class Fut_YuePortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'yue'
assert len(symbol_list) == 2
self.symbol_a = symbol_list[0]
self.symbol_b = symbol_list[1]
self.dual_name = self.symbol_a + '_' + self.symbol_b
symbol_list.append(self.dual_name)
self.got_dict = {}
self.got_dict[self.symbol_a] = False
self.got_dict[self.symbol_b] = False
df = self.load_param()
if df is not None:
for i, row in df.iterrows():
if row.symbol_a in symbol_list and row.symbol_b in symbol_list:
pass
Portfolio.__init__(self, Fut_YueSignal, engine, symbol_list,
signal_param)
self.name_second = 'yue_' + self.dual_name
# print(symbol_list, self.dual_name)
#----------------------------------------------------------------------
def load_param(self):
fn = get_dss() + 'fut/engine/yue/portfolio_yue_param.csv'
df = None
if os.path.exists(fn):
df = pd.read_csv(fn)
return df
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min5': # 本策略为min5
return
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
# print(bar.vtSymbol, bar.time)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
if self.got_dict[self.symbol_a] == True and self.got_dict[
self.symbol_b] == True:
for signal in self.signalDict[self.dual_name]:
for s_a in self.signalDict[self.symbol_a]:
ask_price_a = float(s_a.bar.AskPrice) # 挂卖价
bid_price_a = float(s_a.bar.BidPrice) # 挂买价
for s_b in self.signalDict[self.symbol_b]:
ask_price_b = float(s_b.bar.AskPrice) # 挂卖价
bid_price_b = float(s_b.bar.BidPrice) # 挂买价
long_price = ask_price_a - bid_price_b
short_price = bid_price_a - ask_price_b
bar_dual = VtBarData()
bar_dual.vtSymbol = self.dual_name
bar_dual.high = short_price
bar_dual.low = long_price
bar_dual.date = bar.date
bar_dual.time = bar.time
bar_dual.datetime = bar.date + ' ' + bar.time
# 将bar推送给signal
signal.onBar(bar_dual, minx)
self.result.updateBar(bar_dual)
# print(bar_dual.vtSymbol, bar_dual.datetime )
self.got_dict[self.symbol_a] = False
self.got_dict[self.symbol_b] = False
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
#----------------------------------------------------------------------
def _bc_dual_signal(self, direction, offset, volume):
for signal in self.signalDict[self.symbol_a]:
signal_a = signal
for signal in self.signalDict[self.symbol_b]:
signal_b = signal
# 此处应使用挂买、挂卖价
if direction == DIRECTION_LONG and offset == OFFSET_OPEN:
signal_a.buy(float(signal_a.bar.AskPrice), volume)
signal_b.short(float(signal_b.bar.BidPrice), volume)
if direction == DIRECTION_SHORT and offset == OFFSET_OPEN:
signal_a.short(float(signal_a.bar.BidPrice), volume)
signal_b.buy(float(signal_b.bar.AskPrice), volume)
if direction == DIRECTION_LONG and offset == OFFSET_CLOSE:
signal_a.cover(float(signal_a.bar.AskPrice), volume)
signal_b.sell(float(signal_b.bar.BidPrice), volume)
if direction == DIRECTION_SHORT and offset == OFFSET_CLOSE:
signal_a.sell(float(signal_a.bar.BidPrice), volume)
signal_b.cover(float(signal_b.bar.AskPrice), volume)
class Fut_Skew_StrdPortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'skew_strd'
self.tm = '00:00:00'
self.got_dict = {}
for symbol in symbol_list:
self.got_dict[symbol] = False
# self.d_base_dict = {}
Portfolio.__init__(self, Fut_Skew_StrdSignal, engine, symbol_list,
signal_param)
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min1': # 本策略为min1
return
if self.tm != bar.time:
self.tm = bar.time
for symbol in self.vtSymbolList:
self.got_dict[symbol] = False
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
# print(bar.vtSymbol, bar.time)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
# print('here')
self.control_in_p(bar)
# print('here3')
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
#----------------------------------------------------------------------
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 = ['tm','basic_m0','basic_m1','strike_m0','strike_m1','fixed_size','profit','state','source','hold_m0','hold_m1','skew_low_open','skew_high_open','price_c_m0','price_p_m0','price_c_m1','price_p_m1','skew_max','dida_max','skew_min','dida_min','profit_m0','profit_m1','profit_o','date']
fn = get_dss(
) + 'fut/engine/skew_strd/portfolio_skew_strd_param.csv'
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'
df = pd.read_csv(fn)
df_straddle = pd.read_csv(fn_straddle)
symbol_got_list = []
for i, row in df.iterrows():
try:
r = []
if row.state == 'stop':
continue
if row.basic_m0[:2] == 'IO':
symbol_obj = 'IF' + row.basic_m0[2:]
else:
symbol_obj = row.basic_m0
exchangeID = str(get_contract(row.basic_m0).exchangeID)
if exchangeID in ['CFFEX', 'DCE']:
symbol_c_m0 = row.basic_m0 + '-C-' + str(row.strike_m0)
symbol_p_m0 = row.basic_m0 + '-P-' + str(row.strike_m0)
symbol_c_m1 = row.basic_m1 + '-C-' + str(row.strike_m1)
symbol_p_m1 = row.basic_m1 + '-P-' + str(row.strike_m1)
else:
symbol_c_m0 = row.basic_m0 + 'C' + str(row.strike_m0)
symbol_p_m0 = row.basic_m0 + 'P' + str(row.strike_m0)
symbol_c_m1 = row.basic_m1 + 'C' + str(row.strike_m1)
symbol_p_m1 = row.basic_m1 + 'P' + str(row.strike_m1)
if symbol_obj not in self.got_dict or 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_obj] == False or 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_obj)
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_obj = self.signalDict[symbol_obj][0]
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]
df.at[i, 'tm'] = bar.time
# 开仓
if row.hold_m0 == 0 and row.hold_m1 == 0:
iv_right_c = self.calc_iv(row.basic_m1, 'C',
s_obj.bar.close,
row.strike_m1,
s_c_m1.bar.close)
iv_right_p = self.calc_iv(row.basic_m1, 'P',
s_obj.bar.close,
row.strike_m1,
s_p_m1.bar.close)
iv_left_c = self.calc_iv(row.basic_m0, 'C',
s_obj.bar.close,
row.strike_m0,
s_c_m0.bar.close)
iv_left_p = self.calc_iv(row.basic_m0, 'P',
s_obj.bar.close,
row.strike_m0,
s_p_m0.bar.close)
skew = round(
100 * (iv_right_c + iv_right_p - iv_left_c -
iv_left_p) / (iv_left_c + iv_left_p), 2)
# print(skew)
if skew > row.skew_max:
df.at[i, 'skew_max'] = skew
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 skew < row.skew_min:
df.at[i, 'skew_min'] = skew
df.at[i, 'dida_min'] = 0
else:
df.at[i, 'dida_min'] = row.dida_min + 1
# 做空m0，做多m1
if df.at[
i,
'skew_min'] < row.skew_low_open and skew >= row.skew_low_open and df.at[
i, 'dida_min'] > 0:
r.append([
'00:00:00', row.basic_m0, row.strike_m0,
row.basic_m0, row.strike_m0,
row.fixed_size, row.fixed_size, 'kong', 0,
0, 1000, 'run', 'skew_strd', '', '', '',
'', '', bar.date
])
r.append([
'00:00:00', row.basic_m1, row.strike_m1,
row.basic_m1, row.strike_m1,
row.fixed_size, row.fixed_size, 'duo', 0,
0, 1000, 'run', 'skew_strd', '', '', '',
'', '', bar.date
])
df.at[i, 'hold_m0'] = -1
df.at[i, 'hold_m1'] = 1
if self.engine.type == 'backtest':
df.at[i, 'price_c_m0'] = s_c_m0.bar.close
df.at[i, 'price_p_m0'] = s_p_m0.bar.close
df.at[i, 'price_c_m1'] = s_c_m1.bar.close
df.at[i, 'price_p_m1'] = s_p_m1.bar.close
else:
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
# 做多m0，做空m1
if df.at[
i,
'skew_max'] > row.skew_high_open and skew <= row.skew_high_open and df.at[
i, 'dida_max'] > 0:
r.append([
'00:00:00', row.basic_m0, row.strike_m0,
row.basic_m0, row.strike_m0,
row.fixed_size, row.fixed_size, 'duo', 0,
0, 1000, 'run', 'skew_strd', '', '', '',
'', '', bar.date
])
r.append([
'00:00:00', row.basic_m1, row.strike_m1,
row.basic_m1, row.strike_m1,
row.fixed_size, row.fixed_size, 'kong', 0,
0, 1000, 'run', 'skew_strd', '', '', '',
'', '', bar.date
])
df.at[i, 'hold_m0'] = 1
df.at[i, 'hold_m1'] = -1
