def compass(date):
listfile = os.listdir(dirname)
for fn in listfile:
os.remove(dirname + fn)
d2 = get_dss() + 'info/hold/img/'
listfile = os.listdir(d2)
for fn in listfile:
os.remove(d2 + fn)
fn = get_dss() + 'fut/cfg/opt_mature.csv'
df2 = pd.read_csv(fn)
df2 = df2[pd.notnull(df2.flag)]
fn_list = []
for func in [CF, m, RM, al, IO]:
# for func in [m]:
try:
fn_list += func(date, df2)
except Exception as e:
s = traceback.format_exc()
to_log(s)
# print(fn_list)
send_email(get_dss(), 'compass', '', fn_list)
def on_bar_minx(self, bar):
self.am.updateBar(bar)
if not self.am.inited:
return
# 涨跌停时暂停交易
if bar.close == bar.UpperLimitPrice:
self.pause = True
to_log(self.vtSymbol + ' 已涨停，该品种dali策略暂停交易')
if bar.close == bar.LowerLimitPrice:
self.pause = True
to_log(self.vtSymbol + ' 已跌停，该品种dali策略暂停交易')
if self.paused == True and self.backtest == False:
self.counter += 1
if self.counter == 3:
filename = get_dss() + 'gateway_closed.csv'
if os.path.exists(filename):
pass
else:
send_email(get_dss(), self.vtSymbol + ' 挂单未成交！！！', '')
return
self.calculateIndicator() # 计算指标
self.generateSignal(bar) # 触发信号，产生交易指令
def deal_single_ins(item):
r = False
if item['ins'] == 'down_sell':
df = ts.get_realtime_quotes(item['code'])
b3_price = float(df.at[0, 'b3_p'])
if b3_price <= item['price'] and b3_price > 0:
to_log('reach price by down_sell ins ')
item['ins'] = 'sell_order'
send_instruction(item)
r = True
if item['ins'] == 'up_warn':
df = ts.get_realtime_quotes(item['code'])
b3_price = float(df.at[0, 'b3_p'])
if b3_price >= item['price']:
to_log('reach price by up_warn ins ')
send_email(dss, 'up_warn', str(item))
r = True
if item['ins'] == 'down_warn':
df = ts.get_realtime_quotes(item['code'])
b3_price = float(df.at[0, 'b3_p'])
if b3_price <= item['price'] and b3_price > 0:
to_log('reach price by down_warn ins ')
send_email(dss, 'down_warn', str(item))
r = True
if item['ins'] in ['sell_order', 'buy_order']:
to_log('send sell_order or buy_order ins ')
send_instruction(item)
r = True
return r
def mail_1515():
to_log('in mail_1515')
try:
now = datetime.now()
today = now.strftime('%Y-%m-%d')
weekday = int(now.strftime('%w'))
if 1 <= weekday <= 5:
r = []
logfile = dss + 'log/autotrade.log'
df = pd.read_csv(logfile, sep=' ', header=None, encoding='ansi')
df = df[df[0] == today]
for i, row in df.iterrows():
r.append(str(list(row)[:7]))
send_email(dss, 'show log', '\n'.join(r))
r = []
txtfile = dss + 'csv/ins.txt'
with open(txtfile, 'r', encoding='utf-8') as f:
line = f.readline()
while line:
if line[0] == '{':
#line_dict = eval(line)
r.append(line)
line = f.readline()
send_email(dss, 'show ins ', '\n'.join(r))
except Exception as e:
print('error')
print(e)
def worker_1450(self):
"""盘中推送bar"""
to_log('in TradeEngine.worker_1450')
for p in self.portfolio_list:
for vtSymbol in p.vtSymbolList:
#print(vtSymbol)
df = None
i = 0
while df is None and i < 2:
try:
i += 1
df = ts.get_realtime_quotes(vtSymbol)
except Exception as e:
print('error get_realtime_quotes')
print(e)
time.sleep(0.1)
if df is None:
continue
code = vtSymbol
df1 = None
i = 0
while df1 is None and i < 2:
try:
i += 1
df1 = get_adj_factor(self.dss, code)
except Exception as e:
print('error adj_factor ' + code)
print(e)
time.sleep(0.1)
if df1 is None:
continue
factor = float(df1.at[0, 'adj_factor'])
d = df.loc[0, :]
bar = VtBarData()
bar.vtSymbol = vtSymbol
bar.symbol = vtSymbol
bar.open = float(d['open']) * factor
bar.high = float(d['high']) * factor
bar.low = float(d['low']) * factor
bar.close = float(d['price']) * factor
bar.close_bfq = float(d['price'])
date = d['date'].split('-') #去掉字符串中间的'-'
date = ''.join(date)
bar.date = date
bar.time = '00:00:00'
bar.datetime = datetime.strptime(bar.date + ' ' + bar.time,
'%Y%m%d %H:%M:%S')
bar.volume = float(d['volume'])
p.onBar(bar)
send_email(self.dss, 'worker_1450处理完毕', '')
def mail_pdf(s):
try:
# 将url页面转化为pdf
url = 'http://114.116.190.167:5000/show_' + s
fn = 'web/static/out3.pdf'
pdfkit.from_url(url, fn)
send_email(dss, url[33:], '', [fn])
except Exception as e:
s = traceback.format_exc()
to_log(s)
def run_examine():
kj = round(get_free_space_mb('C:\\'), 2)
# print(kj,'GB')
if kj < 3:
send_email(dss, '预警：磁盘空间不足, 仅剩余', str(kj) + 'GB')
now = datetime.datetime.now()
weekday = int(now.strftime('%w'))
if 1 <= weekday <= 5 and is_market_date():
print('\n' + str(now) + " examine begin...")
