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@ -9,7 +9,6 @@ Author: luxuemin2108@gmail.com
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-----
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Copyright (c) 2020 Camel Lu
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'''
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import time
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import re
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import decimal
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from pprint import pprint
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@ -19,6 +18,7 @@ from fund_info.statistic import FundStatistic
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from utils.index import get_last_quarter_str, get_stock_market, find_from_list_of_dict, update_xlsx_file
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from utils.file_op import read_dir_all_file
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def get_fund_code_pool(condition_dict):
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each_statistic = FundStatistic()
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morning_star_rating_5_condition = {
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@ -44,12 +44,15 @@ def stocks_compare(stock_list, *, market=None, quarter_index=None, is_A_stock=No
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quarter_index = get_last_quarter_str(2)
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print("比较-->quarter_index", quarter_index)
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last_quarter_input_file = './outcome/数据整理/strategy/all_stock_rank/' + quarter_index + '.xlsx'
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data_last_quarter = pd.read_excel(io=last_quarter_input_file, engine="openpyxl", dtype={"代码": np.str}, sheet_name=None)
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last_quarter_input_file = './outcome/数据整理/strategy/all_stock_rank/' + \
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quarter_index + '.xlsx'
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data_last_quarter = pd.read_excel(
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io=last_quarter_input_file, engine="openpyxl", dtype={"代码": np.str}, sheet_name=None)
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if market:
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df_data_target_market = data_last_quarter.get(market)
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df_data_target_market[quarter_index + '持有数量（只）'] = df_data_target_market[quarter_index + '持有数量（只）'].astype(int)
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df_data_target_market[quarter_index +
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'持有数量（只）'] = df_data_target_market[quarter_index + '持有数量（只）'].astype(int)
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filter_list = []
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for stock in stock_list:
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@ -74,8 +77,10 @@ def stocks_compare(stock_list, *, market=None, quarter_index=None, is_A_stock=No
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target_loc[col_target].iloc[0]), 4)
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diff_holder_count = holder_count - last_holder_count
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diff_holder_asset = holder_asset - last_holder_asset
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diff_holder_count_percent = '{:.2%}'.format(diff_holder_count / last_holder_count) if last_holder_count != 0 else "+∞"
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diff_holder_asset_percent = '{:.2%}'.format(diff_holder_asset / last_holder_asset) if last_holder_asset != 0 else "+∞"
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diff_holder_count_percent = '{:.2%}'.format(
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diff_holder_count / last_holder_count) if last_holder_count != 0 else "+∞"
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diff_holder_asset_percent = '{:.2%}'.format(
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diff_holder_asset / last_holder_asset) if last_holder_asset != 0 else "+∞"
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# flag = '📈' if diff_holder_count > 0 else '📉'
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# if diff_holder_count == 0:
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# flag = '⏸'
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@ -85,10 +90,14 @@ def stocks_compare(stock_list, *, market=None, quarter_index=None, is_A_stock=No
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item_tuple = [stock_code, stock_name, holder_count, last_holder_count,
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diff_holder_count, diff_holder_count_percent, flag_count, holder_asset, last_holder_asset, diff_holder_asset, diff_holder_asset_percent, flag_asset]
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if is_A_stock:
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industry_name_third = stock_holder_detail.get('industry_name_third')
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industry_name_second = stock_holder_detail.get('industry_name_second')
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industry_name_first = stock_holder_detail.get('industry_name_first')
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item_tuple = [*item_tuple, industry_name_third,industry_name_second, industry_name_first]
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industry_name_third = stock_holder_detail.get(
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'industry_name_third')
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industry_name_second = stock_holder_detail.get(
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'industry_name_second')
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industry_name_first = stock_holder_detail.get(
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'industry_name_first')
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item_tuple = [*item_tuple, industry_name_third,
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industry_name_second, industry_name_first]
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# if diff_percent == "+∞" or not float(diff_percent.rstrip('%')) < -20:
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filter_list.append(item_tuple)
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@ -124,13 +133,15 @@ def select_condition_stocks_rank(each_statistic=None, *, quarter_index=None):
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stock_name = stock_name_code[0].split('-', 1)[1]
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stock_count = stock_name_code[1]['count']
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stock_holder_asset = stock_name_code[1]['holder_asset']
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stock_rank_item = [stock_code, stock_name, stock_count, stock_holder_asset]
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stock_rank_item = [stock_code, stock_name,
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stock_count, stock_holder_asset]
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stock_rank_list.append(stock_rank_item)
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df_stock_top_list = pd.DataFrame(stock_rank_list, columns=columns)
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print(df_stock_top_list)
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update_xlsx_file(output_file, df_stock_top_list, quarter_index)
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def t100_stocks_rank(each_statistic=None, *, quarter_index=None):
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# T100权重股排名
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if each_statistic == None:
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@ -140,7 +151,8 @@ def t100_stocks_rank(each_statistic=None, *, quarter_index=None):
