def test_position_short_twice(): """ Tests that the properties on the Position are calculated for two consective short trades with differing quantities and market prices. """ # Initial short details asset = 'EQ:MSFT' quantity = -100 dt = pd.Timestamp('2020-06-16 15:00:00', tz=pytz.UTC) price = 194.55 order_id = 123 commission = 1.44 # Create the initial transaction and position first_transaction = Transaction(asset, quantity=quantity, dt=dt, price=price, order_id=order_id, commission=commission) position = Position.open_from_transaction(first_transaction) assert position.asset == asset assert position.current_price == price assert position.current_dt == dt # Second short second_quantity = -60 second_dt = pd.Timestamp('2020-06-16 16:00:00', tz=pytz.UTC) second_price = 194.76 second_order_id = 234 second_commission = 1.27 second_transaction = Transaction(asset, quantity=second_quantity, dt=second_dt, price=second_price, order_id=second_order_id, commission=second_commission) position.transact(second_transaction) assert position.current_price == second_price assert position.current_dt == second_dt assert position.buy_quantity == 0 assert position.sell_quantity == 160 assert position.avg_bought == 0.0 assert position.avg_sold == 194.62875 assert position.commission == 2.71 assert position.direction == -1 assert np.isclose(position.market_value, -31161.6) assert np.isclose(position.avg_price, 194.6118125) assert position.net_quantity == -160 assert position.total_bought == 0.0 assert position.total_sold == 31140.60 assert position.net_total == 31140.6 assert position.net_incl_commission == 31137.89 assert np.isclose(position.unrealised_pnl, -23.71) assert np.isclose(position.realised_pnl, 0.0)
def test_transact_position_current_position(): """ Tests the 'transact_position' method for a transaction with a current asset and checks that all objects are set correctly. """ # Create the PositionHandler, Transaction and # carry out a transaction ph = PositionHandler() asset = Equity('Amazon, Inc.', 'AMZN') dt = pd.Timestamp('2015-05-06') transaction_long = Transaction(asset, quantity=100, dt=dt, price=960.0, order_id=123, commission=26.83) transaction_long_again = Transaction(asset, quantity=200, dt=dt, price=990.0, order_id=234, commission=18.53) ph.transact_position(transaction_long) ph.transact_position(transaction_long_again) # Check that the position object is set correctly pos = ph.positions[asset] assert pos.quantity == 300 assert pos.direction == 1.0 assert pos.book_cost_pu == 980.1512000000001 assert pos.book_cost == 294045.36000000004
def test_transact_position_quantity_zero(): """ Tests the 'transact_position' method for a transaction with net zero quantity after the transaction to ensure deletion of the position. """ # Create the PositionHandler, Transaction and # carry out a transaction ph = PositionHandler() asset = Equity('Amazon, Inc.', 'AMZN') dt = pd.Timestamp('2015-05-06') transaction_long = Transaction(asset, quantity=100, dt=dt, price=960.0, order_id=123, commission=26.83) transaction_close = Transaction(asset, quantity=-100, dt=dt, price=980.0, order_id=234, commission=18.53) # Go long and then close, then check that the # positions OrderedDict is empty ph.transact_position(transaction_long) ph.transact_position(transaction_close) od = OrderedDict() assert ph.positions == od
def test_total_values_for_two_separate_transactions(): """ Tests 'total_book_cost', 'total_market_value', 'total_gain' and 'total_perc_gain' for single transactions in two separate assets. """ ph = PositionHandler() # Asset 1 asset1 = Equity('Amazon, Inc.', 'AMZN') dt1 = pd.Timestamp('2015-05-06') trans_pos_1 = Transaction(asset1.symbol, quantity=75, dt=dt1, price=483.45, order_id=1, commission=15.97) ph.transact_position(trans_pos_1) # Asset 2 asset2 = Equity('Microsoft, Inc.', 'MSFT') dt2 = pd.Timestamp('2015-05-07') trans_pos_2 = Transaction(asset2.symbol, quantity=250, dt=dt2, price=142.58, order_id=2, commission=8.35) ph.transact_position(trans_pos_2) # Check all total values assert ph.total_book_cost() == 71928.07 assert ph.total_market_value() == 71903.75 assert ph.total_unrealised_gain() == -24.31999999999971 assert ph.total_unrealised_percentage_gain() == -0.03381155646190282
