├── .gitignore
├── LICENSE
├── README.md
├── __init__.py
├── analysis.ipynb
├── fund_info.py
├── fund_list.py
├── main.py
├── output
├── fund_info
│ └── __init__.py
└── fund_list
│ └── __init__.py
├── requirements.txt
├── strategy.py
└── tool.py
/.gitignore:
--------------------------------------------------------------------------------
1 | __pycache__
2 | .vscode
3 | output/*
4 | venv
--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
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574 | version or of any later version published by the Free Software
575 | Foundation. If the Program does not specify a version number of the
576 | GNU General Public License, you may choose any version ever published
577 | by the Free Software Foundation.
578 |
579 | If the Program specifies that a proxy can decide which future
580 | versions of the GNU General Public License can be used, that proxy's
581 | public statement of acceptance of a version permanently authorizes you
582 | to choose that version for the Program.
583 |
584 | Later license versions may give you additional or different
585 | permissions. However, no additional obligations are imposed on any
586 | author or copyright holder as a result of your choosing to follow a
587 | later version.
588 |
589 | 15. Disclaimer of Warranty.
590 |
591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
599 |
600 | 16. Limitation of Liability.
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610 | SUCH DAMAGES.
611 |
612 | 17. Interpretation of Sections 15 and 16.
613 |
614 | If the disclaimer of warranty and limitation of liability provided
615 | above cannot be given local legal effect according to their terms,
616 | reviewing courts shall apply local law that most closely approximates
617 | an absolute waiver of all civil liability in connection with the
618 | Program, unless a warranty or assumption of liability accompanies a
619 | copy of the Program in return for a fee.
620 |
621 | END OF TERMS AND CONDITIONS
622 |
623 | How to Apply These Terms to Your New Programs
624 |
625 | If you develop a new program, and you want it to be of the greatest
626 | possible use to the public, the best way to achieve this is to make it
627 | free software which everyone can redistribute and change under these terms.
628 |
629 | To do so, attach the following notices to the program. It is safest
630 | to attach them to the start of each source file to most effectively
631 | state the exclusion of warranty; and each file should have at least
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633 |
634 |
635 | Copyright (C)
636 |
637 | This program is free software: you can redistribute it and/or modify
638 | it under the terms of the GNU General Public License as published by
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640 | (at your option) any later version.
641 |
642 | This program is distributed in the hope that it will be useful,
643 | but WITHOUT ANY WARRANTY; without even the implied warranty of
644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
645 | GNU General Public License for more details.
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647 | You should have received a copy of the GNU General Public License
648 | along with this program. If not, see .
649 |
650 | Also add information on how to contact you by electronic and paper mail.
651 |
652 | If the program does terminal interaction, make it output a short
653 | notice like this when it starts in an interactive mode:
654 |
655 | Copyright (C)
656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
657 | This is free software, and you are welcome to redistribute it
658 | under certain conditions; type `show c' for details.
659 |
660 | The hypothetical commands `show w' and `show c' should show the appropriate
661 | parts of the General Public License. Of course, your program's commands
662 | might be different; for a GUI interface, you would use an "about box".
663 |
664 | You should also get your employer (if you work as a programmer) or school,
665 | if any, to sign a "copyright disclaimer" for the program, if necessary.
666 | For more information on this, and how to apply and follow the GNU GPL, see
667 | .
668 |
669 | The GNU General Public License does not permit incorporating your program
670 | into proprietary programs. If your program is a subroutine library, you
671 | may consider it more useful to permit linking proprietary applications with
672 | the library. If this is what you want to do, use the GNU Lesser General
673 | Public License instead of this License. But first, please read
674 | .
675 |
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 | # fundSpider
2 | 爬取天天基金数据
3 |
4 | ## 获取全量基金信息(基金代码、基金名、类型...)