if self.engine.type == 'backtest':
df.at[i, 'price_c_m0'] = s_c_m0.bar.close
df.at[i, 'price_p_m0'] = s_p_m0.bar.close
df.at[i, 'price_c_m1'] = s_c_m1.bar.close
df.at[i, 'price_p_m1'] = s_p_m1.bar.close
else:
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)
# 获利平仓
elif row.hold_m0 == -1 and row.hold_m1 == 1:
if self.engine.type == 'backtest':
df.at[i, 'profit_m0'] = round(
(row.price_c_m0 + row.price_p_m0) -
(s_c_m0.bar.close + s_p_m0.bar.close), 2)
df.at[i, 'profit_m1'] = round(
(s_c_m1.bar.close + s_p_m1.bar.close) -
(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)
else:
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)
# print(df.at[i, 'profit_o'])
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_m0 and jow.direction == 'kong' and jow.source == 'skew_strd':
df_straddle.at[j, 'profit'] = -1000
if jow.basic == row.basic_m1 and jow.strike == row.strike_m1 and jow.direction == 'duo' and jow.source == 'skew_strd':
df_straddle.at[j, 'profit'] = -1000
# 获利平仓
elif row.hold_m0 == 1 and row.hold_m1 == -1:
if self.engine.type == 'backtest':
df.at[i, 'profit_m0'] = round(
(s_c_m0.bar.close + s_p_m0.bar.close) -
(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.close + s_p_m1.bar.close), 2)
df.at[i, 'profit_o'] = round(
df.at[i, 'profit_m0'] +
df.at[i, 'profit_m1'], 2)
else:
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)
# print(df.at[i, 'profit_o'])
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_m0 and jow.direction == 'duo' and jow.source == 'skew_strd':
df_straddle.at[j, 'profit'] = -1000
if jow.basic == row.basic_m1 and jow.strike == row.strike_m1 and jow.direction == 'kong' and jow.source == 'skew_strd':
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)
df.to_csv(fn, index=False)
for symbol in symbol_got_list:
self.got_dict[symbol] = False
#----------------------------------------------------------------------
def calc_iv(self, basic, flag, S0, K, C0):
r = 0.03
fn = get_dss() + 'fut/cfg/opt_mature.csv'
df2 = pd.read_csv(fn)
df2 = df2[df2.pz == df2.pz] # 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.now()
T = float((date_mature - td).days) / 365 # 剩余期限
skew = 0
if flag == 'C':
skew = bsm_call_imp_vol(S0, K, T, r, C0)
if flag == 'P':
skew = bsm_put_imp_vol(S0, K, T, r, C0)
return skew
#----------------------------------------------------------------------
def daily_open(self):
Portfolio.daily_open(self)
#----------------------------------------------------------------------
def daily_close(self):
Portfolio.daily_close(self)
class Fut_FollowPortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'follow'
self.symbol_o = ''
self.symbol_c = ''
self.symbol_p = ''
for symbol in symbol_list:
if symbol[:2] == 'IF':
self.symbol_o = symbol
break
self.got_dict = {}
self.strike_high = 0
self.strike_low = 0
self.price_o = 0
self.price_o_high = 0
self.price_o_low = 0
self.price_c = 0
self.price_p = 0
self.hold_o = 0
self.hold_c = 0
self.hold_p = 0
self.profit_o = 0
self.profit_c = 0
self.profit_p = 0
self.switch_state = 'off'
fn = get_dss() + 'fut/engine/follow/follow_switch.csv'
if os.path.exists(fn):
df = pd.read_csv(fn)
if len(df) > 0:
rec = df.iloc[-1, :]
if rec.state == 'on':
self.switch_state = 'on'
Portfolio.__init__(self, Fut_FollowSignal, engine, symbol_list,
signal_param)
#----------------------------------------------------------------------
def rec_profit(self, dt, tm, price_o, price_c, price_p, note):
r = [[
dt, tm, price_o, price_c, self.hold_c, self.price_c, self.profit_c,
price_p, self.hold_p, self.price_p, self.profit_p, note, 60,
self.profit_c + self.profit_p
]]
df = pd.DataFrame(r,
columns=[
'date', 'time', 'price_o', 'price_c', 'hold_c',
'cost_c', 'profit_c', 'price_p', 'hold_p',
'cost_p', 'profit_p', 'note', 'commission',
'profit'
])
pz = str(get_contract(self.symbol_c).pz)
fn = get_dss() + 'fut/engine/follow/portfolio_profit_' + pz + '.csv'
if os.path.exists(fn):
df.to_csv(fn, index=False, mode='a', header=False)
else:
df.to_csv(fn, index=False)
#----------------------------------------------------------------------
def get_open_signal(self):
return True
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min1': # 本策略为min1
return
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
# print(bar.vtSymbol, bar.time)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
if bar.time > '09:35:00': # 因第一根K线的价格为0
if self.switch_state == 'on' and self.get_open_signal() == True:
s_o = self.signalDict[self.symbol_o][0]
self.price_o = s_o.bar.close
self.price_o_high = 1.04 * self.price_o
self.price_o_low = 0.96 * self.price_o
strike_mid = int(round(self.price_o / 100, 0) * 100)
self.strike_high = strike_mid + 300
self.strike_low = strike_mid - 300
self.symbol_c = 'IO' + self.symbol_o[2:6] + '-C-' + str(
self.strike_high)
self.symbol_p = 'IO' + self.symbol_o[2:6] + '-P-' + str(
self.strike_low)
s_c = self.signalDict[self.symbol_c][0]
s_p = self.signalDict[self.symbol_p][0]
if self.engine.type == 'backtest':
s_c.short(s_c.bar.close, 1)
s_p.short(s_p.bar.close, 1)
else:
s_c.short(s_c.bar.BidPrice, 1) # 挂买价
s_p.short(s_p.bar.BidPrice, 1) # 挂买价
self.got_dict[self.symbol_o] = False
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
if self.engine.type == 'backtest':
self.price_c = s_c.bar.close
self.price_p = s_p.bar.close
else:
self.price_c = s_c.bar.BidPrice
self.price_p = s_p.bar.BidPrice
self.hold_c = -1
self.hold_p = -1
self.profit_o = self.price_c + self.price_p # 止盈止损点
self.switch_state = 'off' # 不再开仓
df2 = pd.DataFrame([{'state': 'off'}])
fn = get_dss() + 'fut/engine/follow/follow_switch.csv'
df2.to_csv(fn, index=False) # 回写文件
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '开仓')
if self.hold_c == -1 and self.hold_p == -1:
if self.got_dict[self.symbol_o] == True and self.got_dict[
self.symbol_c] == True and self.got_dict[
self.symbol_p] == True:
self.got_dict[self.symbol_o] = False
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
s_o = self.signalDict[self.symbol_o][0]
s_c = self.signalDict[self.symbol_c][0]
s_p = self.signalDict[self.symbol_p][0]
# 盈亏离场 或 无剩余价值离场
if self.profit_c + self.profit_p > 0.5 * self.profit_o or self.profit_c + self.profit_p < -0.3 * self.profit_o or abs(
self.hold_c * s_c.bar.close +
self.hold_p * s_p.bar.close) <= 3:
if self.engine.type == 'backtest':
s_c.cover(s_c.bar.close, 1)
s_p.cover(s_p.bar.close, 1)
else:
s_c.cover(s_c.bar.AskPrice, 1) # 挂卖价
s_p.cover(s_p.bar.AskPrice, 1) # 挂卖价
self.hold_c = 0
self.hold_p = 0
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '清仓')
# 已持仓
elif self.hold_c == -1 or self.hold_p == -1:
# 上涨2% 或 离行权价小于50点时
if s_o.bar.close > self.price_o_high or self.strike_high - s_o.bar.close < 50:
if self.engine.type == 'backtest':
s_c.cover(s_c.bar.close, 1)
s_p.cover(s_p.bar.close, 1)
else:
s_c.cover(s_c.bar.AskPrice, 1) # 挂卖价
s_p.cover(s_p.bar.AskPrice, 1) # 挂卖价
if self.engine.type == 'backtest':
self.price_c = self.price_c - s_c.bar.close
self.price_p = self.price_p - s_p.bar.close
else:
self.price_c = self.price_c - s_c.bar.AskPrice
self.price_p = self.price_p - s_p.bar.AskPrice
self.hold_c = 0
self.hold_p = 0
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '移仓')
self.price_o = s_o.bar.close
self.price_o_high = 1.04 * self.price_o
self.price_o_low = 0.96 * self.price_o
self.strike_high += 100
self.strike_low += 100
self.symbol_c = 'IO' + self.symbol_o[
2:6] + '-C-' + str(self.strike_high)
self.symbol_p = 'IO' + self.symbol_o[
2:6] + '-P-' + str(self.strike_low)
