From 00731aaad93433d7df85d8deee427e935c76a20e Mon Sep 17 00:00:00 2001 From: dsyoon Date: Tue, 24 Jan 2023 23:00:42 +0900 Subject: [PATCH] init --- hts/BuySellChecker.py | 233 +++++++++++++++++++++++++++++++++++++----- 1 file changed, 206 insertions(+), 27 deletions(-) diff --git a/hts/BuySellChecker.py b/hts/BuySellChecker.py index 39dfd61..f757075 100644 --- a/hts/BuySellChecker.py +++ b/hts/BuySellChecker.py @@ -943,27 +943,68 @@ class BuySellChecker: size = len(data["close"]) bsLine['buy'] = [-1 for i in range(size)] - bsLine['buy_weight'] = [-1.0 for i in range(size)] + bsLine['buy_weight'] = [-1 for i in range(size)] bsLine['sell'] = [-1 for i in range(size)] - bsLine['sell_weight'] = [-1.0 for i in range(size)] + bsLine['sell_weight'] = [-1 for i in range(size)] for i in range(size): if isRealTime: if i < size - 1: continue + """ + # 이전에 산 가격보다 지금 5원이상 떨어졌다면 매도 한다. + price = data['close'][i] if data['close'][i] >= data['open'][i] else data['open'][i] + if self.checkBelow5WonFromPreviousBuyPrice(i, data, price): + data['sell'][i] = price + bsLine['sell'][i] = price + bsLine['sell_weight'][i] = 50 + return bsLine, data + """ + + """ + # middle line에 맞다은 적 없이, low line에 붙었거나 아래에 있었던 캔들의 높은 가격을 얻어옴 + buy, buy_weight = self.getBuyPriceAndWeight_Envelope(i, data) + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = buy_weight + return bsLine, data + """ + + + if 0 < data['gradients_avg60'][i] < 0.001: + if data['high'][i] < data['envelope_middle'][i]: + if -0.015 < data['gradients_avg5'][i] and -0.007 < data['gradients_avg20'][i]: + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 10 + if i > 10: - if data['avg5'][i-1] < data['avg20'][i-1] and data['avg20'][i] < data['avg5'][i]: - buy = data['close'][i] + if ( + data['gradients_avg60'][i - 10] > 0 and data['gradients_avg60'][i - 9] > 0 and data['gradients_avg60'][i - 8] > 0 and + data['gradients_avg60'][i - 7] > 0 and data['gradients_avg60'][i - 6] > 0 and data['gradients_avg60'][i - 5] > 0 and + data['gradients_avg60'][i - 4] > 0 and data['gradients_avg60'][i - 3] > 0 and data['gradients_avg60'][i - 2] > 0 and + data['gradients_avg60'][i - 1] > 0 and data['gradients_avg60'][i] < 0 + ): + if data['disparity'][i] < 3: + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 10 + + if i > 10: + if data['disparity_avg60'][i] < 65: + buy = data['low'][i] data['buy'][i] = buy bsLine['buy'][i] = buy - bsLine['buy_weight'][i] = 3.0 + bsLine['buy_weight'][i] = 20 if data['slow_k'][i] < 3: - sell = data['close'][i] - data['sell'][i] = sell - bsLine['sell'][i] = sell - bsLine['sell_weight'][i] = 100.0 + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 10 return bsLine, data @@ -974,9 +1015,9 @@ class BuySellChecker: size = len(data["close"]) bsLine['buy'] = [-1 for i in range(size)] - bsLine['buy_weight'] = [-1.0 for i in range(size)] + bsLine['buy_weight'] = [-1 for i in range(size)] bsLine['sell'] = [-1 for i in range(size)] - bsLine['sell_weight'] = [-1.0 for i in range(size)] + bsLine['sell_weight'] = [-1 for i in range(size)] for i in range(size): if isRealTime: @@ -984,17 +1025,24 @@ class BuySellChecker: continue if i > 10: - if data['avg5'][i - 1] < data['avg20'][i - 1] and data['avg20'][i] < data['avg5'][i]: - buy = data['close'][i] + if data['disparity_avg60'][i] < 60: + buy = data['low'][i] data['buy'][i] = buy bsLine['buy'][i] = buy - bsLine['buy_weight'][i] = 3.0 + bsLine['buy_weight'][i] = 15 - if data['slow_k'][i] < 3: - sell = data['close'][i] - data['sell'][i] = sell - bsLine['sell'][i] = sell - bsLine['sell_weight'][i] = 100.0 + if data['macd'][i] < -1000: + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 15 + + if data['slow_k'][i] < 7: + if data['slow_d'][i] < data['slow_k'][i]: + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 5 return bsLine, data @@ -1023,23 +1071,154 @@ class BuySellChecker: bsLine['sell'] = [-1 for i in range(size)] bsLine['sell_weight'] = [-1 for i in range(size)] + gap_interval = analyzed_day + gap_state = False for i in range(size): if isRealTime: if i < size - 1: continue if i > 10: - if data['avg5'][i - 1] < data['avg20'][i - 1] and data['avg20'][i] < data['avg5'][i]: - buy = data['close'][i] + # 만약 전일 저가와 오늘 종의 차이가 1만원이 넘으면 향후 60일은 분석하지 