Esempio n. 1
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    def query_index_weights_daily(self, index, start_date, end_date):
        """
        Return all securities that have been in index during start_date and end_date.
        
        Parameters
        ----------
        index : str
        start_date : int
        end_date : int

        Returns
        -------
        res : pd.DataFrame
            Index is trade_date, columns are symbols.

        """
        start_dt = jutil.convert_int_to_datetime(start_date)
        start_dt_extended = start_dt - pd.Timedelta(days=45)
        start_date_extended = jutil.convert_datetime_to_int(start_dt_extended)
        trade_dates = self.query_trade_dates(start_date_extended, end_date)
        
        df_weight_raw = self.query_index_weights_range(index, start_date=start_date_extended, end_date=end_date)
        res = df_weight_raw.reindex(index=trade_dates)
        res = res.fillna(method='ffill')
        res = res.loc[res.index >= start_date]
        res = res.loc[res.index <= end_date]
        
        mask_col = res.sum(axis=0) > 0
        return res
        res = res.loc[:, mask_col]
Esempio n. 2
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    def query_index_weights_daily(self, index, start_date, end_date):
        """
        Return all securities that have been in index during start_date and end_date.
        
        Parameters
        ----------
        index : str
        start_date : int
        end_date : int

        Returns
        -------
        res : pd.DataFrame
            Index is trade_date, columns are symbols.

        """
        
        start_dt = jutil.convert_int_to_datetime(start_date)
        start_dt_extended = start_dt - pd.Timedelta(days=45)
        start_date_extended = jutil.convert_datetime_to_int(start_dt_extended)
        trade_dates = self.query_trade_dates(start_date_extended, end_date)
        
        df_weight_raw = self.query_index_weights_range(index, start_date=start_date_extended, end_date=end_date)
        res = df_weight_raw.reindex(index=trade_dates)
        res = res.fillna(method='ffill')
        res = res.loc[res.index >= start_date]
        res = res.loc[res.index <= end_date]
        
        mask_col = res.sum(axis=0) > 0
        res = res.loc[:, mask_col]
        
        return res
Esempio n. 3
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def test_dtutil():
    import datetime
    date = 20170105
    dt = jutil.convert_int_to_datetime(date)

    assert jutil.shift(date, 2) == 20170119
    assert jutil.convert_datetime_to_int(jutil.shift(dt, 2)) == 20170119

    t = 145539
    dt = jutil.combine_date_time(date, t)
    assert jutil.split_date_time(dt) == (date, t)

    assert jutil.get_next_period_day(date, 'day', 1, 1) == 20170109
    assert jutil.get_next_period_day(date, 'week', 2, 0) == 20170116
    assert jutil.get_next_period_day(date, 'month', 1, 0) == 20170201

    date = 20170808
    assert jutil.get_next_period_day(20170831, 'day',
                                     extra_offset=1) == 20170904
    assert jutil.get_next_period_day(20170831, 'day', n=2,
                                     extra_offset=0) == 20170904
    assert jutil.get_next_period_day(20170831, 'day', n=7,
                                     extra_offset=0) == 20170911
    assert jutil.get_next_period_day(20170831, 'week',
                                     extra_offset=1) == 20170905
    assert jutil.get_next_period_day(20170831, 'month',
                                     extra_offset=0) == 20170901

    monthly = 20170101
    while monthly < 20180301:
        monthly = jutil.get_next_period_day(monthly, 'month', extra_offset=0)
        assert datetime.datetime.strptime(str(monthly), "%Y%m%d").weekday() < 5
Esempio n. 4
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    def _get_first_period_day(self):

        current = self.start_date

        current_date = jutil.convert_int_to_datetime(current)
        period = self.ctx.strategy.period

        # set current date to first date of current period
        # set offset to first date of previous period
        if period == 'day':
            offset = pd.tseries.offsets.BDay()
        elif period == 'week':
            offset = pd.tseries.offsets.Week(weekday=0)
            current_date -= pd.tseries.offsets.Day(current_date.weekday())
        elif period == 'month':
            offset = pd.tseries.offsets.BMonthBegin()
            current_date -= pd.tseries.offsets.Day(current_date.day - 1)
        else:
            raise NotImplementedError(
                "Frequency as {} not support".format(period))

        current_date -= offset * self.ctx.strategy.n_periods

        current = jutil.convert_datetime_to_int(current_date)

        return self._get_next_period_day(
            current,
            self.ctx.strategy.period,
            n=self.ctx.strategy.n_periods,
            extra_offset=self.ctx.strategy.days_delay)
Esempio n. 5
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def matrix_from_different_date():
    dates = pd.date_range(end='2018-09-08', periods=5, freq='3M')
    dataset = pd.DataFrame()
    for dt in dates:
        dataset = dataset.append(
            last_center_matrix(end_date=jutil.convert_datetime_to_int(dt),
                               target=20))
    return dataset
Esempio n. 6
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    def get_next_trade_date(self, date):
        """
        
        Parameters
        ----------
        date : int

        Returns
        -------
        res : int

        """
        dt = jutil.convert_int_to_datetime(date)
        delta = pd.Timedelta(weeks=2)
        dt_new = dt + delta
        date_new = jutil.convert_datetime_to_int(dt_new)

        dates = self.get_trade_date_range(date, date_new)
        mask = dates > date
        res = dates[mask][0]

        return res
Esempio n. 7
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    def get_last_trade_date(self, date):
        """
        