5 | 截止2019-09-21 共有8966只基金
6 |
7 | ```python
8 | import fund_list
9 | # dataframe
10 | fund_list.get_fund_df()
11 | # list
12 | fund_list.get_fund_list()
13 | ```
14 |
15 | ## 获取基金指定日期内单位净值、累计净值、日增长率等
16 | ```python
17 | import fund_info
18 | from datetime import datetime
19 | # 招商中证白酒指数分级
20 | info = fund_info.FuncInfo(code=161725)
21 | # 爬取9.1~9.20的涨跌信息
22 | info.load_net_value_info(datetime(2018, 9, 1), datetime(2019, 9, 20))
23 | # 9.20的单位净值、累计净值、日增长率
24 | # 必须先调用load_net_value_info
25 | date = "2019-09-20"
26 | info.get_unit_value(date)
27 | info.get_cumulative_value(date)
28 | info.get_daily_growth_rate(date)
29 | # dataframe
30 | df = info.get_data_frame()
31 | ```
32 |
33 | ## 爬取所有基金以及相应单位净值、累计净值、日增长率等
34 | 数据以csv格式保存在output/csv_data目录下
35 |
36 | 默认2000-01-01~2019-09-20, 大概耗时1h
37 | ```shell
38 | python main.py
39 | ```
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/__init__.py:
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https://raw.githubusercontent.com/luricheng/fundSpider/2c878a955fd8be05b328b442b0d516855e2a24ee/__init__.py
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/analysis.ipynb:
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1 | {
2 | "cells": [
3 | {
4 | "cell_type": "code",
5 | "execution_count": 1,
6 | "metadata": {
7 | "collapsed": true,
8 | "pycharm": {
9 | "is_executing": false
10 | }
11 | },
12 | "outputs": [],
13 | "source": [
14 | "import sys\n",
15 | "base_path = \"/home/luricheng/PycharmProjects/fundSpider\"\n",
16 | "sys.path.append(base_path)"
17 | ]
18 | },
19 | {
20 | "cell_type": "code",
21 | "execution_count": 2,
22 | "outputs": [],
23 | "source": [
24 | "from tool import Tool\n",
25 | "from strategy import Strategy\n",
26 | "import numpy as np\n",
27 | "# from tqdm import tqdm"
28 | ],
29 | "metadata": {
30 | "collapsed": false,
31 | "pycharm": {
32 | "name": "#%%\n",
33 | "is_executing": false
34 | }
35 | }
36 | },
37 | {
38 | "cell_type": "code",
39 | "execution_count": 3,
40 | "outputs": [
41 | {
42 | "name": "stdout",
43 | "text": [
44 | "total fund: 4301\n"
45 | ],
46 | "output_type": "stream"
47 | }
48 | ],
49 | "source": [
50 | "fund_dict = Tool.load_fund_info_by_type(base_path=base_path)\n",
51 | "print(\"total fund: %s\" % len(fund_dict))"
52 | ],
53 | "metadata": {
54 | "collapsed": false,
55 | "pycharm": {
56 | "name": "#%%\n",
57 | "is_executing": false
58 | }
59 | }
60 | },
61 | {
62 | "cell_type": "code",
63 | "execution_count": 15,
64 | "outputs": [
65 | {
66 | "name": "stdout",
67 | "text": [
68 | "strategy_res_dict len: 2719\n"
69 | ],
70 | "output_type": "stream"
71 | }
72 | ],
73 | "source": [
74 | "invest_time = 120\n",
75 | "strategy_res_dict = {}\n",
76 | "expect_profit_rate = 0.03\n",
77 | "for k, v in fund_dict.items():\n",
78 | " value_list = Tool.get_value_list(v)\n",
79 | " if len(value_list) - 365 > invest_time:\n",
80 | " end_idx = len(value_list) - 365\n",
81 | " start_idx = end_idx - invest_time\n",
82 | " strategy_res_dict[k] = Strategy.bottom_suction_high_throw(value_list,\n",
83 | " start_idx,\n",
84 | " end_idx,\n",
85 | " take_profit_rate=expect_profit_rate)\n",
86 | " # assert strategy_res_dict[k] is not None\n",
87 | "print(\"strategy_res_dict len: %s\" % len(strategy_res_dict))"
88 | ],
89 | "metadata": {
90 | "collapsed": false,
91 | "pycharm": {
92 | "name": "#%%\n",
93 | "is_executing": false
94 | }
95 | }
96 | },
97 | {
98 | "cell_type": "code",
99 | "execution_count": 16,
100 | "outputs": [
101 | {
102 | "name": "stdout",
103 | "text": [