examine()
now = datetime.datetime.now()
print('\n' + str(now) + " examine end ")
def mail_0200():
to_log('in mail_0200')
try:
now = datetime.now()
weekday = int(now.strftime('%w'))
if 2 <= weekday <= 6:
print('\n' + str(now) + " mail_ma begin...")
r = use_ma(dss)
#print(r)
#print(type(r))
send_email(dss, str(len(r)) + ' setting items ', '')
except Exception as e:
print('error')
print(e)
def run_arbitrage():
try:
now = datetime.datetime.now()
weekday = int(now.strftime('%w'))
if 1 <= weekday <= 5 and is_market_date():
print('\n' + str(now) + " arbitrage begin...")
if calc_pcp():
fn = get_dss() + 'opt/pcp.csv'
send_email(dss, 'pcp', '', [fn])
if calc_die():
fn = get_dss() + 'opt/die.csv'
send_email(dss, 'die', '', [fn])
print(" arbitrage end ")
except Exception as e:
s = traceback.format_exc()
to_log(s)
def run_price_signal():
try:
now = datetime.datetime.now()
weekday = int(now.strftime('%w'))
if 2 <= weekday <= 6:
dates = get_trading_dates(dss)
today = dates[-1]
arr = price_signal(dss, today)
r = []
for a in arr:
r.append(str(a))
#print(str(r))
send_email(dss, 'price_signal', '\n'.join(r))
except Exception as e:
s = traceback.format_exc()
to_log(s)
def check_trade(self):
fn = get_dss() + 'fut/engine/gateway_order.csv'
df1 = pd.read_csv(fn)
df1 = df1[self.file_order_length:]
# 读取发单文件，获得最新的发单记录，按合约、多空、开平字段进行汇总
if len(df1) > 0:
g1 = df1.groupby(by=['symbol', 'direction', 'offset'])
r1 = g1.agg({'volume': np.sum})
r1 = r1.reset_index()
#print(r1)
fn = get_dss() + 'fut/engine/gateway_trade.csv'
df2 = pd.read_csv(fn)
df2 = df2[self.file_trade_length:]
# 读取成交文件，获得最新的成交记录，按合约、多空、开平字段进行汇总
if len(df2) > 0:
# 处理路由记录存在重复的情况
df2 = df2.drop_duplicates()
g2 = df2.groupby(by=['InstrumentID', 'Direction', 'Offset'])
r2 = g2.agg({'Volume': np.sum})
r2 = r2.reset_index()
r2.columns = ['symbol', 'direction', 'offset', 'volume']
#print(r2)
if len(df1) > 0:
if len(df2) > 0:
result = pd.merge(
r1,
r2,
how='left',
on=['symbol', 'direction', 'offset', 'volume'],
indicator=True)
#print(result)
result = result[result._merge == 'left_only']
#print(result)
if len(result) > 0:
# symbol_name = str(set(result.symbol))
# send_email(get_dss(), 'Alert: 发单未成交：' + symbol_name, '')
send_email(get_dss(), 'Alert: 发单未成交', '')
else:
to_log('all order dealed')
else:
send_email(get_dss(), 'Alert: 发单全部未成交', '')
def calculateIndicator(self):
"""计算技术指标"""
r = []
for row in self.ins_list:
self.can_buy = False
self.can_sell = False
self.can_short = False
self.can_cover = False
ins = row[0]
price = row[1]
self.fixedSize = row[2]
# print(ins, price, self.fixedSize)
if ins == 'up_buy' and self.bar.close >= price:
self.can_buy = True
elif ins == 'down_buy' and self.bar.close <= price:
self.can_buy = True
elif ins == 'up_sell' and self.bar.close >= price:
self.can_sell = True
elif ins == 'down_sell' and self.bar.close <= price:
self.can_sell = True
elif ins == 'up_short' and self.bar.close >= price:
self.can_short = True
elif ins == 'down_short' and self.bar.close <= price:
self.can_short = True
elif ins == 'up_cover' and self.bar.close >= price:
self.can_cover = True
