17.上市、上櫃個股融資、融券

2019 iT 邦幫忙鐵人賽

DAY 17

AI & Data

量化投資與機器學習研究系列第 17 篇

2019鐵人賽

kuankuan

2018-10-31 21:10:18

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上市欄位比較少，所以上櫃對齊上市的欄位

其中有個註記欄位
上市
備註欄符號依序說明
1. 數字(1、2、3…)：合計降低融資比率、提高融券保證金成數
2. O：停止融資
3. X：停止融券
4. @：融資分配
5. %：融券分配
6. *：融券餘額占融資餘額百分之六十以上者
7. A：股價波動過度劇烈
8. B：股權過度集中
9. C：成交量過度異常
10. D：監視第二次處置
11. 數字(1、2、3…)：監視業務督導會報決議降低融資比率、提高融券保證金成數

來自

上櫃
說明：

備註欄係表明成交日次一營業日股票融資融券狀況
符號說明： O：停止融資, X：停止融券, @：融資分配, %：融券分配
限額：
融資餘額達該種股票上市股份25%時，暫停融資買進。
融券餘額達該種股票上市股份25%時，暫停融券賣出。
融資、融券餘額達限額之八成時，次一營業日進行額度分配。
得為融資融券之證券於停止買賣期間，本報表停止揭露該證券信用交易資訊，待恢復交易日時再行揭露，並參考該證券之融資融券餘額，調整當日報表『前日餘額』之統計數字；至有價證券停止、恢復交易相關訊息，請參閱本公司MIS即時公告。

來自

寫入兩張表，每日個股融資券添加到stock_day

{
    "_id" : "2018/10/30_0050",
    "市場別" : "上市",
    "產業別" : "",
    "name" : "元大台灣50",
    "code" : "0050",
    "date" : "2018/10/30",
    "成交股數" : 6119,
    "成交金額" : 464489,
    "開盤價" : 75.8,
    "最高價" : 76.25,
    "最低價" : 75.5,
    "收盤價" : 75.95,
    "漲跌價差" : 0.2,
    "成交筆數" : 2313,
    "三大法人買賣超" : -1777.0,
    "外資自營商買賣超" : 0.0,
    "外資自營商買進" : 0.0,
    "外資自營商賣出" : 0.0,
    "外陸資買賣超" : -1749.0,
    "外陸資買進" : 33.0,
    "外陸資賣出" : 1782.0,
    "投信買賣超" : 100.0,
    "投信買進" : 100.0,
    "投信賣出" : 0.0,
    "自營商買賣超" : 186.0,
    "自營商買賣超避險" : -314.0,
    "自營商買進" : 292.0,
    "自營商買進避險" : 1747.0,
    "自營商賣出" : 106.0,
    "自營商賣出避險" : 2061.0,
    "融券今日餘額" : 1056,
    "融券前日餘額" : 962,
    "融券現金償還" : 0,
    "融券買進" : 50,
    "融券賣出" : 144,
    "融券限額" : 201500,
    "融資今日餘額" : 4386,
    "融資前日餘額" : 4375,
    "融資現金償還" : 2,
    "融資買進" : 96,
    "融資賣出" : 83,
    "融資限額" : 201500,
    "資券互抵" : 3,
    "資券註記" : ""
}

當天的統計總額寫入到stock_margin_trading，其中金額單位是(仟元)

{
    "_id" : ObjectId("5bd9a7ae8998344b6ec63912"),
    "date" : "2018/10/30",
    "市場別" : "上市",
    "融資買進" : "149,018",
    "融資賣出" : "169,272",
    "融資現金償還" : "5,538",
    "融資前日餘額" : "7,257,679",
    "融資今日餘額" : "7,231,887",
    "融券買進" : "57,292",
    "融券賣出" : "79,670",
    "融券現金償還" : "635",
    "融券前日餘額" : "579,350",
    "融券今日餘額" : "601,093",
    "融資買進金額" : "2,992,718",
    "融資賣出金額" : "3,697,797",
    "融資現金償還金額" : "356,826",
    "融資前日餘額金額" : "128,263,246",
    "融資今日餘額金額" : "127,201,340"
}
    "_id" : ObjectId("5bd9a7948998344b6ec63908"),
    "date" : "2018/10/30",
    "市場別" : "上櫃",
    "融資買進" : "26,163",
    "融資賣出" : "31,834",
    "融資現金償還" : "1,771",
    "融資前日餘額" : "1,809,526",
    "融資今日餘額" : "1,802,084",
    "融券買進" : "12,880",
    "融券賣出" : "14,698",
    "融券現金償還" : "165",
    "融券前日餘額" : "142,193",
    "融券今日餘額" : "143,846",
    "融資買進金額" : "768,781",
    "融資賣出金額" : "991,894",
    "融資現金償還金額" : "122,714",
    "融資前日餘額金額" : "43,860,143",
    "融資今日餘額金額" : "43,514,316"
}