        Parameters
        ----------
        date : int

        Returns
        -------
        res : int

        """
        dt = jutil.convert_int_to_datetime(date)
        delta = pd.Timedelta(weeks=2)
        dt_old = dt - delta
        date_old = jutil.convert_datetime_to_int(dt_old)

        dates = self.get_trade_date_range(date_old, date)
        mask = dates < date
        res = dates[mask][-1]

        return res
Esempio n. 8
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    def query_last_trade_date(self, date):
        """
        
        Parameters
        ----------
        date : int

        Returns
        -------
        res : int

        """
        dt = jutil.convert_int_to_datetime(date)
        delta = pd.Timedelta(weeks=2)
        dt_old = dt - delta
        date_old = jutil.convert_datetime_to_int(dt_old)
    
        dates = self.query_trade_dates(date_old, date)
        mask = dates < date
        res = dates[mask][-1]
    
        return int(res)
Esempio n. 9
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    def query_next_trade_date(self, date, n=1):
        """
        
        Parameters
        ----------
        date : int
        n : int, optional
            Next n trade dates, default 0 (next trade date).

        Returns
        -------
        res : int

        """
        dt = jutil.convert_int_to_datetime(date)
        delta = pd.Timedelta(weeks=(n // 7 + 2))
        dt_new = dt + delta
        date_new = jutil.convert_datetime_to_int(dt_new)

        dates = self.query_trade_dates(date, date_new)
        mask = dates > date
        res = dates[mask][n - 1]

        return res
Esempio n. 10
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    def query_next_trade_date(self, date, n=1):
        """
        
        Parameters
        ----------
        date : int
        n : int, optional
            Next n trade dates, default 0 (next trade date).

        Returns
        -------
        res : int

        """
        dt = jutil.convert_int_to_datetime(date)
        delta = pd.Timedelta(weeks=(n // 7 + 2))
        dt_new = dt + delta
        date_new = jutil.convert_datetime_to_int(dt_new)
    
        dates = self.query_trade_dates(date, date_new)
        mask = dates > date
        res = dates[mask][n-1]
    
        return int(res)
Esempio n. 11
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 def _get_current_date():
     now_utc = datetime.datetime.utcnow()
     now_utc8 = now_utc + datetime.timedelta(hours=8)
     now_date = jutil.convert_datetime_to_int(now_utc8)
     return now_date
Esempio n. 12
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    def _get_next_period_day(self, current, period, n=1, extra_offset=0):
        """
        Get the n'th day in next period from current day.

        Parameters
        ----------
        current : int
            Current date in format "%Y%m%d".
        period : str
            Interval between current and next. {'day', 'week', 'month'}
        n : int
            n times period.
        extra_offset : int
            n'th business day after next period.

        Returns
        -------
        nxt : int

        """
        #while True:
        #for _ in range(4):

        current_date = jutil.convert_int_to_datetime(current)
        while current <= self.end_date:
            if period == 'day':
                offset = pd.tseries.offsets.BDay()  # move to next business day
                if extra_offset < 0:
                    raise ValueError("Wrong offset for day period")
            elif period == 'week':
                offset = pd.tseries.offsets.Week(
                    weekday=0)  # move to next Monday
                if extra_offset < -5:
                    raise ValueError("Wrong offset for week period")
            elif period == 'month':
                offset = pd.tseries.offsets.BMonthBegin(
                )  # move to first business day of next month
                if extra_offset < -31:
                    raise ValueError("Wrong offset for month period")
            else:
                raise NotImplementedError(
                    "Frequency as {} not support".format(period))

            offset = offset * n

            begin_date = current_date + offset
            if period == 'day':
                end_date = begin_date + pd.tseries.offsets.Day() * 366
            elif period == 'week':
                end_date = begin_date + pd.tseries.offsets.Day() * 6
            elif period == 'month':
                end_date = begin_date + pd.tseries.offsets.BMonthBegin(
                )  #- pd.tseries.offsets.BDay()

            if extra_offset > 0:
                next_date = begin_date + extra_offset * pd.tseries.offsets.BDay(
                )
                if next_date >= end_date:
                    next_date = end_date - pd.tseries.offsets.BDay()
            elif extra_offset < 0:
                next_date = end_date + extra_offset * pd.tseries.offsets.BDay()
                if next_date < begin_date:
                    next_date = begin_date
            else:
                next_date = begin_date

            date = next_date
            while date < end_date:
                nxt = jutil.convert_datetime_to_int(date)
                if self._is_trade_date(nxt):
                    return nxt
                date += pd.tseries.offsets.BDay()

            date = next_date
            while date >= begin_date:
                nxt = jutil.convert_datetime_to_int(date)
                if self._is_trade_date(nxt):
                    return nxt
                date -= pd.tseries.offsets.BDay()

            # no trading day in this period, try next period
            current_date = end_date - pd.tseries.offsets.BDay()
            current = jutil.convert_datetime_to_int(current_date)
            # Check if there are more trade dates
            self._get_next_trade_date(current)

        raise ValueError("no trading day after {0}".format(current))