python 期货程序化_期货程序化交易

在这里给大家一个Python期货模型参考，作为入门参考应该还可以，这个我曾经写的第一个完整的python期货交易模型源码，历史数据来源于自己的数据库，交易接口也是基于CTP的自己的交易接口。

相当一部分函数是基于其他的python自定义类，太多了放不下，只放策略主题部分作为参考，高手们请忽略！

import math, sys, os, NMath

import NLog as lg

import NDateTime as dt

import Future as ft

import TradeQuery as tq

import time

# import numpy as np

_investorid = '106474'

_instrument = 'rb1805'

#模型名称,默认为文件名称

_s_model_name = 'Python:%s' % os.path.basename(sys.argv[0])[:os.path.basename(sys.argv[0]).find(".")]

#模型参数

param_ma = 20

param_loss = 30

param_hl = 10

#信号记录

_signals = []

_math = NMath.NMath()

sf = ft.SingleFutureFast()

_dc_orginal_data = sf._get_data('rb', sort = 'asc')#, startdate='20160101', enddate = '20171231', cycle='d1', ideliverydate='1801')

if _dc_orginal_data == None:

print('获取数据错误:要获取的合约数据量为0！')

j = param_ma

while j < (len(_dc_orginal_data['index'])):

#动态止损SP;

if len(_signals) > 0 and (_signals[-1].sig == 'BK' or _signals[-1].sig == 'BPK') and _signals[-1].index < j:

if _signals[-1].price - _dc_orginal_data['dMinPrice'][j] > param_loss:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'SP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

if _signals[-1].index < j:

max1 = _math.max_series(_dc_orginal_data['dClosePrice'][_signals[-1].index : j])

max2 = _math.max_series(_dc_orginal_data['dOpenPrice'][_signals[-1].index : j])

max3 = _math.Nmax(max1, max2)

if max3 - _signals[-1].price >= 50 and max3 - _signals[-1].price < 100 and max3 - _dc_orginal_data['dClosePrice'][j] > 40:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'SP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

if max3 - _signals[-1].price >= 100 and max3 - _signals[-1].price < 200 and max3 - _dc_orginal_data['dClosePrice'][j] > 80:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'SP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

if max3 - _signals[-1].price >= 200 and max3 - _signals[-1].price < 400 and max3 - _dc_orginal_data['dClosePrice'][j] > 120:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'SP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

if max3 - _signals[-1].price >= 400 and max3 - _dc_orginal_data['dClosePrice'][j] > 200:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'SP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

# 动态止损BP

if len(_signals) > 0 and (_signals[-1].sig == 'SK' or _signals[-1].sig == 'SPK') and _signals[-1].index < j:

if _dc_orginal_data['dMaxPrice'][j] - _signals[-1].price > param_loss:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'BP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

if _signals[-1].index < j:

min1 = _math.min_series(_dc_orginal_data['dClosePrice'][_signals[-1].index : j])

min2 = _math.min_series(_dc_orginal_data['dOpenPrice'][_signals[-1].index : j])

min3 = _math.Nmin(max1, max2)

if _signals[-1].price - min3 >= 50 and _signals[-1].price - min3 < 100 and _dc_orginal_data['dClosePrice'][j] - min3 > 40:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'BP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

if _signals[-1].price - min3 >= 100 and _signals[-1].price - min3 < 200 and _dc_orginal_data['dClosePrice'][j] - min3 > 80:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'BP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

if _signals[-1].price - min3 >= 200 and _signals[-1].price - min3 < 400 and _dc_orginal_data['dClosePrice'][j] - min3 > 120:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'BP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

if _signals[-1].price - min3 >= 400 and _dc_orginal_data['dClosePrice'][j] - min3 > 200:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'BP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

mh = _math.ma_series(_dc_orginal_data['dMaxPrice'][j - param_ma : j - 1])

ml = _math.ma_series(_dc_orginal_data['dMinPrice'][j - param_ma : j - 1])

mc = _math.ma_series(_dc_orginal_data['dClosePrice'][j - param_ma : j - 1])

mo = _math.ma_series(_dc_orginal_data['dOpenPrice'][j - param_ma : j - 1])

mc = (mh + ml + mc + mo) / 4

if _dc_orginal_data['dMinPrice'][j] > mc and _dc_orginal_data['dOpenPrice'][j] < _dc_orginal_data['dClosePrice'][j]:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'BP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

if _dc_orginal_data['dMaxPrice'][j] < mc and _dc_orginal_data['dOpenPrice'][j] > _dc_orginal_data['dClosePrice'][j]:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'SP', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

min1 = _math.min_series(_dc_orginal_data['dClosePrice'][j - param_hl : j - 1])

min2 = _math.min_series(_dc_orginal_data['dOpenPrice'][j - param_hl : j - 1])

min3 = _math.Nmin(min1, min2)

max1 = _math.max_series(_dc_orginal_data['dClosePrice'][j - param_hl : j - 1])

max2 = _math.max_series(_dc_orginal_data['dOpenPrice'][j - param_hl : j - 1])

max3 = _math.Nmax(max1, max2)

if _dc_orginal_data['dClosePrice'][j] > mh and _dc_orginal_data['dMaxPrice'][j] > max3 and _dc_orginal_data['dClosePrice'][j] > _dc_orginal_data['dOpenPrice'][j]:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'BPK', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

if _dc_orginal_data['dClosePrice'][j] < ml and _dc_orginal_data['dMinPrice'][j] < min3 and _dc_orginal_data['dClosePrice'][j] < _dc_orginal_data['dOpenPrice'][j]:

_signals = ft.FilterAddWH(_signals, ft.whSignal(_dc_orginal_data['iReceiveDate'][j], 'SPK', _dc_orginal_data['dClosePrice'][j], _dc_orginal_data['index'][j]))

j += 1

k = 0

for _s in _signals:

print(_s.date, _s.sig, _s.price, _s.index)

k += 1

print('总盈利:', ft.Signals_SUM(_signals))

#当日交易

_tq = tq.TradeQuery()

cur_date = dt.get_now_date_int()

_s_log = '_signals[-1].date=%s,_signals[-1].sig=%s,cur_date=%s' % (_signals[-1].date, _signals[-1].sig, cur_date)

lg.NFileLog(_s_log)

if int(_signals[-1].date) == int(cur_date):

if _signals[-1].sig =='BP':

lg.NFileLog('进入BP信号处理')

_list = _tq.QuerySignals(_s_model_name, 'BUY', 'CLOSE', ft.OpenVolume)

time.sleep(1)