elif ins == 'down_cover' and self.bar.close <= price:
self.can_cover = True
elif ins == 'up_warn' and self.bar.close >= price:
send_email(get_dss(),
self.bar.vtSymbol + ' up_warn: ' + str(price), '')
elif ins == 'down_warn' and self.bar.close <= price:
send_email(get_dss(),
self.bar.vtSymbol + ' down_warn: ' + str(price), '')
else:
r.append(row)
self.generateSignal(self.bar) # 触发信号，产生交易指令
self.ins_list = r
def mail_value():
try:
now = datetime.datetime.now()
weekday = int(now.strftime('%w'))
if 0 <= weekday <= 5:
pnl_base = 54562
value_base = 103E4
date_base = '2020-12-30'
fn = get_dss() + 'fut/engine/focus/all.csv'
df = pd.read_csv(fn)
df['value'] = 1 + round((df['pnl'] - pnl_base) / value_base, 2)
df = df[df.date >= date_base]
df = df.set_index('date')
date_list = list(df.index)
plt.figure(figsize=(7, 3))
plt.title(date_list[-1] + ': ' +
str(df.at[date_list[-1], 'value']))
plt.plot(df.value)
# plt.xticks(rotation=90)
plt.xticks('off')
plt.grid(True, axis='y')
# ax = plt.gca()
# for label in ax.get_xticklabels():
# label.set_visible(False)
# for label in ax.get_xticklabels()[0:1]:
# label.set_visible(True)
# for label in ax.get_xticklabels()[-1:]:
# label.set_visible(True)
# plt.legend()
fn = get_repo() + 'nature/web/static/value_all.jpg'
plt.savefig(fn)
plt.cla()
send_email(dss, 'value', '', [fn])
except Exception as e:
s = traceback.format_exc()
to_log(s)
def stare_hold():
print('stare_hold begin... ')
loaded = False
codes = ()
mailed = []
while True:
time.sleep(30)
if is_price_time():
# 读入codes
if not loaded:
b1 = Book(dss)
codes = b1.get_codes()
loaded = True
for code in codes:
try:
time.sleep(1)
df = ts.get_realtime_quotes(code)
name = df.at[0, 'name']
price = float(df.at[0, 'price'])
pre_close = float(df.at[0, 'pre_close'])
#print(code, price, pre_close)
if code not in mailed:
if price / pre_close - 1 > 0.05:
send_email(dss, 'up_warn', str(code + ' ' + name))
#print('up_warn', str(code+' '+name))
mailed.append(code)
if price / pre_close - 1 < -0.05:
send_email(dss, 'down_warn',
str(code + ' ' + name))
#print('down_warn', str(code+' '+name))
mailed.append(code)
except Exception as e:
print('error')
print(e)
else:
loaded = False
codes = ()
mailed = []
time.sleep(300)
def mail_log():
try:
now = datetime.datetime.now()
preday = now - datetime.timedelta(days=1)
preday = preday.strftime('%Y-%m-%d %H:%M:%S')
weekday = int(now.strftime('%w'))
r = []
logfile = dss + 'log/autotrade.log'
#df = pd.read_csv(logfile,sep='$',header=None,encoding='ansi')
df = pd.read_csv(logfile, sep='$', header=None, encoding='utf-8')
df['datetime'] = df[0] + ' ' + df[1]
df = df[df['datetime'] >= preday]
if len(df) > 0:
df = df.sort_values('datetime', ascending=False)
del df['datetime']
for i, row in df.iterrows():
s = str(list(row)[:7])
r.append(s)
send_email(dss, 'show log', '\n'.join(r))
except Exception as e:
print(now, '-' * 30)
traceback.print_exc()
def mail_1815():
to_log('in mail_1815')
try:
now = datetime.now()
weekday = int(now.strftime('%w'))
if 1 <= weekday <= 5:
print('\n' + str(now) + " mail_factor begin...")
