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hkex_fut_opt.py
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hkex_fut_opt.py
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import os
import requests
import re
import pandas as pd
import zipfile
import datetime
import numpy as np
import akshare as ak
from utils import *
import math as m
from io import StringIO, BytesIO
def get_hkex_stock_option_contract_size():
url = 'https://www.hkex.com.hk/Products/Listed-Derivatives/Single-Stock/Stock-Options?sc_lang=en'
HKCE_HEADERS = {"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)",
'Host': 'www.hkex.com.hk'}
se = requests.session()
r = se.get(url, headers=HKCE_HEADERS)
df1 = pd.read_html(r.text, attrs={'class_':"table migrate;"})[0]
df1 = df1[['SEHK Code', 'HKATS Code', 'Contract Size (shares)']]
df1['Number of Board Lots'] = 1
df2 = pd.read_html(r.text, attrs={'width':"100%"})[0]
df2 = df2[['SEHK Code', 'HKATS Code', 'Contract Size (shares)', 'Number of Board Lots']]
df = pd.concat([df1, df2], axis=0)
path = os.path.join(option_price_dir, 'hkex', 'contract size'+'.csv')
df.to_csv(path, encoding='utf-8', index=False)
def update_hkex_stock_option_expiry_date():
url = 'https://www.hkex.com.hk/Services/Trading/Derivatives/Overview/Trading-Calendar-and-Holiday-Schedule?sc_lang=en'
HKCE_HEADERS = {"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)",
'Host': 'www.hkex.com.hk'}
se = requests.session()
r = se.get(url, headers=HKCE_HEADERS)
df = pd.read_html(r.text, attrs={'class_':"table migrate"})[0]
df.rename(columns={"Last Trading Day / Expiry Day":"Expiry Day",}, inplace=True)
for i in range(len(df)):
contract_month = df.loc[i, 'Contract Month']
month = contract_month[:3]
year = '20'+contract_month[4:6]
month = month_dict[month.upper()]
contract_month_tm = year+'-'+month
df.loc[i, 'Contract Month'] = contract_month_tm
expiry_date = df.loc[i, 'Expiry Day'].split('-')
day = expiry_date[0]
month = expiry_date[1]
year = '20'+expiry_date[2]
month = month_dict[month.upper()]
expiry_date_tm = datetime.datetime(year=int(year), month=int(month), day=int(day)).strftime('%Y-%m-%d')
df.loc[i, 'Expiry Day'] = expiry_date_tm
Settlement_date = df.loc[i, 'Final Settlement Day'].split('-')
day = Settlement_date[0]
month = Settlement_date[1]
year = '20'+Settlement_date[2]
month = month_dict[month.upper()]
Settlement_date_tm = datetime.datetime(year=int(year), month=int(month), day=int(day)).strftime('%Y-%m-%d')
df.loc[i, 'Final Settlement Day'] = Settlement_date_tm
path = os.path.join(option_price_dir, 'hkex', 'stock option expiry date'+'.csv')
if os.path.exists(path):
old_df = pd.read_csv(path)
old_df = pd.concat([old_df, df], axis=0)
old_df.drop_duplicates(subset=['Expiry Day'], keep='last', inplace=True)
old_df['Expiry Day'] = old_df['Expiry Day'].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d'))
old_df.sort_values(by = 'Expiry Day', inplace=True)
old_df['Expiry Day'] = old_df['Expiry Day'].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
df.to_csv(path, encoding='utf-8', index=False)
def update_hkex_stock_option():
se = requests.session()
earlist_time = '2023-01-01 00:00:00'