def test_position_long_twice(): """ Tests that the properties on the Position are calculated for two consective long trades with differing quantities and market prices. """ # Initial long details asset = 'EQ:MSFT' quantity = 100 dt = pd.Timestamp('2020-06-16 15:00:00', tz=pytz.UTC) price = 193.74 order_id = 123 commission = 1.0 # Create the initial transaction and position first_transaction = Transaction(asset, quantity=quantity, dt=dt, price=price, order_id=order_id, commission=commission) position = Position.open_from_transaction(first_transaction) assert position.asset == asset assert position.current_price == price assert position.current_dt == dt # Second long second_quantity = 60 second_dt = pd.Timestamp('2020-06-16 16:00:00', tz=pytz.UTC) second_price = 193.79 second_order_id = 234 second_commission = 1.0 second_transaction = Transaction(asset, quantity=second_quantity, dt=second_dt, price=second_price, order_id=second_order_id, commission=second_commission) position.transact(second_transaction) assert position.current_price == second_price assert position.current_dt == second_dt assert position.buy_quantity == 160 assert position.sell_quantity == 0 assert np.isclose(position.avg_bought, 193.75875) assert position.avg_sold == 0.0 assert position.commission == 2.0 assert position.direction == 1 assert np.isclose(position.market_value, 31006.40) assert position.avg_price == 193.77125 assert position.net_quantity == 160 assert position.total_bought == 31001.40 assert position.total_sold == 0.0 assert position.net_total == -31001.40 assert position.net_incl_commission == -31003.40 assert np.isclose(position.unrealised_pnl, 3.0) assert np.isclose(position.realised_pnl, 0.0)
def test_transact_position_quantity_zero(): """ Tests the 'transact_position' method for a transaction with net zero quantity after the transaction to ensure deletion of the position. """ # Create the PositionHandler, Transaction and # carry out a transaction ph = PositionHandler() asset = 'EQ:AMZN' dt = pd.Timestamp('2015-05-06 15:00:00', tz=pytz.UTC) new_dt = pd.Timestamp('2015-05-06 16:00:00', tz=pytz.UTC) transaction_long = Transaction( asset, quantity=100, dt=dt, price=960.0, order_id=123, commission=26.83 ) ph.transact_position(transaction_long) transaction_close = Transaction( asset, quantity=-100, dt=new_dt, price=980.0, order_id=234, commission=18.53 ) ph.transact_position(transaction_close) # Go long and then close, then check that the # positions OrderedDict is empty assert ph.positions == OrderedDict()
def test_position_long_close(): """ Tests that the properties on the Position are calculated for a long opening trade and subsequent closing trade. """ # Initial long details asset = 'EQ:AMZN' quantity = 100 dt = pd.Timestamp('2020-06-16 15:00:00', tz=pytz.UTC) price = 2615.27 order_id = 123 commission = 1.0 # Create the initial transaction and position first_transaction = Transaction(asset, quantity=quantity, dt=dt, price=price, order_id=order_id, commission=commission) position = Position.open_from_transaction(first_transaction) assert position.asset == asset assert position.current_price == price assert position.current_dt == dt # Closing trade second_quantity = -100 second_dt = pd.Timestamp('2020-06-16 16:00:00', tz=pytz.UTC) second_price = 2622.0 second_order_id = 234 second_commission = 6.81 second_transaction = Transaction(asset, quantity=second_quantity, dt=second_dt, price=second_price, order_id=second_order_id, commission=second_commission) position.transact(second_transaction) assert position.current_price == second_price assert position.current_dt == second_dt assert position.buy_quantity == 100 assert position.sell_quantity == 100 assert position.avg_bought == 2615.27 assert position.avg_sold == 2622.0 assert position.commission == 7.81 assert position.direction == 0 assert position.market_value == 0.0 assert position.avg_price == 0.0 assert position.net_quantity == 0 assert position.total_bought == 261527.0 assert position.total_sold == 262200.0 assert position.net_total == 673.0 assert position.net_incl_commission == 665.19 assert position.unrealised_pnl == 0.0 assert position.realised_pnl == 665.19
