init
This commit is contained in:
dsyoon
121
HTS_etf.py
121
HTS_etf.py
@@ -143,6 +143,8 @@ class HTS_etf(HTS):
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avg120 = [item[0] for item in avg120_list]
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avg240_list = close_df.rolling(window=240).mean().fillna(close[0]).values.tolist()
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avg240 = [item[0] for item in avg240_list]
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avg420_list = close_df.rolling(window=420).mean().fillna(close[0]).values.tolist()
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avg420 = [item[0] for item in avg420_list]
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avg480_list = close_df.rolling(window=480).mean().fillna(close[0]).values.tolist()
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avg480 = [item[0] for item in avg480_list]
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avg1500_list = close_df.rolling(window=1500).mean().fillna(close[0]).values.tolist()
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@@ -214,11 +216,11 @@ class HTS_etf(HTS):
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if "volume_up" in result and "volume_updown_diff" in result:
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for i in range(len(open)):
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STOCK.append({'volume': volume[i], 'volume_down': volume_down[i], 'volume_up': volume_up[i], 'volume_updown_diff': volume_updown_diff[i], 'close': close[i], 'open': open[i], 'high': high[i], 'low': low[i],
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'avg5': avg5[i], 'avg20': avg20[i], 'avg60': avg60[i], 'avg120': avg120[i], 'avg240': avg240[i], 'avg480': avg480[i], 'avg1500': avg1500[i]})
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'avg5': avg5[i], 'avg20': avg20[i], 'avg60': avg60[i], 'avg120': avg120[i], 'avg240': avg240[i], 'avg420': avg420[i], 'avg480': avg480[i], 'avg1500': avg1500[i]})
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else:
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for i in range(len(open)):
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STOCK.append({'volume': volume[i], 'close': close[i], 'open': open[i], 'high': high[i], 'low': low[i],
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'avg5': avg5[i], 'avg20': avg20[i], 'avg60': avg60[i], 'avg120': avg120[i], 'avg240': avg240[i], 'avg480': avg480[i], 'avg1500': avg1500[i]})
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'avg5': avg5[i], 'avg20': avg20[i], 'avg60': avg60[i], 'avg120': avg120[i], 'avg240': avg240[i], 'avg420': avg420[i], 'avg480': avg480[i], 'avg1500': avg1500[i]})
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# stochastic
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stochastic_df = self.stochastic.apply(STOCK, n=30, m=5, t=5)
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@@ -254,7 +256,7 @@ class HTS_etf(HTS):
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"open": open, "high": high, "low": low, "close": close, "volume": volume, "volume_down": volume_down,
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"volume_up": volume_up, "volume_updown_diff": volume_updown_diff,
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"trend": trend, "trend_avg": trend_avg,
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"avg5": avg5, "avg20": avg20, "avg60": avg60, "avg120": avg120, "avg240": avg240, "avg480": avg480,
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"avg5": avg5, "avg20": avg20, "avg60": avg60, "avg120": avg120, "avg240": avg240, "avg420": avg420, "avg480": avg480,
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"avg1500": avg1500,
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"disparity_avg5": disparity_avg5, "disparity_avg20": disparity_avg20,
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"disparity_avg30": disparity_avg30, "disparity_avg60": disparity_avg60,
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@@ -273,7 +275,7 @@ class HTS_etf(HTS):
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"ymd": point_temp,
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"open": open, "high": high, "low": low, "close": close, "volume": volume,
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"trend": trend, "trend_avg": trend_avg,
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"avg5": avg5, "avg20": avg20, "avg60": avg60, "avg120": avg120, "avg240": avg240, "avg480": avg480,
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"avg5": avg5, "avg20": avg20, "avg60": avg60, "avg120": avg120, "avg240": avg240, "avg420": avg420, "avg480": avg480,
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"avg1500": avg1500,
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"disparity_avg5": disparity_avg5, "disparity_avg20": disparity_avg20,
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"disparity_avg30": disparity_avg30, "disparity_avg60": disparity_avg60,
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@@ -422,26 +424,46 @@ class HTS_etf(HTS):
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disparity = {
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'avg': {},
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"limit_top_1": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_bottom_1": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_top_3": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_bottom_3": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_top_5": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_bottom_5": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_top_10": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_bottom_10": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_top_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_bottom_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_top_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_bottom_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_top_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_bottom_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_top_30": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_bottom_30": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_top_40": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_bottom_40": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_top_99": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None},
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"limit_bottom_99": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None, "avg1500": None}
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"limit_top_1": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None,
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"avg1500": None},
