# for target_delta in [-0.1,-0.2,-0.3,-0.4]:
for target_delta in [None]:
option_amt = []
optionset = BaseOptionSet(df_metrics)
optionset.init()
underlying = BaseInstrument(df_underlying)
underlying.init()
account = BaseAccount(init_fund=10000000, leverage=1.0, rf=0.03)
""" init open position """
unit_underlying = np.floor(pct_underlying_invest * account.cash /
underlying.mktprice_close() /
underlying.multiplier())
order_underlying = account.create_trade_order(underlying,
c.LongShort.LONG,
unit_underlying)
record_underlying = underlying.execute_order(order_underlying,
slippage=slippage)
account.add_record(record_underlying, underlying)
maturity1 = optionset.select_maturity_date(nbr_maturity=nbr_maturity,
min_holding=min_holding)
list_atm_call, list_atm_put = optionset.get_options_list_by_moneyness_mthd1(
moneyness, maturity1)
if list_atm_put is None:
# list_atm_call, list_atm_put = optionset.get_options_list_by_moneyness_mthd1(0, maturity1)
print('choose min strike')
list_atm_put = optionset.get_deepest_otm_put_list(maturity1)
atm_put = optionset.select_higher_volume(list_atm_put)
underlying_value = unit_underlying * underlying.mktprice_close(
) * underlying.multiplier()
unit = get_option_unit(atm_put, underlying_value, target_delta)
order = account.create_trade_order(atm_put, c.LongShort.LONG, unit)
record = atm_put.execute_order(order, slippage=slippage)
class HedgeIndexByOptions(object):
def __init__(self,
df_baseindex,
df_option_metrics,
df_c1=None,
df_all=None,
cd_direction_timing='ma',
cd_strategy='bull_spread',
cd_volatility='close_std',
cd_short_ma='ma_5',
cd_long_ma='ma_60',
cd_std='std_10'):
self.min_holding = 20
self.slippage = 0
self.nbr_maturity = 0
self.moneyness_rank = 0
self.cd_trade_price = c.CdTradePrice.VOLUME_WEIGHTED
# self.cd_trade_price = c.CdTradePrice.CLOSE
if df_c1 is None:
dt_start = max(df_option_metrics[c.Util.DT_DATE].values[0],
df_baseindex[c.Util.DT_DATE].values[0])
self.end_date = min(df_option_metrics[c.Util.DT_DATE].values[-1],
df_baseindex[c.Util.DT_DATE].values[-1])
df_metrics = df_option_metrics[
df_option_metrics[c.Util.DT_DATE] >= dt_start].reset_index(
drop=True)
df_baseindex = df_baseindex[
df_baseindex[c.Util.DT_DATE] >= dt_start].reset_index(
drop=True)
self.invst_portfolio = BaseInstrument(
df_baseindex) # e.g., top 50 low volatility index
self.invst_portfolio.init()
else:
dt_start = max(df_option_metrics[c.Util.DT_DATE].values[0],
df_baseindex[c.Util.DT_DATE].values[0],
df_c1[c.Util.DT_DATE].values[0])
self.end_date = min(df_option_metrics[c.Util.DT_DATE].values[-1],
df_baseindex[c.Util.DT_DATE].values[-1],
df_c1[c.Util.DT_DATE].values[-1])
df_metrics = df_option_metrics[
df_option_metrics[c.Util.DT_DATE] >= dt_start].reset_index(
drop=True)
df_baseindex = df_baseindex[
df_baseindex[c.Util.DT_DATE] >= dt_start].reset_index(
drop=True)
df_c1 = df_c1[df_c1[c.Util.DT_DATE] >= dt_start].reset_index(
drop=True)
df_all = df_all[df_all[c.Util.DT_DATE] >= dt_start].reset_index(
drop=True)
self.invst_portfolio = BaseFutureCoutinuous(
df_c1, df_futures_all_daily=df_all
) # e.g., top 50 low volatility index
self.invst_portfolio.init()
self.optionset = BaseOptionSet(df_metrics)
self.index = BaseInstrument(df_baseindex)
self.optionset.init()
self.index.init()
self.account = BaseAccount(init_fund=c.Util.BILLION,
leverage=1.0,
rf=0.03)
self.prepare_timing(df_baseindex)
self.cd_direction_timing = cd_direction_timing
self.cd_strategy = cd_strategy
self.cd_volatility = cd_volatility
self.cd_short_ma = cd_short_ma
self.cd_long_ma = cd_long_ma
self.cd_std = cd_std
self.dict_strategy = {}
self.nbr_timing = 0
self.nbr_stop_loss = 0
self.nvp_adjustment = 0
self.sl_npv_high_point = 1.0
self.strategy_pause = False
def prepare_timing(self, df_index):
df_index['ma_3'] = c.Statistics.moving_average(
df_index[c.Util.AMT_CLOSE], n=3).shift()
df_index['ma_5'] = c.Statistics.moving_average(
df_index[c.Util.AMT_CLOSE], n=5).shift()
df_index['ma_10'] = c.Statistics.moving_average(
df_index[c.Util.AMT_CLOSE], n=10).shift()
df_index['ma_15'] = c.Statistics.moving_average(
df_index[c.Util.AMT_CLOSE], n=15).shift()
df_index['ma_20'] = c.Statistics.moving_average(
df_index[c.Util.AMT_CLOSE], n=20).shift()
df_index['ma_30'] = c.Statistics.moving_average(
df_index[c.Util.AMT_CLOSE], n=30).shift()
df_index['ma_40'] = c.Statistics.moving_average(