s_c = self.signalDict[self.symbol_c][0]
s_p = self.signalDict[self.symbol_p][0]
if self.engine.type == 'backtest':
s_c.short(s_c.bar.close, 1)
s_p.short(s_p.bar.close, 1)
else:
s_c.short(s_c.bar.BidPrice, 1) # 挂买价
s_p.short(s_p.bar.BidPrice, 1) # 挂买价
self.got_dict[self.symbol_o] = False
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
if self.engine.type == 'backtest':
self.price_c += s_c.bar.close
self.price_p += s_p.bar.close
else:
self.price_c += s_c.bar.BidPrice
self.price_p += s_p.bar.BidPrice
self.hold_c = -1
self.hold_p = -1
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '移仓')
# 下跌2% 或 离行权价小于50点时
if s_o.bar.close < self.price_o_low or s_o.bar.close - self.strike_low < 50:
if self.engine.type == 'backtest':
s_c.cover(s_c.bar.close, 1)
s_p.cover(s_p.bar.close, 1)
else:
s_c.cover(s_c.bar.AskPrice, 1) # 挂卖价
s_p.cover(s_p.bar.AskPrice, 1) # 挂卖价
if self.engine.type == 'backtest':
self.price_c = self.price_c - s_c.bar.close
self.price_p = self.price_p - s_p.bar.close
else:
self.price_c = self.price_c - s_c.bar.AskPrice
self.price_p = self.price_p - s_p.bar.AskPrice
self.hold_c = 0
self.hold_p = 0
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '移仓')
self.price_o = s_o.bar.close
self.price_o_high = 1.04 * self.price_o
self.price_o_low = 0.96 * self.price_o
self.strike_high -= 100
self.strike_low -= 100
self.symbol_c = 'IO' + self.symbol_o[
2:6] + '-C-' + str(self.strike_high)
self.symbol_p = 'IO' + self.symbol_o[
2:6] + '-P-' + str(self.strike_low)
s_c = self.signalDict[self.symbol_c][0]
s_p = self.signalDict[self.symbol_p][0]
if self.engine.type == 'backtest':
s_c.short(s_c.bar.close, 1)
s_p.short(s_p.bar.close, 1)
else:
s_c.short(s_c.bar.BidPrice, 1) # 挂买价
s_p.short(s_p.bar.BidPrice, 1) # 挂买价
self.got_dict[self.symbol_o] = False
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
if self.engine.type == 'backtest':
self.price_c += s_c.bar.close
self.price_p += s_p.bar.close
else:
self.price_c += s_c.bar.BidPrice
self.price_p += s_p.bar.BidPrice
self.hold_c = -1
self.hold_p = -1
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '移仓')
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
#----------------------------------------------------------------------
def daily_open(self):
Portfolio.daily_open(self)
fn = get_dss() + 'fut/engine/follow/portfolio_follow_param.csv'
if os.path.exists(fn):
df = pd.read_csv(fn)
if len(df) > 0:
rec = df.iloc[-1, :] # 取最近日期的记录
self.symbol_c = rec.symbol_c
self.symbol_p = rec.symbol_p
self.strike_high = rec.strike_high
self.strike_low = rec.strike_low
self.profit_o = rec.profit_o
self.price_o = rec.price_o
self.price_o_high = 1.04 * self.price_o
self.price_o_low = 0.96 * self.price_o
self.price_c = rec.price_c
self.price_p = rec.price_p
self.hold_c = rec.hold_c
self.hold_p = rec.hold_p
#----------------------------------------------------------------------
def daily_close(self):
Portfolio.daily_close(self)
r = [ [self.result.date, self.symbol_c, self.symbol_p, self.strike_high, self.strike_low, \
self.profit_o, self.price_o, self.price_c, self.price_p, self.hold_c, self.hold_p] ]
df = pd.DataFrame(r,
columns=[
'datetime', 'symbol_c', 'symbol_p',
'strike_high', 'strike_low', 'profit_o',
'price_o', 'price_c', 'price_p', 'hold_c',
'hold_p'
])
fn = get_dss() + 'fut/engine/follow/portfolio_follow_param.csv'
if os.path.exists(fn):
df.to_csv(fn, index=False, mode='a', header=False)
else:
df.to_csv(fn, index=False)
class Fut_FollowPortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'follow'
assert len(symbol_list) == 3
self.symbol_o = symbol_list[0]
self.symbol_c = symbol_list[1]
self.symbol_p = symbol_list[2]
if self.symbol_o[:2] == 'IF':
self.symbol_future = 'IO' + self.symbol_o[2:]
else:
self.symbol_future = self.symbol_o
self.dual_name = self.symbol_future
self.got_dict = {}
self.got_dict[self.symbol_o] = False
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
self.price_o = 0
self.price_o_high = 0
self.price_o_low = 0
self.price_c = 0
self.price_p = 0
self.hold_o = 0
self.hold_c = 0
self.hold_p = 0
self.profit_o = 0
self.profit_c = 0
self.profit_p = 0
self.flag_c, self.flag_p, self.strike_high, self.strike_low, self.fixed_size, self.switch_state, self.percent, self.gap = self.load_param(self.symbol_c, self.symbol_p)
Portfolio.__init__(self, Fut_FollowSignal, engine, symbol_list, signal_param)
self.name_second = 'follow_' + self.dual_name
#----------------------------------------------------------------------
def load_param(self, s_c, s_p):
fn = get_dss() + 'fut/engine/follow/portfolio_follow_param.csv'
df = pd.read_csv(fn)
df = df[(df.symbol_c == s_c) & (df.symbol_p == s_p)]
row = df.iloc[-1,:]
return row.flag_c, row.flag_p, int(row.strike_high), int(row.strike_low), int(row.fixed_size), row.switch_state, float(row.percent), int(row.gap)
#----------------------------------------------------------------------
def set_param(self, rec):
fn = get_dss() + 'fut/engine/follow/portfolio_follow_param.csv'
df = pd.read_csv(fn)
df = df[(df.symbol_c != rec[1]) & (df.symbol_p != rec[2])]
df.to_csv(fn, index=False)
df = pd.DataFrame([rec], columns=['symbol_o','symbol_c','symbol_p','flag_c','flag_p','strike_high','strike_low','fixed_size','switch_state','percent','gap'])
df.to_csv(fn, index=False, mode='a', header=False)
#----------------------------------------------------------------------
def rec_profit(self, dt, tm, price_o, price_c, price_p, note):
r = [[dt, tm, price_o, price_c, self.hold_c, self.price_c, self.profit_c, price_p, self.hold_p, self.price_p, self.profit_p, note, 60, self.profit_c + self.profit_p]]
df = pd.DataFrame(r, columns=['date','time','price_o','price_c','hold_c','cost_c','profit_c','price_p','hold_p','cost_p','profit_p','note','commission','profit'])
pz = str(get_contract(self.symbol_c).pz)
fn = get_dss() + 'fut/engine/follow/portfolio_' + self.name_second + '_profit.csv'
if os.path.exists(fn):
df.to_csv(fn, index=False, mode='a', header=False)
else:
df.to_csv(fn, index=False)
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min1': # 本策略为min1
return
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
# print(bar.vtSymbol, bar.time)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
if (bar.time > '09:35:00' and bar.time < '11:25:00' and bar.vtSymbol[:2] in ['IF','IO']) or \
(bar.time > '13:05:00' and bar.time < '14:55:00' and bar.vtSymbol[:2] in ['IF','IO']) or \
(bar.time > '09:05:00' and bar.time < '11:25:00' and bar.vtSymbol[:2] not in ['IF','IO']) or \
(bar.time > '13:35:00' and bar.time < '14:55:00' and bar.vtSymbol[:2] not in ['IF','IO']) or \
(bar.time > '21:05:00' and bar.time < '22:55:00' and bar.vtSymbol[:2] not in ['IF','IO']) : # 因第一根K线的价格为0
# 开仓
if self.switch_state == 'on' and self.hold_c == 0 and self.hold_p == 0:
if self.got_dict[self.symbol_o] == True and self.got_dict[self.symbol_c] == True and self.got_dict[self.symbol_p] == True:
self.got_dict[self.symbol_o] = False
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
s_o = self.signalDict[self.symbol_o][0]
s_c = self.signalDict[self.symbol_c][0]
s_p = self.signalDict[self.symbol_p][0]
self.price_o = s_o.bar.close
self.price_o_high = (1+self.percent) * self.price_o
self.price_o_low = (1-self.percent) * self.price_o
if self.engine.type == 'backtest':
s_c.short(s_c.bar.close, self.fixed_size)
s_p.short(s_p.bar.close, self.fixed_size)
else:
s_c.short(s_c.bar.BidPrice, self.fixed_size) # 挂买价
