Example #1
0
 def OnCalcTech(self, df_hisdat, df_five, df_fenshi):
     """df : kline
     后面两个参数可能为None
     """
     closes = df_hisdat['c']
     self.calc_tech['four'] = stock.FOUR(closes)
     self.calc_tech['boll'] = stock.TDX_BOLL2(closes)
     self.calc_tech['adx'] = stock.TDX_ADX(df_hisdat['h'], df_hisdat['l'], closes)
Example #2
0
def getData(code):
    """return: upper, middle, lower, df, adx
    """
    #加载数据
    #df = stock.LiveData().getFiveMinHisdat(code)
    df = data_interface.loadData(code)
    #df = df[:200]
    upper, middle, lower = stock.TDX_BOLL(df['c'].values)
    highs, lows, closes = df['h'], df['l'], df['c']
    adx = stock.TDX_ADX(highs, lows, closes)
    #closes = df['c'].values
    return upper, middle, lower, df, adx
Example #3
0
    def Run(self):
        """
        """
        #self._log('Strategy_Boll_Pre')

        #以下为交易测试
        code = self.data.get_code()  #当前策略处理的股票
        self.code = code
        if not self.is_backtesting and not self.AllowCode(code):
            return

        df_hisdat = self.data.get_hisdat(code)  #日k线
        df_five_hisdat = self.data.get_hisdat(code, dtype='5min')  #5分钟k线
        df_fenshi = self.data.get_fenshi(code)  #日分时
        if len(df_fenshi) == 0:
            self.data.log(code + u"未取到分时数据")
            return
        account = self._getAccount()  #获取交易账户
        price = float(df_fenshi.tail(1)['p'])  #当前股价
        closes = df_hisdat['c']
        yestoday_close = closes[-2]  #昨日收盘价
        zhangfu = stock.ZhangFu(price, yestoday_close)
        self._log(
            'price=%.2f %s %s' %
            (price, str(df_fenshi.index[-1]), str(df_five_hisdat.iloc[-1])))
        account_mgr = ac.AccountMgr(account, price, code)
        trade_num = ac.ShouShu(account_mgr.init_money() *
                               self.trade_num_use_money_percent / price)
        trade_num = max(100, trade_num)

        # 信号计算
        four = stock.FOUR(closes)
        four = four[-1]
        upper, middle, lower = stock.TDX_BOLL(df_five_hisdat['c'])
        highs, lows, closes = df_five_hisdat['h'], df_five_hisdat[
            'l'], df_five_hisdat['c']
        adx = stock.TDX_ADX(highs, lows, closes)
        self._log('boll : %.2f,%.2f,%.2f' % (upper[-1], middle[-1], lower[-1]))
        boll_w = abs(upper[-1] - lower[-1]) / middle[-1] * 100
        #50个周期内最高值
        is_high = abs(price - max(df_five_hisdat[-1000:]['h'])) / price < 0.005

        boll_poss = [
            upper[-1],
            (upper[-1] - middle[-1]) / 2 + middle[-1],
            middle[-1],
            (middle[-1] - lower[-1]) / 2 + lower[-1],
            lower[-1],
        ]
        self._log('boll_poss: %.2f, %.2f boll_w=%.2f adx=%.2f' %
                  (boll_poss[0], boll_poss[1], boll_w, adx[-1]))

        #上一个成交的价位
        pre_price = account_mgr.last_chengjiao_price()
        pre_pre_price = account_mgr.last_chengjiao_price(index=-2)
        sell_count = account_mgr.queryTradeCount(1)
        buy_count = account_mgr.queryTradeCount(0)
        #买入均价

        adx = adx[-1]
        boll_up_ratio = 0.02
        #信号判断
        num = 0
        if so.assemble(
                price > boll_poss[1],
                price > pre_price * (1 + self.trade_ratio),
                #price > boll_poss[2],
                #price > self.max_buy_price*(1+self.trade_ratio),
                #boll_w > 3.5,
                #adx > 60,
                #sell_count < 2,
                #pr.horizontal(df_five_hisdat),
                0,
        ):
            num = -trade_num
            self.trade_status = self.enum.boll_up_mid
            #if self.order(1, code, price, num):
            #self._log(agl.utf8_to_ascii('一档卖出%s, %.2f, %d'%(code, price, num)))
        if so.assemble(
                price > boll_poss[0],
                price > pre_price * (1 + self.trade_ratio),
                #price > self.max_buy_price*(1+self.trade_ratio),
                #boll_w > 3,
                adx > 60,
                is_high,
                #four > self.trade_four[1],
                #sell_count < 2,
                #self.trade_status == self.enum.nothing,
                #0,
        ):
            num = -trade_num * 3
            self.trade_status = self.enum.boll_up
            #if self.order(1, code, price, num):
            #self._log(agl.utf8_to_ascii('二档卖出%s, %.2f, %d'%(code, price, num)))
        if so.assemble(
                price < boll_poss[-2] * (1 + boll_up_ratio),
                price < pre_price * (1 - self.trade_ratio),
                #price < boll_poss[2],
                #price < self.min_sell_price*(1-0.03),
                #boll_w > 3.5,
                #adx>60,
                #buy_count < 2,
                #pr.horizontal(df_five_hisdat),
                0,
        ):
            num = trade_num
            self.trade_status = self.enum.boll_down_mid
            #if boll_w > 6:
            #num *= self.trade_num_ratio
            #if self.order(0, code, price, num):
            #self._log(agl.utf8_to_ascii('一档买入%s, %.2f, %d'%(code, price, num)))
        if so.assemble(
                price < boll_poss[-1],
                price < pre_price * (1 - self.trade_ratio),
                #price < self.min_sell_price*(1-0.03),
                #boll_w > 3,
                #buy_count < 2,
                #self.trade_status == self.enum.nothing,
                #adx>70,
                #four < self.trade_four[0],
                #0,
        ):
            num = trade_num * 3
            #num = account_mgr.last_chengjiao_num()
            self.trade_status = self.enum.boll_down
            #if self.order(0, code, price, num):
            #self._log(agl.utf8_to_ascii('二档买入%s, %.2f, %d'%(code, price, num)))