df_index[c.Util.AMT_CLOSE], n=40).shift()
df_index['ma_50'] = c.Statistics.moving_average(
df_index[c.Util.AMT_CLOSE], n=50).shift()
df_index['ma_60'] = c.Statistics.moving_average(
df_index[c.Util.AMT_CLOSE], n=60).shift()
df_index['ma_120'] = c.Statistics.moving_average(
df_index[c.Util.AMT_CLOSE], n=120).shift()
df_index['std_5'] = c.Statistics.standard_deviation(
df_index[c.Util.AMT_CLOSE], n=5).shift()
df_index['std_10'] = c.Statistics.standard_deviation(
df_index[c.Util.AMT_CLOSE], n=10).shift()
df_index['std_15'] = c.Statistics.standard_deviation(
df_index[c.Util.AMT_CLOSE], n=15).shift()
df_index['std_20'] = c.Statistics.standard_deviation(
df_index[c.Util.AMT_CLOSE], n=20).shift()
df_index['ma_3-20'] = df_index['ma_3'] - df_index['ma_20']
self.df_timing = df_index.set_index(c.Util.DT_DATE)
def open_signal(self):
if self.cd_direction_timing == 'ma':
return self.open_position_ma()
def close_signal(self):
if self.cd_direction_timing == 'ma':
return self.close_position_ma()
def stop_loss_beg(self, drawdown, P_mdd):
if drawdown.loc[self.optionset.eval_date, c.Util.DRAWDOWN] <= P_mdd:
return True
def stop_loss_end(self, drawdown, P_mdd):
if drawdown.loc[
self.optionset.eval_date,
c.Util.PORTFOLIO_NPV] >= self.account.account[
c.Util.PORTFOLIO_NPV].values[-1] + self.nvp_adjustment:
self.nvp_adjustment = drawdown.loc[
self.optionset.eval_date,
c.Util.PORTFOLIO_NPV] - self.account.account[
c.Util.PORTFOLIO_NPV].values[-1]
self.nbr_stop_loss += 1
print(self.optionset.eval_date, ' stop loss end ')
print(self.nvp_adjustment,
self.account.account[c.Util.PORTFOLIO_NPV].values[-1],
drawdown.loc[self.optionset.eval_date, c.Util.PORTFOLIO_NPV])
return True
def strategy(self, cd_price=c.CdPriceType.OPEN):
if self.cd_strategy == 'bull_spread':
if self.cd_volatility == 'close_std':
dt_date = self.optionset.eval_date
std_close = self.df_timing.loc[dt_date, self.cd_std]
k_short = self.index.mktprice_open() - std_close
put_long, put_short = self.bull_spread(k_short, cd_price)
return {
c.LongShort.SHORT: put_short,
c.LongShort.LONG: put_long
}
def shift(self):
if self.cd_strategy == 'bull_spread':
return self.shift_bull_spread()
def open_position_ma(self):
dt_date = self.optionset.eval_date
if dt_date not in self.df_timing.index:
return False
ma_5 = self.df_timing.loc[dt_date, self.cd_short_ma]
ma_60 = self.df_timing.loc[dt_date, self.cd_long_ma]
if ma_5 < ma_60:
return True
else:
return False
def close_position_ma(self):
dt_date = self.optionset.eval_date
dt_maturity = None
for option in self.account.dict_holding.values():
if isinstance(option, BaseOption) and option is not None:
dt_maturity = option.maturitydt()
break
if dt_maturity is not None and (dt_maturity - dt_date).days <= 5:
return True
ma_5 = self.df_timing.loc[dt_date, self.cd_short_ma]
ma_60 = self.df_timing.loc[dt_date, self.cd_long_ma]
if ma_5 >= ma_60:
print(self.optionset.eval_date)
self.nbr_timing += 1
return True
else:
return False
def bull_spread(self, k_short, cd_price=c.CdPriceType.OPEN):
maturity = self.optionset.select_maturity_date(
nbr_maturity=self.nbr_maturity, min_holding=self.min_holding)
xx, list_put0 = self.optionset.get_options_list_by_moneyness_mthd1(
moneyness_rank=self.moneyness_rank,
maturity=maturity,
cd_price=cd_price)
put_long = self.optionset.select_higher_volume(list_put0)
# if put_long is None:
# xxx, list_put0 = optionset.get_options_list_by_moneyness_mthd1(moneyness_rank=0,
# maturity=maturity,
# cd_price=c.CdPriceType.OPEN)
# put_long = optionset.select_higher_volume(list_put0)
put_short = self.optionset.select_higher_volume(
self.optionset.get_option_closest_strike(c.OptionType.PUT, k_short,
maturity))
if put_short is not None:
if put_short.strike() >= (k_short + put_long.strike()) / 2.0:
put_short = None
elif put_short.id_instrument() == put_long.id_instrument():
xx, list_put1 = self.optionset.get_options_list_by_moneyness_mthd1(
moneyness_rank=-1, maturity=maturity, cd_price=cd_price)
put_short = self.optionset.select_higher_volume(list_put1)
# put_short = None
return put_long, put_short
def shift_bull_spread(self):
option_short = self.dict_strategy[c.LongShort.SHORT]
option_long = self.dict_strategy[c.LongShort.LONG]
if option_short is None:
return self.strategy()
else:
if self.index.mktprice_last_close() <= (option_long.strike() +
