A期客期货期权宽跨策略
import datetime
import jqdata
from jqdata import *
from jqdata import jy
import numpy as np
import pandas as pd
from scipy import stats
import seaborn as sns
import matplotlib.pyplot as plt
# 获得交易日日期序列
end_date=datetime.date.today()
start_date=datetime.date(2018,3,25)
date_list=list(jqdata.get_trade_days(start_date=start_date,end_date=end_date))
# 获得假期前一个工作日
open_date_list=[]
close_date_list=[]
for i in range(len(date_list)-1):
if (date_list[i+1]-date_list[i]).days!=1:
open_date_list.append(date_list[i])
close_date_list.append(date_list[i+1])
收起代码 ↑
def get_50ETF_option(date,dfSignal=False):
S0=get_price('510050.XSHG',start_date=date,end_date=date,fields=['close']).values[0][0]
r=0.03
q=query(jy.Opt_DailyPreOpen).filter(jy.Opt_DailyPreOpen.TradingDate==date,jy.Opt_DailyPreOpen.ULAName=='50ETF')
df=jy.run_query(q).loc[:,['ContractCode','TradingCode','StrikePrice','ExerciseDate']]
exercise_date_list=sorted(df['ExerciseDate'].unique())
key_list=[]
Contract_dict={}
Price_dict={}
impVol_dict={}
for exercise_date in exercise_date_list:
#获得T型代码
df1=df[df['ExerciseDate']==exercise_date]
#去除调整合约
check=[]
for i in df1['TradingCode']:
x=True if i[11]=='M' and i[6]=='C' else False
check.append(x)
df_C=df1[check][['ContractCode','StrikePrice']]
df_C.index=df_C.StrikePrice.values
del df_C['StrikePrice']
df_C.columns=['Call']
df_C=df_C.sort_index()
#去除调整合约
check=[]
for i in df1['TradingCode']:
x=True if i[11]=='M' and i[6]=='P' else False
check.append(x)
df_P=df1[check][['ContractCode','StrikePrice']]
df_P.index=df_P.StrikePrice.values
del df_P['StrikePrice']
df_P.columns=['Put']
df_P=df_P.sort_index()
dfT=pd.concat([df_C,df_P],axis=1)
exercise_date=datetime.datetime.strptime(str(exercise_date)[:10],'%Y-%m-%d')
exercise_date=datetime.date(exercise_date.year,exercise_date.month,exercise_date.day)
Contract_dict[exercise_date]=dfT
#T型价格
q=query(jy.Opt_DailyQuote).filter(jy.Opt_DailyQuote.TradingDate==date)
df2=jy.run_query(q).loc[:,['ContractCode','ClosePrice']]
df2.index=df2['ContractCode'].values
del df2['ContractCode']
dfPrice=dfT.copy()
dfPrice['Call']=df2.loc[dfT.loc[:,'Call'].values,:].values
dfPrice['Put']=df2.loc[dfT.loc[:,'Put'].values,:].values
dfPrice=dfPrice
Price_dict[exercise_date]=dfPrice
key_list.append(exercise_date)
strike_price=list(Contract_dict[key_list[0]].index)
atm_index=list(abs(np.round(S0-strike_price,3))).index(min(abs(np.round(S0-strike_price,3))))
atm_K=strike_price[atm_index]
if dfSignal:
value_list=[]
for key,value in Contract_dict.items():
value['exercise_date']=key
value_list.append(value)
Contract_df=pd.concat(value_list).sort('exercise_date')
value_list=[]
for key,value in Price_dict.items():
value['exercise_date']=key
value_list.append(value)
Price_df=pd.concat(value_list).sort('exercise_date')
return Contract_df,Price_df,key_list,S0
return Contract_dict,Price_dict,key_list,S0
def get_target_option(Contract_dict,Price_dict,key_list,S0,term=0,strategy=1):
# Contract合约数据 Price价格数据 key_list是四个合约的到期日
#S0当前标的价格 term远近合约选择 strategy策略