# -*- coding: utf-8 -*-
import json
import time
from datetime import datetime
import pandas as pd
import scrapy

from skhome.extensions import MongoDatabase

TWSE_URL = 'http://www.tse.com.tw/exchangeReport/MI_MARGN?response=json&date={y}{m:02d}{d:02d}&selectType=ALL'
TPEX_URL = 'http://www.tpex.org.tw/web/stock/margin_trading/margin_balance/margin_bal_result.php?l=zh-tw&o=json&d={y}/{m:02d}/{d:02d}'

columns = [
    "_id",
    "融資買進",
    "融資賣出",
    "融資現金償還",
    "融資前日餘額",
    "融資今日餘額",
    "融資限額",
    "融券買進",
    "融券賣出",
    "融券現金償還",
    "融券前日餘額",
    "融券今日餘額",
    "融券限額",
    "資券互抵",
    "資券註記",
]

creditFields = [
    "date",
    "市場別",
    "融資買進",
    "融資賣出",
    "融資現金償還",
    "融資前日餘額",
    "融資今日餘額",
    "融券買進",
    "融券賣出",
    "融券現金償還",
    "融券前日餘額",
    "融券今日餘額",
    "融資買進金額",
    "融資賣出金額",
    "融資現金償還金額",
    "融資前日餘額金額",
    "融資今日餘額金額",
]


def parse_info(d, m):
    _id = m['date'] + '_' + d[0]
    if m['市場別'] == '上市':
        note = d[-1]
        d = d[2:-1]
        d = [int(x.replace(',', '')) for x in d]
        d.append(note)
    else:
        note = d[-1]
        d = [d[3], d[4], d[5], d[2], d[6], d[9], d[10 + 2], d[10 + 1], d[10 + 3], d[10], d[10 + 4], d[10 + 7],
             d[10 + 8]]
        d = [int(x.replace(',', '')) for x in d]
        d.append(note)

    return dict(zip(columns, [_id, *d]))


class StockDaySpider(scrapy.Spider):
    name = 'stock_margin_trading'

    custom_settings = {
        'DOWNLOAD_DELAY': 8,
        'CONCURRENT_REQUESTS': 1,
        'MONGODB_COLLECTION': 'stock_day',
        'MONGODB_ITEM_CACHE': 1,
        'MONGODB_HAS_ID_FIELD': True,
        'COOKIES_ENABLED': False
    }

    def __init__(self, beginDate=None, endDate=None, *args, **kwargs):
        super(StockDaySpider, self).__init__(beginDate=beginDate, endDate=endDate, *args, **kwargs)

    def start_requests(self):
        if self.beginDate and self.endDate:
            start = self.beginDate
            end = self.endDate
        else:
            date = datetime.today().strftime("%Y-%m-%d")
            start = date
            end = date

        for date in pd.date_range(start, end)[::-1]:
            today = '{}/{:02d}/{:02d}'.format(date.year, date.month, date.day)
            with MongoDatabase('stock_day') as conn:
                isopen = list(conn.collection.find({'date': today}, {'_id': 1}).limit(1))

            if isopen:
                today = '{}/{:02d}/{:02d}'.format(date.year, date.month, date.day)
                y = date.year
                m = date.month
                d = date.day

                url = TWSE_URL.format(y=y, m=m, d=d)
                time.sleep(8)
                yield scrapy.Request(url, meta={'date': today, '市場別': '上市'})
                y = y - 1911
                url = TPEX_URL.format(y=y, m=m, d=d)
                yield scrapy.Request(url, meta={'date': today, '市場別': '上櫃'})

    def parse(self, response):
        m = response.meta
        json_data = json.loads(response.text)

        if m['市場別'] == '上市':
            try:
                data = json_data['data']
                for d in data:
                    yield parse_info(d, m)

                d = json_data['creditList']
                item = dict(zip(creditFields, [m['date'], m['市場別'], *d[0][1:], *d[1][1:], *d[2][1:]]))
                with MongoDatabase('stock_margin_trading') as conn:
                    conn.collection.insert_one(item)
            except KeyError:
                pass
        else:
            try:
                data = json_data['aaData']
                for d in data:
                    yield parse_info(d, m)

                d1 = json_data['tfootData_one']
                d2 = json_data['tfootData_two']
                item = dict(zip(creditFields,
                                [m['date'], m['市場別'], d1[1], d1[2], d1[3], d1[0], d1[4], d1[10], d1[9], d1[11], d1[8],
                                 d1[12], d2[1], d2[2], d2[3], d2[0], d2[4]]))
                with MongoDatabase('stock_margin_trading') as conn:
                    conn.collection.insert_one(item)
            except KeyError:
                pass