init
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dsyoon
@@ -50,9 +50,14 @@ class Simulation (HTS):
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'volume': 'int',
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'avg5': 'float',
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'avg20': 'float',
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'avg30': 'float',
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'avg60': 'float',
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'avg120': 'float',
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'avg200': 'float',
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'disparity_avg5': 'float',
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'disparity_avg20': 'float',
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'disparity_avg60': 'float',
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'disparity_avg120': 'float',
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'disparity_avg200': 'float',
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'fast_k': 'float',
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'slow_k': 'float',
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'slow_d': 'float',
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@@ -84,11 +89,11 @@ class Simulation (HTS):
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sell_check = go.Scatter(x=data['date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0))
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upper = go.Scatter(x=data['date'], y=data["upper"], name="upper", line_color='#000000')
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lower = go.Scatter(x=data['date'], y=data["lower"], name="lower", line_color='#000000')
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avg5 = go.Scatter(x=data['date'], y=data["avg5"], name="avg5", line_color='#8F8203')
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avg20 = go.Scatter(x=data['date'], y=data["avg20"], name="avg20", line_color='#089B5B')
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avg30 = go.Scatter(x=data['date'], y=data["avg30"], name="avg30", line_color='#ff00ff')
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avg60 = go.Scatter(x=data['date'], y=data["avg60"], name="avg60", line_color='#1469F4')
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avg120 = go.Scatter(x=data['date'], y=data["avg120"], name="avg120", line_color='#000000')
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avg5 = go.Scatter(x=data['date'], y=data["avg5"], name="avg5", line_color='#F81191')
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avg20 = go.Scatter(x=data['date'], y=data["avg20"], name="avg20", line_color='#097F19')
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avg60 = go.Scatter(x=data['date'], y=data["avg60"], name="avg60", line_color='#671BEA')
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avg120 = go.Scatter(x=data['date'], y=data["avg120"], name="avg120", line_color='#DFB809')
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avg200 = go.Scatter(x=data['date'], y=data["avg200"], name="avg200", line_color='#000000')
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laggingSpan = go.Scatter(x=data['date'], y=data["laggingSpan"], name='laggingSpan', line_color='#B50ABB')
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changeLine = go.Scatter(x=data['date'], y=data["changeLine"], name='changeLine', line_color='#14A200')
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baseLine = go.Scatter(x=data['date'], y=data["baseLine"], name='baseLine', line_color='#CF6E0D')
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@@ -97,11 +102,11 @@ class Simulation (HTS):
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#volume_line = go.Scatter(x=data['date'], y=data["volume"], mode='lines', name='volume')
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volume_line = go.Bar(x=data['date'], y=data["volume"], marker_color='red', name='volume')
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disparity_avg5 = go.Scatter(x=data['date'], y=data["disparity_avg5"], name="disparity_avg5", line_color='#8F8203')
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disparity_avg10 = go.Scatter(x=data['date'], y=data["disparity_avg10"], name="disparity_avg10", line_color='#089B5B')
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disparity_avg20 = go.Scatter(x=data['date'], y=data["disparity_avg20"], name="disparity_avg20", line_color='#ff00ff')
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disparity_avg60 = go.Scatter(x=data['date'], y=data["disparity_avg60"], name="disparity_avg60", line_color='#1469F4')
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disparity_avg120 = go.Scatter(x=data['date'], y=data["disparity_avg120"], name="disparity_avg120", line_color='#000000')
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disparity_avg5 = go.Scatter(x=data['date'], y=data["disparity_avg5"], name="disparity_avg5", line_color='#F81191')
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disparity_avg20 = go.Scatter(x=data['date'], y=data["disparity_avg20"], name="disparity_avg20", line_color='#097F19')
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disparity_avg60 = go.Scatter(x=data['date'], y=data["disparity_avg60"], name="disparity_avg60", line_color='#671BEA')
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disparity_avg120 = go.Scatter(x=data['date'], y=data["disparity_avg120"], name="disparity_avg120", line_color='#DFB809')
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disparity_avg200 = go.Scatter(x=data['date'], y=data["disparity_avg200"], name="disparity_avg200", line_color='#000000')
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macd_line = go.Scatter(x=data['date'], y=data["macd"], line=dict(color='red', width=2), name='macd')