        #成本区间
        if so.assemble(
                price < pre_price * (1 - 0.05),
                four < -0.1,
                self.trade_status == self.enum.boll_up,
                0,
        ):
            num = trade_num * self.trade_num_ratio
            self.trade_status = self.enum.nothing
        if so.assemble(
                price > pre_price * (1 + 0.05),
                four > 0.1,
                self.trade_status == self.enum.boll_down,
                0,
        ):
            num = -trade_num * self.trade_num_ratio
            self.trade_status = self.enum.nothing

        #zz顶抛出后回补
        if so.assemble(
                price < pre_price * (1 - 0.02),
                #sell_count >= 2,
                self.trade_status == self.enum.zz_up,
                0,
        ):
            #上次zz卖出的数量
            num = account_mgr.last_chengjiao_num()
            self.trade_status = self.enum.zz_hui_bu
        if so.assemble(
                price > pre_price * (1 + 0.02),
                #sell_count >= 2,
                self.trade_status == self.enum.zz_down,
                0,
        ):
            #上次zz卖出的数量
            num = account_mgr.last_chengjiao_num()
            self.trade_status = self.enum.zz_hui_bu

        #计算分时zz
        zz_sign = 0
        closes = df_five_hisdat['c'][-200:].values
        zz = stock.ZigZag(closes)
        if len(zz) > 2:
            zz_result = stock.analyzeZZ(zz)
            zz_line_ratio = zz_result[1] / zz_result[0]  #线段比率
            #扑捉大涨回头的信号
            if abs(zz_result[0]) > 0.05 and abs(zz_line_ratio) > 0.05 and abs(
                    zz_line_ratio) < 0.2 and abs(zz_result[0]) > 0.04:
                zz_sign = agl.where(zz_result[1] > 0, 1, -1)

        if num != 0:
            bSell = agl.where(num > 0, 0, 1)
            num = abs(num)
            #if bSell:
            #num = self._compensate(num, bSell, code)
            #基本上每天的振幅都在1个点以上
            if abs(stock.ZhangFu(price, yestoday_close)) > 0.01:
                self.order(bSell, code, price, num)

        zz_pre_price = myredis.createRedisVal('policy_basesign_zz_pre_price',
                                              price)
        if so.assemble(
                zz_sign != 0,
                0,
        ):
            #print self.price, getZZPrePrice(self.price),abs(self.price-getZZPrePrice(self.price))/self.price
            num = trade_num * 12
            bSell = agl.where(zz_sign > 0, 0, 1)
            num = self._compensate(num, bSell, code)
            bCanOrder = False
            if so.assemble(
                    bSell,
                    price > zz_pre_price.get() * (1 + 0.03),
                    #price > pre_price*(1+self.trade_ratio),
            ):
                bCanOrder = True
                self.trade_status = self.enum.zz_up
            if so.assemble(
                (not bSell),
                    price < zz_pre_price.get() * (1 - 0.03),
                    #price < pre_price*(1-self.trade_ratio)
            ):
                bCanOrder = True
                self.trade_status = self.enum.zz_down
            if bCanOrder:
                self._getAccount().Order(bSell, code, price, num)
                zz_pre_price.set(price)

        #信号发生时语音播报, 并通知界面回显
        if not self.is_backtesting and (price > boll_poss[1]
                                        or price < boll_poss[-2]):
            codename = stock.GetCodeName(code)
            s = '%s, %.2f' % (codename, price)
            self.data.show(codename)  #通知界面显示
            self.data.speak2(s)  #语音播报

        #tick report
        if self.is_backtesting and self.is_tick_report:
            self._getAccount().TickReport(df_five_hisdat, 'win')
        return
Example #4
0
 def OnCalcTech(self, df_hisdat, df_five_hisdat, df_fenshi):
     self.calc_tech['four'] = stock.FOUR(df_five_hisdat['c'])
     self.calc_tech['boll'] = stock.TDX_BOLL(df_five_hisdat['c'])
     highs, lows, closes = df_five_hisdat['h'], df_five_hisdat[
         'l'], df_five_hisdat['c']
     self.calc_tech['adx'] = stock.TDX_ADX(highs, lows, closes)