option_short.strike()) / 2:
return self.strategy()
else:
return None
def excute(self, dict_strategy, cd_trade_price=None):
if cd_trade_price is None:
cd_trade_price = self.cd_trade_price
if dict_strategy is None: return
for long_short in dict_strategy.keys():
option = dict_strategy[long_short]
if option is None:
continue
elif long_short in self.dict_strategy.keys() and self.dict_strategy[long_short] is not None \
and option.id_instrument() == self.dict_strategy[long_short].id_instrument():
continue
unit = self.unit_index / option.multiplier()
order = self.account.create_trade_order(
option, long_short, unit, cd_trade_price=cd_trade_price)
record = option.execute_order(order, slippage=self.slippage)
self.account.add_record(record, option)
self.dict_strategy = dict_strategy
def close_options(self):
for option in self.account.dict_holding.values():
if isinstance(option, BaseOption):
order = self.account.create_close_order(
option, cd_trade_price=self.cd_trade_price)
record = option.execute_order(order, slippage=self.slippage)
self.account.add_record(record, option)
self.dict_strategy = {}
def close_out(self):
close_out_orders = self.account.creat_close_out_order(
cd_trade_price=c.CdTradePrice.CLOSE)
for order in close_out_orders:
execution_record = self.account.dict_holding[order.id_instrument] \
.execute_order(order, slippage=self.slippage, execute_type=c.ExecuteType.EXECUTE_ALL_UNITS)
self.account.add_record(
execution_record,
self.account.dict_holding[order.id_instrument])
def back_test(self):
self.unit_index = np.floor(self.account.cash /
self.index.mktprice_close() /
self.index.multiplier())
unit_portfolio = np.floor(self.account.cash /
self.invst_portfolio.mktprice_close() /
self.invst_portfolio.multiplier())
order_index = self.account.create_trade_order(
self.invst_portfolio,
c.LongShort.LONG,
unit_portfolio,
cd_trade_price=c.CdTradePrice.CLOSE)
record_index = self.invst_portfolio.execute_order(
order_index, slippage=self.slippage)
self.account.add_record(record_index, self.invst_portfolio)
empty_position = True
init_index = self.index.mktprice_close()
init_portfolio = self.invst_portfolio.mktprice_close()
base_npv = []
index_npv = []
while self.optionset.eval_date <= self.end_date:
# if self.optionset.eval_date == datetime.date(2016,5,20):
# print('')
# print(self.optionset.eval_date)
if self.optionset.eval_date >= self.end_date: # Final close out all.
close_out_orders = self.account.creat_close_out_order()
for order in close_out_orders:
execution_record = self.account.dict_holding[order.id_instrument] \
.execute_order(order, slippage=self.slippage, execute_type=c.ExecuteType.EXECUTE_ALL_UNITS)
self.account.add_record(
execution_record,
self.account.dict_holding[order.id_instrument])
self.account.daily_accounting(self.optionset.eval_date)
base_npv.append(self.invst_portfolio.mktprice_close() /
init_portfolio)
index_npv.append(self.index.mktprice_close() / init_index)
print(self.optionset.eval_date, ' close out ')
break
if not empty_position:
if self.close_signal():
self.close_options()
empty_position = True
else:
strategy = self.shift()
if strategy is not None:
self.close_options()
self.excute(strategy)
if empty_position and self.open_signal():
self.excute(self.strategy())
empty_position = False
#TODO:移仓换月
if isinstance(self.invst_portfolio, BaseFutureCoutinuous):
self.invst_portfolio.shift_contract_month(
self.account, self.slippage)
self.account.daily_accounting(self.optionset.eval_date)
self.account.account.loc[self.optionset.eval_date,
'unit_index'] = self.unit_index
self.account.account.loc[
self.optionset.eval_date,
'close_index'] = self.index.mktprice_close()
# print(self.optionset.eval_date,estimated_npv1,estimated_npv2,estimated_npv3,self.account.account.loc[self.optionset.eval_date,c.Util.PORTFOLIO_NPV])
base_npv.append(self.invst_portfolio.mktprice_close() /
init_portfolio)
index_npv.append(self.index.mktprice_close() / init_index)
# print(self.invst_portfolio.eval_date, self.account.account.loc[self.optionset.eval_date,c.Util.PORTFOLIO_NPV],
# self.invst_portfolio.mktprice_close() / init_index)
if not self.optionset.has_next(): break
self.optionset.next()
self.index.next()
self.invst_portfolio.next()
self.account.account['base_npv'] = base_npv
self.account.account['index_npv'] = index_npv