def test_position_short_close(): """ Tests that the properties on the Position are calculated for a short opening trade and subsequent closing trade. """ # Initial short details asset = 'EQ:TSLA' quantity = -100 dt = pd.Timestamp('2020-06-16 15:00:00', tz=pytz.UTC) price = 982.13 order_id = 123 commission = 3.18 # Create the initial transaction and position first_transaction = Transaction(asset, quantity=quantity, dt=dt, price=price, order_id=order_id, commission=commission) position = Position.open_from_transaction(first_transaction) assert position.asset == asset assert position.current_price == price assert position.current_dt == dt # Closing trade second_quantity = 100 second_dt = pd.Timestamp('2020-06-16 16:00:00', tz=pytz.UTC) second_price = 982.13 second_order_id = 234 second_commission = 1.0 second_transaction = Transaction(asset, quantity=second_quantity, dt=second_dt, price=second_price, order_id=second_order_id, commission=second_commission) position.transact(second_transaction) assert position.current_price == second_price assert position.current_dt == second_dt assert position.buy_quantity == 100 assert position.sell_quantity == 100 assert position.avg_bought == 982.13 assert position.avg_sold == 982.13 assert position.commission == 4.18 assert position.direction == 0 assert position.market_value == 0.0 assert position.avg_price == 0.0 assert position.net_quantity == 0 assert position.total_bought == 98213.0 assert position.total_sold == 98213.0 assert position.net_total == 0.0 assert position.net_incl_commission == -4.18 assert position.unrealised_pnl == 0.0 assert position.realised_pnl == -4.18
def test_portfolio_to_dict_for_two_holdings(): """ Test portfolio_to_dict for two holdings. """ start_dt = pd.Timestamp('2017-10-05 08:00:00', tz=pytz.UTC) asset1_dt = pd.Timestamp('2017-10-06 08:00:00', tz=pytz.UTC) asset2_dt = pd.Timestamp('2017-10-07 08:00:00', tz=pytz.UTC) update_dt = pd.Timestamp('2017-10-08 08:00:00', tz=pytz.UTC) asset1 = Equity("AAA Inc.", "EQ:AAA", tax_exempt=False) asset2 = Equity("BBB Inc.", "EQ:BBB", tax_exempt=False) port = Portfolio(start_dt, portfolio_id='1234') port.subscribe_funds(start_dt, 100000.0) tn_asset1 = Transaction(asset=asset1.symbol, quantity=100, dt=asset1_dt, price=567.0, order_id=1, commission=15.78) port.transact_asset(tn_asset1) tn_asset2 = Transaction(asset=asset2.symbol, quantity=100, dt=asset2_dt, price=123.0, order_id=2, commission=7.64) port.transact_asset(tn_asset2) port.update_market_value_of_asset(asset2.symbol, 134.0, update_dt) test_holdings = { asset1.symbol: { "quantity": 100, "book_cost": 56715.78, "market_value": 56700.0, "gain": -15.78, "perc_gain": -0.027822944513854874 }, asset2.symbol: { "quantity": 100, "book_cost": 12307.64, "market_value": 13400.0, "gain": 1092.3600000000006, "perc_gain": 8.8754627207165679 } } port_holdings = port.portfolio_to_dict() # This is needed because we're not using Decimal # datatypes and have to compare slightly differing # floating point representations for asset in (asset1.symbol, asset2.symbol): for key, val in test_holdings[asset].items(): assert port_holdings[asset][key] == pytest.approx( test_holdings[asset][key])
def test_portfolio_to_dict_for_two_holdings(): """ Test portfolio_to_dict for two holdings. """ start_dt = pd.Timestamp('2017-10-05 08:00:00', tz=pytz.UTC) asset1_dt = pd.Timestamp('2017-10-06 08:00:00', tz=pytz.UTC) asset2_dt = pd.Timestamp('2017-10-07 08:00:00', tz=pytz.UTC) update_dt = pd.Timestamp('2017-10-08 08:00:00', tz=pytz.UTC) asset1 = 'EQ:AAA' asset2 = 'EQ:BBB' port = Portfolio(start_dt, portfolio_id='1234') port.subscribe_funds(start_dt, 100000.0) tn_asset1 = Transaction(asset=asset1, quantity=100, dt=asset1_dt, price=567.0, order_id=1, commission=15.78) port.transact_asset(tn_asset1) tn_asset2 = Transaction(asset=asset2, quantity=100, dt=asset2_dt, price=123.0, order_id=2, commission=7.64) port.transact_asset(tn_asset2) port.update_market_value_of_asset(asset2, 134.0, update_dt) test_holdings = { asset1: { "quantity": 100, "market_value": 56700.0, "unrealised_pnl": -15.78, "realised_pnl": 0.0, "total_pnl": -15.78 }, asset2: { "quantity": 100, "market_value": 13400.0, "unrealised_pnl": 1092.3600000000006, "realised_pnl": 0.0, "total_pnl": 1092.3600000000006 } } port_holdings = port.portfolio_to_dict() # This is needed because we're not using Decimal # datatypes and have to compare slightly differing # floating point representations for asset in (asset1, asset2): for key, val in test_holdings[asset].items(): assert port_holdings[asset][key] == pytest.approx( test_holdings[asset][key])
