示例#1
0
 def get_stock_1d_k_data(provider: Provider, sleep, desc, pc, lock, region,
                         batch):
     # 日线
     Stock1dKdata.record_data(provider=provider,
                              share_para=(desc, pc, lock, True, region),
                              sleeping_time=sleep,
                              batch_size=batch)
示例#2
0
def report_vol_up_250():
    while True:
        error_count = 0
        email_action = EmailInformer()

        try:
            # 抓取k线数据
            StockTradeDay.record_data(provider='joinquant')
            Stock1dKdata.record_data(provider='joinquant')

            latest_day: StockTradeDay = StockTradeDay.query_data(
                order=StockTradeDay.timestamp.desc(),
                limit=1,
                return_type='domain')
            if latest_day:
                target_date = latest_day[0].timestamp
            else:
                target_date = now_pd_timestamp()

            # 计算均线
            my_selector = TargetSelector(start_timestamp='2018-01-01',
                                         end_timestamp=target_date)
            # add the factors
            factor1 = VolumeUpMa250Factor(start_timestamp='2018-01-01',
                                          end_timestamp=target_date)

            my_selector.add_filter_factor(factor1)

            my_selector.run()

            long_targets = my_selector.get_open_long_targets(
                timestamp=target_date)
            if long_targets:
                stocks = get_entities(provider='joinquant',
                                      entity_schema=Stock,
                                      entity_ids=long_targets,
                                      return_type='domain')
                info = [f'{stock.name}({stock.code})' for stock in stocks]
                msg = ' '.join(info)
            else:
                msg = 'no targets'

            logger.info(msg)

            email_action.send_message("*****@*****.**",
                                      f'{target_date} 放量突破年线选股结果', msg)

            break
        except Exception as e:
            logger.exception('report_vol_up_250 error:{}'.format(e))
            time.sleep(60 * 3)
            error_count = error_count + 1
            if error_count == 10:
                email_action.send_message(
                    "*****@*****.**", f'report_vol_up_250 error',
                    'report_vol_up_250 error:{}'.format(e))
示例#3
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    def make_decision(self, timestamp, trading_level: IntervalLevel):
        longs, shorts = super().make_decision(timestamp, trading_level)
        if longs or shorts:
            # 成交超过1亿的前300个股
            df = Stock1dKdata.query_data(
                start_timestamp=timestamp,
                end_timestamp=timestamp,
                columns=[Stock1dKdata.entity_id],
                filters=[Stock1dKdata.turnover > 100000000],
                limit=300,
                order=Stock1dKdata.volume.desc())
            longs1 = set(df['entity_id'].to_list())
            long_targets = set(longs) & longs1

            if shorts:
                all = Stock.query_data(columns=[Stock.entity_id])
                short_targets = set(shorts) | (
                    set(all['entity_id'].to_list()) - longs1)
            else:
                short_targets = shorts

            return long_targets, short_targets
        return longs, shorts
示例#4
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def report_state():
    while True:
        error_count = 0
        email_action = EmailInformer(ssl=True)

        try:
            latest_day: Stock1dKdata = Stock1dKdata.query_data(order=Stock1dKdata.timestamp.desc(), limit=1,
                                                               return_type='domain')
            target_date = latest_day[0].timestamp
            # target_date = to_pd_timestamp('2020-01-02')

            # 计算均线
            my_selector = TargetSelector(start_timestamp='2018-01-01', end_timestamp=target_date)
            # add the factors
            factor1 = VolumeUpMa250Factor(start_timestamp='2018-01-01', end_timestamp=target_date)

            my_selector.add_filter_factor(factor1)

            my_selector.run()

            long_stocks = my_selector.get_open_long_targets(timestamp=target_date)

            msg = 'no targets'
            # 过滤亏损股
            # check StockValuation data
            pe_date = target_date - datetime.timedelta(10)
            if StockValuation.query_data(start_timestamp=pe_date, limit=1, return_type='domain'):
                positive_df = StockValuation.query_data(provider='joinquant', entity_ids=long_stocks,
                                                        start_timestamp=pe_date,
                                                        filters=[StockValuation.pe > 0],
                                                        columns=['entity_id'])
                bad_stocks = set(long_stocks) - set(positive_df['entity_id'].tolist())
                if bad_stocks:
                    stocks = get_entities(provider='joinquant', entity_schema=Stock, entity_ids=bad_stocks,
                                          return_type='domain')
                    info = [f'{stock.name}({stock.code})' for stock in stocks]
                    msg = '亏损股:' + ' '.join(info) + '\n'