# active_npv = self.df_index[self.df_index[c.Util.DT_DATE]<=self.optionset.eval_date].reset_index(drop=True)
# self.account.account['active_npv'] = active_npv[c.Util.AMT_CLOSE]
self.account.nbr_timing = self.nbr_timing
# print(self.account.account.loc[self.invst_portfolio.eval_date,c.Util.PORTFOLIO_NPV])
return self.account
def back_test_with_stop_loss(self, drawdown, P_mdd):
self.P_mdd = P_mdd
self.unit_index = np.floor(self.account.cash /
self.index.mktprice_close() /
self.index.multiplier())
order_index = self.account.create_trade_order(
self.index,
c.LongShort.LONG,
self.unit_index,
cd_trade_price=c.CdTradePrice.CLOSE)
record_index = self.index.execute_order(order_index,
slippage=self.slippage)
self.account.add_record(record_index, self.index)
empty_position = True
init_index = self.index.mktprice_close()
base_npv = []
stop_loss_paused = False
while self.optionset.eval_date <= self.end_date:
# if self.optionset.eval_date == datetime.date(2016,5,20):
# print('')
# print(self.optionset.eval_date)
if self.optionset.eval_date >= self.end_date: # Final close out all.
close_out_orders = self.account.creat_close_out_order()
for order in close_out_orders:
execution_record = self.account.dict_holding[order.id_instrument] \
.execute_order(order, slippage=self.slippage, execute_type=c.ExecuteType.EXECUTE_ALL_UNITS)
self.account.add_record(
execution_record,
self.account.dict_holding[order.id_instrument])
self.account.daily_accounting(self.optionset.eval_date)
base_npv.append(self.index.mktprice_close() / init_index)
print(self.optionset.eval_date, ' close out ')
break
# Option Hedge
if not stop_loss_paused:
if not empty_position:
if self.close_signal():
self.close_all_options()
empty_position = True
else:
strategy = self.shift()
if strategy is not None:
self.close_all_options()
self.excute(strategy)
if empty_position and self.open_signal():
self.excute(self.strategy())
empty_position = False
estimated_npv = self.account.estimate_npv()
self.sl_npv_high_point = max(self.sl_npv_high_point, estimated_npv)
# if self.account.account.loc[self.optionset.eval_date, c.Util.DRAWDOWN]>= 0.0:
# self.P_mdd = P_mdd
# 止损控制
if (estimated_npv - self.sl_npv_high_point
) / self.sl_npv_high_point < self.P_mdd:
self.close_out()
self.sl_npv_high_point = estimated_npv
self.strategy_npv_paused = drawdown.loc[
self.optionset.eval_date, c.Util.PORTFOLIO_NPV]
print(self.optionset.eval_date, 'stop loss',
self.sl_npv_high_point, self.P_mdd)
self.account.daily_accounting(self.optionset.eval_date, False)
base_npv.append(self.index.mktprice_close() / init_index)
if not self.optionset.has_next(): break
self.optionset.next()
self.index.next()
stop_loss_paused = True
empty_position = True
# self.P_mdd = -0.02
continue
if stop_loss_paused:
strategy_npv = drawdown.loc[self.optionset.eval_date,
c.Util.PORTFOLIO_NPV]
# 止损后空仓
# if strategy_npv <= self.strategy_npv_paused:
if (strategy_npv - self.strategy_npv_paused
) / self.strategy_npv_paused < 0.01:
self.account.daily_accounting(self.optionset.eval_date)
base_npv.append(self.index.mktprice_close() / init_index)
if not self.optionset.has_next(): break
self.optionset.next()
self.index.next()
continue
# 止损信号解除
else:
order_index = self.account.create_trade_order(
self.index,
c.LongShort.LONG,
self.unit_index,
cd_trade_price=c.CdTradePrice.CLOSE)
record_index = self.index.execute_order(
order_index, slippage=self.slippage)
self.account.add_record(record_index, self.index)
stop_loss_paused = False
self.nbr_stop_loss += 1
print(self.optionset.eval_date, 'stop loss end')
# if empty_position and self.open_signal():
# self.excute(self.strategy(cd_price=c.CdPriceType.CLOSE),cd_trade_price=c.CdTradePrice.CLOSE)
# empty_position = False
# 每日结算
self.account.daily_accounting(self.optionset.eval_date)
base_npv.append(self.index.mktprice_close() / init_index)
if not self.optionset.has_next(): break
self.optionset.next()
self.index.next()
self.account.account['base_npv'] = base_npv
# active_npv = self.df_index[self.df_index[c.Util.DT_DATE] <= self.optionset.eval_date].reset_index(drop=True)
# self.account.account['active_npv'] = active_npv[c.Util.AMT_CLOSE]
self.account.nbr_timing = self.nbr_timing
self.account.nbr_stop_loss = self.nbr_stop_loss
return self.account
dt_maturity = synthetic_option.eval_date + datetime.timedelta(days=30)
vol = 0.2