# URL = 'https://www.hkex.com.hk/eng/stat/dmstat/dayrpt/dqe230907.zip'
URL = 'https://www.hkex.com.hk/eng/stat/dmstat/dayrpt/dqe{}.zip'
HKEX_HEADERS = {"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)",
'Host': 'www.hkex.com.hk'}
path = os.path.join(option_price_dir, 'hkex', 'TCH'+'_info'+'.csv')
last_line_time = get_last_line_time(path, '', earlist_time, 19, '%Y-%m-%d %H:%M:%S')
data_time_dt = pd.to_datetime(last_line_time, format='%Y-%m-%d %H:%M:%S')
start_time_dt = data_time_dt + pd.Timedelta(days=1)
current_time_dt = datetime.datetime.now()
while start_time_dt <= current_time_dt:
t = datetime.datetime(year=start_time_dt.year, month=start_time_dt.month, day=start_time_dt.day, hour=16, minute=0, second=0 )
start_time = start_time_dt.strftime('%Y-%m-%d')
start_time_ = start_time_dt.strftime('%Y%m%d')
url = URL.format(start_time_[2:])
print(url)
start_time_dt = start_time_dt + pd.Timedelta(days=1)
count = 0
while (1):
try:
r = se.get(url, headers=HKEX_HEADERS, timeout=10)
if r.status_code == 200:
break
if r.status_code == 404:
count = count + 1
if count >= 2:
break
except Exception as e:
print('HK STOCK OPTION ERROR: ', e)
time.sleep(5)
if count >= 2:
print(start_time, " 404 NOT FOUND")
continue
# TMP
# path = os.path.join(data_dir, 'dqe230907.zip')
# TMP
with zipfile.ZipFile(BytesIO(r.content), "r") as z:
# with zipfile.ZipFile(path, "r") as z:
# print(z.namelist())
file_name = z.namelist()[0]
f = z.open(file_name, mode='r')
variety_dict = {}
while (1):
s = f.readline().decode('utf-8')
if 'End of Report' in s:
break
# SUMMARY
if 'HKATS' in s:
a = s.split(',')
# EACH STOCK'S SUMMARY
while (1):
s = f.readline().decode('utf-8')
a = s.split(',')
L = len(a)
if L < 5:
break
a[L-1] = a[L-1].removesuffix('\r\n')
volume = float(a[3])
oi = float(a[6])
# 只要有成交量和持仓量的股票数据
if (volume >= 1000) and (oi >= 15000):
variety_dict[a[0]] = 1
print(variety_dict)
# OPTION DATA
if 'CLASS' in s:
inst_ids_list = []
a = s.split(',')
L = len(a)
a[L-1] = a[L-1].removesuffix('"\r\n')
a[L-1] = a[L-1].removeprefix('"CLOSING PRICE HK$')
close = float(a[L-1])
b = a[0].split(' ')
variety = b[1]
if not(variety in variety_dict):
continue
# print(variety, close)
# skip one line
f.readline()
# read option data
data_dict = {}
while (1):
s = f.readline().decode('utf-8')
a = s.split(',')
L = len(a)
if L < 5:
break
a[L-1] = a[L-1].removesuffix('\r\n')
month = month_dict[a[0][:3]]
year = a[0][3:5]
tm = year+month
inst_id = variety + tm
otype = a[2]
strike = a[1]
if not (inst_id in data_dict):
inst_ids_list.append(inst_id)
data_dict[inst_id] = [['time', 'close'],
['time', 'close'],
['time', 'close'],
[t, close],
[0.0, 0.0],]
data_dict[inst_id][0] = data_dict[inst_id][0] + [otype, otype, otype, otype]
data_dict[inst_id][1] = data_dict[inst_id][1] + [strike, strike, strike, strike]
data_dict[inst_id][2] = data_dict[inst_id][2] + ['settle', 'volume', 'oi', 'imp_vol']
iv = a[8]
if iv == '0':
iv = np.nan
else:
iv = float(iv)/100
data_dict[inst_id][3] = data_dict[inst_id][3] + [a[6], a[9], a[10], iv]
data_dict[inst_id][4][0] = data_dict[inst_id][4][0] + float(a[9])
data_dict[inst_id][4][1] = data_dict[inst_id][4][1] + float(a[10])
# skip 2 lines
f.readline()
f.readline()
