def implied_dist(date, basic, gap):
try:
fn = get_dss() + 'opt/' + date[:7] + '_greeks.csv'
df = pd.read_csv(fn)
df['date'] = df.Localtime.str.slice(0, 10)
df = df[df.date == date]
df = df[df.Instrument.str.slice(0, len(basic)) == basic]
strike_list = []
for i, row in df.iterrows():
strike_list.append(get_contract(row.Instrument).strike)
atm = int(
round(
round(min(strike_list) * (100 / gap) / 1E4, 2) * 1E4 /
(100 / gap), 0)) # 获得平值
strike_list = range(atm, max(strike_list) + 1, gap)
# print( [*strike_list] )
if basic[:2] == 'IO':
symbol_obj = 'IF' + basic[2:]
else:
symbol_obj = basic
fn = get_dss() + 'fut/bar/min5_' + symbol_obj + '.csv'
df = pd.read_csv(fn)
df = df[(df.date == date) & (df.time == '14:54:00')]
obj_close = df.iat[0, 5]
# print(obj_close)
c_list = []
p_list = []
for strike in strike_list:
# print(strike)
symbol_c = basic + get_contract(basic).opt_flag_C + str(strike)
fn = get_dss() + 'fut/bar/min5_' + symbol_c + '.csv'
df = pd.read_csv(fn)
df = df[(df.date == date) & (df.time == '14:54:00')]
c_list.append(df.iat[0, 5])
symbol_p = basic + get_contract(basic).opt_flag_P + str(strike)
fn = get_dss() + 'fut/bar/min5_' + symbol_p + '.csv'
df = pd.read_csv(fn)
df = df[(df.date == date) & (df.time == '14:54:00')]
# print(date, symbol_p, df.tail())
p_list.append(df.iat[0, 5])
prop_list = []
n = len(strike_list)
for i in range(1, n - 1):
if strike_list[i] < obj_close:
prop_list.append(
int(100 * (p_list[i - 1] - 2 * p_list[i] + p_list[i + 1]) /
gap))
else:
prop_list.append(
int(100 * (c_list[i - 1] - 2 * c_list[i] + c_list[i + 1]) /
gap))
df = pd.DataFrame([])
df['strike'] = strike_list[1:n - 1]
df['strike'] = df['strike'].astype('str')
df['value'] = prop_list
df = df.set_index('strike')
df.index.name = basic + '_implied_dist'
return df
except Exception as e:
s = traceback.format_exc()
# to_log(s)
to_log(date + ' ' + basic +
' 数据缺失 in implied_dist from file compass.py')
return None
def df_atm_plus_obj_min5(basic, date, gap, shift=0):
"""
选取每天的平值合约，按要求组装包含close_obj的df
返回的df包括以下字段：dt, symbol, close, close_obj
"""
try:
r_c = []
r_p = []
if basic[:2] == 'IO':
symbol_obj = 'IF' + basic[2:]
else:
symbol_obj = basic
fn = get_dss() + 'fut/bar/min5_' + symbol_obj + '.csv'
df_obj = pd.read_csv(fn)
df_obj = df_obj[(df_obj.date == date) & (df_obj.time <= '14:54:00')]
df_obj = df_obj.reset_index()
# print(df_obj.head())
if df_obj.empty:
pass
else:
close_obj = df_obj.iloc[-1, :].close
atm = int(
round(
round(close_obj * (100 / gap) / 1E4, 2) * 1E4 /
(100 / gap), 0)) # 获得平值
# if date == '2020-11-10':
# print(basic, '-------------------------', close_obj, atm )
symbol_c = basic + get_contract(basic).opt_flag_C + str(
atm + shift * gap)
fn = get_dss() + 'fut/bar/min5_' + symbol_c + '.csv'
df_atm_c = pd.read_csv(fn)
df_atm_c = df_atm_c[(df_atm_c.date == date)
& (df_atm_c.time <= '14:54:00')]
symbol_p = basic + get_contract(basic).opt_flag_P + str(
atm + shift * gap)
fn = get_dss() + 'fut/bar/min5_' + symbol_p + '.csv'
df_atm_p = pd.read_csv(fn)
df_atm_p = df_atm_p[(df_atm_p.date == date)
& (df_atm_p.time <= '14:54:00')]
if df_atm_c.empty or df_atm_p.empty:
pass
else:
for i, row in df_obj.iterrows():
rec = df_atm_c.iloc[i, :]
r_c.append([
row.date + ' ' + row.time, symbol_c, rec.close,
row.close
])
rec = df_atm_p.iloc[i, :]
r_p.append([
row.date + ' ' + row.time, symbol_p, rec.close,
row.close
])
cols = ['dt', 'symbol', 'close', 'close_obj']
df_c = pd.DataFrame(r_c, columns=cols)
df_p = pd.DataFrame(r_p, columns=cols)
df_c.index.name = basic + '_iv_c'
df_p.index.name = basic + '_iv_p'
# print(df_c.tail())
# print(df_p.tail())
return df_c, df_p