def test_transact_position_new_position(): """ Tests the 'transact_position' method for a transaction with a brand new asset and checks that all objects are set correctly. """ # Create the PositionHandler, Transaction and # carry out a transaction ph = PositionHandler() asset = Equity('Amazon, Inc.', 'AMZN') dt = pd.Timestamp('2015-05-06') transaction = Transaction(asset, quantity=100, dt=dt, price=960.0, order_id=123, commission=26.83) ph.transact_position(transaction) # Check that the position object is set correctly pos = ph.positions[asset] assert pos.quantity == 100 assert pos.direction == 1.0 assert pos.book_cost_pu == 960.2683000000001 assert pos.book_cost == 96026.83
def test_update_position_for_non_none_values(): """ Tests the 'update_position' method for non-None values when updating a Position entity. """ ph = PositionHandler() # Asset 1 asset1 = Equity('Amazon, Inc.', 'AMZN') dt1 = pd.Timestamp('2015-05-06') trans_pos_1 = Transaction(asset1, quantity=75, dt=dt1, price=483.45, order_id=1, commission=13.76) ph.transact_position(trans_pos_1) # Update values manually quantity = 100 current_price = 504.32 current_dt = pd.Timestamp('2015-05-07') book_cost_pu = 23.65 ph.update_position(asset1, quantity=quantity, current_price=current_price, current_dt=current_dt, book_cost_pu=book_cost_pu) assert ph.positions[asset1].quantity == quantity assert ph.positions[asset1].current_price == current_price assert ph.positions[asset1].current_dt == current_dt assert ph.positions[asset1].book_cost_pu == book_cost_pu
def test_position_long_short_positive_gain(): """ Tests that the quantity and book cost are correctly calculated for an initial long position with an additional short transaction in the same asset, where the short does not completely eliminate the position and the result is a gain. """ asset = Equity('Apple, Inc.', 'AAPL') position = Position(asset, quantity=100, book_cost_pu=950.0, current_price=950.0) dt = pd.Timestamp('2015-05-06') transaction = Transaction(asset, quantity=-50, dt=dt, price=960.0, order_id=123, commission=None) position.update(transaction) assert position.quantity == 50 assert position.book_cost_pu == 950.0 assert position.direction == 1.0 assert position.current_price == 960.0 assert position.market_value == 48000.0 assert position.unrealised_gain == 500.0 assert position.unrealised_percentage_gain == 1.0526315789473684
def test_position_long_twice(): """ Tests that the quantity and book cost are correctly calculated for an initial long position with an additional long transaction in the same asset. """ asset = Equity('Apple, Inc.', 'AAPL') position = Position(asset, quantity=100, book_cost_pu=950.0, current_price=950.0) dt = pd.Timestamp('2015-05-06') transaction = Transaction(asset, quantity=100, dt=dt, price=960.0, order_id=123, commission=None) position.update(transaction) assert position.quantity == 200 assert position.book_cost_pu == 955.0 assert position.direction == 1.0 assert position.current_price == 960.0 assert position.market_value == 192000.0 assert position.unrealised_gain == 1000.0 assert position.unrealised_percentage_gain == 0.5235602094240838
def test_transact_for_incorrect_asset(): """ Tests that the 'transact' method, when provided with a Transaction with an Asset that does not match the position's asset, raises an Exception. """ asset1 = 'EQ:AAPL' asset2 = 'EQ:AMZN' position = Position(asset1, current_price=950.0, current_dt=pd.Timestamp('2020-06-16 15:00:00', tz=pytz.UTC), buy_quantity=100, sell_quantity=0, avg_bought=950.0, avg_sold=0.0, buy_commission=1.0, sell_commission=0.0) new_dt = pd.Timestamp('2020-06-16 16:00:00') transaction = Transaction(asset2, quantity=50, dt=new_dt, price=960.0, order_id=123, commission=1.0) with pytest.raises(Exception): position.update(transaction)
def test_position_short_long_excess_cover(): """ Tests that the quantity and book cost are correctly calculated for an initial short position with an additional long transaction in the same asset, where the long position is in excess of the short position. """ asset = Equity('Apple, Inc.', 'AAPL') position = Position(asset, quantity=-100, book_cost_pu=700.0, current_price=700.0) dt = pd.Timestamp('2015-05-06') transaction = Transaction(asset, quantity=175, dt=dt, price=873.0, order_id=123, commission=None) position.update(transaction) assert position.quantity == 75 assert position.book_cost_pu == 873.0 assert position.direction == 1.0 assert position.current_price == 873.0 assert position.market_value == 65475.0 assert position.unrealised_gain == 0.0 assert position.unrealised_percentage_gain == 0.0
