# 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()