| | |
| | | |
| | | |
| | | # 获取K线形态 |
| | | # 返回 (15个交易日涨幅是否大于24.9%,是否破前高,是否超跌,是否接近前高,是否N,是否V,是否有形态,天量大阳信息,是否具有辨识度) |
| | | # 返回 (15个交易日涨幅是否大于24.9%,是否破前高,是否超跌,是否接近前高,是否N,是否V,是否有形态,天量大阳信息,是否具有辨识度,近2天有10天内最大量,上个交易日是否炸板) |
| | | def get_k_format(limit_up_price, record_datas): |
| | | p1_data = get_lowest_price_rate(record_datas) |
| | | p1 = p1_data[0] >= 0.249, p1_data[1] |
| | |
| | | |
| | | # 是否具有辨识度 |
| | | p9 = is_special(record_datas) |
| | | p10 = is_latest_10d_max_volume_at_latest_2d(record_datas) |
| | | # 最近5天是否炸板 |
| | | p11 = __is_latest_open_limit_up(record_datas, 5) |
| | | # 30天内是否有涨停 |
| | | p12 = __has_limit_up(record_datas, 30) |
| | | # 最近5天是否跌停 |
| | | p13 = __is_latest_limit_down(record_datas, 5) |
| | | |
| | | return p1, p2, p3, p4, p5, p6, p7, p8, p9 |
| | | return p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12, p13 |
| | | |
| | | |
| | | # 是否具有K线形态 |
| | | def is_has_k_format(limit_up_price, record_datas): |
| | | is_too_high, is_new_top, is_lowest, is_near_new_top, is_n, is_v, has_format, volume_info, is_special = get_k_format( |
| | | is_too_high, is_new_top, is_lowest, is_near_new_top, is_n, is_v, has_format, volume_info, is_special, has_max_volume, open_limit_up, is_limit_up_in_30days, is_latest_limit_down = get_k_format( |
| | | float(limit_up_price), record_datas) |
| | | if not has_format: |
| | | return False, "不满足K线形态" |
| | |
| | | |
| | | |
| | | # 是否涨得太高 |
| | | def is_up_too_high_in_10d(record_datas): |
| | | def is_up_too_high_in_10d_with_limit_up(record_datas): |
| | | datas = copy.deepcopy(record_datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | datas = datas[-10:] |
| | |
| | | return False |
| | | |
| | | |
| | | # 10天内的最高量是否集中在最近两天 |
| | | def is_latest_10d_max_volume_at_latest_2d(record_datas): |
| | | datas = copy.deepcopy(record_datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | datas = datas[-10:] |
| | | max_volume_info = None |
| | | for i in range(0, len(datas)): |
| | | if not max_volume_info: |
| | | max_volume_info = (i, datas[i]["volume"]) |
| | | else: |
| | | if max_volume_info[1] < datas[i]["volume"]: |
| | | max_volume_info = (i, datas[i]["volume"]) |
| | | return len(datas) - max_volume_info[0] <= 2 |
| | | |
| | | |
| | | # 120 天内是否长得太高 |
| | | def is_up_too_high_in_120d(record_datas): |
| | | datas = copy.deepcopy(record_datas) |
| | |
| | | return False |
| | | |
| | | |
| | | # 暂时不使用 |
| | | # 从最近一次涨停开始,是否涨幅过高 |
| | | def is_up_too_high_from_latest_limit_up(record_datas): |
| | | datas = copy.deepcopy(record_datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | datas = datas[-20:] |
| | | datas.reverse() |
| | | today_limit_up_price = round(float(gpcode_manager.get_limit_up_price_by_preprice(datas[0]["close"])), 2) |
| | | max_price = 0 |
| | | limit_up_price = None |
| | | for i in range(0, len(datas)): |
| | | item = datas[i] |
| | | if item['high'] > max_price: |
| | | max_price = item['high'] |
| | | if __is_limited_up(item): |
| | | limit_up_price = item['high'] |
| | | break |
| | | if not limit_up_price: |
| | | return False |
| | | if today_limit_up_price < max_price: |
| | | return False |
| | | if (today_limit_up_price - limit_up_price) / limit_up_price > 0.25: |
| | | return True |
| | | return False |
| | | |
| | | |
| | | # 最近几天是否有最大量 |
| | | def is_have_latest_max_volume(record_datas, day_count): |
| | | datas = copy.deepcopy(record_datas) |
| | |
| | | if len(datas) - max_volume[0] <= day_count: |
| | | return True |
| | | return False |
| | | |
| | | |
| | | # 在最近几天内股价是否长得太高 |
| | | def is_price_too_high_in_days(record_datas, limit_up_price, day_count=5): |
| | | datas = copy.deepcopy(record_datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | datas = datas[0 - day_count:] |
| | | min_price = None |
| | | max_price = None |
| | | for d in datas: |
| | | if min_price is None: |
| | | min_price = d["low"] |
| | | if max_price is None: |
| | | max_price = d["high"] |
| | | if min_price > d["low"]: |
| | | min_price = d["low"] |
| | | if max_price < d["high"]: |
| | | max_price = d["high"] |
| | | # if max_price > float(limit_up_price): |
| | | # return False |
| | | rate = (float(limit_up_price) - min_price) / min_price |
| | | # print(rate) |
| | | if rate >= 0.319: |
| | | return True |
| | | return False |
| | | |
| | | |
| | | # 连续涨停后是否回调不足够 |
| | | def is_continue_limit_up_not_enough_fall_dwon(record_datas): |
| | | # 10 天内是否有连续3板 |
| | | datas = copy.deepcopy(record_datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | datas = datas[0 - 10:] |
| | | limit_up_continue_count_info = None |
| | | max_limit_up_continue_count_info_list = [] # [连续涨停次数,涨停起点] |