def test_transact_position_new_position(): """ Tests the 'transact_position' method for a transaction with a brand new asset and checks that all objects are set correctly. """ # Create the PositionHandler, Transaction and # carry out a transaction ph = PositionHandler() asset = 'EQ:AMZN' transaction = Transaction( asset, quantity=100, dt=pd.Timestamp('2015-05-06 15:00:00', tz=pytz.UTC), price=960.0, order_id=123, commission=26.83 ) ph.transact_position(transaction) # Check that the position object is set correctly pos = ph.positions[asset] assert pos.buy_quantity == 100 assert pos.sell_quantity == 0 assert pos.net_quantity == 100 assert pos.direction == 1 assert pos.avg_price == 960.2683000000001
def test_transact_position_current_position(): """ Tests the 'transact_position' method for a transaction with a current asset and checks that all objects are set correctly. """ # Create the PositionHandler, Transaction and # carry out a transaction ph = PositionHandler() asset = 'EQ:AMZN' dt = pd.Timestamp('2015-05-06 15:00:00', tz=pytz.UTC) new_dt = pd.Timestamp('2015-05-06 16:00:00', tz=pytz.UTC) transaction_long = Transaction( asset, quantity=100, dt=dt, price=960.0, order_id=123, commission=26.83 ) ph.transact_position(transaction_long) transaction_long_again = Transaction( asset, quantity=200, dt=new_dt, price=990.0, order_id=234, commission=18.53 ) ph.transact_position(transaction_long_again) # Check that the position object is set correctly pos = ph.positions[asset] assert pos.buy_quantity == 300 assert pos.sell_quantity == 0 assert pos.net_quantity == 300 assert pos.direction == 1 assert np.isclose(pos.avg_price, 980.1512)
def test_basic_short_equities_position(): """ Tests that the properties on the Position are calculated for a simple short equities position. """ # Initial short details asset = 'EQ:TLT' quantity = -100 dt = pd.Timestamp('2020-06-16 15:00:00', tz=pytz.UTC) price = 162.39 order_id = 123 commission = 1.37 # Create the initial transaction and position transaction = Transaction(asset, quantity=quantity, dt=dt, price=price, order_id=order_id, commission=commission) position = Position.open_from_transaction(transaction) assert position.asset == asset assert position.current_price == price assert position.current_dt == dt # Update the market price new_market_price = 159.43 new_dt = pd.Timestamp('2020-06-16 16:00:00', tz=pytz.UTC) position.update_current_price(new_market_price, new_dt) assert position.current_price == new_market_price assert position.current_dt == new_dt assert position.buy_quantity == 0 assert position.sell_quantity == 100 assert position.avg_bought == 0.0 assert position.avg_sold == 162.39 assert position.commission == 1.37 assert position.direction == -1 assert position.market_value == -15943.0 assert position.avg_price == 162.3763 assert position.net_quantity == -100 assert position.total_bought == 0.0 # np.isclose used for floating point precision assert np.isclose(position.total_sold, 16239.0) assert np.isclose(position.net_total, 16239.0) assert np.isclose(position.net_incl_commission, 16237.63) assert np.isclose(position.unrealised_pnl, 294.63) assert np.isclose(position.realised_pnl, 0.0)
def test_total_values_for_two_separate_transactions(): """ Tests 'total_market_value', 'total_unrealised_pnl', 'total_realised_pnl' and 'total_pnl' for single transactions in two separate assets. """ ph = PositionHandler() # Asset 1 asset1 = 'EQ:AMZN' dt1 = pd.Timestamp('2015-05-06 15:00:00', tz=pytz.UTC) trans_pos_1 = Transaction( asset1, quantity=75, dt=dt1, price=483.45, order_id=1, commission=15.97 ) ph.transact_position(trans_pos_1) # Asset 2 asset2 = 'EQ:MSFT' dt2 = pd.Timestamp('2015-05-07 15:00:00', tz=pytz.UTC) trans_pos_2 = Transaction( asset2, quantity=250, dt=dt2, price=142.58, order_id=2, commission=8.35 ) ph.transact_position(trans_pos_2) # Check all total values assert ph.total_market_value() == 71903.75 assert np.isclose(ph.total_unrealised_pnl(), -24.31999999999971) assert ph.total_realised_pnl() == 0.0 assert np.isclose(ph.total_pnl(), -24.31999999999971)
