233 lines
10 KiB
Python
233 lines
10 KiB
Python
# -*- encoding:utf-8 -*-
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"""
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交易订单模块
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"""
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from __future__ import print_function
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from __future__ import absolute_import
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from __future__ import division
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import math
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import numpy as np
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from ..CoreBu import ABuEnv
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from ..CoreBu.ABuEnv import EMarketTargetType
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from ..MarketBu.ABuSymbolFutures import AbuFuturesCn, AbuFuturesGB
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from ..MarketBu.ABuHkUnit import AbuHkUnit
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from ..MarketBu import ABuMarket
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from ..MarketBu.ABuMarket import MarketMixin
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__author__ = '阿布'
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__weixin__ = 'abu_quant'
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class OrderMarket(MarketMixin):
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"""根据AbuOrder对象，设置混入类MarketMixin中symbol_name"""
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def __init__(self, order):
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"""
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设置混入类MarketMixin中symbol_name，以获取symbol_market等信息
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:param order: AbuOrder对象
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"""
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if isinstance(order, AbuOrder):
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self.symbol_name = order.buy_symbol
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else:
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raise TypeError('order is AbuOrder object!!!')
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# noinspection PyAttributeOutsideInit
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class AbuOrder(object):
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"""交易订单类"""
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# 多个因子买入条件可能生成几百万个order对象使用__slots__降低内存消耗
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__slots__ = ('order_deal', 'buy_symbol', 'buy_date', 'buy_factor', 'buy_factor_class',
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'buy_price', 'buy_cnt', 'buy_pos', 'sell_date',
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'buy_type_str', 'expect_direction',
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'sell_type', 'keep_days', 'sell_price', 'sell_type_extra', 'ml_features')
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def __init__(self):
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"""初始设置只需要将order_deal设置未成交状态"""
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self.order_deal = False
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def fit_buy_order(self, day_ind, factor_object):
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"""
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根据买入交易日当当天数据以及买入因子，拟合计算买入订单
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:param day_ind: 买入交易发生的时间索引，即对应self.kl_pd.key
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:param factor_object: ABuFactorBuyBases子类实例对象
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"""
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kl_pd = factor_object.kl_pd
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# 要执行买入当天的数据
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kl_pd_buy = kl_pd.iloc[day_ind + 1]
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# 买入因子名称
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factor_name = factor_object.factor_name if hasattr(factor_object, 'factor_name') else 'unknown'
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# 日内滑点决策类
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slippage_class = factor_object.slippage_class
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# 仓位管理类设置
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position_class = factor_object.position_class
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# 初始资金，也可修改策略使用剩余资金
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read_cash = factor_object.capital.read_cash
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# 实例化滑点类
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fact = slippage_class(kl_pd_buy, factor_name)
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# 执行fit_price, 计算决策买入价格
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bp = fact.fit()
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# 如果滑点类中决定不买入，撤单子，bp就返回正无穷
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if bp < np.inf:
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"""
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实例化仓位管理类
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仓位管理默认保证金比例是1，即没有杠杆，修改ABuPositionBase.g_deposit_rate可提高融资能力，
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如果margin＝2－>ABuPositionBase.g_deposit_rate = 0.5, 即只需要一半的保证金，也可同过构建
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时使用关键字参数完成保证金比例传递
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"""
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position = position_class(kl_pd_buy, factor_name, factor_object.kl_pd.name, bp, read_cash,
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**factor_object.position_kwargs)
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market = ABuEnv.g_market_target if ABuMarket.g_use_env_market_set else position.symbol_market
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"""
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由于模块牵扯复杂，暂时不迁移保证金融资相关模块，期货不使用杠杆，即回测不牵扯资金总量的评估
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if market == EMarketTargetType.E_MARKET_TARGET_FUTURES_CN:
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deposit_rate = 0.10
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q_df = AbuFuturesCn().query_symbol(factor_object.kl_pd.name)
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if q_df is not None:
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deposit_rate = q_df.min_deposit.values[0]
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# 重新设置保证金比例
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position.deposit_rate = deposit_rate
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"""
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# 执行fit_position，通过仓位管理计算买入的数量
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bc = position.fit_position(factor_object)
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if np.isnan(bc):
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return
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if market != EMarketTargetType.E_MARKET_TARGET_TC:
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# 除了比特币市场外，都向下取整数到最小交易单位个数
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buy_cnt = int(math.floor(bc))
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else:
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# 币类市场可以买非整数个, 保留三位小数
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buy_cnt = round(bc, 3)
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if market == EMarketTargetType.E_MARKET_TARGET_US:
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# 美股1
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min_cnt = 1
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elif market == EMarketTargetType.E_MARKET_TARGET_TC:
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# 国内一般只支持到0.01个
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min_cnt = 0.01
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elif market == EMarketTargetType.E_MARKET_TARGET_CN:
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# A股最小100一手
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min_cnt = 100
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# 向最小的手量看齐
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buy_cnt -= buy_cnt % min_cnt
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elif market == EMarketTargetType.E_MARKET_TARGET_HK:
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# 港股从AbuHkUnit读取数据，查询对应symbol每一手的交易数量
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min_cnt = AbuHkUnit().query_unit(factor_object.kl_pd.name)
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# 向最小的手量看齐
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buy_cnt -= buy_cnt % min_cnt
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elif market == EMarketTargetType.E_MARKET_TARGET_FUTURES_CN:
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# 国内期货，查询最少一手单位
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min_cnt = AbuFuturesCn().query_min_unit(factor_object.kl_pd.name)
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# 向最小的手量看齐
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buy_cnt -= buy_cnt % min_cnt
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elif market == EMarketTargetType.E_MARKET_TARGET_OPTIONS_US:
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# 美股期权最小合约单位1contract，代表100股股票权利
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min_cnt = 100
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buy_cnt -= buy_cnt % min_cnt
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elif market == EMarketTargetType.E_MARKET_TARGET_FUTURES_GLOBAL:
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# 国际期货, 查询最少一手单位
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min_cnt = AbuFuturesGB().query_min_unit(factor_object.kl_pd.name)
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buy_cnt -= buy_cnt % min_cnt
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else:
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raise TypeError('ABuEnv.g_market_target ERROR, market={}, g_market_target={}'.format(
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market, ABuEnv.g_market_target))
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if buy_cnt < min_cnt:
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# 不够买最少单位量
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return
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# 如下生成order内部数据
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self.buy_symbol = kl_pd.name
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# 订单写入买入日期
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self.buy_date = int(kl_pd_buy.date)
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# 订单写入买入因子名字
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self.buy_factor = factor_name
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# 订单对象中添加买入因子类名，和buy_factor不同没有具体参数等唯一key
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self.buy_factor_class = factor_object.__class__.__name__
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# 订单写入买入价格
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self.buy_price = bp
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# 订单写入买入数量
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self.buy_cnt = buy_cnt
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# 订单写入仓位管理类名称
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self.buy_pos = position.__class__.__name__
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# 订单写入买入类型，call or put
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self.buy_type_str = factor_object.buy_type_str
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# 订单写入买入因子期望方向
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self.expect_direction = factor_object.expect_direction
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# 如下卖出信息具体写入在fit_sell_order中
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# 订单卖出时间
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self.sell_date = None
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# 订单卖出类型，keep：持有
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self.sell_type = 'keep'
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# 交易日持有天数
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self.keep_days = 0
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# 订单卖出价格
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self.sell_price = None
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# 订单卖出额外信息
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self.sell_type_extra = ''
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# 订单买入，卖出特征
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self.ml_features = None
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# 订单形成
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self.order_deal = True
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def fit_sell_order(self, day_ind, factor_object):
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"""
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根据卖出交易日当当天数据以及卖出因子，拟合计算卖出信息，完成订单
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:param day_ind: 卖出交易发生的时间索引，即对应self.kl_pd.key
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:param factor_object: AbuFactorSellBase子类实例对象
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"""
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if self.sell_type != 'keep':
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# 保证外部不需要过滤单子，内部自己过滤已经卖出成交的订单
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return
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# 卖出策略中进行特征合成, 以及ump拦截卖出行为
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if factor_object.make_sell_order(self, day_ind):
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kl_pd_sell = factor_object.kl_pd.iloc[day_ind + 1]
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# 日内滑点决策类
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slippage_class = factor_object.slippage_class
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# 卖出因子名称
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factor_name = factor_object.factor_name if hasattr(factor_object, 'factor_name') else 'unknown'
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# 实例化日内滑点决策类，进行具体卖出价格决策
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sell_price = slippage_class(kl_pd_sell, factor_name).fit()
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if sell_price == -np.inf:
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# 如果卖出执行返回负无穷说明无法卖出，例如跌停
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return
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self.sell_price = sell_price
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# 卖出原因其它描述
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sell_type_extra = factor_object.sell_type_extra if hasattr(factor_object, 'sell_type_extra') else 'unknown'
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self.sell_type_extra = sell_type_extra
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if self.buy_type_str == 'call':
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# call卖出类型: win = self.sell_price > self.buy_price
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self.sell_type = 'win' if self.sell_price > self.buy_price else 'loss'
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else:
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# put卖出类型: loss = self.sell_price > self.buy_price
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self.sell_type = 'loss' if self.sell_price > self.buy_price else 'win'
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# 卖出日期写入单子
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self.sell_date = int(kl_pd_sell.date)
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def __str__(self):
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"""打印对象显示：buy_symbol， buy_price， buy_cnt， buy_date，buy_factor，sell_date，sell_type， sell_price"""
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return 'buy Symbol = ' + str(self.buy_symbol) + '\n' \
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+ 'buy Prices = ' + str(self.buy_price) + '\n' \
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+ 'buy cnt = ' + str(self.buy_cnt) + '\n' \
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+ 'buy date = ' + str(self.buy_date) + '\n' \
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+ 'buy factor = ' + str(self.buy_factor) + '\n' \
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+ 'sell date = ' + str(self.sell_date) + '\n' \
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+ 'sell type = ' + str(self.sell_type) + '\n' \
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+ 'sell Price = ' + str(self.sell_price) + '\n'
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__repr__ = __str__
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