except Exception as e:
s = traceback.format_exc()
to_log(s)
return None, None
def df_smile(date, basic):
try:
fn = get_dss() + 'opt/' + date[:7] + '_greeks.csv'
df = pd.read_csv(fn)
df['date'] = df.Localtime.str.slice(0, 10)
df = df[df.date == date]
df = df[df.Instrument.str.slice(0, len(basic)) == basic]
strike_list = []
for i, row in df.iterrows():
strike_list.append(get_contract(row.Instrument).strike)
strike_list = sorted(list(set(strike_list)))
# print(strike_list)
if basic[:2] == 'IO':
symbol_obj = 'IF' + basic[2:]
else:
symbol_obj = basic
fn = get_dss() + 'fut/bar/min5_' + symbol_obj + '.csv'
df = pd.read_csv(fn)
df = df[(df.date == date) & (df.time == '14:54:00')]
close_obj = df.iat[0, 5]
# print(obj_close)
r_c = []
r_p = []
strike_c = []
strike_p = []
for strike in strike_list:
# print(strike)
symbol_c = basic + get_contract(basic).opt_flag_C + str(strike)
fn = get_dss() + 'fut/bar/min5_' + symbol_c + '.csv'
df = pd.read_csv(fn)
df = df[(df.date == date) & (df.time == '14:54:00')]
if df.empty:
continue
r_c.append([date, symbol_c, df.iat[0, 5], close_obj])
strike_c.append(str(strike))
symbol_p = basic + get_contract(basic).opt_flag_P + str(strike)
fn = get_dss() + 'fut/bar/min5_' + symbol_p + '.csv'
df = pd.read_csv(fn)
df = df[(df.date == date) & (df.time == '14:54:00')]
# print(date, symbol_p, df.tail())
if df.empty:
continue
r_p.append([date, symbol_p, df.iat[0, 5], close_obj])
strike_p.append(str(strike))
df_c = pd.DataFrame(r_c,
columns=['dt', 'symbol', 'close', 'close_obj'])
df_p = pd.DataFrame(r_p,
columns=['dt', 'symbol', 'close', 'close_obj'])
# print(df_c)
# print(df_p)
df_c = df_iv(basic, df_c)
df_p = df_iv(basic, df_p)
# 去掉深度虚值的干扰项
for i in [0, 1, 2]:
df_c.iat[i, 0] = np.nan
df_p.iat[-i - 1, 0] = np.nan
df_c.index = strike_c
df_c.index.name = date + '_smile_c'
df_p.index = strike_p
df_p.index.name = date + '_smile_p'
# print(df_c)
# print(df_p)
return df_c, df_p
except Exception as e:
s = traceback.format_exc()
to_log(s)
return None, None
def pandian_dali(today):
dss = get_dss()
# 加载品种
config = open(dss + 'fut/cfg/config.json')
setting = json.load(config)
symbols = setting['symbols_dali']
dali_symbol_list = symbols.split(',')
# 读取value_dali文件
fn_value = dss + 'fut/engine/value_dali.csv'
if os.path.exists(fn_value):
df_value = pd.read_csv(fn_value)
else:
return
fn_param = dss + 'fut/engine/dali/signal_dali_param.csv'
df_param = pd.read_csv(fn_param)
df_param = df_param.set_index('pz')
# print(df_param)
r = []
for symbol in dali_symbol_list:
c = get_contract(symbol)
pz = str(c.pz)
df = df_value[df_value.pz == pz]
# 获得该品种最近日期的一条记录，新品种必须事先维护一条记录！！！
if len(df) > 0:
rec = df.iloc[-1, :]
capital = rec.capital
date = rec.date
# 跨年了
if today[:4] == date[:4]:
newyear_value = rec.newyear_value
else:
newyear_value = rec.cur_value # 换年
else:
continue
# 更新该品种的最新数据
fn_signal = dss + 'fut/engine/dali/signal_dali_' + 'multi' + '_var_' + pz + '.csv'
if os.path.exists(fn_signal):
df = pd.read_csv(fn_signal)
df = df[df.vtSymbol == symbol]
rec = df.iloc[-1, :]
# print(rec)
cur_value = int(capital + rec.pnl_net)
year_ratio = round(100 * (cur_value / newyear_value - 1), 2)
net_pos = rec.unit
multi_duo_list = eval(rec.price_duo_list)
multi_kong_list = eval(rec.price_kong_list)
active_price = (int(multi_duo_list[0]) +
int(multi_kong_list[0])) * 0.5
margin = df_param.at[pz, 'fixed_size'] * active_price * float(
c.size) * float(
c.margin) * (len(multi_duo_list) + len(multi_kong_list))
risk = round(100 * (margin / capital), 2)
r.append([
today, pz, capital, cur_value, newyear_value, year_ratio,
margin, risk, net_pos, multi_duo_list, multi_kong_list
])
#print(r)