않는다. + if data['high'][i] < int(data['low'][i-1] * 0.7): + gap_state = True + gap_interval -= 1 + continue + if gap_state: + if gap_interval <= 0: + gap_state = False + gap_interval = 60 + else: + gap_interval -= 1 + continue + + if data['disparity'][i] < 2: + check = True + for l in range(i-3, i): + if ( + data['gradients_avg60'][l-1] > data['gradients_avg60'][l] or + data['gradients_avg20'][l-1] > data['gradients_avg20'][l] or + data['gradients_low'][l-1] > data['gradients_low'][l] or + data['disparity_avg5'][l-1] > data['disparity_avg5'][l] or + data['disparity'][l-1] < data['disparity'][l] + ): + check = False + break + if check and 99 < sum(data['disparity_avg5'][i-4:i+1])/5 < 100 and 99 < sum(data['disparity_avg60'][i-4:i+1])/5 < 100: + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 20 + + check = True + for l in range(i - 2, i): + if ( + data['gradients_avg60'][l - 1] > data['gradients_avg60'][l] or + data['gradients_low'][l - 1] > data['gradients_low'][l] + ): + check = False + break + if ( + check and + -0.0011 < data['gradients_low'][i] < 0 and -0.007 < data['gradients_avg5'][i] < 0.001 and + -0.0012 < data['gradients_avg60'][i] < 0 and + 98.90 < data['disparity_avg5'][i] < 101 + ): + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 20 + + check = True + for l in range(i - 6, i): + if ( + data['gradients_avg60'][l - 1] < data['gradients_avg60'][l] or + data['gradients_avg20'][l - 1] < data['gradients_avg20'][l] or + data['gradients_low'][l - 1] < data['gradients_low'][l] or + -0.039 < data['gradients_low'][l - 1] < -0.35 or + -0.05 < data['gradients_avg20'][l - 1] < -0.30 or + -0.40 < data['gradients_avg60'][l - 1] < -0.30 + ): + check = False + break + if check and 99 < min (data['disparity_avg5'][i - 6:i]) < max (data['disparity_avg5'][i - 6:i]) < 101: + buy = data['low'][i] data['buy'][i] = buy bsLine['buy'][i] = buy - bsLine['buy_weight'][i] = 3.0 + bsLine['buy_weight'][i] = 20 + + check = True + for l in range(i - 3, i): + if ( + data['gradients_low'][l - 1] < data['gradients_low'][l] or + data['gradients_avg60'][l - 1] < data['gradients_avg60'][l] or + data['gradients_avg20'][l - 1] < data['gradients_avg20'][l] or + 0.01 < data['gradients_low'][l - 1] < 0.21 or + -0.09 < data['gradients_avg20'][l - 1] < -0.002 or + 0.01 < data['gradients_avg60'][l - 1] < 0.021 + ): + check = False + break + if check: + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 20 + + + if (data['disparity'][i] < 5 and 99.0 < data['disparity_avg60'][i] < 99.1 and + -0.009 < data['gradients_avg60'][i] < -0.008 and 0.015 < data['gradients_avg20'][i] < 0.016 and + -0.006 < data['gradients_avg5'][i] < -0.005 and -0.009 < data['gradients_low'][i] < -0.008): + check = True + for l in range(i-5, i): + if ( + data['gradients_avg60'][l-1] > data['gradients_avg60'][l] or + data['gradients_low'][l-1] > data['gradients_low'][l] or + data['disparity'][l - 1] < data['disparity'][l] + ): + check = False + break + if check: + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 20 + + if data['macd'][i] < -4000: + if data['macd'][i-1] < data['macd'][i]: + if not self.notBuy(data, i) and data['slow_k'][i] < 30: + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 20 + + # macd 이전에 없던 바닥인 경우 상승할 찰나 매수 + if data['macds'][i-1] < min(data['macds'][:i-1]): + if data['macds'][i-1] < data['macds'][i]: + if not self.notBuy(data, i) and data['slow_k'][i] < 30: + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 20 + + if ( + 98 < data['disparity_avg5'][i] < 100 and data['disparity_avg20'][i] < 93.5 and data['disparity_avg60'][i] < 89 and + -0.014 < data['gradients_avg60'][i] < -0.013 and -0.03 < data['gradients_avg20'][i] < -0.02 and -0.014 < data['gradients_low'][i] < -0.013 and + data['slow_k'][i] < 11 + ): + if not self.notBuy(data, i): + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 20 + + + if data['slow_k'][i]<20 and data['slow_k'][i-1] < data['slow_d'][i-1] and data['slow_d'][i] < data['slow_k'][i]: + buy = data['low'][i] + data['buy'][i] = buy + bsLine['buy'][i] = buy + bsLine['buy_weight'][i] = 30 - if data['slow_k'][i] < 3: - sell = data['close'][i] - data['sell'][i] = sell - bsLine['sell'][i] = sell - bsLine['sell_weight'][i] = 100.0 return bsLine, data