Option = EuropeanOption(strike, dt_maturity, OptionType.PUT)
delta = synthetic_option.get_black_delta(Option, vol)
id_future = synthetic_option.current_state[Util.ID_INSTRUMENT]
synthetic_unit = synthetic_option.get_synthetic_unit(delta)
if synthetic_unit > 0:
long_short = LongShort.LONG
else:
long_short = LongShort.SHORT
# """ 用第一天的日收盘价开仓标的现货多头头寸 """
underlying_unit = np.floor(Util.BILLION / underlying.mktprice_close())
order_underlying = account.create_trade_order(underlying, LongShort.LONG,
underlying_unit)
execution_record = underlying.execute_order(
order_underlying, slippage=0, execute_type=ExecuteType.EXECUTE_ALL_UNITS)
account.add_record(execution_record, underlying)
underlying.next()
# """ 用第一天的成交量加权均价初次开仓复制期权头寸 """
order = account.create_trade_order(synthetic_option, long_short,
synthetic_unit)
execution_record = synthetic_option.execute_order_by_VWAP(
order, slippage=0, execute_type=ExecuteType.EXECUTE_ALL_UNITS)
account.add_record(execution_record, synthetic_option)
#####################################################################
while synthetic_option.has_next() and synthetic_option.eval_date < dt_maturity:
if id_future != synthetic_option.current_state[Util.ID_INSTRUMENT]:
open_long_short = account.trade_book.loc[id_future,
Util.TRADE_LONG_SHORT]
hold_unit = account.trade_book.loc[id_future, Util.TRADE_UNIT]
class SyntheticOptionHedgedPortfolio():
def __init__(self, start_date, end_date):
self.ttm = 30
self.buywrite = BuyWrite.BUY
self.fund = Util.BILLION
self.invest_underlying_ratio = 0.7
# self.invest_underlying_ratio = 1
self.slippage = 2
self.start_date = start_date
self.end_date = end_date
hist_date = start_date - datetime.timedelta(days=40)
df_future_c1 = get_dzqh_cf_c1_minute(start_date, end_date, 'if')
df_future_c1_daily = get_dzqh_cf_c1_daily(hist_date, end_date, 'if')
df_futures_all_daily = get_dzqh_cf_daily(
start_date, end_date, 'if') # daily data of all future contracts
df_index = get_index_mktdata(
start_date, end_date,
'index_300sh') # daily data of underlying index
df_index = df_index[df_index[Util.DT_DATE].isin(
Util.DZQH_CF_DATA_MISSING_DATES) == False].reset_index(drop=True)
# df_index.to_csv('df_index.csv')
self.trade_dates = sorted(df_future_c1_daily[Util.DT_DATE].unique())
self.df_vol_1m = Histvol.hist_vol(df_future_c1_daily)
# df_parkinson_1m = Histvol.parkinson_number(df_future_c1_daily)
self.df_garman_klass = Histvol.garman_klass(df_future_c1_daily)
# df_hist_vol = self.df_vol_1m.join(self.df_garman_klass, how='left')
# df_hist_vol.to_csv('../../data/df_hist_vol.csv')
self.underlying = BaseInstrument(df_data=df_index)
self.underlying.init()
self.synthetic_option = SytheticOption(
df_c1_data=df_future_c1,
# df_c1_daily=df_future_c1_daily,
df_futures_all_daily=df_futures_all_daily,
df_index_daily=df_index)
self.synthetic_option.init()
self.account = BaseAccount(self.fund, leverage=20.0, rf=0.0)
self.trading_desk = Trade()
self.init_spot = self.synthetic_option.underlying_state_daily[
Util.AMT_CLOSE]
self.df_analysis = pd.DataFrame()
def next(self):
if self.synthetic_option.is_last_minute():
self.underlying.next()
self.synthetic_option.next()
def init_portfolio(self, fund):
""" Init position """
dt_maturity = self.synthetic_option.eval_date + datetime.timedelta(
days=self.ttm)
# strike = self.underlying.mktprice_close()
strike = self.synthetic_option.mktprice_close()
# dt_maturity = self.synthetic_option.eval_date + datetime.timedelta(days=30)
self.Option = EuropeanOption(strike, dt_maturity, OptionType.PUT)
# self.Option = EuropeanOption(strike, dt_maturity, OptionType.CALL)
""" 用第一天的日收盘价开仓标的现货多头头寸 """
underlying_unit = np.floor(fund * self.invest_underlying_ratio /
self.underlying.mktprice_close())
order_underlying = self.account.create_trade_order(
self.underlying, LongShort.LONG, underlying_unit)
execution_record = self.underlying.execute_order(
order_underlying,
slippage=0,
execute_type=ExecuteType.EXECUTE_ALL_UNITS)
self.account.add_record(execution_record, self.underlying)
self.synthetic_option.amt_option = underlying_unit
""" 用第一天的成交量加权均价开仓/调整复制期权头寸 """
vol = self.get_vol()
self.delta = self.synthetic_option.get_black_delta(self.Option, vol)
synthetic_unit = self.synthetic_option.get_synthetic_unit(
self.delta, self.buywrite)
self.synthetic_option.synthetic_unit = synthetic_unit