def test_basic_long_equities_position(): """ Tests that the properties on the Position are calculated for a simple long equities position. """ # Initial long details asset = 'EQ:MSFT' quantity = 100 dt = pd.Timestamp('2020-06-16 15:00:00', tz=pytz.UTC) price = 193.74 order_id = 123 commission = 1.0 # Create the initial transaction and position transaction = Transaction(asset, quantity=quantity, dt=dt, price=price, order_id=order_id, commission=commission) position = Position.open_from_transaction(transaction) assert position.asset == asset assert position.current_price == price assert position.current_dt == dt # Update the market price new_market_price = 192.80 new_dt = pd.Timestamp('2020-06-16 16:00:00', tz=pytz.UTC) position.update_current_price(new_market_price, new_dt) assert position.current_price == new_market_price assert position.current_dt == new_dt assert position.buy_quantity == 100 assert position.sell_quantity == 0 assert position.avg_bought == 193.74 assert position.avg_sold == 0.0 assert position.commission == 1.0 assert position.direction == 1 assert position.market_value == 19280.0 assert position.avg_price == 193.75 assert position.net_quantity == 100 assert position.total_bought == 19374.0 assert position.total_sold == 0.0 assert position.net_total == -19374.0 assert position.net_incl_commission == -19375.0 assert np.isclose(position.unrealised_pnl, -95.0) assert np.isclose(position.realised_pnl, 0.0)
def test_update_commission(): """ Tests the 'update_commission' method to ensure commission is correctly set on the Position entities. """ ph = PositionHandler() # Asset 1 asset1 = Equity('Amazon, Inc.', 'AMZN') dt1 = pd.Timestamp('2015-05-06') trans_pos_1 = Transaction(asset1.symbol, quantity=75, dt=dt1, price=483.45, order_id=1, commission=0.0) ph.transact_position(trans_pos_1) ph.update_commission(asset1.symbol, 15.97) # Asset 2 asset2 = Equity('Microsoft, Inc.', 'MSFT') dt2 = pd.Timestamp('2015-05-07') trans_pos_2 = Transaction(asset2.symbol, quantity=250, dt=dt2, price=142.58, order_id=2, commission=0.0) ph.transact_position(trans_pos_2) ph.update_commission(asset2.symbol, 8.35) # Check all total values assert ph.total_book_cost() == 71928.07 assert ph.total_market_value() == 71903.75 assert ph.total_unrealised_gain() == -24.31999999999971 assert ph.total_unrealised_percentage_gain() == -0.03381155646190282
def test_transaction_representation(): """ Tests that the Transaction representation correctly recreates the object. """ dt = pd.Timestamp('2015-05-06') asset = Equity('Apple, Inc.', 'AAPL') transaction = Transaction(asset, quantity=168, dt=dt, price=56.18, order_id=153) exp_repr = ( "Transaction(asset=Equity(name='Apple, Inc.', symbol='AAPL', tax_exempt=True), " "quantity=168, dt=2015-05-06 00:00:00, price=56.18, order_id=153)") assert repr(transaction) == exp_repr
def test_update_market_value_of_asset_negative_price(): """ Test update_market_value_of_asset for asset with negative price. """ start_dt = pd.Timestamp('2017-10-05 08:00:00', tz=pytz.UTC) later_dt = pd.Timestamp('2017-10-06 08:00:00', tz=pytz.UTC) port = Portfolio(start_dt) asset = 'EQ:AAA' port.subscribe_funds(later_dt, 100000.0) tn_asset = Transaction(asset=asset, quantity=100, dt=later_dt, price=567.0, order_id=1, commission=15.78) port.transact_asset(tn_asset) with pytest.raises(ValueError): port.update_market_value_of_asset(asset, -54.34, later_dt)
def test_update_market_value_of_asset_earlier_date(): """ Test update_market_value_of_asset for asset with current_trade_date in past """ start_dt = pd.Timestamp('2017-10-05 08:00:00', tz=pytz.UTC) earlier_dt = pd.Timestamp('2017-10-04 08:00:00', tz=pytz.UTC) later_dt = pd.Timestamp('2017-10-06 08:00:00', tz=pytz.UTC) port = Portfolio(start_dt, portfolio_id='1234') asset = 'EQ:AAA' port.subscribe_funds(later_dt, 100000.0) tn_asset = Transaction(asset=asset, quantity=100, dt=later_dt, price=567.0, order_id=1, commission=15.78) port.transact_asset(tn_asset) with pytest.raises(ValueError): port.update_market_value_of_asset(asset, 50.23, earlier_dt)
def test_update_for_incorrect_asset(): """ Tests that the 'update' method, when provided with a transaction with an asset that does not match the position's asset, raises an Exception. """ asset1 = Equity('Apple, Inc.', 'AAPL') asset2 = Equity('Amazon, Inc.', 'AMZN') position = Position(asset1, quantity=100, book_cost_pu=950.0, current_price=950.0) dt = pd.Timestamp('2015-05-06') transaction = Transaction(asset2, quantity=50, dt=dt, price=960.0, order_id=123, commission=None) with pytest.raises(Exception): position.update(transaction)