r = has_factor(dss)
if r == []:
send_email(dss, 'no factor', '')
else:
send_email(dss, 'has factor', '\n'.join(r))
print('\n' + str(now) + " mail_stk_report begin...")
r = stk_report(dss)
send_email(dss, 'show stk_report', '\n'.join(r))
except Exception as e:
print('error')
print(e)
def worker_1450(self):
"""盘中推送bar"""
to_log('in TradeEngine.worker_1450')
print('begin worker_1450')
r, dt = self.is_trade_day()
if r == False:
return
self.currentDt = dt
for vtSymbol in self.vtSymbolList:
#print(vtSymbol)
df = None
i = 0
while df is None and i < 3:
try:
i += 1
df = ts.get_realtime_quotes(vtSymbol)
except Exception as e:
print('error get_realtime_quotes')
print(e)
time.sleep(1)
if df is None:
continue
code = vtSymbol
df1 = None
i = 0
while df1 is None and i < 3:
try:
i += 1
df1 = get_adj_factor(self.dss, code)
except Exception as e:
print('error adj_factor')
print(e)
time.sleep(1)
if df1 is None:
continue
factor = float(df1.at[0, 'adj_factor'])
d = df.loc[0, :]
bar = VtBarData()
bar.vtSymbol = vtSymbol
bar.symbol = vtSymbol
bar.open = float(d['open']) * factor
bar.high = float(d['high']) * factor
bar.low = float(d['low']) * factor
bar.close = float(d['price']) * factor
bar.close_bfq = float(d['price'])
date = d['date'].split('-') #去掉字符串中间的'-'
date = ''.join(date)
bar.date = date
bar.time = '00:00:00'
bar.datetime = datetime.strptime(bar.date + ' ' + bar.time,
'%Y%m%d %H:%M:%S')
bar.volume = float(d['volume'])
barDict = self.dataDict.setdefault(bar.datetime, OrderedDict())
barDict[bar.vtSymbol] = bar
self.portfolio.onBar(bar)
send_email(self.dss, 'worker_1450处理完毕', '')
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 on_qry_account(self, pTradingAccount, pRspInfo, nRequestID, bIsLast):
self.t.OnAccount(pTradingAccount, pRspInfo, nRequestID, bIsLast)
risk = round(float(self.t.account.Risk), 2)
if self.state == 'OPEN':
send_email(get_dss(), 'Risk: ' + str(risk), ' ')
def calculateIndicator(self):
"""计算技术指标"""
# 记录数据
r = [[self.bar.date, self.bar.time, self.bar.close]]
df = pd.DataFrame(r)
filename = get_dss(
) + 'fut/engine/owl/bar_owl_' + self.type + '_' + self.vtSymbol + '.csv'
if os.path.exists(filename):
df.to_csv(filename, index=False, mode='a', header=False)
else:
df.to_csv(filename, index=False)
r = []
fn = get_dss(
) + 'fut/engine/owl/signal_owl_' + self.type + '_var_' + self.vtSymbol + '.csv'
if os.path.exists(fn):
df = pd.read_csv(fn)
for i, row in df.iterrows():
self.can_buy = False
self.can_sell = False
self.can_short = False
self.can_cover = False
ins = row['ins']
price = float(row['price'])
self.fixedSize = int(row['num'])
# print(ins, price, self.fixedSize)
if ins == 'up_buy' and self.bar.close >= price:
self.can_buy = True
elif ins == 'down_buy' and self.bar.close <= price:
self.can_buy = True
elif ins == 'up_sell' and self.bar.close >= price:
self.can_sell = True
elif ins == 'down_sell' and self.bar.close <= price:
self.can_sell = True
elif ins == 'up_short' and self.bar.close >= price:
self.can_short = True
elif ins == 'down_short' and self.bar.close <= price:
self.can_short = True
elif ins == 'up_cover' and self.bar.close >= price:
self.can_cover = True