s_p.short(s_p.bar.BidPrice, self.fixed_size) # 挂买价
if self.engine.type == 'backtest':
self.price_c = s_c.bar.close
self.price_p = s_p.bar.close
else:
self.price_c = s_c.bar.BidPrice
self.price_p = s_p.bar.BidPrice
self.hold_c = -1
self.hold_p = -1
self.profit_o = self.price_c + self.price_p # 止盈止损点
self.switch_state = 'off' # 不再开仓
self.set_param([self.symbol_o,self.symbol_c,self.symbol_p,self.flag_c,self.flag_p,self.strike_high,self.strike_low,self.fixed_size,self.switch_state,self.percent,self.gap])
self.rec_profit(bar.date, bar.time, s_o.bar.close, s_c.bar.close, s_p.bar.close, '开仓')
if self.hold_c == -1 and self.hold_p == -1 :
if self.got_dict[self.symbol_o] == True and self.got_dict[self.symbol_c] == True and self.got_dict[self.symbol_p] == True:
s_o = self.signalDict[self.symbol_o][0]
s_c = self.signalDict[self.symbol_c][0]
s_p = self.signalDict[self.symbol_p][0]
# 盈亏离场 或 无剩余价值离场
if self.profit_c + self.profit_p > 0.5*self.profit_o or self.profit_c + self.profit_p < -0.3*self.profit_o or abs(s_c.bar.close + s_p.bar.close) <= 3:
if self.engine.type == 'backtest':
s_c.cover(s_c.bar.close, self.fixed_size)
s_p.cover(s_p.bar.close, self.fixed_size)
else:
s_c.cover(s_c.bar.AskPrice, self.fixed_size) # 挂卖价
s_p.cover(s_p.bar.AskPrice, self.fixed_size) # 挂卖价
self.hold_c = 0
self.hold_p = 0
self.rec_profit(bar.date, bar.time, s_o.bar.close, s_c.bar.close, s_p.bar.close, '清仓')
# 已持仓
elif self.hold_c == -1 or self.hold_p == -1:
# 上涨4% 或 离行权价小于50点时
if s_o.bar.close > self.price_o_high or self.strike_high - s_o.bar.close < self.gap:
if self.engine.type == 'backtest':
s_c.cover(s_c.bar.close, self.fixed_size)
s_p.cover(s_p.bar.close, self.fixed_size)
else:
s_c.cover(s_c.bar.AskPrice, self.fixed_size) # 挂卖价
s_p.cover(s_p.bar.AskPrice, self.fixed_size) # 挂卖价
if self.engine.type == 'backtest':
self.price_c = self.price_c - s_c.bar.close
self.price_p = self.price_p - s_p.bar.close
else:
self.price_c = self.price_c - s_c.bar.AskPrice
self.price_p = self.price_p - s_p.bar.AskPrice
self.hold_c = 0
self.hold_p = 0
self.rec_profit(bar.date, bar.time, s_o.bar.close, s_c.bar.close, s_p.bar.close, '移仓')
self.price_o = s_o.bar.close
self.price_o_high = (1+self.percent) * self.price_o
self.price_o_low = (1-self.percent) * self.price_o
self.strike_high += 2*self.gap
self.strike_low += 2*self.gap
self.symbol_c = self.symbol_future + self.flag_c + str(self.strike_high)
self.symbol_p = self.symbol_future + self.flag_p + str(self.strike_low)
self.set_param([self.symbol_o,self.symbol_c,self.symbol_p,self.flag_c,self.flag_p,self.strike_high,self.strike_low,self.fixed_size,self.switch_state,self.percent,self.gap])
self.switch_state = 'on'
self.vtSymbolList = [self.symbol_o,self.symbol_c,self.symbol_p]
for s in [self.symbol_c,self.symbol_p]:
self.posDict[s] = 0
signal1 = Fut_FollowSignal(self, s)
l = self.signalDict[s]
l.append(signal1)
# 下跌4% 或 离行权价小于50点时
elif s_o.bar.close < self.price_o_low or s_o.bar.close - self.strike_low < self.gap:
if self.engine.type == 'backtest':
s_c.cover(s_c.bar.close, self.fixed_size)
s_p.cover(s_p.bar.close, self.fixed_size)
else:
s_c.cover(s_c.bar.AskPrice, self.fixed_size) # 挂卖价
s_p.cover(s_p.bar.AskPrice, self.fixed_size) # 挂卖价
if self.engine.type == 'backtest':
self.price_c = self.price_c - s_c.bar.close
self.price_p = self.price_p - s_p.bar.close
else:
self.price_c = self.price_c - s_c.bar.AskPrice
self.price_p = self.price_p - s_p.bar.AskPrice
self.hold_c = 0
self.hold_p = 0
self.rec_profit(bar.date, bar.time, s_o.bar.close, s_c.bar.close, s_p.bar.close, '移仓')
self.price_o = s_o.bar.close
self.price_o_high = (1+self.percent) * self.price_o
self.price_o_low = (1-self.percent) * self.price_o
self.strike_high -= 2*self.gap
self.strike_low -= 2*self.gap
self.symbol_c = self.symbol_future + self.flag_c + str(self.strike_high)
self.symbol_p = self.symbol_future + self.flag_p + str(self.strike_low)
self.set_param([self.symbol_o,self.symbol_c,self.symbol_p,self.flag_c,self.flag_p,self.strike_high,self.strike_low,self.fixed_size,self.switch_state,self.percent,self.gap])
self.switch_state = 'on'
self.vtSymbolList = [self.symbol_o,self.symbol_c,self.symbol_p]
for s in [self.symbol_c, self.symbol_p]:
self.posDict[s] = 0
signal1 = Fut_FollowSignal(self, s)
l = self.signalDict[s]
l.append(signal1)
self.got_dict[self.symbol_o] = False
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
#----------------------------------------------------------------------
def daily_open(self):
Portfolio.daily_open(self)
fn = get_dss() + 'fut/engine/follow/portfolio_' + self.name_second + '_save.csv'
if os.path.exists(fn):
df = pd.read_csv(fn)
if len(df) > 0:
rec = df.iloc[-1,:] # 取最近日期的记录
self.profit_o = rec.profit_o
self.price_o = rec.price_o
self.price_o_high = (1+self.percent) * self.price_o
self.price_o_low = (1-self.percent) * self.price_o
self.price_c = rec.price_c
self.price_p = rec.price_p
self.hold_c = rec.hold_c
self.hold_p = rec.hold_p
#----------------------------------------------------------------------
def daily_close(self):
Portfolio.daily_close(self)
r = [ [self.result.date, self.profit_o, self.price_o, self.price_c, self.price_p, self.hold_c, self.hold_p] ]
df = pd.DataFrame(r, columns=['datetime', 'profit_o','price_o', 'price_c', 'price_p', 'hold_c', 'hold_p'])
fn = get_dss() + 'fut/engine/follow/portfolio_' + self.name_second + '_save.csv'
if os.path.exists(fn):
df.to_csv(fn, index=False, mode='a', header=False)
else:
df.to_csv(fn, index=False)
class Fut_Skew_BiliPortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'skew_bili'
self.tm = '00:00:00'
self.got_dict = {}
for symbol in symbol_list:
self.got_dict[symbol] = False
# self.d_base_dict = {}
Portfolio.__init__(self, Fut_Skew_BiliSignal, engine, symbol_list,
signal_param)
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min1': # 本策略为min1
return
if self.tm != bar.time:
self.tm = bar.time
for symbol in self.vtSymbolList:
self.got_dict[symbol] = False
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
# print(bar.vtSymbol, bar.time)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
# print('here')
self.control_in_p(bar)
# print('here3')
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
#----------------------------------------------------------------------
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
fn = get_dss(
) + 'fut/engine/skew_bili/portfolio_skew_bili_param.csv'
cols_ratio = [
'tm', 'symbol_b', 'symbol_s', 'num_b', 'num_s', 'gap',
'profit', 'hold_b', 'hold_s', 'state', 'source', 'price_b',
'price_s', 'gap_open', 'profit_b', 'profit_s', 'profit_o',
'date', 'delta', 'theta'
]
fn_ratio = get_dss() + 'fut/engine/ratio/portfolio_ratio_param.csv'
df = pd.read_csv(fn)
df_ratio = pd.read_csv(fn_ratio)
symbol_got_list = []
for i, row in df.iterrows():
try:
r = []
if row.state == 'stop':
continue
basic_b = get_contract(row.symbol_b).basic
basic_s = get_contract(row.symbol_s).basic
if basic_b[:2] == 'IO':
symbol_obj = 'IF' + basic_b[2:]
else:
symbol_obj = basic_b
if symbol_obj not in self.got_dict or row.symbol_b not in self.got_dict or row.symbol_s not in self.got_dict:
continue
if self.got_dict[symbol_obj] == False or self.got_dict[
row.symbol_b] == False or self.got_dict[
row.symbol_s] == False:
continue
else:
symbol_got_list.append(symbol_obj)
symbol_got_list.append(row.symbol_b)
symbol_got_list.append(row.symbol_s)
s_obj = self.signalDict[symbol_obj][0]
s_b = self.signalDict[row.symbol_b][0]
s_s = self.signalDict[row.symbol_s][0]