104 | "profit_rate:\n\tmean: 0.026267830594902473, \n\tmax: 8.889860674865464, \n\tmin: -0.14285379837719955\ntotal_cost:\n\tmean: 276.65318131666055, \n\tmax: 1220, \n\tmin: 100\ntime_cost:\n\tmean: 50.111805810959915, \n\tmax: 119, \n\tmin: 2\n"
105 | ],
106 | "output_type": "stream"
107 | }
108 | ],
109 | "source": [
110 | "def fmt_mean_max_min(ls, title):\n",
111 | " return \"%s:\\n\\tmean: %s, \\n\\tmax: %s, \\n\\tmin: %s\" % (title, np.mean(ls), np.max(ls), np.min(ls))\n",
112 | " \n",
113 | "profit_rate_list = [v.get(\"profit_rate\") for v in strategy_res_dict.values()]\n",
114 | "cost_list = [v.get(\"total_cost\") for v in strategy_res_dict.values()]\n",
115 | "time_list = [v.get(\"cost_time\") for v in strategy_res_dict.values()]\n",
116 | "print(fmt_mean_max_min(profit_rate_list, \"profit_rate\"))\n",
117 | "print(fmt_mean_max_min(cost_list, \"total_cost\"))\n",
118 | "print(fmt_mean_max_min(time_list, \"time_cost\"))"
119 | ],
120 | "metadata": {
121 | "collapsed": false,
122 | "pycharm": {
123 | "name": "#%%\n",
124 | "is_executing": false
125 | }
126 | }
127 | },
128 | {
129 | "cell_type": "code",
130 | "execution_count": null,
131 | "outputs": [],
132 | "source": [
133 | "\n"
134 | ],
135 | "metadata": {
136 | "collapsed": false,
137 | "pycharm": {
138 | "name": "#%%\n"
139 | }
140 | }
141 | }
142 | ],
143 | "metadata": {
144 | "language_info": {
145 | "codemirror_mode": {
146 | "name": "ipython",
147 | "version": 2
148 | },
149 | "file_extension": ".py",
150 | "mimetype": "text/x-python",
151 | "name": "python",
152 | "nbconvert_exporter": "python",
153 | "pygments_lexer": "ipython2",
154 | "version": "2.7.6"
155 | },
156 | "kernelspec": {
157 | "name": "spider",
158 | "language": "python",
159 | "display_name": "spider"
160 | },
161 | "pycharm": {
162 | "stem_cell": {
163 | "cell_type": "raw",
164 | "source": [],
165 | "metadata": {
166 | "collapsed": false
167 | }
168 | }
169 | }
170 | },
171 | "nbformat": 4,
172 | "nbformat_minor": 0
173 | }
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/fund_info.py:
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1 | # -*- coding: utf-8 -*-
2 | import requests
3 | from datetime import datetime
4 | from bs4 import BeautifulSoup
5 | import copy
6 | import pandas as pd
7 |
8 |
9 | class FuncInfo(object):
10 | def __init__(self, code, name=None, fund_type=None):
11 | self.code = code, # 基金代码
12 | self.name = name # 基金名
13 | self.fund_type = fund_type # 类型
14 | self._unit_value_ls = [] # 单位净值list
15 | self._cumulative_value_ls = [] # 累计净值list
16 | self._daily_growth_rate_ls = [] # 日增长率
17 | self._date_ls = [] # 交易日list
18 | self._purchase_state_ls = [] # 申购状态
19 | self._redemption_state_ls = [] # 赎回状态
20 | self._bonus_distribution_ls = [] # 分红送配
21 | self._date2idx_map = {} # 交易日 -> 单位净值list/累计净值list.. idx
22 |
23 | def clear_data(self):
24 | self._unit_value_ls = []
25 | self._cumulative_value_ls = []
26 | self._daily_growth_rate_ls = []
27 | self._date_ls = []
28 | self._date2idx_map = {}
29 |
30 | @staticmethod
31 | def _parse_date(date, fmt):
32 | if isinstance(date, datetime):
33 | date = date.strftime(fmt)
34 | if not isinstance(date, str):
35 | raise Exception("date type(%s) error, required: datetime or str" % type(date))
36 | return date
37 |
38 | def _date2idx(self, date):
39 | date = self._parse_date(date, "%Y-%m-%d")
40 | return self._date2idx_map.get(date)
41 |
42 | def get_unit_value(self, date):
43 | idx = self._date2idx(date)
44 | return None if idx is None else self._unit_value_ls[idx]
45 |
46 | def get_cumulative_value(self, date):
47 | idx = self._date2idx(date)
48 | return None if idx is None else self._cumulative_value_ls[idx]
49 |
50 | def get_purchase_state(self, date):
51 | idx = self._date2idx(date)
