Method transaction_sim

tests/test_finance.py:163–366

This is a utility method that asserts expected results for conversion of orders to transactions given a trade history

(self, **params)

        self.transaction_sim(**params1)

    def transaction_sim(self, **params):
        """This is a utility method that asserts expected
        results for conversion of orders to transactions given a
        trade history
        """
        trade_count = params['trade_count']
        trade_interval = params['trade_interval']
        order_count = params['order_count']
        order_amount = params['order_amount']
        order_interval = params['order_interval']
        expected_txn_count = params['expected_txn_count']
        expected_txn_volume = params['expected_txn_volume']

        # optional parameters
        # ---------------------
        # if present, alternate between long and short sales
        alternate = params.get('alternate')

        # if present, expect transaction amounts to match orders exactly.
        complete_fill = params.get('complete_fill')

        asset1 = self.asset_finder.retrieve_asset(1)
        with TempDirectory() as tempdir:

            if trade_interval < timedelta(days=1):
                sim_params = factory.create_simulation_parameters(
                    start=self.start,
                    end=self.end,
                    data_frequency="minute"
                )

                minutes = self.trading_calendar.minutes_window(
                    sim_params.first_open,
                    int((trade_interval.total_seconds() / 60) * trade_count)
                    + 100)

                price_data = np.array([10.1] * len(minutes))
                assets = {
                    asset1.sid: pd.DataFrame({
                        "open": price_data,
                        "high": price_data,
                        "low": price_data,
                        "close": price_data,
                        "volume": np.array([100] * len(minutes)),
                        "dt": minutes
                    }).set_index("dt")
                }

                write_bcolz_minute_data(
                    self.trading_calendar,
                    self.trading_calendar.sessions_in_range(
                        self.trading_calendar.minute_to_session_label(
                            minutes[0]
                        ),
                        self.trading_calendar.minute_to_session_label(
                            minutes[-1]
                        )
                    ),