def test_close_open_positions_with_open_no_force_all_write(self):
# close values DataFrame
cv_df = pd.read_csv('./data/sample_data.csv',
parse_dates=True,
index_col=0)[['close']]
# input_data DataFrame
id_df = pd.read_csv('./data/sample_data.csv',
parse_dates=True,
index_col=0)
ts = TradingSimulation(input_data_index=id_df.index,
close_values=cv_df,
max_exposure=None,
short_exposure_factor=1.5)
ts._portfolio = pd.read_csv(
'./data/portfolio_simulation_data_all_open_ten_rounds.csv',
parse_dates=True,
index_col=0).to_numpy(dtype=np.float64, copy=True)
portfolio_expected_result = pd.read_csv(
'./data/portfolio_simulation_data_all_open_ten_rounds.csv',
parse_dates=True,
index_col=0).to_numpy(dtype=np.float64, copy=True)
portfolio_expected_result[0, 1] = 2.0
portfolio_expected_result[2, 1] = 2.0
portfolio_expected_result[5, 1] = 2.0
portfolio_expected_result[5, 2] = 40.00
ts._simulation_data['exposure'].iat[8] = 100.0
ts._simulation_data['earnings'].iat[8] = 200.0
ts._portfolio[5, 2] = 40.00
ts._close_values[9, 0] = 24.0
earnings, closed_exposure = ts._closeOpenPositions(i_index=9)
exposure_expected = 20.50 + 22.50 + 40.00
earnings_expected = (2 * 24.0 - 20.5 - 22.5) + \
((40.00 / 1.5) - 1 * 24.0)
self.assertEqual(earnings, earnings_expected)
self.assertEqual(closed_exposure, exposure_expected)
np.testing.assert_equal(
ts._simulation_data['exposure'].iat[9],
ts._simulation_data['exposure'].iat[8] - exposure_expected)
np.testing.assert_equal(
ts._simulation_data['earnings'].iat[9],
ts._simulation_data['earnings'].iat[8] + earnings_expected)
np.testing.assert_equal(ts._portfolio, portfolio_expected_result)
def test_close_open_positions_none_open_no_force_all_write(self):
# close values DataFrame
cv_df = pd.read_csv('./data/sample_data.csv',
parse_dates=True,
index_col=0)[['close']]
# input_data DataFrame
id_df = pd.read_csv('./data/sample_data.csv',
parse_dates=True,
index_col=0)
ts = TradingSimulation(input_data_index=id_df.index,
close_values=cv_df,
max_exposure=None,
short_exposure_factor=1.5)
ts._portfolio = pd.read_csv(
'./data/portfolio_simulation_data_none_open_ten_rounds.csv',
parse_dates=True,
index_col=0).to_numpy(dtype=np.float64, copy=True)
portfolio_expected_result = pd.read_csv(
'./data/portfolio_simulation_data_none_open_ten_rounds.csv',
parse_dates=True,
index_col=0).to_numpy(dtype=np.float64, copy=True)
ts._simulation_data['exposure'].iat[8] = 100.0
ts._simulation_data['earnings'].iat[8] = 200.0
earnings, closed_exposure = ts._closeOpenPositions(i_index=9)
self.assertEqual(earnings, 0.0)
self.assertEqual(closed_exposure, 0.0)
np.testing.assert_equal(ts._simulation_data['exposure'].iat[9], 100.0)
np.testing.assert_equal(ts._simulation_data['earnings'].iat[9], 200.0)
np.testing.assert_equal(ts._portfolio, portfolio_expected_result)