52 | return None if idx is None else self._purchase_state_ls[idx]
53 |
54 | def get_redemption_state(self, date):
55 | idx = self._date2idx(date)
56 | return None if idx is None else self._redemption_state_ls[idx]
57 |
58 | def get_bonus_distribution(self, date):
59 | idx = self._date2idx(date)
60 | return None if idx is None else self._bonus_distribution_ls[idx]
61 |
62 | def get_daily_growth_rate(self, date):
63 | idx = self._date2idx(date)
64 | return None if idx is None else self._daily_growth_rate_ls[idx]
65 |
66 | def load_net_value_info(self, start_date, end_date):
67 | url = "http://fund.eastmoney.com/f10/F10DataApi.aspx"
68 | date_fmt = "%Y-%m-%d"
69 | info = {
70 | "type": "lsjz",
71 | "code": self.code,
72 | "per": 49,
73 | "sdate": self._parse_date(start_date, date_fmt),
74 | "edate": self._parse_date(end_date, date_fmt),
75 | }
76 | page = 0
77 | # fp = open("./output/fund_info/%s_%s_raw.txt" % (self.code, self.name), "w")
78 | update_flag = True
79 | while update_flag:
80 | page = page + 1
81 | update_flag = False
82 | info["page"] = page
83 | r = requests.get(url, info)
84 | soup = BeautifulSoup(r.text, 'lxml')
85 | th_list = None
86 | for idx, tr in enumerate(soup.find_all('tr')):
87 | if idx == 0:
88 | th_list = [x.text for x in tr.find_all("th")]
89 | else:
90 | tds = tr.find_all('td')
91 | values = [w.text for w in tds]
92 | if values[0] == "暂无数据!":
93 | break
94 | dict_data = dict(zip(th_list, values))
95 | # fp.write("%s\n" % dict_data)
96 | date = dict_data.get("净值日期")
97 | if date and not self._date2idx_map.get(date):
98 | self._date2idx_map[dict_data.get("净值日期")] = len(self._unit_value_ls)
99 | self._unit_value_ls.append(dict_data.get("单位净值"))
100 | self._cumulative_value_ls.append(dict_data.get("累计净值"))
101 | self._date_ls.append(date)
102 | self._purchase_state_ls.append(dict_data.get("申购状态"))
103 | self._redemption_state_ls.append(dict_data.get("赎回状态"))
104 | self._bonus_distribution_ls.append(dict_data.get("分红送配"))
105 | self._daily_growth_rate_ls.append(dict_data.get("日增长率"))
106 | update_flag = True
107 |
108 | def get_data_frame(self):
109 | date_list = self._date_ls
110 | df = pd.DataFrame({
111 | "净值日期": date_list,
112 | "单位净值": [self.get_unit_value(date) for date in date_list],
113 | "累计净值": [self.get_cumulative_value(date) for date in date_list],
114 | "日增长率": [self.get_daily_growth_rate(date) for date in date_list],
115 | "申购状态": [self.get_purchase_state(date) for date in date_list],
116 | "赎回状态": [self.get_redemption_state(date) for date in date_list],
117 | "分红送配": [self.get_bonus_distribution(date) for date in date_list],
118 | })
119 | return df
120 |
121 |
122 | if __name__ == '__main__':
123 | j = FuncInfo(code=161725, name="招商中证白酒指数分级")
124 | j.load_net_value_info(datetime(2018, 9, 1), datetime(2019, 9, 20))
125 | date = "2019-09-20"
126 | print(j.get_unit_value(date), j.get_cumulative_value(date), j.get_daily_growth_rate(date))
127 | df = j.get_data_frame()
128 | df.to_csv("./output/fund_info/161725招商中证白酒指数分级.csv")
129 |
130 |
131 |
132 |
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/fund_list.py:
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1 | # -*- coding: utf-8 -*-
2 |
3 | import requests
4 | import json
5 | import pandas as pd
6 | import numpy as np
7 |
8 |
9 | fund_list_url = "http://fund.eastmoney.com/js/fundcode_search.js"
10 |
11 |
12 | def fund_list_str2fmt_data(raw_str):
13 | """
14 | :param raw_str: "var r = [["000001","HXCZHH","华夏成长混合","混合型","HUAXIACHENGZHANGHUNHE"],["000002","HXCZHH","华夏成长混合(后端)","混合型","HUAXIACHENGZHANGHUNHE"]];"
15 | :return: [
16 | ["000001","HXCZHH","华夏成长混合","混合型","HUAXIACHENGZHANGHUNHE"],