#return
df = pd.DataFrame(r)
df.to_csv(fn_value, index=False, mode='a', header=None)
def df_atm_plus_obj_day(basic, date, gap, shift=0):
"""
选取每天的平值合约，按要求组装包含close_obj的df
返回的df包括以下字段：dt, symbol, close, close_obj
"""
try:
if basic[:2] == 'IO':
symbol_obj = 'IF' + basic[2:]
else:
symbol_obj = basic
fn = get_dss() + 'fut/bar/min5_' + symbol_obj + '.csv'
df_obj = pd.read_csv(fn)
date_list = sorted(list(set(df_obj.date)))
date_list = [d for d in date_list if d <= date]
# print(date_list)
r_c = []
r_p = []
for date in date_list:
df2 = df_obj[(df_obj.date == date) & (df_obj.time <= '14:54:00')]
if df2.empty:
print('df empty: ', basic, date)
continue
close_obj = df2.iloc[-1, :].close
atm = int(
round(
round(close_obj * (100 / gap) / 1E4, 2) * 1E4 /
(100 / gap), 0)) # 获得平值
# if date == '2020-11-10':
# print(basic, '-------------------------', close_obj, atm )
symbol_c = basic + get_contract(basic).opt_flag_C + str(
atm + shift * gap)
fn = get_dss() + 'fut/bar/min5_' + symbol_c + '.csv'
df_atm_c = pd.read_csv(fn)
df_atm_c = df_atm_c[(df_atm_c.date == date)
& (df_atm_c.time == '14:54:00')]
symbol_p = basic + get_contract(basic).opt_flag_P + str(
atm + shift * gap)
fn = get_dss() + 'fut/bar/min5_' + symbol_p + '.csv'
df_atm_p = pd.read_csv(fn)
df_atm_p = df_atm_p[(df_atm_p.date == date)
& (df_atm_p.time == '14:54:00')]
if df_atm_c.empty or df_atm_p.empty:
pass
# print('df empty: ', basic, date)
else:
rec = df_atm_c.iloc[0, :]
r_c.append([date, symbol_c, rec.close, close_obj])
rec = df_atm_p.iloc[0, :]
r_p.append([date, symbol_p, rec.close, close_obj])
cols = ['dt', 'symbol', 'close', 'close_obj']
df_c = pd.DataFrame(r_c, columns=cols)
df_p = pd.DataFrame(r_p, columns=cols)
df_c.index.name = basic + '_iv_c'
df_p.index.name = basic + '_iv_p'
# print(df_c.tail())
# print(df_p.tail())
return df_c, df_p
except Exception as e:
s = traceback.format_exc()
to_log(s)
return None, None
def calc_iv_atm():
''' 计算IO合约min5的iv值，保存在文件中'''
now = datetime.now()
# today = now.strftime('%Y-%m-%d %H:%M:%S')
today = now.strftime('%Y-%m-%d')
# today = '2020-07-09'
fn = get_dss() + 'fut/cfg/opt_mature.csv'
df2 = pd.read_csv(fn)
df2 = df2[df2.pz == 'IO']
df2 = df2[df2.flag == df2.flag] # 筛选出不为空的记录
df2 = df2[df2.mature >= today] # 过期的合约就不要了
df2 = df2.set_index('symbol')
mature_dict = dict(df2.mature)
print(mature_dict)
# for symbol in mature_dict.keys():
# if mature_dict[symbol] < today:
# mature_dict.pop(symbol)
# break
# print(mature_dict)
cur_io = min(mature_dict.keys())
cur_if = 'IF' + cur_io[2:]
# print(cur_if)
fn = get_dss() + 'fut/bar/day_' + cur_if + '.csv'
df = pd.read_csv(fn)
df = df[df.date == today]
# print(df)
if len(df) > 0:
row = df.iloc[0, :]
strike = row.open * 0.5 + row.close * 0.5
strike = int(round(strike / 1E4, 2) * 1E4)
else:
return
atm = str(strike) # 获得平值
print(atm)
# for symbol in ['IO2007']:
for symbol in mature_dict.keys():
# print(symbol)
# 取IF min5数据
fn = get_dss() + 'fut/bar/min5_IF' + symbol[2:] + '.csv'
if os.path.exists(fn) == False:
continue
df = pd.read_csv(fn)
df = df[df.date == today]
if len(df) == 0:
continue
df['obj'] = df['close']
df = df.set_index(['date', 'time'])
df_IF = df[['obj']]
# print(df_IF.head())
for flag in ['C', 'P']:
fn = get_dss(
) + 'fut/bar/min5_' + symbol + '-' + flag + '-' + atm + '.csv'
df = pd.read_csv(fn)
df = df[df.date == today]
df = df.set_index(['date', 'time'])
df['close' + '_' + flag] = df['close']
df_IO = df[['close' + '_' + flag]]
# print(df_IO.head())
# 与IF 数据进行join
df_IF = df_IF.join(df_IO)
# print(df_IF.head())
df_IF = df_IF.reset_index()
# print(df_IF.head())
df_IF['pz'] = str(get_contract(symbol).pz)