while (1):
s = f.readline().decode('utf-8')
a = s.split(',')
L = len(a)
if L < 5:
break
a[L-1] = a[L-1].removesuffix('\r\n')
month = month_dict[a[0][:3]]
year = a[0][3:5]
tm = year+month
inst_id = variety + tm
otype = a[2]
strike = a[1]
if not (inst_id in data_dict):
inst_ids_list.append(inst_id)
data_dict[inst_id] = [['time', 'close'],
['time', 'close'],
['time', 'close'],
[t, close]]
data_dict[inst_id][0] = data_dict[inst_id][0] + [otype, otype, otype, otype]
data_dict[inst_id][1] = data_dict[inst_id][1] + [strike, strike, strike, strike]
data_dict[inst_id][2] = data_dict[inst_id][2] + ['settle', 'volume', 'oi', 'imp_vol']
iv = a[8]
if iv == '0':
iv = np.nan
else:
iv = float(iv)/100
data_dict[inst_id][3] = data_dict[inst_id][3] + [a[6], a[9], a[10], iv]
data_dict[inst_id][4][0] = data_dict[inst_id][4][0] + float(a[9])
data_dict[inst_id][4][1] = data_dict[inst_id][4][1] + float(a[10])
# skip 2 lines
f.readline()
f.readline()
# sort volume
inst_ids = ''
z1 = []
z2 = []
for inst_id in data_dict:
z1.append(inst_id)
z2.append(data_dict[inst_id][4][0])
z1 = np.array(z1)
z2 = np.array(z2)
sort = np.argsort(z2)[::-1]
inst_ids = ''
for i in range(len(z1)):
inst_ids += z1[sort][i]
inst_ids += ','
for inst_id in inst_ids_list:
# inst_ids += inst_id
# inst_ids += ','
df = pd.DataFrame(columns=[data_dict[inst_id][0], data_dict[inst_id][1], data_dict[inst_id][2]], data=[data_dict[inst_id][3]])
path = os.path.join(option_price_dir, 'hkex', inst_id+'.csv')
if os.path.exists(path):
old_df = pd.read_csv(path, header=[0,1,2])
old_df = pd.concat([old_df, df], axis=0)
old_df.drop_duplicates(subset=[('time','time','time')], keep='last', inplace=True) # last
old_df.loc[:, pd.IndexSlice['time','time','time']] = old_df.loc[:, pd.IndexSlice['time','time','time']].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = ('time','time','time'), inplace=True)
old_df.loc[:, pd.IndexSlice['time','time','time']] = old_df.loc[:, pd.IndexSlice['time','time','time']].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
df.to_csv(path, encoding='utf-8', index=False)
info_df = pd.DataFrame(columns=['time', 'inst_ids'])
info_df.loc[0, 'time'] = t
info_df.loc[0, 'inst_ids'] = inst_ids
path = os.path.join(option_price_dir, 'hkex', variety+'_info'+'.csv')
# print(df)
if os.path.exists(path):
old_df = pd.read_csv(path)
old_df = pd.concat([old_df, info_df], axis=0)
old_df.drop_duplicates(subset=['time'], keep='last', inplace=True)
old_df['time'] = old_df['time'].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = 'time', inplace=True)
old_df['time'] = old_df['time'].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
info_df.to_csv(path, encoding='utf-8', index=False)
def update_hkex_usdcnh():
variety = 'USDCNH'
se = requests.session()
earlist_time = '2023-01-01 00:00:00'
URL = 'https://www.hkex.com.hk/eng/stat/dmstat/dayrpt/cusf{}.zip'
HKEX_HEADERS = {"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)",
'Host': 'www.hkex.com.hk'}
path = os.path.join(future_price_dir, 'hkex', 'USDCNH'+'.csv')
last_line_time = get_last_line_time(path, '', earlist_time, 19, '%Y-%m-%d %H:%M:%S')
data_time_dt = pd.to_datetime(last_line_time, format='%Y-%m-%d %H:%M:%S')