17 | ["000002","HXCZHH","华夏成长混合(后端)","混合型","HUAXIACHENGZHANGHUNHE"]
18 | ]
19 | """
20 | prefix = "var r = "
21 | suffix = ";"
22 | json_str = raw_str[len(prefix): len(raw_str) - len(suffix)]
23 | fmt_data = json.loads(json_str)
24 | return fmt_data
25 |
26 |
27 | def fund_list2dict_list(fund_list):
28 | dict_list = []
29 | for fund in fund_list:
30 | dict_list.append({
31 | "code": fund[0],
32 | "name_short": fund[1],
33 | "name": fund[2],
34 | "type": fund[3],
35 | })
36 | return dict_list
37 |
38 |
39 | def fund_list2data_frame(fund_list):
40 | """
41 | :param fund_list: [
42 | ["000001","HXCZHH","华夏成长混合","混合型","HUAXIACHENGZHANGHUNHE"],
43 | ["000002","HXCZHH","华夏成长混合(后端)","混合型","HUAXIACHENGZHANGHUNHE"]
44 | ]
45 | :return:
46 | code name type name_short
47 | 0 000001 华夏成长混合 混合型 HXCZHH
48 | 1 000002 华夏成长混合(后端) 混合型 HXCZHH
49 | """
50 | np_array = np.array(fund_list)
51 | np_array = np_array.transpose()
52 | df = pd.DataFrame({
53 | "code": np_array[0],
54 | "name_short": np_array[1],
55 | "name": np_array[2],
56 | "type": np_array[3]
57 | }, columns=["code", "name", "type", "name_short"])
58 | return df
59 |
60 |
61 | def _get_fund_list():
62 | r = requests.get(fund_list_url)
63 | raw_fund_list = r.content.decode("utf-8")
64 | with open("./output/fund_list/raw.txt", "w", encoding='utf-8') as fp:
65 | fp.write(raw_fund_list)
66 | print("get fund raw list: %s..." % raw_fund_list[:100])
67 | fund_list = fund_list_str2fmt_data(raw_fund_list)
68 | return fund_list
69 |
70 |
71 | def get_fund_df():
72 | """
73 | 获取基金表单
74 | :return: dataFrame
75 | """
76 | fund_df = fund_list2data_frame(_get_fund_list())
77 | fund_df.to_csv("./output/fund_list/fund_list.csv")
78 | print("parse raw data to data frame success, df head:")
79 | print(fund_df.head())
80 | return fund_df
81 |
82 |
83 | def get_fund_list():
84 | dict_list = fund_list2dict_list(_get_fund_list())
85 | return dict_list
86 |
87 |
88 | if __name__ == '__main__':
89 | get_fund_df()
90 |
--------------------------------------------------------------------------------
/main.py:
--------------------------------------------------------------------------------
1 | # -*- coding: utf-8 -*-
2 |
3 | from fund_list import get_fund_list
4 | from fund_info import FuncInfo
5 | # from tqdm import tqdm
6 | import os
7 | from p_tqdm import p_umap
8 | import time
9 |
10 | csv_data_dir = "./output/csv_data"
11 | start_date, end_date = "2015-01-01", time.strftime("%Y-%m-%d", time.localtime())
12 |
13 |
14 | def get_fund(fund):
15 | code = fund.get("code")
16 | # name = fund.get("name")
17 | file_name = os.path.join(csv_data_dir, u"%s.csv" % code)
18 | if not os.path.exists(csv_data_dir):
19 | os.mkdir(csv_data_dir)
20 | if os.path.isfile(file_name):
21 | return
22 | info = FuncInfo(code=code)
23 | info.load_net_value_info(start_date, end_date)
24 | df = info.get_data_frame()
25 | df.to_csv(file_name)
26 |
27 |
28 | if __name__ == '__main__':
29 | # 抓取全量基金 start_date~end_date净值数据
30 | fund_list = get_fund_list()
31 | fund_num = len(fund_list)
32 | print("total fund: %s" % fund_num)
33 | p_umap(get_fund, fund_list)
34 |
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/output/fund_info/__init__.py:
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https://raw.githubusercontent.com/luricheng/fundSpider/2c878a955fd8be05b328b442b0d516855e2a24ee/output/fund_info/__init__.py
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/output/fund_list/__init__.py:
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https://raw.githubusercontent.com/luricheng/fundSpider/2c878a955fd8be05b328b442b0d516855e2a24ee/output/fund_list/__init__.py
