init

2021-09-22 21:04:41 +09:00
parent 50a669ad1f
commit 448cd9aeb6
11 changed files with 2859 additions and 5608 deletions
--- a/hts/20210909.csv
+++ b/hts/20210909.csv
@@ -0,0 +1,383 @@
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--- a/hts/20210910.csv
+++ b/hts/20210910.csv
@@ -0,0 +1,383 @@
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--- a/hts/20210913.csv
+++ b/hts/20210913.csv
@@ -0,0 +1,383 @@
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--- a/hts/20210914.csv
+++ b/hts/20210914.csv
@@ -0,0 +1,383 @@
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--- a/hts/20210915.csv
+++ b/hts/20210915.csv
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--- a/hts/20210916.csv
+++ b/hts/20210916.csv
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--- a/hts/20210917.csv
+++ b/hts/20210917.csv
@@ -0,0 +1,383 @@
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--- a/hts/HTS.py
+++ b/hts/HTS.py
@@ -1,14 +1,9 @@
+#import win32com.client
 import os
-import re
-import win32com.client
-from datetime import datetime
-#import matplotlib.pyplot as plt
-#import matplotlib.ticker as ticker
-#import mplfinance as mpf
+from datetime import datetime, timedelta
+import matplotlib.pyplot as plt
 import pandas as pd
-
-#import cufflinks as cf
-#import plotly.graph_objects as go
+import plotly.graph_objects as go

 class HTS:

@@ -248,6 +243,24 @@ class HTS:

        return

+    def write(self, day, result):
+        #날짜,시간,시가,고가,저가,종가,거래량
+        #20210909,900,2070,2070,2070,2070,0
+
+        outFp = open(day+".csv", "w")
+        outFp.write("날짜,시간,시가,고가,저가,종가,거래량\n")
+        for i in range(len(result["time"])):
+            outFp.write("%s,%s,%s,%s,%s,%s,%s\n"%(
+                result["time"][i].strftime('%Y%m%d'),
+                result["time"][i].strftime('%H%M'),
+                result["open"][i],
+                result["high"][i],
+                result["low"][i],
+                result["close"][i],
+                result["vol"][i]))
+        outFp.close()
+        return
+
    # 주식 현재가 조회
    def getRealTime(self, stock_code, day, result):
        objCpCybos = win32com.client.Dispatch("CpUtil.CpCybos")
@@ -273,25 +286,32 @@ class HTS:
        size = objStockChart.GetHeaderValue(3)

        #print("날짜", "시간", "시가", "고가", "저가", "종가", "거래량")
-        start_time = datetime.strptime(day+" 093000", '%Y%m%d %H%M%S')
+        start_time = datetime.strptime(day + " 090000", '%Y%m%d %H%M%S')
        for i in range(size-1, -1, -1):
-            #day = objStockChart.GetDataValue(0, i)
            time = datetime.strptime(day+" "+objStockChart.GetDataValue(1, i), '%Y%m%d %H%M%S')
            if time < start_time:
                continue

-            #open = objStockChart.GetDataValue(2, i)
-            #high = objStockChart.GetDataValue(3, i)
-            #low = objStockChart.GetDataValue(4, i)
+            open = objStockChart.GetDataValue(2, i)
            close = objStockChart.GetDataValue(5, i)
+            high = objStockChart.GetDataValue(3, i)
+            low = objStockChart.GetDataValue(4, i)
            vol = objStockChart.GetDataValue(6, i)
-            #print(day, time, open, high, low, close, vol)

-            if time[i] not in result["check"]:
+            if len(result["check"]) == 0:
+                result["check"].add(start_time)
+                result["time"].append(start_time)
+
+            if time not in result["check"]:
                result["check"].add(time)
                result["time"].append(time)
+
+            result["open"].append(open)
            result["close"].append(close)
+            result["high"].append(high)
+            result["low"].append(low)
            result["vol"].append(vol)
+
        return

    def getCSV(self, fileName, day, result):
@@ -299,112 +319,171 @@ class HTS:

        days = data.날짜
        time = data.시간
+        open = data.시가
        close = data.종가
+        high = data.고가
+        low = data.저가
        vol = data.거래량
-        start_time = datetime.strptime(day + " 093000", '%Y%m%d %H%M%S')
+        start_time = datetime.strptime(day + " 090000", '%Y%m%d %H%M%S')

        for i in range(len(data)):
-            temp = datetime.strptime(str(days[i]) + " " + str(time[i]), '%Y%m%d %H%M%S')
+            temp = datetime.strptime(str(days[i]) + " " + str(time[i]).zfill(4)+"00", '%Y%m%d %H%M%S')
            if temp < start_time:
                continue

            if temp not in result["check"]:
                result["check"].add(temp)
                result["time"].append(temp)
+                result["open"].append(open[i])
                result["close"].append(close[i])
+                result["high"].append(high[i])
+                result["low"].append(low[i])
                result["vol"].append(vol[i])
        return

    def analyze(self, result):
-        y_value = result["close"]
-        #x_value = [i for i in range(len(y_value))]
-        vol = result["vol"]
-        df = pd.DataFrame(y_value)
-        point = result["time"]
+        df = pd.DataFrame(result["close"])