elif ins == 'down_cover' and self.bar.close <= price:
self.can_cover = True
elif ins == 'up_warn' and self.bar.close >= price:
send_email(get_dss(),
self.bar.vtSymbol + ' up_warn: ' + str(price),
'')
elif ins == 'down_warn' and self.bar.close <= price:
send_email(get_dss(),
self.bar.vtSymbol + ' down_warn: ' + str(price),
'')
else:
r.append([row.ins, row.price, row.num])
self.generateSignal(self.bar) # 触发信号，产生交易指令
fn = get_dss() + 'fut/engine/owl/history.csv'
df = pd.read_csv(fn)
df1 = df[(df.code == self.bar.vtSymbol) & (df.got == 'no')]
if len(df1) > 0:
for i, row in df1.iterrows():
r.append([row.ins, row.price, row.num])
df.at[i, 'got'] = 'yes'
df.to_csv(fn, index=False)
fn = get_dss(
) + 'fut/engine/owl/signal_owl_' + self.type + '_var_' + self.vtSymbol + '.csv'
df = pd.DataFrame(r, columns=['ins', 'price', 'num'])
df.to_csv(fn, index=False)
def worker_1450(self):
"""盘中推送bar"""
to_log('in TradeEngine.worker_1450')
for p in self.portfolio_list:
for vtSymbol in p.vtSymbolList:
#print(vtSymbol)
df = None
i = 0
while df is None and i < 2:
try:
i += 1
df = ts.get_realtime_quotes(vtSymbol)
except Exception as e:
print('error get_realtime_quotes')
print(e)
time.sleep(0.1)
if df is None:
to_log('ignore ' + vtSymbol)
continue
adj_factor = None
df1 = None
i = 0
while df1 is None and i < 2:
try:
i += 1
df1 = get_adj_factor(self.dss, vtSymbol)
adj_factor = float(df1.at[0, 'adj_factor'])
except Exception as e:
print('error adj_factor ' + vtSymbol)
print(e)
time.sleep(0.1)
if df1 is None:
to_log('ignore ' + vtSymbol)
continue
hfq_factor = get_hfq_factor(self.dss, vtSymbol)
factor = hfq_factor
if adj_factor is not None:
if abs((adj_factor - hfq_factor) /
adj_factor) > 0.01: # 差异大，今天有除权
factor = adj_factor
d = df.loc[0, :]
bar = VtBarData()
bar.vtSymbol = vtSymbol
bar.symbol = vtSymbol
bar.open = float(d['open']) * factor
bar.high = float(d['high']) * factor
bar.low = float(d['low']) * factor
bar.close = float(d['price']) * factor
bar.close_bfq = float(d['price'])
date = d['date'].split('-') #去掉字符串中间的'-'
date = ''.join(date)
bar.date = date
bar.time = '00:00:00'
bar.datetime = datetime.strptime(bar.date + ' ' + bar.time,
'%Y%m%d %H:%M:%S')
bar.volume = float(d['volume'])
#to_log(vtSymbol+' '+d['price']+' * '+str(factor)+' = '+str(bar.close))
p.onBar(bar)
send_email(self.dss, 'worker_1450处理完毕', '')
def die(self):
r = []
tm = self.tm
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 basic in self.slice_dict.keys():
if basic not in mature_dict:
continue
date_mature = mature_dict[ basic ]
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 >= 0.2:
continue
strike_list = []
v = self.slice_dict[basic]
for row in v:
# if basic == 'm2105':
# print(row)
symbol = row[0]
if get_contract(symbol).be_opt:
strike_list.append( get_contract(symbol).strike )
strike_list = sorted(set(strike_list))
n = len(strike_list)
for gap in [1,2,3]:
for i in range(n-2*gap):
try:
s1 = strike_list[i]
s2 = strike_list[i+gap]
s3 = strike_list[i+2*gap]
if s2 -s1 != s3 -s2:
continue
c1 = self.get_rec_from_slice(basic+get_contract(basic).opt_flag_C+str(s1))[2] # AskPrice
c2 = self.get_rec_from_slice(basic+get_contract(basic).opt_flag_C+str(s2))[3] # BidPrice