df_IF['symbol'] = symbol
df_IF['atm'] = atm
date_mature = datetime.strptime(mature_dict[symbol], '%Y-%m-%d')
td = datetime.strptime(today, '%Y-%m-%d')
T = float((date_mature - td).days) / 365 # 剩余期限，已做年化处理
T = 0.0015 if T == 0 else T # 最后一天特殊处理
df = proc_iv(df_IF, T)
# print(df.head())
fn = get_dss() + 'opt/iv_atm_' + today[:4] + '.csv'
if os.path.exists(fn):
df.to_csv(fn, index=False, header=None, mode='a')
else:
df.to_csv(fn, index=False)
def calc_skew():
now = datetime.now()
date = now.strftime('%Y-%m-%d')
# date = '2020-09-02'
# 数据基于greeks文件，该文件中已计算好合约的iv
fn = get_dss() + 'opt/' + date[:7] + '_greeks.csv'
if os.path.exists(fn) == False:
return
r = []
basic_list = [] # 提取当日的basic
df = pd.read_csv(fn)
df = df[df.Localtime.str.slice(0,10) == date]
for i, row in df.iterrows():
basic_list.append( get_contract(row.Instrument).basic )
basic_list = list(set(basic_list))
for basic in basic_list:
try:
df1 = df[df.Instrument.str.slice(0,len(basic)) == basic]
df1 = df1.drop_duplicates(subset=['Instrument'],keep='last')
# df1 = df1.sort_values('Instrument')
# print(df1.tail())
if len(df1) > 0:
rec = df1.iloc[0, :]
obj = int(rec.obj)
pz = str(get_contract(rec.Instrument).pz)
gap = 50
if pz == 'CF':
gap = 200
if pz == 'm':
gap = 50
if pz in ['RM', 'MA']:
gap = 25
atm = int(round(round(obj*(100/gap)/1E4,2) * 1E4/(100/gap), 0)) # 获得平值
# print(gap)
# print(obj)
# print(atm)
exchangeID = str(get_contract(rec.Instrument).exchangeID)
if exchangeID in ['CFFEX', 'DCE']:
atm_c = basic + '-C-' + str(atm)
atm_p = basic + '-P-' + str(atm)
otm_right_c = basic + '-C-' + str(atm+2*gap)
otm_right_p = basic + '-P-' + str(atm+2*gap)
otm_left_c = basic + '-C-' + str(atm-2*gap)
otm_left_p = basic + '-P-' + str(atm-2*gap)
else:
atm_c = basic + 'C' + str(atm)
atm_p = basic + 'P' + str(atm)
otm_right_c = basic + 'C' + str(atm+2*gap)
otm_right_p = basic + 'P' + str(atm+2*gap)
otm_left_c = basic + 'C' + str(atm-2*gap)
otm_left_p = basic + 'P' + str(atm-2*gap)
df1 = df1.set_index('Instrument')
skew_c = round( 100*(df1.at[otm_right_c,'iv']-df1.at[atm_c,'iv']) / df1.at[atm_c,'iv'], 2)
skew_p = round( 100*(df1.at[otm_left_p,'iv']-df1.at[atm_p,'iv']) / df1.at[atm_p,'iv'], 2)
# skew_mean_c = round( 100*( df1.at[otm_right_c,'iv'] + df1.at[otm_right_p,'iv'] - df1.at[atm_c,'iv'] - df1.at[atm_p,'iv'] ) / (df1.at[atm_c,'iv'] + df1.at[atm_p,'iv']), 2)
# skew_mean_p = round( 100*( df1.at[otm_left_c,'iv'] + df1.at[otm_left_p,'iv'] - df1.at[atm_c,'iv'] - df1.at[atm_p,'iv'] ) / (df1.at[atm_c,'iv'] + df1.at[atm_p,'iv']), 2)
skew_mean = round( 100*( df1.at[otm_right_c,'iv'] + df1.at[otm_right_p,'iv'] - df1.at[otm_left_c,'iv'] - df1.at[otm_left_p,'iv'] ) / (df1.at[otm_left_c,'iv'] + df1.at[otm_left_p,'iv']), 2)
r.append([date, pz, basic, obj, atm, atm+2*gap, atm-2*gap, skew_c, skew_p, skew_mean])
except:
pass
df = pd.DataFrame(r, columns=['date', 'pz', 'basic', 'obj', 'atm', 'otm_c', 'otm_p', 'skew_c', 'skew_p', 'skew_mean'])
fn = get_dss() + 'opt/skew.csv'
if os.path.exists(fn):
df.to_csv(fn, index=False, header=None, mode='a')
else:
df.to_csv(fn, index=False)
def save_var(self):
try:
# 按照新逻辑，收盘不再调整队列
self.adjust_price_head()
self.price_duo_list = sorted( self.price_duo_list )
self.price_kong_list = sorted( self.price_kong_list, reverse=True )
pnl_trade = 0
commission = 0
slippage = 0
pz = str(get_contract(self.vtSymbol).pz)
filename = get_dss() + 'fut/engine/dali/signal_dali_'+self.type+ '_deal_' + pz + '.csv'
if os.path.exists(filename):
df = pd.read_csv(filename)
pnl_trade = df.pnl.sum()
commission = df.commission.sum()
slippage = df.slippage.sum()
settle = self.bar.close
pnl_hold = 0