df.at[i, 'tm'] = bar.time
# 开仓
if row.hold_b == 0 and row.hold_s == 0:
opt_flag = get_contract(row.symbol_b).opt_flag
strike_b = get_contract(row.symbol_b).strike
strike_s = get_contract(row.symbol_s).strike
if opt_flag == 'C':
iv_b = self.calc_iv(basic_b, 'C',
s_obj.bar.close, strike_b,
s_b.bar.close)
iv_s = self.calc_iv(basic_s, 'C',
s_obj.bar.close, strike_s,
s_s.bar.close)
else:
iv_b = self.calc_iv(basic_b, 'P',
s_obj.bar.close, strike_b,
s_b.bar.close)
iv_s = self.calc_iv(basic_s, 'P',
s_obj.bar.close, strike_s,
s_s.bar.close)
skew = round(100 * (iv_s / iv_b - 1), 2)
print(skew)
if skew > row.skew_max:
df.at[i, 'skew_max'] = skew
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 skew < row.skew_min:
df.at[i, 'skew_min'] = skew
df.at[i, 'dida_min'] = 0
else:
df.at[i, 'dida_min'] = row.dida_min + 1
# 做多symbol_s，做空symbol_b
if df.at[
i,
'skew_min'] < row.skew_low_open and skew >= row.skew_low_open and df.at[
i, 'dida_min'] > 0:
r.append([
'00:00:00', row.symbol_s, row.symbol_b,
row.num_s, row.num_b, -1000, row.profit, 0,
0, 'run', 'skew_bili', 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, bar.date, 0.0, 0.0
])
df.at[i, 'hold_b'] = -row.num_b
df.at[i, 'hold_s'] = row.num_s
if self.engine.type == 'backtest':
df.at[i, 'price_b'] = s_b.bar.close
df.at[i, 'price_s'] = s_s.bar.close
else:
df.at[i, 'price_b'] = s_b.bar.BidPrice
df.at[i, 'price_s'] = s_s.bar.AskPrice
# 做多symbol_b，做空symbol_s
if df.at[
i,
'skew_max'] > row.skew_high_open and skew <= row.skew_high_open and df.at[
i, 'dida_max'] > 0:
r.append([
'00:00:00', row.symbol_b, row.symbol_s,
row.num_b, row.num_s, -1000, row.profit, 0,
0, 'run', 'skew_bili', 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, bar.date, 0.0, 0.0
])
df.at[i, 'hold_b'] = row.num_b
df.at[i, 'hold_s'] = -row.num_s
if self.engine.type == 'backtest':
df.at[i, 'price_b'] = s_b.bar.close
df.at[i, 'price_s'] = s_s.bar.close
else:
df.at[i, 'price_b'] = s_b.bar.AskPrice
df.at[i, 'price_s'] = s_s.bar.BidPrice
df2_ratio = pd.DataFrame(r, columns=cols_ratio)
df_ratio = pd.concat([df_ratio, df2_ratio],
sort=False)
# 获利平仓
elif row.hold_b <= -1 and row.hold_s >= 1:
if self.engine.type == 'backtest':
df.at[i, 'profit_b'] = round(
(s_b.bar.close - row.price_b) * row.hold_b,
2)
df.at[i, 'profit_s'] = round(
(s_s.bar.close - row.price_s) * row.hold_s,
2)
df.at[i, 'profit_o'] = round(
df.at[i, 'profit_b'] +
df.at[i, 'profit_s'], 2)
else:
df.at[i, 'profit_b'] = round(
(s_b.bar.AskPrice - row.price_b) *
row.hold_b, 2)
df.at[i, 'profit_s'] = round(
(s_s.bar.BidPrice - row.price_s) *
row.hold_s, 2)
df.at[i, 'profit_o'] = round(
df.at[i, 'profit_b'] +
df.at[i, 'profit_s'], 2)
# print(df.at[i, 'profit_o'])
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_ratio.iterrows():
if jow.symbol_b == row.symbol_s and jow.symbol_s == row.symbol_b and jow.num_b == row.num_s and jow.num_s == row.num_b and jow.source == 'skew_bili':
df_ratio.at[j, 'profit'] = -1000
# 获利平仓
elif row.hold_b >= 1 and row.hold_s <= -1:
if self.engine.type == 'backtest':
df.at[i, 'profit_b'] = round(
(s_b.bar.close - row.price_b) * row.hold_b,
2)
df.at[i, 'profit_s'] = round(
(s_s.bar.close - row.price_s) * row.hold_s,
2)
df.at[i, 'profit_o'] = round(
df.at[i, 'profit_b'] +
df.at[i, 'profit_s'], 2)
else:
df.at[i, 'profit_b'] = round(
(s_b.bar.BidPrice - row.price_b) *
row.hold_b, 2)
df.at[i, 'profit_s'] = round(
(s_s.bar.AskPrice - row.price_s) *
row.hold_s, 2)
df.at[i, 'profit_o'] = round(
df.at[i, 'profit_b'] +
df.at[i, 'profit_s'], 2)
# print(df.at[i, 'profit_o'])
if df.at[i, 'profit_o'] >= row.profit:
df.at[i, 'hold_b'] = 0
df.at[i, 'hold_s'] = 0
df.at[i, 'state'] = 'stop'
for j, jow in df_ratio.iterrows():
if jow.symbol_b == row.symbol_b and jow.symbol_s == row.symbol_s and jow.num_b == row.num_b and jow.num_s == row.num_s and jow.source == 'skew_bili':
df_ratio.at[j, 'profit'] = -1000
except Exception as e:
s = traceback.format_exc()
to_log(s)
df_ratio.to_csv(fn_ratio, index=False)
df.to_csv(fn, index=False)
for symbol in symbol_got_list:
self.got_dict[symbol] = False
#----------------------------------------------------------------------
def calc_iv(self, basic, flag, S0, K, C0):
r = 0.03
fn = get_dss() + 'fut/cfg/opt_mature.csv'
df2 = pd.read_csv(fn)
df2 = df2[df2.pz == df2.pz] # 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.now()
T = float((date_mature - td).days) / 365 # 剩余期限
skew = 0
if flag == 'C':
skew = bsm_call_imp_vol(S0, K, T, r, C0)
if flag == 'P':
skew = bsm_put_imp_vol(S0, K, T, r, C0)
return skew
#----------------------------------------------------------------------
def daily_open(self):
Portfolio.daily_open(self)
#----------------------------------------------------------------------
def daily_close(self):
Portfolio.daily_close(self)
class Fut_SwapPortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'swap'
self.symbol_o = ''
self.symbol_a = ''
for symbol in symbol_list:
if len(symbol) == 6:
self.symbol_o = symbol
break
assert self.symbol_o != ''
self.got_dict = {}
self.price_o = 0
self.price_a = 0
self.hold_o = 0
self.hold_a = 0
self.profit_o = 0
self.profit_a = 0
self.can_duo = False
self.can_kong = False
self.switch_state = 'on'
pz = str(get_contract(self.symbol_c).pz)
fn = get_dss() + 'fut/engine/swap/swap_switch_' + pz + '.csv'
if os.path.exists(fn):
df = pd.read_csv(fn)
if len(df) > 0:
rec = df.iloc[-1, :]
if rec.state == 'off':
self.switch_state = 'off'
Portfolio.__init__(self, Fut_SwapSignal, engine, symbol_list,
signal_param)
#----------------------------------------------------------------------
def rec_profit(self, dt, tm, price_o, price_c, price_p, note):
r = [[
dt, tm, price_o, price_c, self.hold_c, self.price_c, self.profit_c,
price_p, self.hold_p, self.price_p, self.profit_p, note, 60,
self.profit_c + self.profit_p
]]
df = pd.DataFrame(r,
columns=[
'date', 'time', 'price_o', 'price_c', 'hold_c',
'cost_c', 'profit_c', 'price_p', 'hold_p',
'cost_p', 'profit_p', 'note', 'commission',
'profit'
])
pz = str(get_contract(self.symbol_c).pz)
fn = get_dss() + 'fut/engine/swap/portfolio_profit_' + pz + '.csv'
if os.path.exists(fn):
df.to_csv(fn, index=False, mode='a', header=False)
else:
df.to_csv(fn, index=False)
#----------------------------------------------------------------------
def got_all_bar(self):
for symbol in self.vtSymbolList:
if symbol not in self.got_dict:
return False
if self.got_dict[symbol] == False:
return False
for symbol in self.vtSymbolList:
self.got_dict[symbol] = False
return True
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 策略未启用
if self.switch_state == 'off':
return
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min30': # 本策略为min30
return
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
if bar.time > '09:35:00' and self.got_all_bar() == True:
s_o = self.signalDict[self.symbol_o][0]
# 做多
if self.can_duo == True:
if self.hold_a == -1:
s_a = self.signalDict[self.symbol_a][0]
s_a.cover(s_a.bar.close, 1)
# s_a.cover(s_a.bar.AskPrice, 1) # 挂卖价
self.hold_a = 0
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '平仓')
strike = int(round((self.price_o - 150) / 100, 0) * 100)
self.symbol_a = 'IO' + self.symbol_o[2:6] + '-P-' + str(strike)
s_a = self.signalDict[self.symbol_a][0]
s_a.short(s_a.bar.close, 1)
# s_a.short(s_a.bar.BidPrice, 1) # 挂买价
self.price_o = s_o.bar.close
self.price_a = s_a.bar.close
# self.price_a = s_a.bar.BidPrice
self.hold_a = -1
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '做多开仓')