c3 = self.get_rec_from_slice(basic+get_contract(basic).opt_flag_C+str(s3))[2] # AskPrice
if c1 == 0 or c2 == 0 or c3 == 0 or c1 != c1 or c2 != c2 or c3 != c3:
pass
else:
cost = round(c1 - 2*c2 + c3, 2)
if cost <= 0:
self.id += 1
seq = today[-5:-3] + today[-2:] + str(self.id)
r.append( [seq, today, tm, 'die', ['forward', basic, 'C', s1, c1, s2, c2, s3, c3, cost]] )
p1 = self.get_rec_from_slice(basic+get_contract(basic).opt_flag_P+str(s1))[2] # AskPrice
p2 = self.get_rec_from_slice(basic+get_contract(basic).opt_flag_P+str(s2))[3] # BidPrice
p3 = self.get_rec_from_slice(basic+get_contract(basic).opt_flag_P+str(s3))[2] # AskPrice
if p1 == 0 or p2 == 0 or p3 == 0 or p1 != p1 or p2 != p2 or p3 != p3:
pass
else:
cost = round(p1 - 2*p2 + p3, 2)
if cost <= 0:
self.id += 1
seq = today[-5:-3] + today[-2:] + str(self.id)
r.append( [seq, today, tm, 'die', ['forward', basic, 'P', s1, p1, s2, p2, s3, p3, cost]] )
except:
pass
# s = traceback.format_exc()
# to_log(s)
fn = get_dss() + 'fut/engine/arbitrage/portfolio_arbitrage_chance.csv'
df = pd.read_csv(fn)
df = df[(df.date== today) & (df.type=='die')]
result = []
for rr in r:
rec = rr[4]
for i, row in df.iterrows():
c = eval(row['content'])
if c[1] == rec[1] and c[2] == rec[2] and c[3] == rec[3] and c[5] == rec[5] and c[7] == rec[7]:
pass
else:
result.append(rec)
if result != []:
df = pd.DataFrame(result, columns=['seq', 'date', 'time', 'type', 'content'])
df.to_csv(fn, index=False, mode='a', header=False)
if tm > '09:00:00' and tm < '15:00:00':
send_email(get_dss(), '无风险套利机会'+' '+today+' '+tm, '', [], '*****@*****.**')
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 basic in self.slice_dict.keys():
# print(pz)
v = self.slice_dict[basic]
for row in v:
# if basic == 'm2105':
# print(row)
symbol = row[0]
tm = row[1]
ask_price = row[2]
bid_price = row[3]
opt_flag = get_contract(symbol).opt_flag
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]] )
fn = get_dss() + 'fut/engine/arbitrage/portfolio_arbitrage_chance.csv'
df = pd.read_csv(fn)
df = df[(df.date== today) & (df.type=='pcp')]
result = []
for rr in r:
rec = rr[4]
for i, row in df.iterrows():
c = eval(row['content'])
if c[1] == rec[1] and c[2] == rec[2] and c[3] == rec[3] and c[5] == rec[5] and c[7] == rec[7]:
pass
else:
result.append(rec)
if result != []:
df = pd.DataFrame(result, columns=['seq', 'date', 'time', 'type', 'content'])
df.to_csv(fn, index=False, mode='a', header=False)
if tm > '09:00:00' and tm < '15:00:00':
send_email(get_dss(), '无风险套利机会'+' '+today+' '+tm, '', [], '*****@*****.**')
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
cols = [
'date', 'basic_m0', 'basic_m1', 'strike', 'fixed_size',
'hold_m0', 'hold_m1', 'price_c_m0', 'price_p_m0', 'price_c_m1',
'price_p_m1', 'd_low_open', 'd_high_open', 'd_max', 'dida_max',
'd_min', 'dida_min', 'profit', 'state', 'source', 'profit_m0',
'profit_m1', 'profit_o'
]
fn = get_dss() + 'fut/engine/sdiffer/portfolio_sdiffer_param.csv'
# while get_file_lock(fn) == False:
# time.sleep(0.01)
cols_straddle = [
'tm', 'basic_c', 'strike_c', 'basic_p', 'strike_p', 'num_c',
'num_p', 'direction', 'hold_c', 'hold_p', 'profit', 'state',