ct = get_contract(self.vtSymbol)
size = ct.size
d_list = [2,2,2,2,2] + self.size_duo_list
k_list = [2,2,2,2,2] + self.size_kong_list
# print(self.vtSymbol)
# print(d_list)
# print(k_list)
for d, item in zip( d_list, sorted(self.price_duo_list,reverse=True) ):
pnl_hold += (settle - item) * d * size
# print(d, pnl_hold)
for k, item in zip( k_list, sorted(self.price_kong_list) ):
pnl_hold += (item - settle) * k * size
# print(k, pnl_hold)
# print(pnl_hold)
self.unit = len(self.price_duo_list) - len(self.price_kong_list)
print(self.unit)
r = [ [self.portfolio.result.date,self.vtSymbol, settle, self.unit, \
pnl_trade+pnl_hold-commission-slippage, pnl_trade, pnl_hold, \
commission, slippage, str(self.price_duo_list), str(self.price_kong_list), \
str(self.size_duo_list), str(self.size_kong_list)] ]
df = pd.DataFrame(r, columns=['datetime','vtSymbol','price','unit', \
'pnl_net','pnl_trade','pnl_hold', \
'commission','slippage','price_duo_list','price_kong_list', \
'size_duo_list', 'size_kong_list'])
filename = get_dss() + 'fut/engine/dali/signal_dali_'+self.type+ '_var_' + pz + '.csv'
if os.path.exists(filename):
df.to_csv(filename, index=False, mode='a', header=False)
else:
df.to_csv(filename, index=False)
assert self.unit == len(self.size_duo_list) - len(self.size_kong_list)
assert len(self.size_duo_list) == 0 or len(self.size_kong_list) == 0
except Exception as e:
s = traceback.format_exc()
to_log(s)
def pcp(self):
"""
将行情切片整理成k_dict，其以basic+strike为键，
以[basic, strike, c_ask_price, c_bid_price, p_ask_price, p_bid_price, obj_ask_price, obj_bid_price, tm]为值
"""
k_dict = {}
tm = '00:00:00'
now = datetime.now()
today = now.strftime('%Y-%m-%d')
# 获取期权的到期日
fn = get_dss() + 'fut/cfg/opt_mature.csv'
df2 = pd.read_csv(fn)
df2 = df2[df2.flag == df2.flag] # 筛选出不为空的记录
df2 = df2.set_index('symbol')
mature_dict = dict(df2.mature)
for pz in self.slice_dict.keys():
# print(pz)
v = self.slice_dict[pz]
for row in v:
# print(row)
symbol = row[0]
tm = row[1]
ask_price = row[2]
bid_price = row[3]
opt_flag = get_contract(symbol).opt_flag
basic = get_contract(symbol).basic
strike = get_contract(symbol).strike
if basic[:2] == 'IO':
symbol_obj = 'IF' + basic[2:]
else:
symbol_obj = basic
# 当键值出现时，一次性将认购和认沽合约都处理了
if basic + str(strike) not in k_dict.keys():
if opt_flag == 'C':
symbol_p = basic + get_contract(
symbol).opt_flag_P + str(strike)
rec_p = self.get_rec_from_slice(symbol_p)
rec_obj = self.get_rec_from_slice(symbol_obj)
if rec_p is not None and rec_obj is not None:
k_dict[basic + str(strike)] = [
basic, strike, ask_price, bid_price, rec_p[2],
rec_p[3], rec_obj[2], rec_obj[3], tm
]
if opt_flag == 'P':
symbol_c = basic + get_contract(
symbol).opt_flag_C + str(strike)
rec_c = self.get_rec_from_slice(symbol_c)
rec_obj = self.get_rec_from_slice(symbol_obj)
if rec_c is not None and rec_obj is not None:
k_dict[basic + str(strike)] = [
basic, strike, rec_c[2], rec_c[3], ask_price,
bid_price, rec_obj[2], rec_obj[3], tm
]
r = []
# 逐条记录验证pcp规则
for k in k_dict.keys():
rec = k_dict[k]
term = rec[0]
x = rec[1]
tm = rec[8]
date_mature = mature_dict[term]
date_mature = datetime.strptime(date_mature, '%Y-%m-%d')
td = datetime.strptime(today, '%Y-%m-%d')
T = round(float((date_mature - td).days) / 365, 4) # 剩余期限
if T == 0 or T >= 0.3:
continue
# 正向套利
S = rec[6]
cb = rec[3]
pa = rec[4]
if cb > 1E8 or cb == 0 or cb != cb or pa > 1E8 or pa == 0 or pa != pa:
pass
else:
pSc_forward = int(pa + S - cb)
diff_forward = float(x) - pSc_forward
rt_forward = round(diff_forward / (S * 2 * 0.15) / T, 2)
if rt_forward >= 0.12 and diff_forward >= 3:
self.id += 1
seq = today[-5:-3] + today[-2:] + str(self.id)