def test_position_short_long_short_long_ending_short(): """ Tests that the properties on the Position are calculated for four trades consisting of a short, long, short and long ending net short after all trades with varying quantities and market prices. """ # First trade (first short) asset = 'EQ:AGG' quantity = -762 dt = pd.Timestamp('2020-06-16 15:00:00', tz=pytz.UTC) price = 117.74 order_id = 100 commission = 5.35 transaction = Transaction(asset, quantity=quantity, dt=dt, price=price, order_id=order_id, commission=commission) position = Position.open_from_transaction(transaction) # Second trade (first long) quantity = 477 dt = pd.Timestamp('2020-06-16 16:00:00', tz=pytz.UTC) price = 117.875597 order_id = 101 commission = 2.31 transaction = Transaction(asset, quantity=quantity, dt=dt, price=price, order_id=order_id, commission=commission) position.transact(transaction) # Third trade (second short) quantity = -595 dt = pd.Timestamp('2020-06-16 17:00:00', tz=pytz.UTC) price = 117.74 order_id = 102 commission = 4.18 transaction = Transaction(asset, quantity=quantity, dt=dt, price=price, order_id=order_id, commission=commission) position.transact(transaction) # Fourth trade (second long), now net short quantity = 427 dt = pd.Timestamp('2020-06-16 18:00:00', tz=pytz.UTC) price = 117.793115 order_id = 103 commission = 2.06 transaction = Transaction(asset, quantity=quantity, dt=dt, price=price, order_id=order_id, commission=commission) position.transact(transaction) assert position.asset == asset assert position.current_price == price assert position.current_dt == dt assert position.buy_quantity == 904 assert position.sell_quantity == 1357 assert position.avg_bought == 117.83663702876107 assert position.avg_sold == 117.74 assert np.isclose(position.commission, 13.90) assert position.direction == -1 assert np.isclose(position.market_value, -53360.281095) assert position.avg_price == 117.73297715549005 assert position.net_quantity == -453 assert position.total_bought == 106524.31987400001 assert np.isclose(position.total_sold, 159773.18) assert np.isclose(position.net_total, 53248.86) assert np.isclose(position.net_incl_commission, 53234.95) assert np.isclose(position.unrealised_pnl, -27.242443563) assert np.isclose(position.realised_pnl, -98.0785254)
def test_position_three_longs_one_short_one_long(): """ Tests that the quantity and book cost are correctly calculated for three long transactions, followed by a partial closing position, followed by a new long position, all in the same asset. Buy 100 qty at £1.00 -> £100 Buy 100 qty at £2.00 -> £200 Buy 200 qty at £3.00 -> £600 Total qty after 3 longs is 400, with book cost £900 (£2.25 p/u) Sell 100 qty -> Book cost now £675 (25% holdings reduced), still at £2.25 p/u Buy 100 at £4.00 -> 400 Final qty is 400, but book cost is now £1,075 (£2.6875 p/u). """ asset = Equity('Apple, Inc.', 'AAPL') # Initial long position = Position(asset, quantity=100, book_cost_pu=1.0, current_price=1.0) # Second long dt = pd.Timestamp('2015-05-06') transaction = Transaction(asset, quantity=100, dt=dt, price=2.0, order_id=123, commission=None) position.update(transaction) assert position.quantity == 200 assert position.book_cost_pu == 1.5 # Third long dt = pd.Timestamp('2015-05-07') transaction = Transaction(asset, quantity=200, dt=dt, price=3.0, order_id=123, commission=None) position.update(transaction) assert position.quantity == 400 assert position.book_cost_pu == 2.25 # First short dt = pd.Timestamp('2015-05-08') transaction = Transaction(asset, quantity=-100, dt=dt, price=3.5, order_id=123, commission=None) position.update(transaction) assert position.quantity == 300 assert position.book_cost_pu == 2.25 # Final long dt = pd.Timestamp('2015-05-09') transaction = Transaction(asset, quantity=100, dt=dt, price=4.0, order_id=123, commission=None) position.update(transaction) assert position.quantity == 400 assert position.book_cost_pu == 2.6875 assert position.direction == 1.0 assert position.current_price == 4.0 assert position.market_value == 1600.0 assert position.unrealised_gain == 525.0 assert position.unrealised_percentage_gain == 48.837209302325576
