merge: 合并 wikillm 与 wikillm-git,全部内容入库(abuquant-src/OCR产物/images/IDEA.md)

raw/量化/abuquant-src/python/stock_days.py

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+# -*- encoding:utf-8 -*-
+from abc import ABCMeta, abstractmethod
+from collections import OrderedDict
+from collections import namedtuple
+
+from abupy import six, reduce, map, filter
+
+
+class StockTradeDays(object):
+    def __init__(self, price_array, start_date, date_array=None):
+        # 私有价格序列
+        self.__price_array = price_array
+        # 私有日期序列
+        self.__date_array = self._init_days(start_date, date_array)
+        # 私有涨跌幅序列
+        self.__change_array = self.__init_change()
+        # 进行OrderedDict的组装
+        self.stock_dict = self._init_stock_dict()
+
+    def __init_change(self):
+        """
+        从price_array生成change_array
+        :return:
+        """
+        price_float_array = [float(price_str) for price_str in
+                             self.__price_array]
+        # 通过将时间平移形成两个错开的收盘价序列，通过zip打包成为一个新的序列
+        # 每个元素为相邻的两个收盘价格
+        pp_array = [(price1, price2) for price1, price2 in
+                    zip(price_float_array[:-1], price_float_array[1:])]
+        change_array = list(map(lambda pp: reduce(lambda a, b: round((b - a) / a, 3), pp), pp_array))
+        # list insert插入数据，将第一天的涨跌幅设置为0
+        change_array.insert(0, 0)
+        return change_array
+
+    def _init_days(self, start_date, date_array):
+        """
+        protect方法，
+        :param start_date: 初始日期
+        :param date_array: 给定日期序列
+        :return:
+        """
+        if date_array is None:
+            # 由start_date和self.__price_array来确定日期序列
+            date_array = [str(start_date + ind) for ind, _ in
+                          enumerate(self.__price_array)]
+        else:
+            # 稍后的内容会使用外部直接设置的方式
+            # 如果外面设置了date_array，就直接转换str类型组成新date_array
+            date_array = [str(date) for date in date_array]
+        return date_array
+
+    def _init_stock_dict(self):
+        """
+        使用namedtuple，OrderedDict将结果合并
+        :return:
+        """
+        stock_namedtuple = namedtuple('stock',
+                                      ('date', 'price', 'change'))
+
+        # 使用以被赋值的__date_array等进行OrderedDict的组装
+        stock_dict = OrderedDict(
+            (date, stock_namedtuple(date, price, change))
+            for date, price, change in
+            zip(self.__date_array, self.__price_array,
+                self.__change_array))
+        return stock_dict
+
+    def filter_stock(self, want_up=True, want_calc_sum=False):
+        """
+        筛选结果子集
+        :param want_up: 是否筛选上涨
+        :param want_calc_sum: 是否计算涨跌和
+        :return:
+        """
+        # Python中的三目表达式的写法
+        filter_func = (lambda p_day: p_day.change > 0) if want_up else (
+            lambda p_day: p_day.change < 0)
+        # 使用filter_func做筛选函数
+        want_days = list(filter(filter_func, self.stock_dict.values()))
+
+        if not want_calc_sum:
+            return want_days
+
+        # 需要计算涨跌幅和
+        change_sum = 0.0
+        for day in want_days:
+            change_sum += day.change
+        return change_sum
+
+    """
+        下面的__str__，__iter__， __getitem__， __len__稍后会详细讲解作
+    """
+
+    def __str__(self):
+        return str(self.stock_dict)
+
+    __repr__ = __str__
+
+    def __iter__(self):
+        """
+        通过代理stock_dict的跌倒，yield元素
+        :return:
+        """
+        for key in self.stock_dict:
+            yield self.stock_dict[key]
+
+    def __getitem__(self, ind):
+        date_key = self.__date_array[ind]
+        return self.stock_dict[date_key]
+
+    def __len__(self):
+        return len(self.stock_dict)
+
+
+class TradeStrategyBase(six.with_metaclass(ABCMeta, object)):
+    """
+        交易策略抽象基类
+    """
+
+    @abstractmethod
+    def buy_strategy(self, *args, **kwargs):
+        # 买入策略基类
+        pass
+
+    @abstractmethod
+    def sell_strategy(self, *args, **kwargs):
+        # 卖出策略基类
+        pass
+
+
+class TradeStrategy1(TradeStrategyBase):
+    """
+        交易策略1: 追涨策略，当股价上涨一个阀值默认为7%时
+        买入股票并持有s_keep_stock_threshold（20）天
+    """
+    s_keep_stock_threshold = 20
+
+    def __init__(self):
+        self.keep_stock_day = 0
+        # 7%上涨幅度作为买入策略阀值
+        self.__buy_change_threshold = 0.07
+
+    def buy_strategy(self, trade_ind, trade_day, trade_days):
+        if self.keep_stock_day == 0 and \
+                        trade_day.change > self.__buy_change_threshold:
+
+            # 当没有持有股票的时候self.keep_stock_day == 0 并且
+            # 符合买入条件上涨一个阀值，买入
+            self.keep_stock_day += 1
+        elif self.keep_stock_day > 0:
+            # self.keep_stock_day > 0代表持有股票，持有股票天数递增
+            self.keep_stock_day += 1
+
+    def sell_strategy(self, trade_ind, trade_day, trade_days):
+        if self.keep_stock_day >= \
+                TradeStrategy1.s_keep_stock_threshold:
+            # 当持有股票天数超过阀值s_keep_stock_threshold，卖出股票
+            self.keep_stock_day = 0
+
+    """
+        property属性稍后会讲到
+    """
+
+    @property
+    def buy_change_threshold(self):
+        return self.__buy_change_threshold
+
+    @buy_change_threshold.setter
+    def buy_change_threshold(self, buy_change_threshold):
+        if not isinstance(buy_change_threshold, float):
+            """
+                上涨阀值需要为float类型
+            """
+            raise TypeError('buy_change_threshold must be float!')