r.append([
seq, today, tm, 'pcp',
[
'forward', term, S, cb, pa, T, x, pSc_forward,
diff_forward, rt_forward
]
])
# to_log( 'pcp: ' + str([today, 'forward', term, x, S, cb, pa, pSc_forward, T, diff_forward, rt_forward]) )
# 反向套利
S = rec[7]
ca = rec[2]
pb = rec[5]
if ca > 1E8 or ca == 0 or ca != ca or pb > 1E8 or pb == 0 or pb != pb:
pass
else:
pSc_back = int(pb + S - ca)
diff_back = pSc_back - float(x)
rt_back = round(diff_back / (S * 2 * 0.15) / T, 2)
if rt_back >= 0.12 and diff_back >= 3:
self.id += 1
seq = today[-5:-3] + today[-2:] + str(self.id)
r.append([
seq, today, tm, 'pcp',
[
'back', term, S, ca, pb, T, x, pSc_back, diff_back,
rt_back
]
])
# to_log( 'pcp: ' + str([today, 'back', term, x, S, ca, pb, pSc_back, T, diff_back, rt_back]) )
df = pd.DataFrame(r,
columns=['seq', 'date', 'time', 'type', 'content'])
fn = get_dss() + 'fut/engine/arbitrage/portfolio_arbitrage_chance.csv'
if os.path.exists(fn):
df.to_csv(fn, index=False, mode='a', header=False)
else:
df.to_csv(fn, index=False)
if tm > '09:00:00' and tm < '15:00:00' and r != []:
pass
def get_exchangeID(symbol):
c = get_contract(symbol)
return c.exchangeID
def _bc_sendOrder(self, dt, code, direction, offset, price, volume,
portfolio):
filename = get_dss() + 'gateway_closed.csv'
if os.path.exists(filename):
return
if self.state == 'CLOSE':
print('gateway closed')
return
pz = get_contract(code).pz
if portfolio in self.pf_dict:
pz_list = self.pf_dict[portfolio].split(',')
if (pz in pz_list) or ('*' in pz_list):
print(portfolio, ' ', pz, ' send order here!')
else:
print(portfolio, ' ', pz, ' just test order here!')
return
else:
print(portfolio, ' ', pz, ' just test order here!')
return
exchangeID = get_exchangeID(code)
if exchangeID == '':
return
try:
now = datetime.now()
now = now.strftime('%H:%M')
if now in ['10:14', '10:15', '10:16'
] and code[:2] not in ['IF', 'IO']:
time.sleep(960)
self.lock.acquire()
# 对价格四舍五入
priceTick = get_contract(code).price_tick
price = int(round(price / priceTick, 0)) * priceTick
r = [[dt, code, direction, offset, price, volume]]
print(str(r))
c = [
'datetime', 'symbol', 'direction', 'offset', 'price', 'volume'
]
df = pd.DataFrame(r, columns=c)
filename = get_dss() + 'fut/engine/gateway_order.csv'
if os.path.exists(filename):
df.to_csv(filename, index=False, mode='a', header=False)
else:
df.to_csv(filename, index=False)
if direction == DIRECTION_LONG and offset == 'Open':
self.t.ReqOrderInsert(code, DirectType.Buy, OffsetType.Open,
price, volume, exchangeID)
if direction == DIRECTION_SHORT and offset == 'Open':
self.t.ReqOrderInsert(code, DirectType.Sell, OffsetType.Open,
price, volume, exchangeID)
if direction == DIRECTION_LONG and offset == 'Close':
self.t.ReqOrderInsert(code, DirectType.Buy, OffsetType.Close,
price, volume, exchangeID)
if direction == DIRECTION_SHORT and offset == 'Close':
self.t.ReqOrderInsert(code, DirectType.Sell, OffsetType.Close,
price, volume, exchangeID)
send_email(
get_dss(),
'引擎下单：' + code + ' ' + str(direction) + ' ' + str(offset), '')
except Exception as e:
s = traceback.format_exc()
to_log(s)
send_email(get_dss(), '交易路由出错', s)
# 流控
time.sleep(0.5)
print('流控')
self.lock.release()
def control_in_p(self, bar):
if (bar.time > '09:31:00' and bar.time < '11:27:00' and bar.vtSymbol[:2] in ['IF','IO']) or \
(bar.time > '13:01:00' and bar.time < '14:57:00' and bar.vtSymbol[:2] in ['IF','IO']) or \
(bar.time > '21:01:00' and bar.time < '24:00:00' and bar.vtSymbol[:2] in ['al']) or \
(bar.time > '00:00:00' and bar.time < '01:00:00' and bar.vtSymbol[:2] in ['al']) or \
(bar.time > '09:01:00' and bar.time < '11:27:00' and bar.vtSymbol[:2] not in ['IF','IO']) or \