-        max20 = df.rolling(window=20).mean()
-        stddev20 = df.rolling(window=20).std()
+        max20 = df.rolling(window=10).mean()
+        stddev20 = df.rolling(window=10).std()
        upper_df = max20 + (stddev20 * 2)                  # 상단 볼린저 밴드
        lower_df = max20 - (stddev20 * 2)                  # 하단 볼린저 밴드

-        window = 60
-        open = y_value[:len(y_value)-window] + [y_value[len(y_value)-window] for i in range(window)]    # 시가
-        close = [y_value[window-1] for i in range(window-1)] + y_value[window-1:]                       # 종가
-        high_df = df.rolling(window=window).max()          # 고가
-        low_df = df.rolling(window=window).min()           # 저가
+        size = len(result["open"])
+        window = 5
+        open = [result["open"][i] for i in range(0, size, window)]
+        close = [result["close"][i-1] for i in range(window-1, size, window)]
+        for i in range(len(open)-len(close)):
+            close.append(result["close"][len(result["close"])-1])
+        high = [max(result["high"][i:i+window]) for i in range(0, size, window)]
+        low = [min(result["low"][i:i+window]) for i in range(0, size, window)]

-        high, low, upper, lower = [], [], [], []
-        for i in range(len(high_df)):
+        upper, lower = [], []
+        for i in range(len(upper_df)):
            if i < window:
-                high.append(high_df.values[window - 1][0])
-                low.append(low_df.values[window - 1][0])
-
                upper.append(upper_df.values[window - 1][0])
                lower.append(lower_df.values[window - 1][0])
            else:
-                high.append(high_df.values[i][0])
-                low.append(low_df.values[i][0])
-
                upper.append(upper_df.values[i][0])
                lower.append(lower_df.values[i][0])

-        open_temp = [open[i] for i in range(len(open)) if i % window == 0]
-        high_temp = [high[i] for i in range(len(high)) if i % window == 0]
-        low_temp = [low[i] for i in range(len(low)) if i % window == 0]
-        close_temp = [close[i] for i in range(len(close)) if i % window == 0]
-        vol_temp = [vol[i] for i in range(len(vol)) if i % window == 0]
-        point_temp = [point[i] for i in range(len(point)) if i % window == 0]
-        upper_temp = [upper[i] for i in range(len(upper)) if i % window == 0]
-        lower_temp = [lower[i] for i in range(len(lower)) if i % window == 0]
+        point_temp = [result["time"][i] for i in range(size) if i % window == 0]
+        upper_temp = [upper[i] for i in range(size) if i % window == 0]
+        lower_temp = [lower[i] for i in range(size) if i % window == 0]
+        vol_temp = [sum(result["vol"][i:window]) for i in range(0, size, window)]

-
-        temp = {"Open": open_temp, "High": high_temp, "Low": low_temp, "Close": close_temp, "Volume": vol_temp, "Date": point_temp}
+        temp = {"Open": open, "High": high, "Low": low, "Close": close, "Volume": vol_temp, "Date": point_temp}
        data = pd.DataFrame(temp)
        df_final_time = pd.DatetimeIndex(point_temp)
        data.index = df_final_time

-        return data, upper_temp, lower_temp
+        # 살 시점인지 체크
+        # 볼린저밴드 하단에 연속으로 같은 가격이 왔을 때,
+        #           해당 하단 가격 + 5원에 매수를 시도함
+        check = False
+        buy_line = [-1 for i in range(len(lower_temp))]
+        for i in range(3, len(lower_temp)):
+            for j in range(i-3, i):
+                if (low[j] < lower_temp[j]) and (low[i] < lower_temp[i] and low[j] == low[i]):
+                    #buy_line[i] = low[i]
+                    check = True
+                    break
+            if check and i < len(lower_temp) - 1:
+                buy_line[i+1] = low[i] + 5
+                check = False

-    def buyRealTime(self, stock_code, day):
-        result = {"check": set(),
-                  "time": [],
-                  "close": [],
-                  "vol": []}
+        # 팔 시점 체크
+        # 산 가격에 5원 위로 매도를 건다.
+        sell_line = [-1 for i in range(len(lower_temp))]
+        for i in range(len(buy_line)):
+            if buy_line[i] > 0:
+                for j in range(i+1, len(buy_line)):
+                    # 5원 이득을 보고 판다.
+                    if close[j] >= buy_line[i] + 5:
+                        sell_line[j] = buy_line[i] + 5
+                        break

+        return data, upper_temp, lower_temp, buy_line, sell_line

-        #self.getRealTime(stock_code, day, result)
-        self.getCSV("data_s_1.csv", day, result)
-        self.getCSV("data_s_2.csv", day, result)
-        data, upper, lower = self.analyze(result)
-
+    def draw(self, data, upper, lower, buy_line, sell_line):
+        # 그래프 설정을 위한 변수를 생성한다.
        data['Open'] = pd.to_numeric(data['Open'])
        data['High'] = pd.to_numeric(data['High'])
        data['Low'] = pd.to_numeric(data['Low'])
        data['Close'] = pd.to_numeric(data['Close'])
        data['Volume'] = pd.to_numeric(data['Volume'])

