| | |
| | | @return: |
| | | """ |
| | | return abs(close - cls.calculate_upper_limit_price(code, |
| | | pre_close)) < 0.01 |
| | | pre_close)) < 0.01 |
| | | |
| | | @classmethod |
| | | def get_third_limit_up_days(cls, k_data, days): |
| | |
| | | if i + 3 >= len(k_data): |
| | | continue |
| | | # 判断连续三日涨停且第四日非涨停 |
| | | if cls.__is_limit_up(k_data[i]["sec_id"], k_data[i]['close'], k_data[i]["pre_close"]): |
| | | if cls.__is_limit_up(k_data[i+1]["sec_id"], k_data[i+1]['close'], k_data[i+1]["pre_close"]): |
| | | if cls.__is_limit_up(k_data[i+2]["sec_id"], k_data[i+2]['close'], k_data[i+2]["pre_close"]): |
| | | if not cls.__is_limit_up(k_data[i+3]["sec_id"], k_data[i+3]['close'], k_data[i+3]["pre_close"]): |
| | | count += 1 |
| | | day_count = 3 |
| | | for n in range(day_count + 1): |
| | | if n < day_count: |
| | | if not cls.__is_limit_up(k_data[i + n]["sec_id"], k_data[i + n]['close'], |
| | | k_data[i + n]["pre_close"]): |
| | | # 非涨停 |
| | | break |
| | | else: |
| | | if not cls.__is_limit_up(k_data[i + n]["sec_id"], k_data[i + n]['close'], |
| | | k_data[i + n]["pre_close"]): |
| | | count += 1 |
| | | break |
| | | return count |
| | | |
| | | @classmethod |
| | |
| | | count += 1 |
| | | return count |
| | | |
| | | @classmethod |
| | | def is_too_high_and_not_relase_volume(cls, k_data): |
| | | """ |
| | | 长得太高且没放量:30个交易日内,出现过最低价(最高价之前的交易日)到最高价之间的涨幅≥35%的票,且今日距离最高价那日无涨停/无炸板且>=3板且必须有2连板 |
| | | @param k_data: K线数据列表(近150个交易日,不包含当前交易日,时间倒序) |
| | | @return: 四跌停及以上天数 |
| | | """ |
| | | k_data = k_data[:30] |
| | | code = k_data[0]["sec_id"] |
| | | # 获取最高价信息 |
| | | max_high_price_data = max(k_data, key=lambda x: x["high"]) |
| | | before_datas = [d for d in k_data if d['bob'] < max_high_price_data['bob']] |
| | | after_datas = [d for d in k_data if d['bob'] >= max_high_price_data['bob']] |
| | | if not before_datas: |
| | | return False |
| | | if len(before_datas) > 15: |
| | | # 从最高价日期向前最多看15个交易日 |
| | | before_datas = before_datas[:15] |
| | | min_close_price_data = min(before_datas, key=lambda x: x["close"]) |
| | | if (max_high_price_data['high'] - min_close_price_data['close']) / min_close_price_data['close'] < 0.35: |
| | | # 涨幅小于35% |
| | | return False |
| | | before_k_datas = [d for d in k_data if min_close_price_data['bob'] <= d['bob'] <= max_high_price_data['bob']] |
| | | before_k_datas.sort(key=lambda x: x['bob']) |
| | | |
| | | # [最低价-最高价]日期内有3个板且有两连扳 |
| | | |
| | | continue_2_limit_up_date = None |
| | | for i in range(len(before_k_datas) - 1): |
| | | if cls.__is_limit_up(code, before_k_datas[i]["close"], |
| | | before_k_datas[i]["pre_close"]) and cls.__is_limit_up(code, |
| | | before_k_datas[i + 1]["close"], |
| | | before_k_datas[i + 1][ |
| | | "pre_close"]): |
| | | continue_2_limit_up_date = before_k_datas[i + 1]['bob'][:10] |
| | | break |
| | | if not continue_2_limit_up_date: |
| | | # 无两连板 |
| | | return False |
| | | # 两连板之后是否有炸板/涨停 |
| | | # 取2连板之后的3个交易日 |
| | | temp_k_datas = [d for d in before_k_datas if d['bob'][:10] > continue_2_limit_up_date][:3] |
| | | if len([d for d in temp_k_datas if cls.__is_limit_up(code, d["high"], d["pre_close"])]) < 1: |
| | | # 两连板之后有个涨停/炸板且时间在2连板之后的3个交易日内 |
| | | return False |
| | | |
| | | k_data = [d for d in k_data if d['bob'] > max_high_price_data['bob']] |
| | | # 判断是否涨停过 |
| | | if len([d for d in k_data if cls.__is_limit_up(code, d["high"], d["pre_close"])]) > 0 or len(after_datas) >= 10: |
| | | # 最高价之后有过涨停或者是最高价后10个交易日 |
| | | return False |
| | | return True, f"高价日期:{max_high_price_data['bob'][:10]},低价日期:{min_close_price_data['bob'][:10]},两连扳日期:{continue_2_limit_up_date}" |
| | | |
| | | |
| | | class K60SLineAnalyzer: |
| | | """ |