                long_stocks = set(positive_df['entity_id'].tolist())

            if long_stocks:
                pre_date = target_date - datetime.timedelta(3 * 365)
                ma_state = MaStateStatsFactor(entity_ids=long_stocks, start_timestamp=pre_date,
                                              end_timestamp=target_date, persist_factor=False)
                bad_stocks = []
                for entity_id, df in ma_state.factor_df.groupby(level=0):
                    if df['current_pct'].max() >= 0.35:
                        bad_stocks.append(entity_id)
                        long_stocks.remove(entity_id)
                if bad_stocks:
                    stocks = get_entities(provider='joinquant', entity_schema=Stock, entity_ids=bad_stocks,
                                          return_type='domain')
                    info = [f'{stock.name}({stock.code})' for stock in stocks]
                    msg = msg + '3年内高潮过:' + ' '.join(info) + '\n'

            # 过滤风险股
            if long_stocks:
                risky_codes = risky_company(the_date=target_date, entity_ids=long_stocks)

                if risky_codes:
                    long_stocks = [entity_id for entity_id in long_stocks if
                                   get_entity_code(entity_id) not in risky_codes]

                    stocks = get_entities(provider='joinquant', entity_schema=Stock, entity_ids=risky_codes,
                                          return_type='domain')
                    info = [f'{stock.name}({stock.code})' for stock in stocks]
                    msg = msg + '风险股:' + ' '.join(info) + '\n'
            if long_stocks:
                stocks = get_entities(provider='joinquant', entity_schema=Stock, entity_ids=long_stocks,
                                      return_type='domain')
                # add them to eastmoney
                try:
                    try:
                        eastmoneypy.del_group('real')
                    except:
                        pass
                    eastmoneypy.create_group('real')
                    for stock in stocks:
                        eastmoneypy.add_to_group(stock.code, group_name='real')
                except Exception as e:
                    email_action.send_message("*****@*****.**", f'report state error',
                                              'report state error:{}'.format(e))

                info = [f'{stock.name}({stock.code})' for stock in stocks]
                msg = msg + '盈利股:' + ' '.join(info) + '\n'

            logger.info(msg)
            email_action.send_message('*****@*****.**', f'{target_date} 放量突破年线state选股结果', msg)
            break
        except Exception as e:
            logger.exception('report state error:{}'.format(e))
            time.sleep(60 * 3)
            error_count = error_count + 1
            if error_count == 10:
                email_action.send_message("*****@*****.**", f'report state error',
                                          'report state error:{}'.format(e))
示例#5
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def report_vol_up_120():
    while True:
        error_count = 0
        email_action = EmailInformer()

        try:
            # 抓取k线数据
            # StockTradeDay.record_data(provider='joinquant')
            # Stock1dKdata.record_data(provider='joinquant')

            latest_day: Stock1dKdata = Stock1dKdata.query_data(
                order=Stock1dKdata.timestamp.desc(),
                limit=1,
                return_type='domain')
            target_date = latest_day[0].timestamp

            # 计算均线
            my_selector = TargetSelector(start_timestamp='2019-06-01',
                                         end_timestamp=target_date)
            # add the factors
            factor1 = ImprovedMaFactor(start_timestamp='2019-06-01',
                                       end_timestamp=target_date,
                                       windows=[120])

            my_selector.add_filter_factor(factor1)

            my_selector.run()

            long_stocks = my_selector.get_open_long_targets(
                timestamp=target_date)

            msg = 'no targets'

            # 过滤亏损股
            # check StockValuation data
            pe_date = target_date - datetime.timedelta(10)
            if StockValuation.query_data(start_timestamp=pe_date,
                                         limit=1,
                                         return_type='domain'):
                positive_df = StockValuation.query_data(
                    provider='joinquant',
                    entity_ids=long_stocks,
                    start_timestamp=pe_date,
                    filters=[StockValuation.pe > 0],
                    columns=['entity_id'])
                bad_stocks = set(long_stocks) - set(
                    positive_df['entity_id'].tolist())
                if bad_stocks:
                    stocks = get_entities(provider='joinquant',
                                          entity_schema=Stock,
                                          entity_ids=bad_stocks,
                                          return_type='domain')
                    info = [f'{stock.name}({stock.code})' for stock in stocks]
                    msg = '亏损股:' + ' '.join(info) + '\n'