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macd_s_line = go.Scatter(x=data['date'], y=data["macds"], line=dict(dash='dashdot', color='black', width=2), name='macds')
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@@ -114,9 +119,9 @@ class Simulation (HTS):
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rsi_line = go.Scatter(x=data['date'], y=data["rsi"], line=dict(color='red', width=2), name='rsi')
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rsis_line = go.Scatter(x=data['date'], y=data["rsis"], line=dict(dash='dashdot', color='black', width=2), name='rsis')
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candle_data = [candle_stick, upper, lower, avg5, avg20, avg30, avg60, avg120, buy_check, sell_check, laggingSpan, changeLine, baseLine]
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candle_data = [candle_stick, upper, lower, avg5, avg20, avg60, avg120, avg200, buy_check, sell_check, laggingSpan, changeLine, baseLine]
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volume_data = [volume_line]
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disparity_data = [disparity_avg5, disparity_avg10, disparity_avg20, disparity_avg60, disparity_avg120]
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disparity_data = [disparity_avg5, disparity_avg20, disparity_avg60, disparity_avg120, disparity_avg200]
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macd_data = [macd_line, macd_s_line, macd_o_line]
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stochastic_data = [slow_k_line, slow_d_line]
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rsi_data = [rsi_line, rsis_line]
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@@ -191,23 +196,24 @@ class Simulation (HTS):
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for given_day in stock_codes[stock_code]:
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LAST_DATA = self.stock2Vector.getLastData(stock_code, given_day)
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result = self.stock2Vector.getRealTime(stock_code, given_day, LAST_DATA)
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result_5 = self.makeTickData(result, mins=5)
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result_30 = self.makeTickData(result, mins=30)
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#result_5 = self.makeTickData(result, mins=5)
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#result_30 = self.makeTickData(result, mins=30)
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data = self.buySellChecker.analyze(result)
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data.drop(data.index[:len(data) - analyzed_day], inplace=True)
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# 이동평균, RSI, MACD, 일목균형, 볼린저밴드 상/하단을 계산한다.
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data_5 = self.buySellChecker.analyze(result_5)
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#data_5 = self.buySellChecker.analyze(result_5)
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# 분석일 데이터만 활용한다 (이전 데이터는 제거)
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data_5.drop(data_5.index[:len(data_5) - analyzed_day], inplace=True)
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#data_5.drop(data_5.index[:len(data_5) - analyzed_day], inplace=True)
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data_30 = self.buySellChecker.analyze(result_30)
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#data_30 = self.buySellChecker.analyze(result_30)
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# 분석일 데이터만 활용한다 (이전 데이터는 제거)
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data_30.drop(data_30.index[:len(data_30) - analyzed_day], inplace=True)
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#data_30.drop(data_30.index[:len(data_30) - analyzed_day], inplace=True)
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# 사야 할 시점과 팔아야 할 시점을 체크한다.
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bsLine = self.buySellChecker.checkTransaction(stock_code, data, data_5, data_30, isRealTime=False)
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#bsLine = self.buySellChecker.checkTransaction(stock_code, data, data_5, data_30, isRealTime=False)
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bsLine = self.buySellChecker.checkTransaction(stock_code, data, None, None, isRealTime=False)
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# 그래프를 그린다.
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self.draw(stock_code, given_day, data, bsLine)
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@@ -227,10 +233,10 @@ if __name__ == "__main__":
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# to check bying
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stock_codes = {
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"252670": [
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'20220901', '20220902', '20220905', '20220906', '20220907', '20220908','20220913','20220914','20220915','20220916'
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'20220901', '20220902', '20220905', '20220906'
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],
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"122630": [
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'20220901', '20220902', '20220905', '20220906', '20220907', '20220908', '20220913', '20220914', '20220915', '20220916'
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'20220901', '20220902', '20220905', '20220906'
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]
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}
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#simulation.simulate(stock_codes)
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