df_c1_daily=df_future_c1_daily, df_futures_all_daily=df_futures_all_daily, df_index_daily=df_index) synthetic_option.init() underlying = BaseInstrument(df_data=df_index) underlying.init() account = BaseAccount(2 * Util.BILLION, leverage=10.0, rf=0.0) trading_desk = Trade() ##################################################################### # """ Init position """ strike = synthetic_option.underlying_index_state_daily[Util.AMT_CLOSE] 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()
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)