'source', 'price_c', 'price_p', 'profit_c', 'profit_p',
'profit_o', 'date'
]
fn_straddle = get_dss(
) + 'fut/engine/straddle/portfolio_straddle_param.csv'
# while get_file_lock(fn_straddle) == False:
# time.sleep(0.01)
df = pd.read_csv(fn)
df_straddle = pd.read_csv(fn_straddle)
symbol_got_list = []
# 先确定当日要交易的合约，生成当日交易记录
if self.symbol_obj is None:
try:
temp1 = 'IF' + self.basic_m0[2:]
# print(temp1)
if self.got_dict[temp1]:
self.symbol_obj = temp1
# 临近到期日，暂停自动交易，否则，发出条件单
if self.stop == False:
s_obj = self.signalDict[self.symbol_obj][0]
obj = s_obj.bar.close
gap = 50
atm = int(
round(
round(obj * (100 / gap) / 1E4, 2) * 1E4 /
(100 / gap), 0)) # 获得平值
r = [[bar.date, self.basic_m0, self.basic_m1, atm, 1, \
0, 0, '','','','', \
self.d_low_open, self.d_high_open, 0.0,0,0.0,0, \
13,self.be_run,'sdiffer','','',''] ]
df2 = pd.DataFrame(r, columns=cols)
df = pd.concat([df, df2], sort=False)
# print(df)
except Exception as e:
s = traceback.format_exc()
to_log(s)
else:
for i, row in df.iterrows():
try:
r = []
if row.state == 'stop':
continue
symbol_c_m0 = row.basic_m0 + '-C-' + str(row.strike)
symbol_p_m0 = row.basic_m0 + '-P-' + str(row.strike)
symbol_c_m1 = row.basic_m1 + '-C-' + str(row.strike)
symbol_p_m1 = row.basic_m1 + '-P-' + str(row.strike)
if symbol_c_m0 not in self.got_dict or symbol_p_m0 not in self.got_dict or symbol_c_m1 not in self.got_dict or symbol_p_m1 not in self.got_dict:
continue
if self.got_dict[symbol_c_m0] == False or self.got_dict[
symbol_p_m0] == False or self.got_dict[
symbol_c_m1] == False or self.got_dict[
symbol_p_m1] == False:
continue
else:
symbol_got_list.append(symbol_c_m0)
symbol_got_list.append(symbol_p_m0)
symbol_got_list.append(symbol_c_m1)
symbol_got_list.append(symbol_p_m1)
s_c_m0 = self.signalDict[symbol_c_m0][0]
s_p_m0 = self.signalDict[symbol_p_m0][0]
s_c_m1 = self.signalDict[symbol_c_m1][0]
s_p_m1 = self.signalDict[symbol_p_m1][0]
d_base_m0 = self.d_base_dict[row.basic_m0 + '_' +
str(row.strike)]
d_base_m1 = self.d_base_dict[row.basic_m1 + '_' +
str(row.strike)]
# 开仓
if row.hold_m0 == 0 and row.hold_m1 == 0:
diff_m0 = 0.5 * (
s_c_m0.bar.AskPrice + s_c_m0.bar.BidPrice
) + 0.5 * (s_p_m0.bar.AskPrice +
s_p_m0.bar.BidPrice) - d_base_m0
diff_m1 = 0.5 * (
s_c_m1.bar.AskPrice + s_c_m1.bar.BidPrice
) + 0.5 * (s_p_m1.bar.AskPrice +
s_p_m1.bar.BidPrice) - d_base_m1
differ = diff_m1 - diff_m0
print('differ: ', differ)
if differ <= self.d_low_mail and self.mailed_low == False:
self.mailed_low = True
send_email(get_dss(),
'differ: ' + str(differ), '')
if differ >= self.d_high_mail and self.mailed_high == False:
self.mailed_high = True
send_email(get_dss(),
'differ: ' + str(differ), '')
if differ >= row.d_max:
df.at[i, 'd_max'] = differ
df.at[i, 'dida_max'] = 0
else:
df.at[i, 'dida_max'] = row.dida_max + 1
# print(df.at[i, 'dida_max'], row.dida_max)
if differ <= row.d_min:
df.at[i, 'd_min'] = differ
df.at[i, 'dida_min'] = 0
else:
df.at[i, 'dida_min'] = row.dida_min + 1
# print(df.at[i, 'dida_min'], row.dida_min)
# 做多
# if differ < 9:
if df.at[
i,
'd_min'] <= row.d_low_open and differ >= row.d_low_open and df.at[
i, 'dida_min'] > 0:
r.append([
'00:00:00', row.basic_m0, row.strike,