start_time_dt = data_time_dt + pd.Timedelta(days=1)
current_time_dt = datetime.datetime.now()
while start_time_dt <= current_time_dt:
# 4:30 pm
t = datetime.datetime(year=start_time_dt.year, month=start_time_dt.month, day=start_time_dt.day, hour=16, minute=30, second=0 )
start_time = start_time_dt.strftime('%Y-%m-%d')
start_time_ = start_time_dt.strftime('%Y%m%d')
url = URL.format(start_time_[2:])
print('USDCNH', url)
start_time_dt = start_time_dt + pd.Timedelta(days=1)
count = 0
while (1):
try:
r = se.get(url, headers=HKEX_HEADERS, timeout=10)
if r.status_code == 200:
break
if r.status_code == 404:
count = count + 1
if count >= 2:
break
except Exception as e:
print('HK STOCK OPTION ERROR: ', e)
time.sleep(5)
if count >= 2:
print(start_time, " 404 NOT FOUND")
continue
with zipfile.ZipFile(BytesIO(r.content), "r") as z:
file_name = z.namelist()[0]
f = z.open(file_name, mode='r')
while (1):
s = f.readline().decode('utf-8')
if 'All Contracts Total' in s:
break
if 'Contract Month' in s:
# skip one line
f.readline()
n = 0
col1 = ['time']
col2 = ['time']
data = [t]
dom_data = []
maxv = -1
while (1):
s = f.readline().decode('utf-8')
a = s.split(',')
L = len(a)
if L < 5:
break
a[L-1] = a[L-1].removesuffix('\r\n')
if a[1] == 'EXPIRED':
continue
if (a[1] == '-') and (a[6] == '-'):
break
month = month_dict[a[0][:3]]
year = a[0][4:6]
tm = year+month
inst_id = variety + tm
# c1 - c9
n = n + 1
cn = 'c'+str(n)
if n > 9:
break
# inst_id, open, high low, settle, volume, oi
col1 += [cn, cn, cn, cn, cn, cn, cn]
col2 += ['inst_id', 'open', 'high', 'low', 'settle', 'volume', 'oi']
data += [inst_id, a[6], a[7], a[8], a[10], a[9], a[15]]
volume = float(a[9])
if volume > maxv:
maxv = volume
dom_data = [inst_id, a[6], a[7], a[8], a[10], a[9], a[15]]
cn = 'dom'
col1 += [cn, cn, cn, cn, cn, cn, cn]
col2 += ['inst_id', 'open', 'high', 'low', 'settle', 'volume', 'oi']
data += dom_data
df = pd.DataFrame(columns=[col1, col2], data=[data])
path = os.path.join(future_price_dir, 'hkex', variety+'.csv')
if os.path.exists(path):
old_df = pd.read_csv(path, header=[0,1])
old_df = pd.concat([old_df, df], axis=0)
old_df.drop_duplicates(subset=[('time','time')], keep='last', inplace=True) # last
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:pd.to_datetime(x, format='%Y-%m-%d %H:%M:%S'))
old_df.sort_values(by = ('time','time'), inplace=True)
old_df.loc[:, pd.IndexSlice['time','time']] = old_df.loc[:, pd.IndexSlice['time','time']].apply(lambda x:datetime.datetime.strftime(x,'%Y-%m-%d %H:%M:%S'))
old_df.to_csv(path, encoding='utf-8', index=False)
else:
df.to_csv(path, encoding='utf-8', index=False)
break
def get_hk_stock_index():
code_list = [['HSI', '恒生指数'],
['HSCEI', '恒生中国企业指数'],
['HSTECH', '恒生科技指数'],
]
for code in code_list:
df = ak.stock_hk_index_daily_sina(symbol=code[0])
df.rename(columns={"date":"time"}, inplace=True)
path = os.path.join(data_dir, code[1]+'.csv')
df.to_csv(path, encoding='utf-8', index=False)
print(code[1])
def update_hkex_fut_opt_data():
# 股票期权
update_hkex_stock_option()
# # USDCNH
update_hkex_usdcnh()
# 股指
get_hk_stock_index()
if __name__=="__main__":
# update_hkex_stock_option_expiry_date()
update_hkex_fut_opt_data()