def _execute_order(self, dt, portfolio_id, order): """ For a given portfolio ID string, create a Transaction instance from the provided Order and ensure the Portfolio is appropriately updated with the new information. Parameters ---------- dt : `pd.Timestamp` The current timestamp. portfolio_id : `str` The portfolio ID string. order : `Order` The Order instance to create the Transaction for. """ # Obtain a price for the asset, if no price then # raise a ValueError price_err_msg = ( "Could not obtain a latest market price for " "Asset with ticker symbol '%s'. Order with ID '%s' was " "not executed." % (order.asset, order.order_id)) bid_ask = self.data_handler.get_asset_latest_bid_ask_price( dt, order.asset) if bid_ask == (np.NaN, np.NaN): raise ValueError(price_err_msg) # Calculate the consideration and total commission # based on the commission model if order.direction > 0: price = bid_ask[1] else: price = bid_ask[0] consideration = round(price * order.quantity) total_commission = self.fee_model.calc_total_cost( order.asset, order.quantity, consideration, self) # Check that sufficient cash exists to carry out the # order, else scale it down est_total_cost = consideration + total_commission total_cash = self.portfolios[portfolio_id].total_cash scaled_quantity = order.quantity if est_total_cost > total_cash: print("WARNING: Estimated transaction size of %0.2f exceeds " "available cash of %0.2f. Reducing quantity to allow " "transaction to succeed." % (est_total_cost, total_cash)) scaled_quantity = int(floor(total_cash / price)) # Create a transaction entity and update the portfolio txn = Transaction(order.asset, scaled_quantity, self.current_dt, price, order.order_id, commission=total_commission) self.portfolios[portfolio_id].transact_asset(txn) print("(%s) - executed order: %s, qty: %s, price: %0.2f, " "consideration: %0.2f, commission: %0.2f, total: %0.2f" % (self.current_dt, order.asset, scaled_quantity, price, consideration, total_commission, consideration + total_commission))
def test_transact_asset_behaviour(): """ Test transact_asset raises for incorrect time Test transact_asset raises for transaction total cost exceeding total cash Test correct total_cash and total_securities_value for correct transaction (commission etc), correct portfolio event and correct time update """ start_dt = pd.Timestamp('2017-10-05 08:00:00', tz=pytz.UTC) earlier_dt = pd.Timestamp('2017-10-04 08:00:00', tz=pytz.UTC) later_dt = pd.Timestamp('2017-10-06 08:00:00', tz=pytz.UTC) even_later_dt = pd.Timestamp('2017-10-07 08:00:00', tz=pytz.UTC) port = Portfolio(start_dt) asset = 'EQ:AAA' # Test transact_asset raises for incorrect time tn_early = Transaction(asset=asset, quantity=100, dt=earlier_dt, price=567.0, order_id=1, commission=0.0) with pytest.raises(ValueError): port.transact_asset(tn_early) # Test transact_asset raises for transaction total # cost exceeding total cash port.subscribe_funds(later_dt, 1000.0) assert port.cash == 1000.0 assert port.total_market_value == 0.0 assert port.total_equity == 1000.0 pe_sub1 = PortfolioEvent(dt=later_dt, type='subscription', description="SUBSCRIPTION", debit=0.0, credit=1000.0, balance=1000.0) tn_large = Transaction(asset=asset, quantity=100, dt=later_dt, price=567.0, order_id=1, commission=15.78) with pytest.raises(ValueError): port.transact_asset(tn_large) # Test correct total_cash and total_securities_value # for correct transaction (commission etc), correct # portfolio event and correct time update port.subscribe_funds(even_later_dt, 99000.0) assert port.cash == 100000.0 assert port.total_market_value == 0.0 assert port.total_equity == 100000.0 pe_sub2 = PortfolioEvent(dt=even_later_dt, type='subscription', description="SUBSCRIPTION", debit=0.0, credit=99000.0, balance=100000.0) tn_even_later = Transaction(asset=asset, quantity=100, dt=even_later_dt, price=567.0, order_id=1, commission=15.78) port.transact_asset(tn_even_later) assert port.cash == 43284.22 assert port.total_market_value == 56700.00 assert port.total_equity == 99984.22 description = "LONG 100 EQ:AAA 567.00 07/10/2017" pe_tn = PortfolioEvent(dt=even_later_dt, type="asset_transaction", description=description, debit=56715.78, credit=0.0, balance=43284.22) assert port.history == [pe_sub1, pe_sub2, pe_tn] assert port.current_dt == even_later_dt