                long_stocks = set(positive_df['entity_id'].tolist())

            if long_stocks:
                stocks = get_entities(provider='joinquant',
                                      entity_schema=Stock,
                                      entity_ids=long_stocks,
                                      return_type='domain')
                # add them to eastmoney
                try:
                    try:
                        eastmoneypy.del_group('high')
                    except:
                        pass
                    eastmoneypy.create_group('high')
                    for stock in stocks:
                        eastmoneypy.add_to_group(stock.code, group_name='high')
                except Exception as e:
                    email_action.send_message(
                        "*****@*****.**", f'report_vol_up_120 error',
                        'report_vol_up_120 error:{}'.format(e))

                info = [f'{stock.name}({stock.code})' for stock in stocks]
                msg = msg + '盈利股:' + ' '.join(info) + '\n'

            logger.info(msg)

            email_action.send_message('*****@*****.**',
                                      f'{target_date} 改进版放量突破半年线选股结果', msg)

            break
        except Exception as e:
            logger.exception('report_vol_up_120 error:{}'.format(e))
            time.sleep(60 * 3)
            error_count = error_count + 1
            if error_count == 10:
                email_action.send_message(
                    "*****@*****.**", f'report_vol_up_120 error',
                    'report_vol_up_120 error:{}'.format(e))
示例#6
0
            ]

        df = StockActorSummary.query_data(filters=filters)

        if pd_is_not_null(df):
            self.logger.info(f'{df}')
            self.finish_date = recent_report_date

        long_df = df[df['change_ratio'] > 0.05]
        short_df = df[df['change_ratio'] < -0.5]
        try:
            self.trade_the_targets(
                due_timestamp=timestamp,
                happen_timestamp=timestamp,
                long_selected=set(long_df['entity_id'].to_list()),
                short_selected=set(short_df['entity_id'].to_list()))
        except Exception as e:
            self.logger.error(e)


if __name__ == '__main__':
    entity_id = 'stock_sh_600519'
    Stock1dKdata.record_data(entity_id=entity_id, provider='em')
    StockActorSummary.record_data(entity_id=entity_id, provider='em')
    FollowIITrader(start_timestamp='2002-01-01',
                   end_timestamp='2021-01-01',
                   entity_ids=[entity_id],
                   provider='em',
                   adjust_type=AdjustType.qfq,
                   profit_threshold=None).run()
示例#7
0
def report_real(region):
    while True:
        error_count = 0
        email_action = EmailInformer(ssl=True)

        try:
            latest_day: Stock1dKdata = Stock1dKdata.query_data(
                region=region,
                order=Stock1dKdata.timestamp.desc(),
                limit=1,
                return_type='domain')
            target_date = latest_day[0].timestamp
            # target_date = '2020-02-04'

            # 计算均线
            my_selector = TargetSelector(region=region,
                                         start_timestamp='2018-01-01',
                                         end_timestamp=target_date)
            # add the factors
            factor1 = VolumeUpMa250Factor(region=region,
                                          start_timestamp='2018-01-01',
                                          end_timestamp=target_date)

            my_selector.add_filter_factor(factor1)

            my_selector.run()

            long_stocks = my_selector.get_open_long_targets(
                timestamp=target_date)

            msg = 'no targets'
            # 过滤亏损股
            # check StockValuation data
            pe_date = target_date - datetime.timedelta(10)
            if StockValuation.query_data(region=region,
                                         start_timestamp=pe_date,
                                         limit=1,
                                         return_type='domain'):
                positive_df = StockValuation.query_data(
                    region=region,
                    provider=Provider.JoinQuant,
                    entity_ids=long_stocks,
                    start_timestamp=pe_date,
                    filters=[StockValuation.pe > 0],
                    columns=['entity_id'])
                bad_stocks = set(long_stocks) - set(
                    positive_df['entity_id'].tolist())
                if bad_stocks:
                    stocks = get_entities(region=region,
                                          provider=Provider.JoinQuant,
                                          entity_schema=Stock,
                                          entity_ids=bad_stocks,
                                          return_type='domain')
                    info = [f'{stock.name}({stock.code})' for stock in stocks]
                    msg = '亏损股:' + ' '.join(info) + '\n'

                long_stocks = set(positive_df['entity_id'].tolist())

