JUKUAN/Lib/Options/product_T_price.py

import pandas as pd
import numpy as np
import talib as tb
from pandas.plotting import  table
from jqdata import *

# 期权合约信息
class OptionContract:
    
    close: 0 #现价
    volume: 0 #成交量
    position: 0 #当前持仓量
    priceChangePct: 0 #收盘价涨跌幅
    intrinsic_value: 0 #内在价值
    time_value: 0 #时间价值
        
        
    def __init__(self,close, volume, position, priceChangePct, intrinsic_value=0, time_value=0):
        self.close = close
        self.volume = volume
        self.position = position
        self.priceChangePct = priceChangePct
        self.intrinsic_value = intrinsic_value
        self.time_value = time_value


        
# 同一行权价的一组期权
class OptionGroup:
    
    exercisePrice: 0 ##行权价
    call: None ##提醒的品种
    put: None  ##提醒的类型
        
    def __init__(self, exercisePrice, call, put):
        self.exercisePrice = exercisePrice
        self.call = call
        self.put = put
        
    def __init__(self, exercisePrice):
        self.exercisePrice = exercisePrice

#数据内容

CONTENT = [
    'close', 
    'volume', 
    'position', 
    'priceChangePct', 
]


##数据域
CONTENT_HEADER_MAP = {
    'prePosition': '昨日持仓',
    'close': '现价', 
    'volume': '成交量', 
    'position': '持仓量', 
    'priceChangePct': '涨跌幅'
}


# 豆粕期权
symbol = 'AU'

starttime =  '2025-06-30'
endtime = '2025-07-14'

SUBJECT_MATTER = get_dominant_future(symbol,date = starttime)
print(f"SUBJECT_MATTER: {SUBJECT_MATTER}")

#m2407 匹配 2024-04-19
EXPIRE_MONTH = '2025-09-24'

## 行权价间隔 比如3800 3750 每50元一档
gap = 8

# 获取期货价格
try:
    # 获取期货价格数据
    future_price_data = get_price(SUBJECT_MATTER, end_date=endtime, count=1, fields=['close'])
    current_future_price = float(future_price_data['close'].iloc[-1])
except Exception as e:
    print(f"获取期货价格失败: {e}")
    current_future_price = 781.4  # 使用模拟价格

print(f"标的期货价格: {current_future_price}")

#查询相关的合约,适用于商品

qy = query(opt.OPT_CONTRACT_INFO).filter(
    opt.OPT_CONTRACT_INFO.underlying_symbol == SUBJECT_MATTER, ##期权标的物
    opt.OPT_CONTRACT_INFO.expire_date == EXPIRE_MONTH,##期权到期日
).order_by(opt.OPT_CONTRACT_INFO.exercise_price, opt.OPT_CONTRACT_INFO.contract_type)

optList = opt.run_query(qy)

optList

code = SUBJECT_MATTER.split('.')[0]
print(f"code: {code}")

# optList.to_csv(f'price_list_{code}.csv')

# 获取实时数据
optionGroups = {}

for index, row in optList.iterrows():
    
    code = row['code'] #key - 期权代码
#     print(f"检查{code}的数据")
    #查询具体合约的信息,商品需要去掉开盘前的静态信息
    realTimeQuery = query(opt.OPT_DAILY_PRICE).filter(
        opt.OPT_DAILY_PRICE.code==code, 
        opt.OPT_DAILY_PRICE.date==endtime
    ).order_by(opt.OPT_DAILY_PRICE.date.desc()).limit(1)
    realTimeData = opt.run_query(realTimeQuery)
#     print(f"realTimeQuery: {realTimeQuery}")
#     print(f"realTimeData: {realTimeData}")
    
    #期权基本信息
    exercisePrice = row['exercise_price'] #行权价
    contractType = row['contract_type'] #合约类型。CO-认购期权，PO-认沽期权
    