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"limit_bottom_1": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None,
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"avg480": None, "avg1500": None},
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"limit_top_3": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None,
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"avg1500": None},
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"limit_bottom_3": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None,
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"avg480": None, "avg1500": None},
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"limit_top_5": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None,
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"avg1500": None},
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"limit_bottom_5": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None,
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"avg480": None, "avg1500": None},
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"limit_top_10": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None,
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"avg1500": None},
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"limit_bottom_10": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None,
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"avg480": None, "avg1500": None},
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"limit_top_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None,
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"avg1500": None},
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"limit_bottom_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None,
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"avg480": None, "avg1500": None},
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"limit_top_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None,
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"avg1500": None},
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"limit_bottom_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None,
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"avg480": None, "avg1500": None},
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"limit_top_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None,
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"avg1500": None},
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"limit_bottom_20": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None,
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"avg480": None, "avg1500": None},
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"limit_top_30": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None,
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"avg1500": None},
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"limit_bottom_30": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None,
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"avg480": None, "avg1500": None},
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"limit_top_98": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None,
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"avg1500": None},
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"limit_bottom_98": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None,
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"avg480": None, "avg1500": None},
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"limit_top_99": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None, "avg480": None,
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"avg1500": None},
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"limit_bottom_99": {"avg5": None, "avg20": None, "avg60": None, "avg120": None, "avg240": None,
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"avg480": None, "avg1500": None}
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}
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disparity['avg'] = avg
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disparity_1500 = sorted(list(set(avg['avg1500'])), reverse=True)
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@@ -452,39 +474,28 @@ class HTS_etf(HTS):
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disparity_20 = sorted(list(set(avg['avg20'])), reverse=True)
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disparity_5 = sorted(list(set(avg['avg5'])), reverse=True)
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poses = [1, 3, 5, 10, 20, 30, 40, 99]
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poses = [1, 3, 5, 10, 20, 30, 98, 99]
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for pos in poses:
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loc = pos
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if pos == 99:
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pos = int(len(disparity_20) * 0.03)
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disparity['limit_top_99']['avg1500'] = disparity_1500[pos - 1]
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disparity['limit_bottom_99']['avg1500'] = disparity_1500[len(disparity_1500) - pos - 1]
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disparity['limit_top_99']['avg480'] = disparity_480[pos]
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disparity['limit_bottom_99']['avg480'] = disparity_480[len(disparity_480) - pos - 1]
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disparity['limit_top_99']['avg240'] = disparity_240[pos]
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disparity['limit_bottom_99']['avg240'] = disparity_240[len(disparity_240) - pos - 1]
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disparity['limit_top_99']['avg120'] = disparity_120[pos]
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disparity['limit_bottom_99']['avg120'] = disparity_120[len(disparity_120) - pos - 1]
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disparity['limit_top_99']['avg60'] = disparity_60[pos]
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disparity['limit_bottom_99']['avg60'] = disparity_60[len(disparity_60) - pos - 1]
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disparity['limit_top_99']['avg20'] = disparity_20[pos]
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disparity['limit_bottom_99']['avg20'] = disparity_20[len(disparity_20) - pos - 1]
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disparity['limit_top_99']['avg5'] = disparity_5[pos]
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disparity['limit_bottom_99']['avg5'] = disparity_5[len(disparity_5) - pos - 1]
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else:
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disparity['limit_top_' + str(pos)]['avg1500'] = disparity_1500[pos - 1]
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disparity['limit_bottom_' + str(pos)]['avg1500'] = disparity_1500[len(disparity_1500) - pos - 1]
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disparity['limit_top_' + str(pos)]['avg480'] = disparity_480[pos]
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disparity['limit_bottom_' + str(pos)]['avg480'] = disparity_480[len(disparity_480) - pos - 1]
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disparity['limit_top_' + str(pos)]['avg240'] = disparity_240[pos]
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disparity['limit_bottom_' + str(pos)]['avg240'] = disparity_240[len(disparity_240) - pos - 1]
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disparity['limit_top_' + str(pos)]['avg120'] = disparity_120[pos]
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disparity['limit_bottom_' + str(pos)]['avg120'] = disparity_120[len(disparity_120) - pos - 1]
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disparity['limit_top_' + str(pos)]['avg60'] = disparity_60[pos]
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disparity['limit_bottom_' + str(pos)]['avg60'] = disparity_60[len(disparity_60) - pos - 1]
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disparity['limit_top_' + str(pos)]['avg20'] = disparity_20[pos]
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disparity['limit_bottom_' + str(pos)]['avg20'] = disparity_20[len(disparity_20) - pos - 1]
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disparity['limit_top_' + str(pos)]['avg5'] = disparity_5[pos]
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disparity['limit_bottom_' + str(pos)]['avg5'] = disparity_5[len(disparity_5) - pos - 1]
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loc = int(len(disparity_20) * 0.03)
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elif pos == 98:
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loc = int(len(disparity_20) * 0.05)
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disparity['limit_top_' + str(pos)]['avg1500'] = disparity_1500[loc - 1]
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disparity['limit_bottom_' + str(pos)]['avg1500'] = disparity_1500[len(disparity_1500) - loc - 1]
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disparity['limit_top_' + str(pos)]['avg480'] = disparity_480[pos]
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disparity['limit_bottom_' + str(pos)]['avg480'] = disparity_480[len(disparity_480) - loc - 1]
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disparity['limit_top_' + str(pos)]['avg240'] = disparity_240[pos]
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disparity['limit_bottom_' + str(pos)]['avg240'] = disparity_240[len(disparity_240) - loc - 1]
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disparity['limit_top_' + str(pos)]['avg120'] = disparity_120[pos]
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disparity['limit_bottom_' + str(pos)]['avg120'] = disparity_120[len(disparity_120) - loc - 1]
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disparity['limit_top_' + str(pos)]['avg60'] = disparity_60[pos]
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disparity['limit_bottom_' + str(pos)]['avg60'] = disparity_60[len(disparity_60) - loc - 1]
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disparity['limit_top_' + str(pos)]['avg20'] = disparity_20[pos]
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disparity['limit_bottom_' + str(pos)]['avg20'] = disparity_20[len(disparity_20) - loc - 1]
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disparity['limit_top_' + str(pos)]['avg5'] = disparity_5[pos]
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disparity['limit_bottom_' + str(pos)]['avg5'] = disparity_5[len(disparity_5) - loc - 1]
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return disparity
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@@ -124,7 +124,8 @@ class BuySellChecker():
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check = False
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duration = 5 + 60
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if duration < i:
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if np.average(data['trend_avg'][i - duration:i]) < data['trend_avg'][i]:
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if np.average(data['trend_avg'][i - duration:i]) < data['trend_avg'][i] and data['avg1500'][i] < \
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data['trend_avg'][i]:
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if np.average(data['avg480'][i - duration:i]) < data['avg480'][i]:
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if data['avg480'][i] < data['trend_avg'][i]:
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@@ -142,20 +143,27 @@ class BuySellChecker():
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buy_type = 'upward'
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check = True
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if data['disparity_avg20'][i] < BUY_LIST['disparity']['limit_bottom_1']['avg20']:
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buy_type = 'disparity_avg20'
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max_value = np.max(data['close'][i - 3000:i])
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min_value = np.min(data['close'][i - 3000:i])
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if 0.1 < (max_value - min_value) / max_value:
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if data['close'][i - 1] < data['trend_avg'][i - 1] and data['trend_avg'][i] < data['close'][i]:
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buy_type = 'trend_close'
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check = True
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if data['disparity_avg20'][i] < BUY_LIST['disparity']['limit_bottom_5']['avg20']:
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buy_type = 'disparity_avg'
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check = True
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if data['disparity_avg60'][i] < BUY_LIST['disparity']['limit_bottom_1']['avg60']:
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buy_type = 'disparity_avg60'
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if data['disparity_avg60'][i] < BUY_LIST['disparity']['limit_bottom_5']['avg60']:
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buy_type = 'disparity_avg'
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check = True
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if data['disparity_avg480'][i] < BUY_LIST['disparity']['limit_bottom_3']['avg480']:
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buy_type = 'disparity_avg1500'
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if data['disparity_avg480'][i] < BUY_LIST['disparity']['limit_bottom_10']['avg480']:
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buy_type = 'disparity_avg'
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check = True
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if data['disparity_avg1500'][i] < BUY_LIST['disparity']['limit_bottom_5']['avg1500']:
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buy_type = 'disparity_avg1500'
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if data['disparity_avg1500'][i] < BUY_LIST['disparity']['limit_bottom_20']['avg1500']:
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buy_type = 'disparity_avg'
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check = True
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if check:
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@@ -176,41 +184,65 @@ class BuySellChecker():
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sell_price, sell_count, sell_type = -1, -1, ''
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check = False
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sell_count_disparity_avg = 0
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sell_count_trend_close = 0
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if 0 < len(BUY_LIST['buy_list']):
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# 매수한지 3시간 이내라면
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if data['ymd'][i] - timedelta(hours=3) < BUY_LIST['buy_list'][-1]['buy_ymd']:
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if data['avg480'][i - 1] <= data['avg420'][i] and data['avg420'][i] < data['avg480'][i]:
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sell_count_trend_close = sum(
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[price['buy_count'] for price in BUY_LIST['buy_list'] if price['buy_type'] == 'trend_close'])
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if 0 < sell_count_trend_close:
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check = True
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# 매수한지 12시간 이내라면
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if data['ymd'][i] - timedelta(hours=12) < BUY_LIST['buy_list'][-1]['buy_ymd']:
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if BUY_LIST['disparity']['limit_top_3']['avg20'] < data['disparity_avg20'][i]:
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sell_count_disparity_avg = sum(
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[price['buy_count'] for price in BUY_LIST['buy_list'] if price['buy_type'] == 'disparity_avg'])
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check = True
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if BUY_LIST['disparity']['limit_top_3']['avg60'] < data['disparity_avg60'][i]:
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sell_count_disparity_avg = sum(
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[price['buy_count'] for price in BUY_LIST['buy_list'] if price['buy_type'] == 'disparity_avg'])
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check = True
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if BUY_LIST['disparity']['limit_top_5']['avg480'] < data['disparity_avg480'][i]:
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sell_count_disparity_avg = sum(
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[price['buy_count'] for price in BUY_LIST['buy_list'] if price['buy_type'] == 'disparity_avg'])
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check = True
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if BUY_LIST['disparity']['limit_top_10']['avg1500'] < data['disparity_avg1500'][i]:
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sell_count_disparity_avg = sum(
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[price['buy_count'] for price in BUY_LIST['buy_list'] if price['buy_type'] == 'disparity_avg'])
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check = True
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else:
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# 매수한지 3시간 이후라면
|
||||
if BUY_LIST['buy_list'][-1]['buy_price'] * 1.002 < data['close'][i]:
|
||||
# 매수한지 12시간 이후라면
|
||||
if BUY_LIST['buy_list'][-1]['buy_price'] * 1.004 < data['close'][i]:
|
||||
|
||||
if BUY_LIST['disparity']['limit_top_99']['avg20'] < data['disparity_avg20'][i]:
|
||||
sell_count_disparity_avg = sum([price['buy_count'] for price in BUY_LIST['buy_list'] if
|
||||
price['buy_type'] == 'disparity_avg'])
|
||||
check = True
|
||||
|
||||
if BUY_LIST['disparity']['limit_top_99']['avg60'] < data['disparity_avg60'][i]:
|
||||
sell_count_disparity_avg = sum([price['buy_count'] for price in BUY_LIST['buy_list'] if
|
||||
price['buy_type'] == 'disparity_avg'])
|
||||
check = True
|
||||
|
||||
if BUY_LIST['disparity']['limit_top_99']['avg480'] < data['disparity_avg480'][i]:
|
||||
sell_count_disparity_avg = sum([price['buy_count'] for price in BUY_LIST['buy_list'] if
|
||||
price['buy_type'] == 'disparity_avg'])
|
||||
check = True
|
||||
|
||||
if BUY_LIST['disparity']['limit_top_99']['avg1500'] < data['disparity_avg1500'][i]:
|
||||
sell_count_disparity_avg = sum([price['buy_count'] for price in BUY_LIST['buy_list'] if
|
||||
price['buy_type'] == 'disparity_avg'])
|
||||
check = True
|
||||
|
||||
if check:
|
||||
sell_price = data['close'][i]
|
||||
sell_count = sum([price['buy_count'] for price in BUY_LIST['buy_list']])
|
||||
sell_count = sell_count_disparity_avg + sell_count_trend_close
|
||||
|
||||
return sell_price, sell_count, sell_type
|
||||
|
||||
@@ -243,7 +275,8 @@ class BuySellChecker():
|
||||
bsLine['buy_type'] = [buy_type]
|
||||
|
||||
if 0 < buy_price:
|
||||
BUY_LIST['buy_list'].append({'buy_ymd': buy_ymd, 'buy_price': buy_price, 'buy_count': buy_count, 'buy_cut': buy_cut, 'buy_type': buy_type})
|
||||
BUY_LIST['buy_list'].append(
|
||||
{'buy_ymd': buy_ymd, 'buy_price': buy_price, 'buy_count': buy_count, 'buy_cut': buy_cut, 'buy_type': buy_type})
|
||||
else:
|
||||
# Type=False, 시뮬레이션 적용
|
||||
bsLine['buy_ymd'] = [-1 for i in range(size)]
|
||||
@@ -273,7 +306,8 @@ class BuySellChecker():
|
||||
bsLine['buy_type'][last_index] = buy_type
|
||||
|
||||
if 0 < buy_price:
|
||||
BUY_LIST['buy_list'].append({'buy_ymd': buy_ymd, 'buy_price': buy_price, 'buy_count': buy_count, 'buy_cut': buy_cut, 'buy_type': buy_type})
|
||||
BUY_LIST['buy_list'].append(
|
||||
{'buy_ymd': buy_ymd, 'buy_price': buy_price, 'buy_count': buy_count, 'buy_cut': buy_cut, 'buy_type': buy_type})
|
||||
|
||||
else:
|
||||
bsLine['buy_price'] = [-1]
|
||||
|
||||
Reference in New Issue
Block a user