            if long_stocks:
                # use block to filter
                block_selector = BlockSelector(region=region,
                                               start_timestamp='2020-01-01',
                                               long_threshold=0.8)
                block_selector.run()
                long_blocks = block_selector.get_open_long_targets(
                    timestamp=target_date)

                if long_blocks:
                    blocks: List[Block] = Block.query_data(
                        region=region,
                        provider=Provider.Sina,
                        entity_ids=long_blocks,
                        return_type='domain')

                    info = [f'{block.name}({block.code})' for block in blocks]
                    msg = ' '.join(info) + '\n'

                    block_stocks: List[BlockStock] = BlockStock.query_data(
                        region=region,
                        provider=Provider.Sina,
                        filters=[BlockStock.stock_id.in_(long_stocks)],
                        entity_ids=long_blocks,
                        return_type='domain')
                    if block_stocks:
                        # add them to eastmoney
                        try:
                            try:
                                eastmoneypy.del_group('real')
                            except:
                                pass
                            eastmoneypy.create_group('real')
                            for block_stock in block_stocks:
                                eastmoneypy.add_to_group(
                                    block_stock.stock_code, group_name='real')
                        except Exception as e:
                            email_action.send_message(
                                "*****@*****.**", f'report_real error',
                                'report_real error:{}'.format(e))

                        block_map_stocks = {}
                        for block_stock in block_stocks:
                            stocks = block_map_stocks.get(block_stock.name)
                            if not stocks:
                                stocks = []
                                block_map_stocks[block_stock.name] = stocks
                            stocks.append(
                                f'{block_stock.stock_name}({block_stock.stock_code})'
                            )

                        for block in block_map_stocks:
                            stocks = block_map_stocks[block]
                            stock_msg = ' '.join(stocks)
                            msg = msg + f'{block}:\n' + stock_msg + '\n'

            logger.info(msg)
            email_action.send_message('*****@*****.**',
                                      f'{target_date} 放量突破年线real选股结果', msg)
            break
        except Exception as e:
            logger.exception('report_real error:{}'.format(e))
            time.sleep(60 * 3)
            error_count = error_count + 1
            if error_count == 10:
                email_action.send_message("*****@*****.**",
                                          f'report_real error',
                                          'report_real error:{}'.format(e))
示例#8
0
def report_vol_up_250():
    while True:
        error_count = 0
        email_action = EmailInformer()

        try:
            # 抓取k线数据
            # StockTradeDay.record_data(provider='joinquant')
            # Stock1dKdata.record_data(provider='joinquant')

            latest_day: Stock1dKdata = Stock1dKdata.query_data(order=Stock1dKdata.timestamp.desc(), limit=1,
                                                               return_type='domain')
            target_date = latest_day[0].timestamp

            # 计算均线
            my_selector = TargetSelector(start_timestamp='2018-01-01', end_timestamp=target_date)
            # add the factors
            factor1 = VolumeUpMa250Factor(start_timestamp='2018-01-01', end_timestamp=target_date)

            my_selector.add_filter_factor(factor1)

            my_selector.run()

            long_stocks = my_selector.get_open_long_targets(timestamp=target_date)

            # 过滤亏损股
            positive_df = StockValuation.query_data(provider='joinquant', entity_ids=long_stocks,
                                                    start_timestamp=target_date, end_timestamp=target_date,
                                                    filters=[StockValuation.pe > 0],
                                                    columns=['entity_id'])
            long_stocks = positive_df['entity_id'].tolist()
            if long_stocks:
                stocks = get_entities(provider='joinquant', entity_schema=Stock, entity_ids=long_stocks,
                                      return_type='domain')
                # add them to eastmoney
                try:
                    try:
                        eastmoneypy.del_group('tech')
                    except:
                        pass
                    eastmoneypy.create_group('tech')
                    for stock in stocks:
                        eastmoneypy.add_to_group(stock.code, group_name='tech')
                except Exception as e:
                    email_action.send_message("*****@*****.**", f'report_vol_up_250 error',
                                              'report_vol_up_250 error:{}'.format(e))

                info = [f'{stock.name}({stock.code})' for stock in stocks]
                msg = ' '.join(info)
            else:
                msg = 'no targets'

            logger.info(msg)

            email_action.send_message(get_subscriber_emails(), f'{target_date} 放量突破年线选股结果', msg)

            break
        except Exception as e:
            logger.exception('report_vol_up_250 error:{}'.format(e))
            time.sleep(60 * 3)
            error_count = error_count + 1
            if error_count == 10:
                email_action.send_message("*****@*****.**", f'report_vol_up_250 error',
                                          'report_vol_up_250 error:{}'.format(e))
示例#9
0
def report_state(region):
    while True:
        error_count = 0
        email_action = EmailInformer(ssl=True)

        try:
            latest_day: Stock1dKdata = Stock1dKdata.query_data(
                region=region,
                order=Stock1dKdata.timestamp.desc(),
                limit=1,
                return_type='domain')
            target_date = latest_day[0].timestamp
            # target_date = to_pd_timestamp('2020-01-02')

