JUKUAN/Lib/Options/Jiabailie/11_领口认购策略商品主力合约.py

# 领口看涨策略-商品主力合约
# 参考资料：
# - 原始策略来源: https://www.joinquant.com/view/community/detail/bec4688fd7998652edfd929a4ef1f4df
# - 研究网址: https://www.joinquant.com/research?target=research&url=/user/75474983526/notebooks/Options/%E9%A2%86%E5%8F%A3%E7%9C%8B%E6%B6%A8%E7%AD%96%E7%95%A5-%E5%95%86%E5%93%81%E4%B8%BB%E5%8A%9B%E5%90%88%E7%BA%A6.ipynb

# TODO: 添加领口看涨策略商品主力合约相关代码

import jqdata
from   jqdata import *
import pandas as pd
import numpy as np
import datetime
import matplotlib.pyplot as plt
from datetime import datetime, timedelta

plt.rcParams['font.sans-serif']=['SimHei']
plt.rcParams['axes.unicode_minus'] = False

def is_last_day_of_month(date_str):
    
    # 将字符串转换为日期对象
    date_obj = datetime.strptime(date_str, '%Y-%m-%d')
    
    # 获取下一个日期对象
    next_date_obj = date_obj + timedelta(days=1)
    
    # 判断是否为下个月的第一天，如果是，则当前日期为月末
    return date_obj.month != next_date_obj.month


def get_last_day_of_month(date_str):
    
    # 将字符串转换为日期对象
    date_obj = datetime.strptime(date_str, '%Y-%m-%d')
    
    # 获取下个月的第一天日期对象
    next_month_first_day = datetime(date_obj.year, date_obj.month + 1, 1)
    
    # 从下个月的第一天减去一天，得到当前月的月末日期对象
    last_day_of_month = next_month_first_day - timedelta(days=1)
    
    # 返回月末日期的字符串形式
    return last_day_of_month.strftime('%Y-%m-%d')


#获取期权
def getContract(code,date,type="CO"): #CO为认购，PO为认沽
    q_contract_info = query(opt.OPT_CONTRACT_INFO.code, 
                            opt.OPT_CONTRACT_INFO.trading_code,
                            opt.OPT_CONTRACT_INFO.name,
                            opt.OPT_CONTRACT_INFO.exercise_price, 
                            opt.OPT_CONTRACT_INFO.last_trade_date,
                            # 行权价格,最后交易日
                            opt.OPT_CONTRACT_INFO.list_date
                            ).filter(opt.OPT_CONTRACT_INFO.underlying_symbol == code,
                                     opt.OPT_CONTRACT_INFO.contract_type == type,  # 看涨期权
                                     )
    
    contract_info = opt.run_query(q_contract_info)
    commodity_cls = get_price(code, date, date, fields=['close']).values[0][0]
    
    if type == 'CO':
        
        contract_info['price_spread'] = contract_info['exercise_price'] - commodity_cls
        
    else:
        
        contract_info['price_spread'] = commodity_cls - contract_info['exercise_price']
        
        
    if contract_info['price_spread'].max() > 0:
        
        contract_info = contract_info[contract_info['price_spread'] > 0]  # 选出虚值期权
        contract_info = contract_info.sort_values('exercise_price')
        
    else:  # 全是实值期权
        
        contract_info = contract_info.sort_values('exercise_price', ascending=False)
        
    return(contract_info['code'].iloc[0])


#获取期权价格等信息
def getContractPrice(code,last_trade_date,type='CO'):
    q_contract_info = query(opt.OPT_CONTRACT_INFO.code, 
                            opt.OPT_CONTRACT_INFO.trading_code,
                            opt.OPT_CONTRACT_INFO.name,
                            opt.OPT_CONTRACT_INFO.exercise_price, 
                            opt.OPT_CONTRACT_INFO.last_trade_date,
                            # 行权价格,最后交易日
                            opt.OPT_CONTRACT_INFO.list_date
                            ).filter(opt.OPT_CONTRACT_INFO.code == code,
                                     opt.OPT_CONTRACT_INFO.contract_type == type,  # 期权类型
                                     opt.OPT_CONTRACT_INFO.last_trade_date >= last_trade_date
                                    ) 
    
    contract_info = opt.run_query(q_contract_info)
    
    return(contract_info)