if synthetic_unit > 0:
long_short = LongShort.LONG
else:
long_short = LongShort.SHORT
order = self.account.create_trade_order(self.synthetic_option,
long_short, synthetic_unit)
execution_record = self.synthetic_option.execute_order_by_VWAP(
order, slippage=0, execute_type=ExecuteType.EXECUTE_ALL_UNITS)
self.account.add_record(execution_record, self.synthetic_option)
self.account.daily_accounting(self.synthetic_option.eval_date)
self.add_additional_to_account()
self.disp()
self.next()
def rebalance_sythetic_option(self):
""" Reset and Rebalance sythetic option """
dt_maturity = self.synthetic_option.eval_date + datetime.timedelta(
days=self.ttm)
# strike = self.underlying.mktprice_close()
strike = self.synthetic_option.mktprice_close()
self.Option = EuropeanOption(strike, dt_maturity, OptionType.PUT)
# self.Option = EuropeanOption(strike, dt_maturity, OptionType.CALL)
""" 用成交量加权均价调整复制期权头寸 """
vol = self.get_vol()
self.delta = self.synthetic_option.get_black_delta(self.Option, vol)
synthetic_unit = self.synthetic_option.get_rebalancing_unit(
self.delta, self.Option, vol,
self.synthetic_option.mktprice_close(), DeltaBound.NONE,
self.buywrite)
self.synthetic_option.synthetic_unit += synthetic_unit
if synthetic_unit > 0:
long_short = LongShort.LONG
else:
long_short = LongShort.SHORT
order = self.account.create_trade_order(self.synthetic_option,
long_short, synthetic_unit)
execution_record = self.synthetic_option.execute_order_by_VWAP(
order, slippage=0, execute_type=ExecuteType.EXECUTE_ALL_UNITS)
self.account.add_record(execution_record, self.synthetic_option)
self.account.daily_accounting(self.synthetic_option.eval_date)
self.add_additional_to_account()
self.disp()
self.next()
return
def hedge(self, dt_end=None):
id_future = self.synthetic_option.current_state[Util.ID_INSTRUMENT]
if dt_end is None:
dt_end = self.Option.dt_maturity
dt_time_end = datetime.datetime(dt_end.year, dt_end.month, dt_end.day,
15, 00, 0)
while self.synthetic_option.has_next(
) and self.synthetic_option.eval_datetime <= dt_time_end:
if id_future != self.synthetic_option.current_state[
Util.ID_INSTRUMENT]:
long_short = self.account.trade_book.loc[id_future,
Util.TRADE_LONG_SHORT]
hold_unit = -self.account.trade_book.loc[id_future,
Util.TRADE_UNIT]
spot = self.synthetic_option.mktprice_close()
vol = self.get_vol()
self.delta = self.synthetic_option.get_black_delta(
self.Option, vol, spot)
synthetic_unit = self.synthetic_option.get_synthetic_unit(
self.delta, self.buywrite) # 按照移仓换月日的收盘价计算Delta
id_c2 = self.synthetic_option.current_state[Util.ID_INSTRUMENT]
open_unit = synthetic_unit
self.synthetic_option.synthetic_unit += open_unit - hold_unit
close_execution_record, open_execution_record \
= self.synthetic_option.shift_contract_by_VWAP(id_c1=id_future,
id_c2=id_c2,
hold_unit=hold_unit,
open_unit=open_unit,
long_short=long_short,
slippage=self.slippage,
execute_type=ExecuteType.EXECUTE_ALL_UNITS
)
self.account.add_record(close_execution_record,
self.synthetic_option)
self.synthetic_option._id_instrument = id_c2
self.account.add_record(open_execution_record,
self.synthetic_option)
""" 更新当前持仓头寸 """
""" USE SAME UNIT TO SHIFT CONTRACT AND USE CLOSE PRICE TO REBALANCING DELTA CHANGE. """
print(' Relancing after shift contract, ',
self.synthetic_option.eval_date)
id_future = id_c2
if self.synthetic_option.eval_datetime.time() == datetime.time(
9, 30, 0):
self.next()
if self.synthetic_option.eval_date == self.synthetic_option.get_next_state_date(
):
if not self.if_hedge('5min'):
self.next()
continue
self.rebalancing()
if self.synthetic_option.is_last_minute():
self.account.daily_accounting(
self.synthetic_option.eval_date) # 该日的收盘结算
self.add_additional_to_account()
self.disp()
if self.synthetic_option.eval_date == dt_end and self.synthetic_option.is_last_minute(
):
self.close_out()
self.next()
def if_hedge(self, cd):
if cd == '1h':
""" 1h """
if self.synthetic_option.eval_datetime.minute == 0:
return True
else:
return False
elif cd == '10min':
""" 10min """
if self.synthetic_option.eval_datetime.minute % 10 == 0:
return True
else:
return False
elif cd == '5min':
""" 5min """
if self.synthetic_option.eval_datetime.minute % 5 == 0:
return True
else:
return False
elif cd == '1min':
return True
elif cd == 'half_day':
if self.synthetic_option.eval_datetime.time() == datetime.time(11, 29, 00) or \