expiry_date=key_list[term]
Contract=Contract_dict[expiry_date]
Price=Price_dict[expiry_date]
strike_price=list(Contract.index)
#选择跨式期权位置
check=min(abs(np.round(S0-strike_price,3)))
if check<0.01:
strategy=0
else:
strategy=strategy
if strategy==0:
atm_index=list(abs(np.round(S0-strike_price,3))).index(min(abs(np.round(S0-strike_price,3))))
atm_k=strike_price[atm_index]
result=pd.DataFrame(index=['Strike','ticker','Price'],columns=['Call','Put'])
result.loc['Strike','Call']=atm_k
result.loc['Strike','Put']=atm_k
result.loc['ticker','Call']=Contract.loc[atm_k,'Call']
result.loc['ticker','Put']=Contract.loc[atm_k,'Put']
result.loc['Price','Call']=Price.loc[atm_k,'Call']
result.loc['Price','Put']=Price.loc[atm_k,'Put']
if strategy==1:
#print(S0)
for i in range(len(strike_price)-1):
if strike_price[i]<=S0 and strike_price[i+1]>S0:
#print(i,i+1)
k1=strike_price[i]
k2=strike_price[i+1]
#print(strike_price)
#print(S0,k1,k2)
result=pd.DataFrame(index=['Strike','ticker','Price'],columns=['Call','Put'])
result.loc['Strike','Call']=k2
result.loc['Strike','Put']=k1
result.loc['ticker','Call']=Contract.loc[k2,'Call']
result.loc['ticker','Put']=Contract.loc[k1,'Put']
result.loc['Price','Call']=Price.loc[k2,'Call']
result.loc['Price','Put']=Price.loc[k1,'Put']
if strategy==2:
for i in range(len(strike_price)-1):
if strike_price[i]<=S0 and strike_price[i+1]>S0:
k1=strike_price[i-1]
k2=strike_price[i+2]
result=pd.DataFrame(index=['Strike','ticker','Price'],columns=['Call','Put'])
result.loc['Strike','Call']=k2
result.loc['Strike','Put']=k1
result.loc['ticker','Call']=Contract.loc[k2,'Call']
result.loc['ticker','Put']=Contract.loc[k1,'Put']
result.loc['Price','Call']=Price.loc[k2,'Call']
result.loc['Price','Put']=Price.loc[k1,'Put']
return result
def get_50ETF_price_byday(date,Code):
q=query(jy.Opt_DailyQuote).filter(jy.Opt_DailyQuote.TradingDate==date,jy.Opt_DailyQuote.ContractCode==Code)
df=jy.run_query(q).loc[:,['ContractCode','ClosePrice']]
price=df.loc[0,'ClosePrice']
return price
收起代码 ↑
N=len(open_date_list)
columns=['t','St','CK','PK','Callcode','Putcode','Callt','Putt','T','ST','CallT','PutT']
df=pd.DataFrame(index=list(range(N)),columns=columns)
for i in range(N):
open_date=open_date_list[i]
Contract_dict,Price_dict,key_list,S0=get_50ETF_option(open_date,dfSignal=False)
table=get_target_option(Contract_dict,Price_dict,key_list,S0,1,1)
df.loc[i,'t']=open_date
df.loc[i,'St']=S0
df.loc[i,'CK']=table.loc['Strike','Call']
df.loc[i,'PK']=table.loc['Strike','Put']
Callcode=table.loc['ticker','Call']
Putcode=table.loc['ticker','Put']
df.loc[i,'Callcode']=Callcode
df.loc[i,'Putcode']=Putcode
df.loc[i,'Callt']=table.loc['Price','Call']
df.loc[i,'Putt']=table.loc['Price','Put']
close_date=close_date_list[i]
df.loc[i,'T']=close_date
df.loc[i,'ST']=get_price('510050.XSHG',start_date=close_date,end_date=close_date,fields=['close']).values[0][0]
df.loc[i,'CallT']=get_50ETF_price_byday(close_date,Callcode)
df.loc[i,'PutT']=get_50ETF_price_byday(close_date,Putcode)Click to rate this post!