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last_quarter_index = get_last_quarter_str(2)
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output_file = './outcome/数据整理/strategy/top100_rank.xlsx'
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sheet_name = quarter_index + '基金重仓股T100'
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columns = ['代码','名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比', '持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降']
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columns = ['代码', '名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比',
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'持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降']
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stock_top_list = each_statistic.all_stock_fund_count(
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quarter_index=quarter_index,
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@ -160,7 +172,8 @@ def all_stocks_rank(each_statistic=None):
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quarter_index = get_last_quarter_str(1)
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print("该quarter_index为", quarter_index)
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last_quarter_index = get_last_quarter_str(2)
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columns = ['代码','名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比', '持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降']
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columns = ['代码', '名称', quarter_index + '持有数量（只）', last_quarter_index + '持有数量（只）', '持有数量环比', '持有数量环比百分比',
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'持有数量升或降', quarter_index + '持有市值（亿元）', last_quarter_index + '持有市值（亿元）', '持有市值环比', '持有市值环比百分比', '持有市值升或降']
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output_file = './outcome/数据整理/strategy/all_stock_rank/' + quarter_index + '.xlsx'
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stock_top_list = each_statistic.all_stock_fund_count(
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@ -180,7 +193,8 @@ def all_stocks_rank(each_statistic=None):
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# 'A股/深证主板'、'A股/创业板'、'A股/上证主板'、'A股/科创板'
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a_condition = bool(re.search(
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"^(00(0|1|2|3)\d{3})|(30(0|1)\d{3})|(60(0|1|2|3|5)\d{3})|68(8|9)\d{3}$", stock_code))
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target_item = find_from_list_of_dict(all_a_stocks_industry_info_list, 'stock_code', stock_code)
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target_item = find_from_list_of_dict(
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all_a_stocks_industry_info_list, 'stock_code', stock_code)
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if a_condition and target_item:
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stock_name_code[1]['industry_name_first'] = target_item.get(
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'industry_name_first')
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@ -252,7 +266,8 @@ def all_stock_holder_detail(each_statistic=None, *, quarter_index=None, threshol
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path = 'A股/科创板'
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else:
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print('stock_name_code', stock_name_code)
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hold_fund_list = sorted(stock[1]['fund_list'], key=lambda x: x['持有市值(亿元)'], reverse=True)
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hold_fund_list = sorted(
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stock[1]['fund_list'], key=lambda x: x['持有市值(亿元)'], reverse=True)
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df_list = pd.DataFrame(hold_fund_list)
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stock_name_code = stock_name_code.replace('-*', '-').replace('/', '-')
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path = './outcome/数据整理/stocks/' + path + '/' + stock_name_code + '.xlsx'
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@ -266,33 +281,33 @@ def get_special_fund_code_holder_stock_detail(each_statistic=None, quarter_index
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if each_statistic == None:
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each_statistic = FundStatistic()
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if quarter_index == None:
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quarter_index = get_last_quarter_str()
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quarter_index = get_last_quarter_str(2)
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print("quarter_index", quarter_index)
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holder_history_list = [
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{
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'001811': {
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'name': '中欧明睿新常态混合A',
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'position': 0.2
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'radio': 0.2
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},
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'001705': {
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'name': '泓德战略转型股票',
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'position': 0.2
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'radio': 0.2
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},
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'163415': {
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'name': '兴全商业模式优选混合',
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'position': 0.2
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'radio': 0.2
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},
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'001043': {
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'name': '工银美丽城镇主题股票A',
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'position': 0.1
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'radio': 0.1
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},
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'000547': {
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'name': '建信健康民生混合',
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'position': 0.1
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'radio': 0.1
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},
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'450001': {
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'name': '国富中国收益混合',
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'position': 0.2
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'radio': 0.2
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},
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},
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# """
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@ -305,40 +320,82 @@ def get_special_fund_code_holder_stock_detail(each_statistic=None, quarter_index
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{
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'001811': {
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'name': '中欧明睿新常态混合A',
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'position': 0.2
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'radio': 0.2
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},
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'001054': {
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'name': '工银新金融股票',
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'position': 0.2
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'radio': 0.2
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},
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'000991': {
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'name': '工银瑞信战略转型主题股票A',