    #实时表查询
    close = realTimeData.loc[0].at['close'] #现价
    volume = int(realTimeData.loc[0].at['volume']) #成交量
    position = realTimeData.loc[0].at['position'] #当前持仓量
    priceChangePct = str(round(realTimeData.loc[0].at['change_pct_close'], 2)) + '%' #收盘价涨跌幅
        
    #去除非标准的带A合约
    if(exercisePrice  % gap != 0):
        continue
        
    # 计算内在价值和时间价值
    if contractType == 'CO':  # 认购期权
        intrinsic_value = max(current_future_price - exercisePrice, 0)
        time_value = close - intrinsic_value
        print(f"处理认购期权, 期货价格: {current_future_price}, 行权价：{exercisePrice}")
        print(f"获得内在价值: {intrinsic_value}, 时间价值: {time_value}")
    else:  # 认沽期权
        intrinsic_value = max(exercisePrice - current_future_price, 0)
        time_value = close - intrinsic_value
        print(f"处理认沽期权, 期货价格: {current_future_price}, 行权价：{exercisePrice}")
        print(f"获得内在价值: {intrinsic_value}, 时间价值: {time_value}")
        
    optionContract = OptionContract(close, volume, position, priceChangePct, intrinsic_value, time_value)
    
    if(exercisePrice in optionGroups):
        
        if(contractType == 'CO'):
            optionGroups[exercisePrice].call = optionContract
        else:
            optionGroups[exercisePrice].put = optionContract
            
    else:
        
        optionGroup = OptionGroup(exercisePrice)
        
        if(contractType == 'CO'):
            optionGroup.call = optionContract
        else:
            optionGroup.put = optionContract
            
        optionGroups[exercisePrice] = optionGroup

# 使用optionGroups构造T型报价表
data = []

for exercisePrice in sorted(optionGroups.keys()):
    group = optionGroups[exercisePrice]
#     print(f"exercisePrice: {exercisePrice}, group: {group}")
    
    # 认购期权数据
    call_price = group.call.close if group.call else None
    call_volume = group.call.volume if group.call else None
    call_position = group.call.position if group.call else None
    call_change = group.call.priceChangePct if group.call else None
    call_intrinsic = group.call.intrinsic_value if group.call else None
#     print(f"exercisePrice: {exercisePrice}, call_intrinsic: {call_intrinsic}")
    call_time = group.call.time_value if group.call else None
    
    # 认沽期权数据
    put_price = group.put.close if group.put else None
    put_volume = group.put.volume if group.put else None
    put_position = group.put.position if group.put else None
    put_change = group.put.priceChangePct if group.put else None
    put_intrinsic = group.put.intrinsic_value if group.put else None
    put_time = group.put.time_value if group.put else None
    
    data.append({
        '认购涨跌幅': call_change,
#         '认购持仓量': call_position,
#         '认购成交量': call_volume,
        '认购时间价值': call_time,
        '认购内在价值': call_intrinsic,
        '认购价格': call_price,
        '行权价': exercisePrice,
        '认沽价格': put_price,
        '认沽内在价值': put_intrinsic,
        '认沽时间价值': put_time,
#         '认沽成交量': put_volume,
#         '认沽持仓量': put_position,
        '认沽涨跌幅': put_change
    })

# 创建T型报价DataFrame
df = pd.DataFrame(data)
# 确保df的列顺序为：'认购涨跌幅'，'认购持仓量'，'认购成交量'，'认购时间价值'，'认购内在价值'，'认购价格'，'行权价'，'认沽价格'，'认沽内在价值'，'认沽时间价值'，'认沽成交量'，'认沽持仓量'，'认沽涨跌幅'
df = df[['认购涨跌幅', '认购时间价值', '认购内在价值', '认购价格', '行权价', '认沽价格', '认沽内在价值', '认沽时间价值', '认沽涨跌幅']]

print("\n" + "="*100)
print("期权T型报价表（含内在价值和时间价值）")
print("="*100)
print(f"标的期货价格: {current_future_price}")
print("="*100)

# 显示T型报价
print(df.to_string(index=False))