self.can_duo = False
# 做空
elif self.can_kong == True:
if self.hold_a == -1:
s_a = self.signalDict[self.symbol_a][0]
s_a.cover(s_a.bar.close, 1)
# s_a.cover(s_a.bar.AskPrice, 1) # 挂卖价
self.hold_a = 0
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '平仓')
strike = int(round((self.price_o + 150) / 100, 0) * 100)
self.symbol_a = 'IO' + self.symbol_o[2:6] + '-C-' + str(strike)
s_a = self.signalDict[self.symbol_a][0]
s_a.short(s_a.bar.close, 1)
# s_a.short(s_a.bar.BidPrice, 1) # 挂买价
self.price_o = s_o.bar.close
self.price_a = s_a.bar.close
# self.price_a = s_a.bar.BidPrice
self.hold_a = -1
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '做空开仓')
self.can_kong = False
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
class Fut_AvengerPortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'avenger'
assert len(symbol_list) == 3
self.symbol_o = symbol_list[0]
self.symbol_c = symbol_list[1]
self.symbol_p = symbol_list[2]
self.got_dict = {}
self.got_dict[self.symbol_o] = False
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
self.price_o = 0
self.price_o_high = 0
self.price_o_low = 0
self.price_c = 0
self.price_p = 0
self.hold_o = 0
self.hold_c = 0
self.hold_p = 0
self.profit_o = 0
self.profit_c = 0
self.profit_p = 0
self.switch_state = 'off'
pz = str(get_contract(self.symbol_c).pz)
fn = get_dss() + 'fut/engine/avenger/avenger_switch_' + pz + '.csv'
if os.path.exists(fn):
df = pd.read_csv(fn)
if len(df) > 0:
rec = df.iloc[-1, :]
if rec.state == 'on':
self.switch_state = 'on'
rec.state = 'off'
df2 = pd.DataFrame([rec])
df2.to_csv(fn, index=False) # 回写文件
Portfolio.__init__(self, Fut_AvengerSignal, engine, symbol_list,
signal_param)
#----------------------------------------------------------------------
def rec_profit(self, dt, tm, price_o, price_c, price_p, note):
r = [[
dt, tm, price_o, price_c, self.hold_c, self.price_c, self.profit_c,
price_p, self.hold_p, self.price_p, self.profit_p, note, 60,
self.profit_c + self.profit_p
]]
df = pd.DataFrame(r,
columns=[
'date', 'time', 'price_o', 'price_c', 'hold_c',
'cost_c', 'profit_c', 'price_p', 'hold_p',
'cost_p', 'profit_p', 'note', 'commission',
'profit'
])
pz = str(get_contract(self.symbol_c).pz)
fn = get_dss() + 'fut/engine/avenger/portfolio_profit_' + pz + '.csv'
if os.path.exists(fn):
df.to_csv(fn, index=False, mode='a', header=False)
else:
df.to_csv(fn, index=False)
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min1': # 本策略为min1
return
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
# print(bar.vtSymbol, bar.time)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
if bar.time > '09:35:00' and self.got_dict[
self.symbol_o] == True and self.got_dict[
self.symbol_c] == True and self.got_dict[
self.symbol_p] == True:
s_o = self.signalDict[self.symbol_o][0]
s_c = self.signalDict[self.symbol_c][0]
s_p = self.signalDict[self.symbol_p][0]
# 开仓
if self.switch_state == 'on':
s_c.short(s_c.bar.BidPrice, 1) # 挂买价
s_p.short(s_p.bar.BidPrice, 1) # 挂买价
self.price_o = s_o.bar.close
self.price_o_high = 1.01 * self.price_o
self.price_o_low = 0.99 * self.price_o
self.price_c = s_c.bar.BidPrice
self.price_p = s_p.bar.BidPrice
self.hold_c = -1
self.hold_p = -1
self.profit_o = self.price_c + self.price_p # 止盈止损点
self.switch_state = 'off' # 不再开仓
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '开仓')
# 已持仓
elif self.hold_c != 0 or self.hold_p != 0:
# 盈亏离场 或 无剩余价值离场
if abs(self.profit_c +
self.profit_p) > 0.5 * self.profit_o or abs(
self.hold_c * s_c.bar.close +
self.hold_p * s_p.bar.close) <= 3:
if self.hold_c == -1 and self.hold_p == -1:
s_c.cover(s_c.bar.AskPrice, 1) # 挂卖价
s_p.cover(s_p.bar.AskPrice, 1) # 挂卖价
self.hold_c = 0
self.hold_p = 0
if self.hold_c == 0 and self.hold_p == -2:
s_p.cover(s_p.bar.AskPrice, 2) # 挂卖价
self.hold_p = 0
if self.hold_c == -2 and self.hold_p == 0:
s_c.cover(s_c.bar.AskPrice, 2) # 挂卖价
self.hold_c = 0
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '清仓')
# 复仇
if self.hold_c == -1 and self.hold_p == -1:
# 上涨1%
if s_o.bar.close > self.price_o_high:
s_c.cover(s_c.bar.AskPrice, 1) # 挂卖价
s_p.short(s_p.bar.BidPrice, 1) # 挂买价
self.price_c = self.price_c - s_c.bar.AskPrice
self.price_p = (s_p.bar.BidPrice + self.price_p) / 2
self.hold_c = 0
self.hold_p = -2
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '上涨复仇')
# 下跌1%
if s_o.bar.close < self.price_o_low:
s_p.cover(s_p.bar.AskPrice, 1) # 挂卖价
s_c.short(s_c.bar.BidPrice, 1) # 挂买价
self.price_p = self.price_p - s_p.bar.AskPrice
self.price_c = (s_c.bar.BidPrice + self.price_c) / 2
self.hold_p = 0
self.hold_c = -2
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '下跌复仇')
# 复仇失败，上涨后又回原点
if self.hold_c == 0 and self.hold_p == -2 and s_o.bar.close < self.price_o:
s_c.short(s_c.bar.BidPrice, 1) # 挂买价
s_p.cover(s_p.bar.AskPrice, 1) # 挂卖价
self.price_c = s_c.bar.BidPrice + self.price_c
self.price_p = 2 * self.price_p - s_p.bar.AskPrice
self.hold_p = -1
self.hold_c = -1
self.profit_c = self.hold_c * (s_c.bar.close -
self.price_c)
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '复仇失败')
# 复仇失败，下跌后又回原点
if self.hold_c == -2 and self.hold_p == 0 and s_o.bar.close > self.price_o:
s_p.short(s_p.bar.BidPrice, 1) # 挂买价
s_c.cover(s_c.bar.AskPrice, 1) # 挂卖价
self.price_p = s_p.bar.BidPrice + self.price_p
self.price_c = 2 * self.price_c - s_c.bar.AskPrice
self.hold_p = -1
self.hold_c = -1
self.profit_p = self.hold_p * (s_p.bar.close -
self.price_p)
self.rec_profit(bar.date, bar.time, s_o.bar.close,
s_c.bar.close, s_p.bar.close, '复仇失败')
self.got_dict[self.symbol_o] = False
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
class Fut_SdifferPortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'sdiffer'
self.tm = '00:00:00'
self.got_dict = {}
for symbol in symbol_list:
self.got_dict[symbol] = False
self.be_run = 'stop'
self.d_low_open = -100.0
self.d_high_open = 100.0
self.d_low_mail = -100.0
self.d_high_mail = 100.0
self.mailed_low = False
self.mailed_high = False
self.load_switch()
self.stop = False
self.basic_m0 = None
self.basic_m1 = None
self.cacl_vars()
self.symbol_obj = None
self.d_base_dict = {}
Portfolio.__init__(self, Fut_SdifferSignal, engine, symbol_list,
signal_param)
#----------------------------------------------------------------------
def load_switch(self):
pass
fn = get_dss() + 'fut/engine/sdiffer/portfolio_sdiffer_switch.csv'
if os.path.exists(fn):
df = pd.read_csv(fn)
rec = df.iloc[0]
self.be_run = rec.be_run
self.d_low_open = rec.d_low_open
self.d_high_open = rec.d_high_open
self.d_low_mail = rec.d_low_mail
self.d_high_mail = rec.d_high_mail
# print(self.be_run, self.d_low_open, self.d_high_open)
#----------------------------------------------------------------------
def cacl_vars(self):
now = datetime.now()
next_day = now + timedelta(days=10)
next_day = next_day.strftime('%Y-%m-%d')
fn = get_dss() + 'fut/cfg/opt_mature.csv'
df_opt = pd.read_csv(fn)
df = df_opt[(df_opt.pz == 'IO') & (df_opt.flag == 'm0')]
self.basic_m0 = df.iat[0, 1]
mature = df.iat[0, 2]
df = df_opt[(df_opt.pz == 'IO') & (df_opt.flag == 'm1')]
self.basic_m1 = df.iat[0, 1]
if next_day >= mature:
self.stop = True
# fn = get_dss() + 'opt/straddle_differ.csv'
# df = pd.read_csv(fn)
# df = df[(df.basic_m0 == self.basic_m0) & (df.basic_m1 == self.basic_m1) & (df.stat == 'y')]
# if len(df) >= 480:
# df = df.iloc[-480:, :]
# self.per_10 = df.differ.quantile(0.01)
# self.per_50 = df.differ.quantile(0.5)
# self.per_90 = df.differ.quantile(0.99)
# else:
# self.per_10 = -100
# self.per_50 = 0
# self.per_90 = 100
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min1': # 本策略为min1