#处理合约切换标记
def contractChange(holding_contract,main_list,error_date):
    
    data2 = pd.DataFrame(holding_contract)
    data2.columns = ['holding_contract']
    data2 = data2.reindex(columns=['holding_contract','close','last_close'])
    data2 = data2.drop(error_date)
    main_list = main_list.drop(error_date)
    last_contract = holding_contract.iloc[0]   #记录上个持仓
    
    for i in range(0,len(data2.index)):
        
        t = data2.index[i]
        
        if last_contract == data2.loc[t,'holding_contract']:  #期权未换仓
            
            q_price = query(opt.OPT_DAILY_PRICE.code, 
                            opt.OPT_DAILY_PRICE.date, 
                            opt.OPT_DAILY_PRICE.close,
                     ).filter(opt.OPT_DAILY_PRICE.code==last_contract,
                              opt.OPT_DAILY_PRICE.date==t)
            
            price = opt.run_query(q_price)['close'][0]
            data2.loc[t,'close'] = price
            
        else: #合约换仓
            
            q_price = query(opt.OPT_DAILY_PRICE.code, 
                            opt.OPT_DAILY_PRICE.date, 
                            opt.OPT_DAILY_PRICE.close,
                     ).filter(opt.OPT_DAILY_PRICE.code==data2.loc[t,'holding_contract'],
                             opt.OPT_DAILY_PRICE.date==t)
            
            price = opt.run_query(q_price)['close'][0]
            
            data2.loc[t,'close'] = price
            
            
            #收盘价,旧
            q_price = query(opt.OPT_DAILY_PRICE.code, 
                            opt.OPT_DAILY_PRICE.date, 
                            opt.OPT_DAILY_PRICE.close,
                     ).filter(opt.OPT_DAILY_PRICE.code==last_contract,
                              opt.OPT_DAILY_PRICE.date==data2.index[i-1])
            
            price = opt.run_query(q_price)['close'][0]
            
            data2.loc[t,'last_close'] = price
            
            last_contract = data2.loc[t,'holding_contract']            
            
    return(data2)
        
    
    
def optionProfit(data2,price_gap,fee):
    
    #计算平仓期权的收益
    opt_ret2 = pd.Series(0,index=data2.index)
    pre_close2 = data2['close'].iloc[0]
    
    for t in data2.index[1:]:
        
        if data2.isna().loc[t,'last_close']:   #未换仓,last为空
            
            opt_ret2[t] = -price_gap*(data2.loc[t,'close'] - pre_close2)
            
        else:
            
            opt_ret2[t] = -price_gap*(data2.loc[t,'last_close'] - pre_close2) - fee  #手续费
            
        pre_close2 = data2.loc[t,'close']
        
    return(opt_ret2)

# 设置各项参数
# 合约代码
symbol = 'AU'

#手续费
fee = 5

#合约价差
price_gap = 10

#起始时间
starttime = '2023-03-01'
endtime   = '2024-01-01'

SUBJECT_MATTER = get_dominant_future(symbol,date = starttime)

#获取交易时间和时间间隔（频率：月）
#根据不同交易日分割月份
#指定回测的起始时间
trade_days = pd.Series(index=jqdata.get_trade_days(starttime,endtime))
trade_days.index = pd.to_datetime(trade_days.index)

##持仓情况
#主力合约列表
main_list = pd.Series(index=trade_days.index)
main_list[trade_days.index[0]] = SUBJECT_MATTER
holding_contract_CO = pd.Series(index=trade_days.index)

#获取首个认购持仓合约
contract = getContract(SUBJECT_MATTER,trade_days.index[0],type='CO')
holding_contract_CO[trade_days.index[0]] = contract
print(holding_contract_CO[:3])