| | | |
| | | for i in range(len(datas)): |
| | | item = datas[i] |
| | | if __is_limit_up(item): |
| | | if not limit_up_continue_count_info: |
| | | limit_up_continue_count_info = [1, i] |
| | | else: |
| | | limit_up_continue_count_info[0] += 1 |
| | | else: |
| | | if limit_up_continue_count_info: |
| | | max_limit_up_continue_count_info_list.append(limit_up_continue_count_info) |
| | | limit_up_continue_count_info = None |
| | | max_limit_up_info = None |
| | | for x in max_limit_up_continue_count_info_list: |
| | | if max_limit_up_info is None: |
| | | max_limit_up_info = x |
| | | if max_limit_up_info[0] <= x[0]: |
| | | max_limit_up_info = x |
| | | |
| | | if not max_limit_up_info or max_limit_up_info[0] < 3: |
| | | print("无3连板") |
| | | return False |
| | | start_index = max_limit_up_info[1] |
| | | max_price_info = [0, None] |
| | | for i in range(start_index, len(datas)): |
| | | item = datas[i] |
| | | if item["high"] > max_price_info[0]: |
| | | max_price_info = [item["high"], i] |
| | | # 计算回踩价格 |
| | | lowest_price_threhhold = round((1-0.28) * max_price_info[0], 2) |
| | | for i in range(max_price_info[1] + 1, len(datas)): |
| | | item = datas[i] |
| | | if item["low"] < lowest_price_threhhold: |
| | | print("回踩足够") |
| | | return False |
| | | return True |
| | | |
| | | |
| | | # 是否有涨停 |
| | |
| | | |
| | | def is_new_top(limit_up_price, datas): |
| | | return __is_new_top(float(limit_up_price), datas)[0] |
| | | |
| | | |
| | | def is_near_top(limit_up_price, datas): |
| | | return __is_near_new_top(float(limit_up_price), datas)[0] |
| | | |
| | | |
| | | # 接近新高 |
| | |
| | | return False, '' |
| | | |
| | | |
| | | # 最近几天是否有炸板或跌停 |
| | | def __is_latest_open_limit_up(datas, day_count): |
| | | datas = copy.deepcopy(datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | items = datas[0 - day_count:] |
| | | for item in items: |
| | | limit_up_price = float(gpcode_manager.get_limit_up_price_by_preprice(item["pre_close"])) |
| | | if abs(limit_up_price - item["high"]) < 0.001 and abs(limit_up_price - item["close"]) > 0.001: |
| | | # 炸板 |
| | | return True |
| | | return False |
| | | |
| | | |
| | | def __is_latest_limit_down(datas, day_count): |
| | | datas = copy.deepcopy(datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | items = datas[0 - day_count:] |
| | | for item in items: |
| | | # 是否有跌停 |
| | | limit_down_price = float(gpcode_manager.get_limit_down_price_by_preprice(item["pre_close"])) |
| | | if abs(limit_down_price - item["close"]) < 0.001: |
| | | # 跌停 |
| | | return True |
| | | return False |
| | | |
| | | |
| | | # V字形 |
| | | def __is_v_model(datas): |
| | | datas = copy.deepcopy(datas) |
| | |
| | | return abs(limit_up_price - data["high"]) < 0.001 |
| | | |
| | | |
| | | # 多少天内是否有涨停/曾涨停 |
| | | def __has_limit_up(datas, day_count): |
| | | datas = copy.deepcopy(datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | datas = datas[0 - day_count:] |
| | | if len(datas) >= 1: |
| | | for i in range(0, len(datas)): |
| | | item = datas[i] |
| | | if __is_limit_up(item): |
| | | return True |
| | | return False |
| | | |
| | | |
| | | # 首板涨停溢价率 |
| | | def get_limit_up_premium_rate(datas): |
| | | datas = copy.deepcopy(datas) |
| | |
| | | |
| | | # 是否具有辨识度 |
| | | def is_special(datas): |
| | | # 30个交易日内有≥5天曾涨停且连续涨停数或曾涨停≥2天 |
| | | if len(datas) > 30: |
| | | datas = datas[-30:] |
| | | datas = copy.deepcopy(datas) |
| | | datas.sort(key=lambda x: x["bob"]) |
| | | datas_30 = datas[-30:] |
| | | datas_90 = datas[-90:] |
| | | count = 0 |
| | | # 30个交易日内累计涨停次数≥4次 |
| | | continue_count = 0 |
| | | has_continue = False |
| | | for item in datas_30: |
| | | if __is_limit_up(item): |
| | | continue_count += 1 |
| | | count += 1 |
| | | if continue_count >= 4: |
| | | has_continue = True |
| | | else: |
| | | continue_count = 0 |
| | | if count >= 5 and has_continue: |
| | | return True, "短期辨识度" |
| | | |
| | | count = 0 |
| | | continue_count = 0 |
| | | last_index = -1 |
| | | for i in range(len(datas)): |
| | | if __is_limited_up(datas[i]): |
| | | if last_index >= 0 and i - last_index == 1: |
| | | continue_count += 1 |
| | | has_continue = False |
| | | # 90个交易日内涨停次数≥6次 |
| | | for item in datas_90: |
| | | if __is_limit_up(item): |
| | | continue_count += 1 |
| | | count += 1 |
| | | last_index = i |
| | | if count >= 5 and continue_count > 0: |
| | | return True, '' |
| | | return False, '' |
| | | if continue_count >= 4: |
| | | has_continue = True |
| | | else: |
| | | continue_count = 0 |
| | | if count >= 6 and has_continue: |
| | | return True, "长期辨识度" |
| | | return False, "" |
| | | |
| | | |
| | | if __name__ == "__main__": |