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/requirements.txt:
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1 | beautifulsoup4==4.9.3
2 | bs4==0.0.1
3 | certifi==2020.12.5
4 | chardet==4.0.0
5 | dill==0.3.3
6 | idna==2.10
7 | lxml==4.6.2
8 | multiprocess==0.70.11.1
9 | numpy==1.19.5
10 | p-tqdm==1.3.3
11 | pandas==1.2.0
12 | pathos==0.2.7
13 | pox==0.2.9
14 | ppft==1.6.6.3
15 | python-dateutil==2.8.1
16 | pytz==2020.5
17 | request==1.0.117
18 | requests==2.25.1
19 | six==1.15.0
20 | soupsieve==2.1
21 | tqdm==4.56.0
22 | urllib3==1.26.2
23 |
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/strategy.py:
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1 | # -*- coding: utf-8 -*-
2 |
3 | class Strategy(object):
4 | @classmethod
5 | def bottom_suction_high_throw(cls,
6 | value_list,
7 | start_idx=0,
8 | end_idx=None,
9 | base_money=100,
10 | add_money=10,
11 | take_profit_rate=0.05):
12 | """
13 | 低吸高抛策略, 一只基金从发行到现在 投入资金&回报
14 | :param value_list: 基金净值list
15 | :param start_idx: 开始投资时刻
16 | :param end_idx: 结束投资时刻
17 | :param base_money: 建仓成本
18 | :param add_money: 每次加仓成本
19 | :param take_profit_rate: 止盈率
20 | :return:
21 | """
22 | if len(value_list) < 2:
23 | raise Exception("value_list's length must > 1, but got %s" % len(value_list))
24 | end_idx = end_idx or len(value_list)
25 | end_idx = min(end_idx, len(value_list))
26 | total_cost = base_money # 总成本
27 | holding_share = 1.0 * base_money / value_list[start_idx] # 持有份额
28 | for i in range(start_idx+1, end_idx):
29 | value = value_list[i]
30 | pre_value = value_list[i-1]
31 | # 跌
32 | if value < pre_value:
33 | total_cost += add_money
34 | holding_share += 1.0 * add_money / value
35 | # 涨 收益 > 止盈率
36 | if i + 1 == end_idx or cls._get_growth_rate(total_cost, holding_share, value) > take_profit_rate:
37 | return {
38 | "cost_time": i-start_idx,
39 | "total_cost": total_cost,
40 | "profit_rate": cls._get_growth_rate(total_cost, holding_share, value),
41 | }
42 |
43 | @staticmethod
44 | def _get_growth_rate(cost, holding_share, value):
45 | cur_val = 1.0 * holding_share * value
46 | return (cur_val - cost) / cost
47 |
48 |
49 | if __name__ == '__main__':
50 | value_list = [1.0, 1.01, 1.0125, 0.99, 0.97, 1.009, 1.029, 1.059]
51 | print(Strategy.bottom_suction_high_throw(value_list))
52 |
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/tool.py:
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1 | # -*- coding: utf-8 -*-
2 | import pickle
3 | import numpy as np
4 | import os
5 |
6 |
7 | class Tool(object):
8 | FUND_INFO_DICT_PKL = "pkl_data/fund_info_dict.pkl"
9 | HIGH_RISK_TYPES = ["股票指数", "混合型", "股票型"]
10 |
11 | @classmethod
12 | def load_fund_info_by_type(cls, fund_types=None, base_path='.'):
13 | fund_types = fund_types or cls.HIGH_RISK_TYPES
14 | path = os.path.join(base_path, cls.FUND_INFO_DICT_PKL)
15 | with open(path, 'rb') as fp:
16 | fund_info_dict = pickle.load(fp)
17 | target_funds = {}
18 | for k, v in fund_info_dict.items():
19 | if v['type'] in fund_types:
20 | target_funds[k] = v
21 | return target_funds
22 |
23 | @staticmethod
24 | def get_value_list(fund, unit_value=False):
25 | detail = fund.get("detail")
26 | date_value = []
27 | value_name = "unit_value" if unit_value else "cumulative_value"
28 | for k, v in detail.items():
29 | date_value.append((k, float(v.get(value_name))))
30 | date_value.sort(key=lambda x: x[0])
31 | return [x[1] for x in date_value]
32 |
33 |
34 | if __name__ == '__main__':
35 | f = Tool.load_fund_info_by_type()
36 | print(Tool.get_value_list(f[161725]))
37 |
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