row.basic_m0, row.strike, 1, 1, 'kong',
0, 0, 1000, 'run', 'sdiffer', '', '',
'', '', '', bar.date
])
r.append([
'00:00:00', row.basic_m1, row.strike,
row.basic_m1, row.strike, 1, 1, 'duo',
0, 0, 1000, 'run', 'sdiffer', '', '',
'', '', '', bar.date
])
df.at[i, 'hold_m0'] = -1
df.at[i, 'hold_m1'] = 1
df.at[i,
'price_c_m0'] = s_c_m0.bar.BidPrice
df.at[i,
'price_p_m0'] = s_p_m0.bar.BidPrice
df.at[i,
'price_c_m1'] = s_c_m1.bar.AskPrice
df.at[i,
'price_p_m1'] = s_p_m1.bar.AskPrice
# 做空
# if differ > 9:
if df.at[
i,
'd_max'] >= row.d_high_open and differ <= row.d_high_open and df.at[
i, 'dida_max'] > 0:
r.append([
'00:00:00', row.basic_m1, row.strike,
row.basic_m1, row.strike, 1, 1, 'kong',
0, 0, 1000, 'run', 'sdiffer', '', '',
'', '', '', bar.date
])
r.append([
'00:00:00', row.basic_m0, row.strike,
row.basic_m0, row.strike, 1, 1, 'duo',
0, 0, 1000, 'run', 'sdiffer', '', '',
'', '', '', bar.date
])
df.at[i, 'hold_m0'] = 1
df.at[i, 'hold_m1'] = -1
df.at[i,
'price_c_m0'] = s_c_m0.bar.AskPrice
df.at[i,
'price_p_m0'] = s_p_m0.bar.AskPrice
df.at[i,
'price_c_m1'] = s_c_m1.bar.BidPrice
df.at[i,
'price_p_m1'] = s_p_m1.bar.BidPrice
df2_straddle = pd.DataFrame(
r, columns=cols_straddle)
df_straddle = pd.concat(
[df_straddle, df2_straddle], sort=False)
# 多单获利平仓
elif row.hold_m0 == -1 and row.hold_m1 == 1:
df.at[i, 'profit_m0'] = round(
(row.price_c_m0 + row.price_p_m0) -
(s_c_m0.bar.AskPrice +
s_p_m0.bar.AskPrice), 2)
df.at[i, 'profit_m1'] = round(
(s_c_m1.bar.BidPrice + s_p_m1.bar.BidPrice)
- (row.price_c_m1 + row.price_p_m1), 2)
df.at[i, 'profit_o'] = round(
df.at[i, 'profit_m0'] +
df.at[i, 'profit_m1'], 2)
if df.at[i, 'profit_o'] >= row.profit:
df.at[i, 'hold_m0'] = 0
df.at[i, 'hold_m1'] = 0
df.at[i, 'state'] = 'stop'
for j, jow in df_straddle.iterrows():
if jow.basic == row.basic_m0 and jow.strike == row.strike and jow.direction == 'kong' and jow.source == 'sdiffer':
df_straddle.at[j, 'profit'] = -1000
if jow.basic == row.basic_m1 and jow.strike == row.strike and jow.direction == 'duo' and jow.source == 'sdiffer':
df_straddle.at[j, 'profit'] = -1000
# 空单获利平仓
elif row.hold_m0 == 1 and row.hold_m1 == -1:
df.at[i, 'profit_m0'] = round(
(s_c_m0.bar.BidPrice + s_p_m0.bar.BidPrice)
- (row.price_c_m0 + row.price_p_m0), 2)
df.at[i, 'profit_m1'] = round(
(row.price_c_m1 + row.price_p_m1) -
(s_c_m1.bar.AskPrice +
s_p_m1.bar.AskPrice), 2)
df.at[i, 'profit_o'] = round(
df.at[i, 'profit_m0'] +
df.at[i, 'profit_m1'], 2)
if df.at[i, 'profit_o'] >= row.profit:
df.at[i, 'hold_m0'] = 0
df.at[i, 'hold_m1'] = 0
df.at[i, 'state'] = 'stop'
for j, jow in df_straddle.iterrows():
if jow.basic == row.basic_m0 and jow.strike == row.strike and jow.direction == 'duo' and jow.source == 'sdiffer':
df_straddle.at[j, 'profit'] = -1000
if jow.basic == row.basic_m1 and jow.strike == row.strike and jow.direction == 'kong' and jow.source == 'sdiffer':
df_straddle.at[j, 'profit'] = -1000
except Exception as e:
s = traceback.format_exc()
to_log(s)
df_straddle.to_csv(fn_straddle, index=False)
# release_file_lock(fn_straddle)
df.to_csv(fn, index=False)
# release_file_lock(fn)
for symbol in symbol_got_list:
self.got_dict[symbol] = False