self.synthetic_option.eval_datetime.time() == datetime.time(14, 59, 00):
return True
else:
return False
def rebalancing(self):
vol = self.get_vol()
self.delta = self.synthetic_option.get_black_delta(self.Option, vol)
rebalance_unit = self.synthetic_option.get_rebalancing_unit(
self.delta, self.Option, vol,
self.synthetic_option.mktprice_close(),
DeltaBound.WHALLEY_WILLMOTT, self.buywrite)
self.synthetic_option.synthetic_unit += rebalance_unit
if rebalance_unit > 0:
long_short = LongShort.LONG
else:
long_short = LongShort.SHORT
order = self.account.create_trade_order(self.synthetic_option,
long_short, rebalance_unit)
execution_record = self.synthetic_option.execute_order(
order,
slippage=self.slippage,
execute_type=ExecuteType.EXECUTE_ALL_UNITS)
self.account.add_record(execution_record, self.synthetic_option)
def close_out(self):
while not self.synthetic_option.is_last_minute():
self.next()
close_out_orders = self.account.creat_close_out_order()
for order in close_out_orders:
execution_record = self.account.dict_holding[
order.id_instrument].execute_order(
order,
slippage=0,
execute_type=ExecuteType.EXECUTE_ALL_UNITS)
self.account.add_record(
execution_record,
self.account.dict_holding[order.id_instrument])
self.account.daily_accounting(self.synthetic_option.eval_date)
self.add_additional_to_account()
self.disp()
self.synthetic_option.sythetic_unit = 0
""" Final NPV check """
self.df_records = pd.DataFrame(self.account.list_records)
total_pnl = self.df_records[Util.TRADE_REALIZED_PNL].sum()
final_npv = (self.fund + total_pnl) / self.fund
print('calculate final npv from adding up realized pnl ; ', final_npv)
def get_vol(self):
date = self.synthetic_option.eval_date
if date in self.df_vol_1m.index:
# vol = self.df_vol_1m.loc[date, Util.AMT_HISTVOL]
vol = self.df_garman_klass.loc[self.synthetic_option.eval_date,
Util.AMT_GARMAN_KLASS]
else:
dt1 = Util.largest_element_less_than(port.trade_dates, date)
vol = self.df_garman_klass.loc[dt1, Util.AMT_GARMAN_KLASS]
# vol = self.df_vol_1m.loc[dt1, Util.AMT_HISTVOL]
return vol
def add_additional_to_account(self):
# self.account.account.loc[
# self.synthetic_option.eval_date, 'underlying_npv_1'] = self.invest_underlying_ratio * self.underlying.mktprice_close() / self.init_spot + 1 - self.invest_underlying_ratio
self.account.account.loc[
self.synthetic_option.eval_date,
'underlying_npv'] = self.underlying.mktprice_close(
) / self.init_spot
self.account.account.loc[
self.synthetic_option.eval_date,
'underlying_price'] = self.underlying.mktprice_close()
self.account.account.loc[
self.synthetic_option.eval_date,
'if_c1'] = self.synthetic_option.mktprice_close()
self.account.account.loc[self.synthetic_option.eval_date, 'hedge_position'] \
= - self.account.trade_book[self.account.trade_book[Util.TRADE_LONG_SHORT] == LongShort.SHORT][
Util.TRADE_UNIT].sum()
self.account.account.loc[self.synthetic_option.eval_date, 'hedge_ratio'] = \
self.account.account.loc[self.synthetic_option.eval_date, Util.PORTFOLIO_SHORT_POSITION_SCALE] / \
self.account.account.loc[self.synthetic_option.eval_date, Util.PORTFOLIO_LONG_POSITION_SCALE]
self.account.account.loc[self.synthetic_option.eval_date, 'pct_margin_unrealized_pnl'] = \
self.account.account.loc[
self.synthetic_option.eval_date, Util.MARGIN_UNREALIZED_PNL] / self.account.init_fund
self.account.account.loc[self.synthetic_option.eval_date, 'pct_nonmargin_unrealized_pnl'] = \
self.account.account.loc[
self.synthetic_option.eval_date, Util.NONMARGIN_UNREALIZED_PNL] / self.account.init_fund
self.account.account.loc[self.synthetic_option.eval_date, 'pct_realized_pnl'] = \
self.account.account.loc[self.synthetic_option.eval_date, Util.TRADE_REALIZED_PNL] / self.account.init_fund
self.account.account.loc[self.synthetic_option.eval_date,
'delta'] = self.delta
def save_results(self):
self.df_records.to_csv('../../data/trade_records.csv')
self.account.account.to_csv('../../data/account.csv')
# self.df_hedge_info = pd.DataFrame(self.list_hedge_info)
# self.df_hedge_info.to_csv('../../data/hedge_info.csv')
self.df_analysis.to_csv('../../data/df_analysis.csv')
self.account.trade_book_daily.to_csv('../../data/trade_book_daily.csv')
def disp(self):
if self.synthetic_option.eval_date != self.underlying.eval_date:
print('Date miss matched!')
