JUKUAN/Lib/Options/Jiabailie/08_豆粕备兑认购策略.py

# 豆粕-备兑看涨策略
# 参考资料：
# - 原始策略来源: https://www.joinquant.com/view/community/detail/4bf820b677d7d774f54c122460533b2e
# - 研究网址: https://www.joinquant.com/research?target=research&url=/user/75474983526/notebooks/Options/%E8%B1%86%E7%B2%95-%E5%A4%87%E5%85%91%E7%9C%8B%E6%B6%A8%E7%AD%96%E7%95%A5.ipynb

# TODO: 添加豆粕备兑看涨策略相关代码

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

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

from datetime import datetime, timedelta

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')

# 豆粕合约
SUBJECT_MATTER = 'M2409.XDCE'
info = get_security_info(SUBJECT_MATTER)
starttime = str(info.start_date)
endtime = str(info.end_date)
print(starttime)
print(endtime)

#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.contract_type == 'CO'
).order_by(opt.OPT_CONTRACT_INFO.exercise_price)

#合约价差
price_gap = 10
optList = opt.run_query(qy)
optList

#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)

last_day = get_last_day_of_month(endtime)

month_split = list(trade_days.resample('M',label='left').mean().index) + [pd.to_datetime(last_day)]
month_split

##持仓情况
holding_contract2 = pd.Series(index=trade_days.index)

#获取首个持仓合约
q_contract_info = query(opt.OPT_CONTRACT_INFO.code, 
                        opt.OPT_CONTRACT_INFO.trading_code, 
                        opt.OPT_CONTRACT_INFO.name, #合约代码,合约交易代码,合约简称
                        opt.OPT_CONTRACT_INFO.exercise_price, opt.OPT_CONTRACT_INFO.last_trade_date, 
                        opt.OPT_CONTRACT_INFO.list_date
         ).filter(opt.OPT_CONTRACT_INFO.underlying_symbol == SUBJECT_MATTER,
                 opt.OPT_CONTRACT_INFO.contract_type == 'CO') 

contract_info = opt.run_query(q_contract_info)
contract_info

commodity_cls = get_price(SUBJECT_MATTER,trade_days.index[0],trade_days.index[0],fields=['close']).values[0][0]
contract_info['price_spread'] = contract_info['exercise_price'] - commodity_cls

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) 
    
contract_info

holding_contract2[trade_days.index[0]] = contract_info['code'].iloc[0]
newest_exercise_price = contract_info['exercise_price'].iloc[0]
newest_expire_date = contract_info['last_trade_date'].iloc[0]

print(newest_exercise_price)
print(newest_expire_date)

# 循环访问每一个交易日，判断交易情况
# 规则: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；到期前1天移仓换月至次月合约

for t in trade_days.index[1:]:
    
    # 获取昨日收盘价
    pre_cls = get_price(SUBJECT_MATTER, t, t, fields=['pre_close']).values[0][0]
    
    if pre_cls * 0.95 >= newest_exercise_price:  # 原虚值变为实值,重新开仓略虚值期权
        
        # 寻找month_idx
        for month_idx in range(len(month_split)):
            if month_split[month_idx] >= t:
                break
        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 == SUBJECT_MATTER,
                                         opt.OPT_CONTRACT_INFO.contract_type == 'CO',  # 看涨期权
                                         )  # 在交易前上市
        
        contract_info = opt.run_query(q_contract_info)
        commodity_cls = get_price(SUBJECT_MATTER, t, t, fields=['close']).values[0][0]
        contract_info['price_spread'] = contract_info['exercise_price'] - commodity_cls
        
        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)
            
        holding_contract2[t] = contract_info['code'].iloc[0]
        newest_exercise_price = contract_info['exercise_price'].iloc[0]
        newest_expire_date = contract_info['last_trade_date'].iloc[0]


holding_contract2 = holding_contract2.fillna(method='ffill')
holding_contract2

data2 = pd.DataFrame(holding_contract2)
data2.columns = ['holding_contract']
data2 = data2.reindex(columns=['holding_contract','close','last_close'])

last_contract = holding_contract2.iloc[0]   #记录上个持仓

for t in data2.index:
        #收盘价
    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)
    
    if price.empty:
        continue
    else:
        price = price['close'][0]
        data2.loc[t,'close'] = price
     
data2

t = data2.index[2]

data2.loc[t,'holding_contract']

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)
price

#计算卖出期权的收益
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) - 5  #手续费5元
        
    pre_close2 = data2.loc[t,'close']
    
opt_ret2

#计算持仓收益
commodity_price = get_price(SUBJECT_MATTER,trade_days.index[0],trade_days.index[-1],fields=['close'])['close']
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_ret2).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=SUBJECT_MATTER+'备兑看涨策略净值')
plt.legend(loc='upper left', fontsize='large')
plt.xlabel('时间',size=12)
plt.ylabel('净值',size=12)
plt.show()