            # 计算均线
            my_selector = TargetSelector(region=region,
                                         start_timestamp='2018-01-01',
                                         end_timestamp=target_date)
            # add the factors
            factor1 = ImprovedMaFactor(region=region,
                                       start_timestamp='2018-01-01',
                                       end_timestamp=target_date)

            my_selector.add_filter_factor(factor1)

            my_selector.run()

            long_stocks = my_selector.get_open_long_targets(
                timestamp=target_date)
            stock_map_slope = {}

            logger.info(long_stocks)

            msg = 'no targets'

            if long_stocks:
                pre_date = target_date - datetime.timedelta(2 * 365)
                ma_state = MaStateStatsFactor(region=region,
                                              entity_ids=long_stocks,
                                              start_timestamp=pre_date,
                                              end_timestamp=target_date,
                                              need_persist=False)

                ma_state.factor_df['slope'] = 100 * ma_state.factor_df[
                    'current_pct'] / ma_state.factor_df['current_count']

                high_stocks = []
                for entity_id, df in ma_state.factor_df.groupby(level=0):
                    if df['current_pct'].max() >= 0.7:
                        high_stocks.append(entity_id)

                    stock_map_slope[entity_id] = round(df['slope'].iat[-1], 2)

                if high_stocks:
                    stocks = get_entities(region=region,
                                          provider=Provider.JoinQuant,
                                          entity_schema=Stock,
                                          entity_ids=high_stocks,
                                          return_type='domain')
                    info = [
                        f'{stock.name}({stock.code})[{stock_map_slope.get(stock.entity_id)}]'
                        for stock in stocks
                    ]
                    msg = msg + '2年内高潮过:' + ' '.join(info) + '\n'

            # 过滤风险股
            if long_stocks:
                risky_codes = risky_company(region=region,
                                            the_date=target_date,
                                            entity_ids=long_stocks,
                                            income_yoy=-0.8,
                                            profit_yoy=-0.8)

                if risky_codes:
                    long_stocks = [
                        entity_id for entity_id in long_stocks
                        if get_entity_code(entity_id) not in risky_codes
                    ]

                    stocks = get_entities(region=region,
                                          provider=Provider.JoinQuant,
                                          entity_schema=Stock,
                                          codes=risky_codes,
                                          return_type='domain')
                    info = [
                        f'{stock.name}({stock.code})[{stock_map_slope.get(stock.entity_id)}]'
                        for stock in stocks
                    ]
                    msg = msg + '风险股:' + ' '.join(info) + '\n'
            if long_stocks:
                stocks = get_entities(region=region,
                                      provider=Provider.JoinQuant,
                                      entity_schema=Stock,
                                      entity_ids=long_stocks,
                                      return_type='domain')
                # add them to eastmoney
                try:
                    try:
                        eastmoneypy.del_group('real')
                    except:
                        pass
                    eastmoneypy.create_group('real')
                    for stock in stocks:
                        eastmoneypy.add_to_group(stock.code, group_name='real')
                except Exception as e:
                    email_action.send_message(
                        "*****@*****.**", f'report state error',
                        'report state error:{}'.format(e))

                info = [
                    f'{stock.name}({stock.code})[{stock_map_slope.get(stock.entity_id)}]'
                    for stock in stocks
                ]
                msg = msg + '选中:' + ' '.join(info) + '\n'

            logger.info(msg)
            email_action.send_message('*****@*****.**',
                                      f'{target_date} 放量突破年线state选股结果', msg)
            break
        except Exception as e:
            logger.exception('report state error:{}'.format(e))
            time.sleep(60 * 3)
            error_count = error_count + 1
            if error_count == 10:
                email_action.send_message("*****@*****.**",
                                          f'report state error',
                                          'report state error:{}'.format(e))