(bar.time > '13:31:00' and bar.time < '14:57:00' and bar.vtSymbol[:2] not in ['IF','IO']) or \
(bar.time > '21:01:00' and bar.time < '22:57:00' and bar.vtSymbol[:2] not in ['IF','IO']) : # 因第一根K线的价格为0
symbol_got_list = []
fn = get_dss() + 'fut/engine/straddle/portfolio_straddle_param.csv'
# while get_file_lock(fn) == False:
# time.sleep(0.01)
df = pd.read_csv(fn) # 加载最新参数
for i, row in df.iterrows():
try:
if row.state == 'stop':
continue
exchangeID = str(get_contract(row.basic_c).exchangeID)
if exchangeID in ['CFFEX', 'DCE']:
symbol_c = row.basic_c + '-C-' + str(row.strike_c)
symbol_p = row.basic_p + '-P-' + str(row.strike_p)
else:
symbol_c = row.basic_c + 'C' + str(row.strike_c)
symbol_p = row.basic_p + 'P' + str(row.strike_p)
if symbol_c not in self.got_dict or symbol_p not in self.got_dict:
continue
if self.got_dict[symbol_c] == False or self.got_dict[
symbol_p] == False:
continue
else:
df.at[i, 'tm'] = bar.time
symbol_got_list.append(symbol_c)
symbol_got_list.append(symbol_p)
s_c = self.signalDict[symbol_c][0]
s_p = self.signalDict[symbol_p][0]
# 开仓
if row.hold_c == 0 and row.hold_p == 0:
# print('come here ')
if row.direction == 'duo':
if self.engine.type == 'backtest':
s_c.buy(s_c.bar.close, row.num_c)
s_p.buy(s_p.bar.close, row.num_p)
df.at[i, 'price_c'] = s_c.bar.close
df.at[i, 'price_p'] = s_p.bar.close
else:
s_c.buy(s_c.bar.AskPrice, row.num_c) # 挂卖价
s_p.buy(s_p.bar.AskPrice, row.num_p) # 挂卖价
df.at[i, 'price_c'] = round(
s_c.bar.AskPrice, 2)
df.at[i, 'price_p'] = round(
s_p.bar.AskPrice, 2)
df.at[i, 'hold_c'] = row.num_c
df.at[i, 'hold_p'] = row.num_p
if row.direction == 'kong':
if self.engine.type == 'backtest':
s_c.short(s_c.bar.close, row.num_c)
s_p.short(s_p.bar.close, row.num_p)
df.at[i, 'price_c'] = s_c.bar.close
df.at[i, 'price_p'] = s_p.bar.close
else:
s_c.short(s_c.bar.BidPrice,
row.num_c) # 挂买价
s_p.short(s_p.bar.BidPrice,
row.num_p) # 挂买价
df.at[i, 'price_c'] = round(
s_c.bar.BidPrice, 2)
df.at[i, 'price_p'] = round(
s_p.bar.BidPrice, 2)
df.at[i, 'hold_c'] = -row.num_c
df.at[i, 'hold_p'] = -row.num_p
# 多单获利平仓
if row.hold_c >= 1 and row.hold_p >= 1:
if self.engine.type == 'backtest':
df.at[i,
'profit_c'] = (s_c.bar.close -
row.price_c) * row.hold_c
df.at[i,
'profit_p'] = (s_p.bar.close -
row.price_p) * row.hold_p
df.at[i, 'profit_o'] = df.at[
i, 'profit_c'] + df.at[i, 'profit_p']
if row.profit_o >= row.profit:
s_c.sell(s_c.bar.close, abs(row.hold_c))
s_p.sell(s_p.bar.close, abs(row.hold_p))
df.at[i, 'hold_c'] = 0
df.at[i, 'hold_p'] = 0
df.at[i, 'state'] = 'stop'
else:
df.at[i, 'profit_c'] = round(
(s_c.bar.BidPrice - row.price_c) *
row.hold_c, 2)
df.at[i, 'profit_p'] = round(
(s_p.bar.BidPrice - row.price_p) *
row.hold_p, 2)
df.at[i, 'profit_o'] = round(
df.at[i, 'profit_c'] +
df.at[i, 'profit_p'], 2)
if row.profit_o >= row.profit:
s_c.sell(s_c.bar.BidPrice, abs(row.hold_c))
s_p.sell(s_p.bar.BidPrice, abs(row.hold_p))
df.at[i, 'hold_c'] = 0
df.at[i, 'hold_p'] = 0
df.at[i, 'state'] = 'stop'
# 空单获利平仓
if row.hold_c <= -1 and row.hold_p <= -1:
if self.engine.type == 'backtest':
df.at[i,
'profit_c'] = (s_c.bar.close -
row.price_c) * row.hold_c
df.at[i,
'profit_p'] = (s_p.bar.close -
row.price_p) * row.hold_p
df.at[i, 'profit_o'] = df.at[
i, 'profit_c'] + df.at[i, 'profit_p']
if row.profit_o >= row.profit:
s_c.cover(s_c.bar.close, abs(row.hold_c))
s_p.cover(s_p.bar.close, abs(row.hold_p))
df.at[i, 'hold_c'] = 0
df.at[i, 'hold_p'] = 0
df.at[i, 'state'] = 'stop'
else:
df.at[i, 'profit_c'] = round(
(s_c.bar.AskPrice - row.price_c) *
row.hold_c, 2)
df.at[i, 'profit_p'] = round(
(s_p.bar.AskPrice - row.price_p) *
