JUKUAN/Lib/Options/Jiabailie/01_聚宽平台期权数据获取与绘图.py

# 聚宽平台期权数据获取与绘图
# 参考资料：
# - 原始策略来源: https://www.joinquant.com/view/community/detail/aa77127d7eccdaa699de7e87977f35dc
# - 研究网址: https://www.joinquant.com/research?target=research&url=/user/75474983526/notebooks/Options/%E6%9C%9F%E6%9D%83%E6%95%B0%E6%8D%AE%E8%8E%B7%E5%8F%96%E4%B8%8E%E7%BB%98%E5%9B%BE.ipynb

# TODO: 添加期权数据获取与绘图相关代码

from jqdata import *
import pandas as pd
import numpy as np

import matplotlib.pyplot as plt
from matplotlib import rc
rc("mathtext", default="regular")

import seaborn as sns
sns.set_style("white")

from matplotlib import dates
from pandas import Series,DataFrame,concat
import matplotlib.dates as mdates
from datetime import datetime

warnings.filterwarnings('ignore')

# 通过 get_all_securities 获得期权合约信息
data = get_all_securities(types=['options'])

print(data.head(10))

print("\n")

print(data.tail(10))

# 通过 OPT_CONTRACT_INFO 表获取 50ETF 的所有合约 

start = "2025-01-01"
end   = "2025-03-01"

q = query(opt.OPT_CONTRACT_INFO).filter(
          opt.OPT_CONTRACT_INFO.underlying_symbol=='510050.XSHG',
          opt.OPT_CONTRACT_INFO.list_date > start,
          opt.OPT_CONTRACT_INFO.list_date < end)

ins = opt.run_query(q)

# cal应该是认购，put应该是认沽
callOption = ins[ins["contract_type"]=="CO"].code.tolist()
putOption = ins[ins["contract_type"]=="PO"].code.tolist()

#早期可以使用这个函数获取期权行情数据。近期已失效
#使用 get_price 获取多个期权的日行情
# price = get_price(["10001151.XSHG","10001152.XSHG"],start_date='2018-01-02',panel = False)
# price

for c in callOption[:5]:
    q_price = query(opt.OPT_DAILY_PRICE.code, opt.OPT_DAILY_PRICE.date, opt.OPT_DAILY_PRICE.close,
                     ).filter(opt.OPT_DAILY_PRICE.code.in_([c]),
                             opt.OPT_DAILY_PRICE.date>start)

    price = opt.run_query(q_price)

    print(f"c: {c}, price: {price.head()}")

# 获取 10006932 在 2024-03-08 的 tick 数据
get_ticks("10006932.XSHG", end_dt='2024-03-08 15:30:00', start_dt='2024-03-08 09:00:00')

#获取所有 SR2405 合约的合约资料
info_df = opt.run_query(query(opt.OPT_CONTRACT_INFO).filter(opt.OPT_CONTRACT_INFO.underlying_symbol=="SR2405.XZCE"))
info_df.tail()

#获取 SR405P7800.XZCE 在 2024-03-22 这天及之前10个交易日的行情数据

q = query(opt.OPT_DAILY_PRICE).filter(
    opt.OPT_DAILY_PRICE.code=='SR405P7800.XZCE',# 选择标的,多个合约用in_操作,详细查看query教程
    opt.OPT_DAILY_PRICE.date<='2024-03-22'      # 过滤掉date大于 2024-03-22 的数据
    ).order_by(opt.OPT_DAILY_PRICE.date.desc()  # 根据日期排序
              ).limit(10)

opt.run_query(q)

#获取 20240321 这天所有 CU 合约的日行情数据
q = query(opt.OPT_DAILY_PRICE).filter(
    opt.OPT_DAILY_PRICE.code.like('CU%'),       # 选择code中以CU开头的标的,详细查看query教程
    opt.OPT_DAILY_PRICE.date=='2024-03-21'      # 指定date等于2024-03-21
    ).order_by(opt.OPT_DAILY_PRICE.date.desc()  # 根据日期排序
              ).limit(10)

opt.run_query(q)

# 分别获取etf50的认购以及认沽期权合约
start = "2025-01-01"
end   = "2025-03-01"

q = query(opt.OPT_CONTRACT_INFO).filter(
    opt.OPT_CONTRACT_INFO.underlying_symbol=='510050.XSHG',
    opt.OPT_CONTRACT_INFO.list_date>start,
    opt.OPT_CONTRACT_INFO.list_date<end)

ins = opt.run_query(q)

callOption = ins[ins["contract_type"]=="CO"].code.tolist()
putOption = ins[ins["contract_type"]=="PO"].code.tolist()

# 获取价格数据序列
q= query(opt.OPT_DAILY_PRICE.date,opt.OPT_DAILY_PRICE.volume,opt.OPT_DAILY_PRICE.money).filter(
    opt.OPT_DAILY_PRICE.code.in_(callOption),      
    opt.OPT_DAILY_PRICE.date > start,
    opt.OPT_DAILY_PRICE.date < end,
    )

codf = opt.run_query(q)


q= query(opt.OPT_DAILY_PRICE.date,opt.OPT_DAILY_PRICE.volume,opt.OPT_DAILY_PRICE.money).filter(
    opt.OPT_DAILY_PRICE.code.in_(putOption),      
    opt.OPT_DAILY_PRICE.date > start,
    opt.OPT_DAILY_PRICE.date < end,
    )

podf = opt.run_query(q)

# codf = get_price(callOption,start_date=start, end_date=end, frequency='daily', fields=["volume","money"], skip_paused=False, fq='pre', count=None, panel=False)
# podf = get_price(putOption,start_date=start, end_date=end, frequency='daily', fields=["volume","money"], skip_paused=False, fq='pre', count=None, panel=False)

# 转变数据格式
callvol = pd.pivot_table(codf, values=["money", "volume"], index="date", aggfunc=[np.sum], dropna=True)
putvol  = pd.pivot_table(podf, values=["money", "volume"], index="date", aggfunc=[np.sum], dropna=True)

# 认购于认沽对比

fig = plt.figure(figsize=(10,13))
ax = fig.add_subplot(211)

import matplotlib.dates as mdates
ax.xaxis.set_major_formatter(mdates.DateFormatter('%y-%m-%d'))
ax.plot(putvol.index, putvol["sum", "volume"], '--gs',linewidth=1, label = u'Put Volume')
ax.plot(callvol.index, callvol["sum", "volume"], '--rs',linewidth=1, label = u'Call Volume')

ax.grid()
ax.set_xlabel(u"trade Date")
ax.set_ylabel(r"Turnover Volume")

ax1 = fig.add_subplot(212)
ax1.plot(putvol.index, putvol["sum", "money"], '--gs',linewidth=1, label = u'Put Money')
ax1.plot(callvol.index, callvol["sum", "money"], '--rs',linewidth=1, label = u'Put Money')
ax1.grid()
ax1.set_xlabel(u"trade Date")
ax1.set_ylabel(r"Turnover Money")

ax.legend(loc="best")
ax1.legend(loc="best")
plt.title('50ETF Option TurnoverVolume/ TurnoverMoney')

plt.show()