-        fig = plt.figure(figsize=(10, 10))
-        ax = fig.add_subplot(111)
-
-        """
-        # 이동평균선 그리기
-        ax.plot(upper, label='upper', linewidth=1.5)
-        ax.plot(lower, label='lower', linewidth=1.5)
-
-        # 참고) https://pypi.org/project/mplfinance/
-        mc = mpf.make_marketcolors(up='red', down='blue', inherit=True)
-        style_final = mpf.make_mpf_style(marketcolors=mc)
-        mpf.plot(data, ax=ax, style=style_final)
-        plt.grid()
-        plt.show()
-        """
+        buy_colors = []
+        for i in range(len(buy_line)):
+            if buy_line[i] < 0:
+                buy_colors.append("#ffffff")
+                buy_line[i] = lower[0]
+            else:
+                buy_colors.append("#ff00ff")
+        sell_colors = []
+        for i in range(len(sell_line)):
+            if sell_line[i] < 0:
+                sell_colors.append("#ffffff")
+                sell_line[i] = lower[0]
+            else:
+                sell_colors.append("#00ced1")

+        # 그래프를 설정한다.
+        buy_check = go.Scatter(x=data['Date'], y=buy_line, mode='markers', name="buy", marker=dict(size=14, color=buy_colors, line_width=0))
+        sell_check = go.Scatter(x=data['Date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0))
        bolinger_upper = go.Scatter(x=data['Date'], y=upper, name="upper", line_color='#8B4513')
        bolinger_lower = go.Scatter(x=data['Date'], y=lower, name="lower", line_color='#8B4513')
-        candle_stick = go.Candlestick(x=data['Date'], open=data['Open'], high=data['High'], low=data['Low'], close=data['Close'])
-        fig = go.Figure(data=[candle_stick, bolinger_upper, bolinger_lower])
-        fig.update_layout(title="2x")
+        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')
+
+        # 그래프를 그린다.
+        fig = go.Figure(data=[candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check])
+        fig.update_layout(title=day + "_2x")
        fig.show()
+        return
+
+    def simulate(self, stock_code, day):
+        result = {"check": set(),
+                  "time": [],
+                  "open": [],
+                  "close": [],
+                  "high": [],
+                  "low": [],
+                  "vol": []}
+
+        # 데이터를 가지고 온다.
+        self.getCSV(day+".csv", day, result)
+
+        # 가져온 만큼 데이터를 누적해서 파일로 작성한다.
+        self.write(day, result)
+
+        # 분석을 통해서 볼린저밴드 상/하단을 계산한다.
+        data, upper, lower, buy_line, sell_line = self.analyze(result)
+
+        # 그래프를 그린다.
+        self.draw(data, upper, lower, buy_line, sell_line)
+
+        return
+
+    def buyRealTime(self, stock_code, day):
+        result = {"check": set(),
+                  "time": [],
+                  "open": [],
+                  "close": [],
+                  "high": [],
+                  "low": [],
+                  "vol": []}
+
+        # 데이터를 가지고 온다.
+        self.getRealTime(stock_code, day, result)
+
+        # 가져온 만큼 데이터를 누적해서 파일로 작성한다.
+        self.write(day, result)
+
+        # 분석을 통해서 볼린저밴드 상/하단을 계산한다.
+        data, upper, lower, buy_line, sell_line = self.analyze(result)
+
+        # 그래프를 그린다.
+        self.draw(data, upper, lower, buy_line, sell_line)

        return

@@ -417,13 +496,30 @@ if __name__ == "__main__":

    stock_code = "252670"
    day = datetime.today().strftime("%Y%m%d")
-    day = '20210917'

    hts = HTS()
    #hts.all_stocks()
    #hts.getChartData(stock_code)
    #hts.currentStock(stock_code)
-    hts.printStockData(stock_code, day)
+    #hts.printStockData(stock_code, day)
+
+    """
+    day = '20210909'
+    hts.simulate(stock_code, day)
+    day = '20210910'
+    hts.simulate(stock_code, day)
+    day = '20210913'
+    hts.simulate(stock_code, day)
+    day = '20210914'
+    hts.simulate(stock_code, day)
+    day = '20210915'
+    hts.simulate(stock_code, day)
+    day = '20210916'
+    hts.simulate(stock_code, day)
+    day = '20210917'
+    hts.simulate(stock_code, day)
+    """
+
+    hts.buyRealTime(stock_code, day)

-    #hts.buyRealTime(stock_code, day)
    print ("done...")
--- a/hts/data_s.csv
+++ b/hts/data_s.csv
--- a/hts/data_s_1.csv
+++ b/hts/data_s_1.csv
--- a/hts/data_s_2.csv
+++ b/hts/data_s_2.csv