return
if self.tm != bar.time:
self.tm = bar.time
for symbol in self.vtSymbolList:
self.got_dict[symbol] = False
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
# print(bar.vtSymbol, bar.time)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
# print('here')
self.control_in_p(bar)
# print('here3')
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
#----------------------------------------------------------------------
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
#----------------------------------------------------------------------
def daily_open(self):
Portfolio.daily_open(self)
fn = get_dss() + 'opt/sdiffer_d_base.csv'
df = pd.read_csv(fn)
date_list = sorted(list(set(df.date)))
# print(date_list)
date = date_list[-1]
df = df[df.date == date]
for i, row in df.iterrows():
self.d_base_dict[row.basic + '_' + str(row.strike)] = row.d_base
#----------------------------------------------------------------------
def daily_close(self):
Portfolio.daily_close(self)
fn = get_dss() + 'fut/engine/sdiffer/portfolio_sdiffer_param.csv'
df = pd.read_csv(fn)
for i, row in df.iterrows():
if row.date == self.result.date[:
10] and row.source == 'sdiffer' and row.hold_m0 == 0:
df.at[i, 'state'] = 'stop'
df = df[(df.state == 'run') | (df.date == self.result.date[:10])]
df.to_csv(fn, index=False)
class Fut_IcPortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'ic'
assert len(symbol_list) == 2
self.symbol_g = symbol_list[0]
self.symbol_d = symbol_list[1]
self.dual_name = self.symbol_g + '_' + self.symbol_d
symbol_list.append(self.dual_name)
self.direction_g = 'direction_g'
self.num_g = 0
self.direction_d = 'direction_d'
self.num_d = 0
self.got_dict = {}
self.got_dict[self.symbol_g] = False
self.got_dict[self.symbol_d] = False
df = self.load_param()
if df is not None:
for i, row in df.iterrows():
if row.symbol_g in symbol_list and row.symbol_d in symbol_list:
self.direction_g = row.symbol_g
self.num_g = row.direction_g
self.direction_d = row.num_g
self.num_d = row.num_d
Portfolio.__init__(self, Fut_IcSignal, engine, symbol_list, signal_param)
self.name_second = 'ic_' + self.dual_name
# print(symbol_list, self.dual_name)
#----------------------------------------------------------------------
def load_param(self):
fn = get_dss() + 'fut/engine/ic/portfolio_ic_param.csv'
df = None
if os.path.exists(fn):
df = pd.read_csv(fn)
return df
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min15': # 本策略为min15
return
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
# print(bar.vtSymbol, bar.time)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
if self.got_dict[self.symbol_g] == True and self.got_dict[self.symbol_d] == True:
for signal in self.signalDict[self.dual_name]:
for s_g in self.signalDict[self.symbol_g]:
price_g = s_g.bar.close
for s_d in self.signalDict[self.symbol_d]:
price_d = s_d.bar.close
price_gap = price_g - price_d
bar_dual = VtBarData()
bar_dual.vtSymbol = self.dual_name
bar_dual.open = price_gap
bar_dual.high = price_gap
bar_dual.low = price_gap
bar_dual.close = price_gap
bar_dual.date = bar.date
bar_dual.time = bar.time
bar_dual.datetime = bar.date + ' ' + bar.time
# 将bar推送给signal
signal.onBar(bar_dual, minx)
self.result.updateBar(bar_dual)
# print(bar_dual.vtSymbol, bar_dual.datetime )
self.got_dict[self.symbol_g] = False
self.got_dict[self.symbol_d] = False
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
#----------------------------------------------------------------------
def _bc_dual_signal(self, direction, offset, volume_g, volume_d):
for signal in self.signalDict[self.symbol_g]:
signal_g = signal
for signal in self.signalDict[self.symbol_d]:
signal_d = signal
if direction == DIRECTION_LONG and offset == OFFSET_OPEN:
signal_g.buy(signal_g.bar.close, volume_g)
signal_d.short(signal_d.bar.close, volume_d)
if direction == DIRECTION_SHORT and offset == OFFSET_OPEN:
signal_g.short(signal_g.bar.close, volume_g)
signal_d.buy(signal_d.bar.close, volume_d)
if direction == DIRECTION_LONG and offset == OFFSET_CLOSE:
signal_g.cover(signal_g.bar.close, volume_g)
signal_d.sell(signal_d.bar.close, volume_d)
if direction == DIRECTION_SHORT and offset == OFFSET_CLOSE:
signal_g.sell(signal_g.bar.close, volume_g)
signal_d.cover(signal_d.bar.close, volume_d)
class Fut_RatioPortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'ratio'
self.tm = '00:00:00'
self.got_dict = {}
for symbol in symbol_list:
self.got_dict[symbol] = False
Portfolio.__init__(self, Fut_RatioSignal, engine, symbol_list,
signal_param)
# self.promote = True
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min1': # 本策略为min1
return
# 动态加载新维护的symbol
config = open(get_dss() + 'fut/cfg/config.json')
setting = json.load(config)
symbols = setting['symbols_ratio']
symbols_list = symbols.split(',')
for vtSymbol in symbols_list:
if vtSymbol not in self.vtSymbolList:
self.vtSymbolList.append(vtSymbol)
self.posDict[vtSymbol] = 0
self.got_dict[vtSymbol] = False
signal1 = Fut_RatioSignal(self, vtSymbol)
l = self.signalDict[vtSymbol]
l.append(signal1)
if self.tm != bar.time:
self.tm = bar.time
for symbol in self.vtSymbolList:
self.got_dict[symbol] = False
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
# print(bar.vtSymbol, bar.time)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
self.control_in_p(bar)
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
#----------------------------------------------------------------------
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/ratio/portfolio_ratio_param.csv'
df = pd.read_csv(fn) # 加载最新参数
for i, row in df.iterrows():
try:
if row.state == 'stop':
continue
if row.symbol_b not in self.got_dict or row.symbol_s not in self.got_dict:
continue
if self.got_dict[row.symbol_b] == False or self.got_dict[
row.symbol_s] == False:
continue
else:
df.at[i, 'tm'] = bar.time
symbol_got_list.append(row.symbol_b)
symbol_got_list.append(row.symbol_s)
s_b = self.signalDict[row.symbol_b][0]
s_s = self.signalDict[row.symbol_s][0]
# 开仓
if row.hold_b == 0 and row.hold_s == 0:
if self.engine.type == 'backtest':
if row.num_s * s_s.bar.close - row.num_b * s_b.bar.close >= row.gap:
s_b.buy(s_b.bar.close, row.num_b)
s_s.short(s_s.bar.close, row.num_s)
df.at[i, 'price_b'] = s_b.bar.close
df.at[i, 'price_s'] = s_s.bar.close
df.at[i, 'hold_b'] = row.num_b
df.at[i, 'hold_s'] = row.num_s
else:
gap_open = row.num_s * s_s.bar.BidPrice - row.num_b * s_b.bar.AskPrice
df.at[i, 'gap_open'] = gap_open
df.at[i,
'price_b'] = round(s_b.bar.AskPrice, 2)
df.at[i,
'price_s'] = round(s_s.bar.BidPrice, 2)
if gap_open >= row.gap:
s_b.buy(s_b.bar.AskPrice, row.num_b) # 挂卖价
s_s.short(s_s.bar.BidPrice,
row.num_s) # 挂买价
df.at[i, 'hold_b'] = row.num_b
df.at[i, 'hold_s'] = row.num_s
# 获利平仓
if row.hold_b > 0 and row.hold_s > 0:
if self.engine.type == 'backtest':
df.at[i, 'profit_b'] = round(
(s_b.bar.close - row.price_b) * row.hold_b,
2)
df.at[i, 'profit_s'] = round(
-(s_s.bar.close - row.price_s) *
row.hold_s, 2)
df.at[i, 'profit_o'] = round(
df.at[i, 'profit_b'] +
df.at[i, 'profit_s'], 2)
if df.at[i, 'profit_o'] >= row.profit:
s_b.sell(s_b.bar.close, row.num_b)
s_s.cover(s_s.bar.close, row.num_s)
df.at[i, 'hold_b'] = 0
df.at[i, 'hold_s'] = 0
df.at[i, 'state'] = 'stop'
else:
df.at[i, 'profit_b'] = round(
(s_b.bar.BidPrice - row.price_b) *
row.hold_b, 2)
df.at[i, 'profit_s'] = round(