+        # 上涨阀值只取小数点后两位
+        self.__buy_change_threshold = round(buy_change_threshold, 2)
+
+
+class TradeLoopBack(object):
+    """
+        交易回测系统
+    """
+
+    def __init__(self, trade_days, trade_strategy):
+        """
+        使用上一节封装的StockTradeDays类和本节编写的交易策略类
+        TradeStrategyBase类初始化交易系统
+        :param trade_days: StockTradeDays交易数据序列
+        :param trade_strategy: TradeStrategyBase交易策略
+        """
+        self.trade_days = trade_days
+        self.trade_strategy = trade_strategy
+        # 交易盈亏结果序列
+        self.profit_array = []
+
+    def execute_trade(self):
+        """
+        执行交易回测
+        :return:
+        """
+        for ind, day in enumerate(self.trade_days):
+            """
+                以时间驱动，完成交易回测
+            """
+            if self.trade_strategy.keep_stock_day > 0:
+                # 如果有持有股票，加入交易盈亏结果序列
+                self.profit_array.append(day.change)
+
+            # hasattr: 用来查询对象有没有实现某个方法
+            if hasattr(self.trade_strategy, 'buy_strategy'):
+                # 买入策略执行
+                self.trade_strategy.buy_strategy(ind, day,
+                                                 self.trade_days)
+
+            if hasattr(self.trade_strategy, 'sell_strategy'):
+                # 卖出策略执行
+                self.trade_strategy.sell_strategy(ind, day,
+                                                  self.trade_days)
+
+
+class TradeStrategy2(TradeStrategyBase):
+    """
+        交易策略2: 均值回复策略，当股价连续两个交易日下跌，
+        且下跌幅度超过阀值默认s_buy_change_threshold(-10%)，
+        买入股票并持有s_keep_stock_threshold（10）天
+    """
+    # 买入后持有天数
+    s_keep_stock_threshold = 10
+    # 下跌买入阀值
+    s_buy_change_threshold = -0.10
+
+    def __init__(self):
+        self.keep_stock_day = 0
+
+    def buy_strategy(self, trade_ind, trade_day, trade_days):
+        if self.keep_stock_day == 0 and trade_ind >= 1:
+            """
+                当没有持有股票的时候self.keep_stock_day == 0 并且
+                trade_ind >= 1, 不是交易开始的第一天，因为需要yesterday数据
+            """
+            # trade_day.change < 0 bool：今天是否股价下跌
+            today_down = trade_day.change < 0
+            # 昨天是否股价下跌
+            yesterday_down = trade_days[trade_ind - 1].change < 0
+            # 两天总跌幅
+            down_rate = trade_day.change + trade_days[trade_ind - 1].change
+            if today_down and yesterday_down and down_rate < \
+                    TradeStrategy2.s_buy_change_threshold:
+                # 买入条件成立：连跌两天，跌幅超过s_buy_change_threshold
+                self.keep_stock_day += 1
+        elif self.keep_stock_day > 0:
+            # self.keep_stock_day > 0代表持有股票，持有股票天数递增
+            self.keep_stock_day += 1
+
+    def sell_strategy(self, trade_ind, trade_day, trade_days):
+        if self.keep_stock_day >= \
+                TradeStrategy2.s_keep_stock_threshold:
+            # 当持有股票天数超过阀值s_keep_stock_threshold，卖出股票
+            self.keep_stock_day = 0
+
+    """
+        稍后会详细讲解classmethod，staticmethod
+    """
+
+    @classmethod
+    def set_keep_stock_threshold(cls, keep_stock_threshold):
+        cls.s_keep_stock_threshold = keep_stock_threshold
+
+    @staticmethod
+    def set_buy_change_threshold(buy_change_threshold):
+        TradeStrategy2.s_buy_change_threshold = buy_change_threshold