndWeight(data, data_5, data_30, i)
+                buy, buy_weight = self.getBuyPriceAndWeight(i, data, data_5, data_30)
+                sell, sell_weight = self.getSellPriceAndWeight(i, data, data_5, data_30)

                bsLine['buy'][i] = buy
                bsLine['buy_weight'][i] = buy_weight