-(s_s.bar.AskPrice - row.price_s) *
row.hold_s, 2)
df.at[i, 'profit_o'] = round(
df.at[i, 'profit_b'] +
df.at[i, 'profit_s'], 2)
if df.at[i, 'profit_o'] >= row.profit:
s_b.sell(s_b.bar.BidPrice,
row.num_b) # 挂买价
s_s.cover(s_s.bar.AskPrice,
row.num_s) # 挂卖价
df.at[i, 'hold_b'] = 0
df.at[i, 'hold_s'] = 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
for symbol in symbol_got_list:
self.got_dict[symbol] = False
#----------------------------------------------------------------------
def daily_open(self):
Portfolio.daily_open(self)
#----------------------------------------------------------------------
def daily_close(self):
Portfolio.daily_close(self)
fn = get_dss() + 'fut/engine/ratio/portfolio_ratio_param.csv'
df = pd.read_csv(fn)
for i, row in df.iterrows():
if row.date == self.result.date[:
10] and row.hold_b == 0 and row.hold_s == 0:
df.at[i, 'state'] = 'stop'
df = df[(df.state == 'run') |
(df.date >= get_trade_preday(self.result.date[:10]))]
df.to_csv(fn, index=False)
class Fut_StraddlePortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'straddle'
self.tm = '00:00:00'
self.got_dict = {}
for symbol in symbol_list:
self.got_dict[symbol] = False
Portfolio.__init__(self, Fut_StraddleSignal, engine, symbol_list,
signal_param)
self.promote = True
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min1': # 本策略为min1
return
# 动态加载新维护的symbol
config = open(get_dss() + 'fut/cfg/config.json')
setting = json.load(config)
symbols = setting['symbols_straddle']
symbols_list = symbols.split(',')
for vtSymbol in symbols_list:
if vtSymbol not in self.vtSymbolList:
self.vtSymbolList.append(vtSymbol)
self.posDict[vtSymbol] = 0
self.got_dict[vtSymbol] = False
signal1 = Fut_StraddleSignal(self, vtSymbol)
l = self.signalDict[vtSymbol]
l.append(signal1)
if self.tm != bar.time:
self.tm = bar.time
for symbol in self.vtSymbolList:
self.got_dict[symbol] = False
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
# print(bar.vtSymbol, bar.time)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
self.control_in_p(bar)
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
#----------------------------------------------------------------------
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 daily_open(self):
Portfolio.daily_open(self)
#----------------------------------------------------------------------
def daily_close(self):
Portfolio.daily_close(self)
fn = get_dss() + 'fut/engine/straddle/portfolio_straddle_param.csv'
df = pd.read_csv(fn)
for i, row in df.iterrows():
if row.date == self.result.date[:
10] and row.hold_c == 0 and row.hold_p == 0:
df.at[i, 'state'] = 'stop'
df = df[(df.state == 'run') | (df.date == self.result.date[:10])]
df.to_csv(fn, index=False)
class Fut_RatioPortfolio(Portfolio):
#----------------------------------------------------------------------
def __init__(self, engine, symbol_list, signal_param={}):
self.name = 'ratio'
assert len(symbol_list) == 2
self.symbol_c = symbol_list[0]
self.symbol_p = symbol_list[1]
self.dual_name = self.symbol_c + '_' + self.symbol_p
self.got_dict = {}
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
self.price_c = 0
self.price_p = 0
self.hold_c = 0
self.hold_p = 0
self.profit_c = 0
self.profit_p = 0
self.fixed_size = 1
self.gap = 100
self.profit = 100
self.load_param(self.symbol_c, self.symbol_p)
Portfolio.__init__(self, Fut_RatioSignal, engine, symbol_list,
signal_param)
self.name_second = 'ratio_' + self.dual_name
#----------------------------------------------------------------------
def load_param(self, s_c, s_p):
fn = get_dss() + 'fut/engine/ratio/portfolio_ratio_param.csv'
df = pd.read_csv(fn)
df = df[(df.symbol_c == s_c) & (df.symbol_p == s_p)]
if len(df) > 0:
row = df.iloc[-1, :]
self.fixed_size = int(row.fixed_size)
self.gap = int(row.gap)
self.profit = int(row.profit)
#----------------------------------------------------------------------
def onBar(self, bar, minx='min1'):
"""引擎新推送过来bar，传递给每个signal"""
# 不处理不相关的品种
if bar.vtSymbol not in self.vtSymbolList:
return
if minx != 'min1': # 本策略为min1
return
if self.result.date != bar.date + ' ' + bar.time:
previousResult = self.result
self.result = DailyResult(bar.date + ' ' + bar.time)
self.resultList.append(self.result)
if previousResult:
self.result.updateClose(previousResult.closeDict)
# 将bar推送给signal
for signal in self.signalDict[bar.vtSymbol]:
signal.onBar(bar, minx)
# print(bar.vtSymbol, bar.time)
"""
在此实现P层的业务控制逻辑
为每一个品种来检查是否触发下单条件
# 开始处理组合关心的bar , 尤其是品种对价差的加工和处理
"""
if (bar.time > '09:35:00' and bar.time < '11:25:00' and bar.vtSymbol[:2] in ['IF','IO']) or \
(bar.time > '13:05:00' and bar.time < '14:55:00' and bar.vtSymbol[:2] in ['IF','IO']) or \
(bar.time > '09:05:00' and bar.time < '11:25:00' and bar.vtSymbol[:2] not in ['IF','IO']) or \
(bar.time > '13:35:00' and bar.time < '14:55:00' and bar.vtSymbol[:2] not in ['IF','IO']) or \
(bar.time > '21:05:00' and bar.time < '22:55:00' and bar.vtSymbol[:2] not in ['IF','IO']) : # 因第一根K线的价格为0
# 开仓
if self.hold_c == 0 and self.hold_p == 0:
self.load_param(self.symbol_c, self.symbol_p) # 加载最新参数
if self.got_dict[self.symbol_c] == True and self.got_dict[
self.symbol_p] == True:
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
s_c = self.signalDict[self.symbol_c][0]
s_p = self.signalDict[self.symbol_p][0]
if 2 * s_p.bar.close - s_c.bar.close >= self.gap:
if self.engine.type == 'backtest':
s_c.buy(s_c.bar.close, self.fixed_size)
s_p.short(s_p.bar.close, 2 * self.fixed_size)
self.price_c = s_c.bar.close
self.price_p = s_p.bar.close
else:
s_c.buy(s_c.bar.AskPrice, self.fixed_size) # 挂卖价
s_p.short(s_p.bar.BidPrice,
2 * self.fixed_size) # 挂买价
self.price_c = s_c.bar.AskPrice
self.price_p = s_p.bar.BidPrice
self.hold_c = 1
self.hold_p = -2
# 获利平仓
if self.hold_c == 1 and self.hold_p == -2:
self.load_param(self.symbol_c, self.symbol_p) # 加载最新参数
if self.got_dict[self.symbol_c] == True and self.got_dict[
self.symbol_p] == True:
self.got_dict[self.symbol_c] = False
self.got_dict[self.symbol_p] = False
s_c = self.signalDict[self.symbol_c][0]
s_p = self.signalDict[self.symbol_p][0]
if self.profit_c + self.profit_p >= self.profit:
if self.engine.type == 'backtest':
s_c.sell(s_c.bar.close, self.fixed_size)
s_p.cover(s_p.bar.close, 2 * self.fixed_size)
else:
s_c.sell(s_c.bar.BidPrice, self.fixed_size) # 挂买价
s_p.cover(s_p.bar.AskPrice,
2 * self.fixed_size) # 挂卖价
self.hold_c = 0
self.hold_p = 0
self.result.updateBar(bar)
self.result.updatePos(self.posDict)
#----------------------------------------------------------------------
def daily_open(self):
Portfolio.daily_open(self)
fn = get_dss(
) + 'fut/engine/ratio/portfolio_' + self.name_second + '_save.csv'
if os.path.exists(fn):
df = pd.read_csv(fn)
df = df[(df.symbol_c == self.symbol_c)
& (df.symbol_p == self.symbol_p)]
if len(df) > 0:
rec = df.iloc[-1, :] # 取最近日期的记录
self.price_c = rec.price_c
self.price_p = rec.price_p
self.hold_c = rec.hold_c
self.hold_p = rec.hold_p
#----------------------------------------------------------------------
def daily_close(self):
Portfolio.daily_close(self)
r = [[
self.result.date, self.symbol_c, self.symbol_p, self.price_c,
self.price_p, self.hold_c, self.hold_p
]]
df = pd.DataFrame(r,
columns=[
'datetime', 'symbol_c', 'symbol_p', 'price_c',
'price_p', 'hold_c', 'hold_p'
])
fn = get_dss(
) + 'fut/engine/ratio/portfolio_' + self.name_second + '_save.csv'
if os.path.exists(fn):
df.to_csv(fn, index=False, mode='a', header=False)
else:
df.to_csv(fn, index=False)