row.hold_p, 2)
df.at[i, 'profit_o'] = round(
df.at[i, 'profit_c'] +
df.at[i, 'profit_p'], 2)
if row.profit_o >= row.profit:
s_c.cover(s_c.bar.AskPrice,
abs(row.hold_c))
s_p.cover(s_p.bar.AskPrice,
abs(row.hold_p))
df.at[i, 'hold_c'] = 0
df.at[i, 'hold_p'] = 0
df.at[i, 'state'] = 'stop'
except Exception as e:
s = traceback.format_exc()
to_log(s)
df.to_csv(fn, index=False) # 回写文件
# release_file_lock(fn)
for symbol in symbol_got_list:
self.got_dict[symbol] = False
def open_interest_show_distribution(basic, type, date):
now = datetime.now()
# 本月第一天
first_day = datetime(now.year, now.month, 1)
#前一个月最后一天
pre_month = first_day - timedelta(days=1)
today = now.strftime('%Y-%m-%d')
pre = pre_month.strftime('%Y-%m-%d')
fn = get_dss() + 'opt/' + pre[:7] + '_greeks.csv'
df_pre = pd.read_csv(fn)
fn = get_dss() + 'opt/' + today[:7] + '_greeks.csv'
df_today = pd.read_csv(fn)
df = pd.concat([df_pre, df_today])
df = df[df.Instrument.str.slice(0, len(basic)) == basic]
df['date'] = df.Localtime.str.slice(0, 10)
date_list = sorted(list(set(list(df.date))), reverse=True)
print(date_list)
if len(date_list) < 10:
return ''
plt.figure(figsize=(12, 7))
plt.title(' ')
for i in [0, 1, 9]:
# for i in [0]:
df1 = df[df.date == date_list[i]]
df1 = df1.sort_values('Instrument')
n = len(df1)
assert n % 2 == 0
n = int(n / 2)
df_c = df1.iloc[:n, :]
df_p = df1.iloc[n:, :]
# print(df_c)
# print(df_p)
if type == 'call':
df2 = df_c
else:
df2 = df_p
strike_list = []
for j, row in df2.iterrows():
strike_list.append(get_contract(row.Instrument).strike)
df2['strike'] = strike_list
df2 = df2.set_index('strike')
if i == 0:
plt.plot(df2.OpenInterest, label=date_list[i])
else:
plt.plot(df2.OpenInterest, '--', label=date_list[i])
# print(df2.OpenInterest)
plt.xticks(rotation=90)
plt.legend()
fn = 'static/open_interest.jpg'
plt.savefig(fn)
plt.cla()
fn = 'open_interest.jpg'
now = str(int(time.time()))
r = '<img src=\"static/' + fn + '?rand=' + now + '\" />'
return r
def iv_min5_show(symbol_list, date):
plt.figure(figsize=(13, 7))
plt.title(date)
for symbol in symbol_list:
basic = get_contract(symbol).basic
strike = get_contract(symbol).strike
opt_flag = get_contract(symbol).opt_flag
if basic[:2] == 'IO':
symbol_obj = 'IF' + basic[2:]
else:
symbol_obj = basic
fn = get_dss() + 'fut/put/rec/min5_' + symbol_obj + '.csv'
df_obj = pd.read_csv(fn)
df_obj = df_obj.set_index(['date', 'time'])
df_obj['close_obj'] = df_obj['close']
df_obj = df_obj[['close_obj']]
# print(df_obj.tail())
fn = get_dss() + 'fut/put/rec/min5_' + symbol + '.csv'
df = pd.read_csv(fn)
df = df[df.date == date]
df = df.set_index(['date', 'time'])
# print(df.tail())
df = df.join(df_obj)
df = df.dropna()
df = df.reset_index()
df = df.set_index('time')
# print(df.tail())
r = 0.03
fn = get_dss() + 'fut/cfg/opt_mature.csv'
df2 = pd.read_csv(fn)
df2 = df2[df2.flag == df2.flag] # 筛选出不为空的记录
df2 = df2.set_index('symbol')
mature_dict = dict(df2.mature)
date_mature = mature_dict[basic]
date_mature = datetime.strptime(date_mature, '%Y-%m-%d')
td = datetime.strptime(date, '%Y-%m-%d')
T = float((date_mature - td).days) / 365 # 剩余期限
iv_list = []
for i, row in df.iterrows():
try:
if opt_flag == 'C':
iv = bsm_call_imp_vol(row.close_obj, strike, T, r,
row.close)
else:
iv = bsm_put_imp_vol(row.close_obj, strike, T, r,
row.close)
iv_list.append(round(100 * iv, 2))
except:
break
df['iv'] = iv_list
plt.plot(df.iv, label=symbol)
plt.xticks(rotation=90)
plt.legend()
fn = 'static/iv_min5_show.jpg'
plt.savefig(fn)
plt.cla()
rr = ''
fn = 'iv_min5_show.jpg'
now = str(int(time.time()))
rr = '<img src=\"static/' + fn + '?rand=' + now + '\" />'
return rr