try:
average_cost = int(self.account.trade_book[self.account.trade_book[
Util.TRADE_LONG_SHORT] == LongShort.SHORT][
Util.AVERAGE_POSITION_COST].values[0])
except:
average_cost = 0
pass
print(
self.synthetic_option.eval_datetime,
self.account.account.loc[self.synthetic_option.eval_date,
Util.PORTFOLIO_NPV],
self.underlying.mktprice_close() / self.init_spot,
# self.account.account.loc[self.synthetic_option.eval_date, 'hedge_position'],
# self.synthetic_option.synthetic_unit,
int(self.Option.strike),
int(self.underlying.mktprice_close()),
int(self.synthetic_option.mktprice_close()),
average_cost,
round(self.delta, 2),
round(
self.account.account.loc[self.synthetic_option.eval_date,
'hedge_ratio'], 2),
# self.account.cash,
round(
100 * self.account.account.loc[self.synthetic_option.eval_date,
'pct_margin_unrealized_pnl'],
1),
'%',
round(
100 * self.account.account.loc[self.synthetic_option.eval_date,
'pct_nonmargin_unrealized_pnl'],
1),
'%',
round(
100 * self.account.account.loc[self.synthetic_option.eval_date,
'pct_realized_pnl'], 1),
'%',
self.underlying.eval_date,
)
def reset_option_maturity(self, dt_maturity=None):
if dt_maturity is None:
dt_maturity = self.synthetic_option.eval_date + datetime.timedelta(
days=self.ttm)
self.Option.dt_maturity = dt_maturity
def reset_option_strike(self):
strike = self.synthetic_option.mktprice_close()
self.Option.strike = strike
def analysis(self, dt_start, dt_end):
""" Replicate Period Result Analysis """
self.df_records = pd.DataFrame(self.account.list_records)
analysis = pd.Series()
df_hedge_records = self.df_records[
(self.df_records[Util.ID_INSTRUMENT] != 'index_300sh')
& (self.df_records[Util.DT_TRADE] >= dt_start) &
(self.df_records[Util.DT_TRADE] <= dt_end)]
init_stock_value = self.account.account.loc[
dt_start, Util.PORTFOLIO_TRADES_VALUE]
init_stock_price = \
self.underlying.df_data[self.underlying.df_data[Util.DT_DATE] == dt_start][Util.AMT_CLOSE].values[0]
terminal_stock_price = \
self.underlying.df_data[self.underlying.df_data[Util.DT_DATE] == dt_end][Util.AMT_CLOSE].values[0]
replicate_pnl = df_hedge_records[Util.TRADE_REALIZED_PNL].sum()
option_payoff = self.synthetic_option.amt_option * max(
init_stock_price - terminal_stock_price, 0)
replicate_cost = replicate_pnl - option_payoff
replicate_cost_future = replicate_pnl - self.synthetic_option.amt_option * max(
self.Option.strike - terminal_stock_price, 0)
pct_replicate_cost = replicate_cost / init_stock_value
pct_replicate_pnl = replicate_pnl / init_stock_value
transaction_cost = df_hedge_records[Util.TRANSACTION_COST].sum()
init_portfolio_value = self.account.account.loc[dt_start,
Util.PORTFOLIO_VALUE]
trade_value = np.abs(df_hedge_records[Util.TRADE_BOOK_VALUE]).sum()
ratio = trade_value / init_portfolio_value
pct_underlying_pnl = (terminal_stock_price -
init_stock_price) / init_stock_price
analysis['ratio'] = ratio
analysis['dt_start'] = dt_start
analysis['dt_end'] = dt_end
analysis['init_stock_value'] = init_stock_value
analysis['replicate_pnl'] = replicate_pnl
analysis['option_payoff'] = option_payoff
analysis['replicate_cost_spot'] = replicate_cost
analysis['replicate_cost_future'] = replicate_cost_future
analysis['pct_replicate_cost'] = pct_replicate_cost
analysis['pct_replicate_pnl'] = pct_replicate_pnl
analysis['pct_underlying_pnl'] = pct_underlying_pnl
analysis['transaction_cost'] = transaction_cost
analysis['dt_maturity'] = self.Option.dt_maturity
self.df_analysis = self.df_analysis.append(analysis, ignore_index=True)