#获取首个认沽持仓合约
holding_contract_PO = pd.Series(index=trade_days.index)
contract = getContract(SUBJECT_MATTER,trade_days.index[0],type='PO')
holding_contract_PO[trade_days.index[0]] = contract
print(holding_contract_PO[:3])

#循环访问每一个交易日，判断交易情况
#规则:判断当前主力合约对应的期权，持有略虚值看涨期权，待行权价低于现价的95%时，平仓原期权合约，重新开仓略虚值看涨期权
error_date =[]
pre_hold_CO = holding_contract_CO[0]
pre_hold_PO = holding_contract_PO[0]

for i in range(1,len(trade_days)):
    
    pre_day = trade_days.index[i-1]
    cur_day = trade_days.index[i]
    cur_main = get_dominant_future(symbol,date = cur_day) #当前主力合约
    pre_main = get_dominant_future(symbol,date = pre_day) #上一个交易日的主力合约
    main_list[cur_day] = cur_main
    
    
    if cur_main != pre_main: #主力合约切换
        
        contract_CO = getContract(cur_main,cur_day,type='CO')
        contract_PO = getContract(cur_main,cur_day,type='PO')
        
    else:
        
        pre_cls = get_price(cur_main, cur_day, cur_day, fields=['pre_close']).values[0][0]
        contract_info_CO = getContractPrice(pre_hold_CO,cur_day,"CO")
        pre_exercise_price_CO = contract_info_CO
        contract_info_PO = getContractPrice(pre_hold_PO,cur_day,"PO")
        pre_exercise_price_PO = contract_info_PO
        
        if contract_info_CO.empty | contract_info_PO.empty:
            
            error_date.append(cur_day)
            continue
            
        else:
            
            pre_exercise_price_CO = pre_exercise_price_CO['exercise_price'][0]
            pre_exercise_price_PO = pre_exercise_price_PO['exercise_price'][0]
            
            if pre_cls * 0.95 >= pre_exercise_price_CO:
                
                contract_CO = getContract(pre_main,cur_day)
                
            else:
                
                contract_CO = pre_hold_CO
            
            if pre_cls   <= 0.95 * pre_exercise_price_PO:
                
                contract_PO = getContract(pre_main,cur_day,type='PO')
            else:
                
                contract_PO = pre_hold_PO
    
    
    holding_contract_CO[cur_day] = contract_CO
    pre_hold_CO = contract_CO
    holding_contract_PO[cur_day] = contract_PO
    pre_hold_PO = contract_PO
    
holding_contract_CO = holding_contract_CO.fillna(method='ffill')
holding_contract_PO = holding_contract_PO.fillna(method='ffill')

data_list_CO = contractChange(holding_contract_CO,main_list,error_date)
data_list_PO = contractChange(holding_contract_PO,main_list,error_date)

#计算平仓期权的收益
opt_ret_CO = optionProfit(data_list_CO,price_gap,fee)
opt_ret_PO = optionProfit(data_list_PO,price_gap,fee)
opt_ret = opt_ret_CO + opt_ret_PO
print(opt_ret)

#计算持仓收益
commodity_price = [get_price(main_list[t],data_list_CO.index[t],data_list_CO.index[t],fields=['close'])['close'][0] for t in range(0,len(data_list_CO.index))]
commodity_price = pd.Series(commodity_price,index=data_list_CO.index)

commodity_ret = commodity_price.diff(1).fillna(0)
commodity_ret

#计算净值
init_asset2 = commodity_price.iloc[0]*price_gap
ass2 = init_asset2 + (commodity_ret + opt_ret).cumsum()

pfl_ret2 = (ass2/ass2.shift(1) - 1).fillna(0)
pfl_nv2 = (1 + pfl_ret2).cumprod()
pfl_nv2

#绘制净值图
plt.figure(figsize=(30,20))
plt.plot(commodity_price/commodity_price.iloc[0], label='现货净值')
plt.plot(pfl_nv2, label=symbol+'领式看涨策略净值')
plt.legend(loc='upper left', fontsize='large')
plt.xlabel('时间',size=12)
plt.ylabel('净值',size=12)
plt.show()