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'position': 0.1
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'radio': 0.1
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},
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'540003': {
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'name': '汇丰晋信动态策略混合A',
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'position': 0.2
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'radio': 0.2
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},
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'000547': {
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'name': '建信健康民生混合',
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'position': 0.1
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'radio': 0.1
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},
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'163409': {
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'name': '兴全绿色投资混合(LOF)',
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'position': 0.2
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'radio': 0.2
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},
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},
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[
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{
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'code': '519002',
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'name': '华安安信消费混合',
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'radio': 0.2
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},
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{
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'code': '001718',
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'name': '工银瑞信物流产业股票',
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'radio': 0.2
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},
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{
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'code': '000991',
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'name': '工银瑞信战略转型主题股票A',
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'radio': 0.1
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},
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{
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'code': '540003',
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'name': '汇丰晋信动态策略混合A',
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'radio': 0.1
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},
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{
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'code': '450001',
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'name': '国富中国收益混合',
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'radio': 0.1
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},
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{
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'code': '000547',
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'name': '建信健康民生混合',
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'radio': 0.1
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},
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{
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'code': '163409',
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'name': '兴全绿色投资混合(LOF)',
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'radio': 0.2
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},
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]
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]
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# 基金组合信息
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fund_portfolio = holder_history_list[1]
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fund_code_pool = list(fund_portfolio.keys())
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holder_stock_industry_list = each_statistic.summary_special_funds_stock_detail(fund_code_pool, quarter_index)
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path = './outcome/数据整理/funds/高分权益基金组合十大持仓明细.xlsx'
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columns = ['基金代码', '基金名称', '基金类型', '基金经理', '基金总资产（亿元）', '基金股票总仓位', '十大股票仓位', '股票代码', '股票名称', '所占仓位', '所处仓位排名', '三级行业', '二级行业', '一级行业']
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fund_portfolio = holder_history_list[2]
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fund_code_pool = [] #list(fund_portfolio.keys())
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for item in fund_portfolio:
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fund_code_pool.append(item.get('code'))
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print("fund_code_pool", fund_code_pool)
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holder_stock_industry_list = each_statistic.summary_special_funds_stock_detail(
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fund_code_pool, quarter_index)
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path = './outcome/数据整理/funds/高分权益基金组合十大持仓明细-加工.xlsx'
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columns = ['基金代码', '基金名称', '基金类型', '基金经理', '基金总资产（亿元）', '基金股票总仓位',
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'十大股票仓位', '股票代码', '股票名称', '所占仓位', '所处仓位排名', '三级行业', '二级行业', '一级行业']
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df_a_list = pd.DataFrame(holder_stock_industry_list, columns=columns)
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# print("df_a_list", df_a_list)
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update_xlsx_file(path, df_a_list, sheet_name='十大持仓明细--' + quarter_index)
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update_xlsx_file(path, df_a_list, sheet_name='十大持仓明细--' + '2022-01')
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def calculate_quarter_fund_count():
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@ -358,11 +415,14 @@ def calculate_quarter_fund_count():
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item_quarter_data = [sheet_name]
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df_cur_sheet = xls.parse(sheet_name)
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item_quarter_data.append(len(df_cur_sheet))
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item_quarter_data.append(round(df_cur_sheet['持有市值(亿元)'].sum(),2))
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item_quarter_data.append(
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round(df_cur_sheet['持有市值(亿元)'].sum(), 2))
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quarter_list.append(item_quarter_data)
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columns = ["日期", "持有数量", '持有市值']
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columns = ["日期", "持有数量(只)", '持有市值(亿元)']
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df_quarter_list = pd.DataFrame(quarter_list, columns=columns)
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update_xlsx_file(path, df_quarter_list, sum_column_name)
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if __name__ == '__main__':
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# 所有股票的基金持仓细节
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# all_stock_holder_detail(each_statistic)
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@ -374,7 +434,7 @@ if __name__ == '__main__':
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# t100_stocks_rank(each_statistic=each_statistic)
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# 获取某些基金的十大持仓股票信息
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# get_special_fund_code_holder_stock_detail(each_statistic)
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get_special_fund_code_holder_stock_detail()
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# calculate_quarter_fund_count()
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select_condition_stocks_rank()
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jackluson
3 years ago