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
