def calculate_positions_value(self):
multipliers = [
get_multiplier(symbol) for symbol in self._position_amounts.keys()
]
result = 0
for amount, price, multiplier in zip(self._position_amounts,
self._position_last_sale_prices,
multipliers):
result += amount * price * multiplier
return result
def execute_transaction(self, txn):
# Update Position
# ----------------
if 'contract' in txn.__dict__:
sid = (txn.sid, txn.contract)
else:
sid = txn.sid
position = self.positions[sid]
position.update(txn)
self.ensure_position_index(sid)
self._position_amounts[sid] = position.amount
# Max Leverage
# ---------------
# Calculate the maximum capital used and maximum leverage
transaction_cost = txn.price * txn.amount
self.cumulative_capital_used += transaction_cost
# * #
# now we update ending_mav and ending_total_value such that the performance tracker doesn't think we
# profited when in fact we just entered another position.
# how? just put a negative balance into cash_adjustment equal to the value of the position entered
self.cash_adjustment -= txn.price * txn.amount * get_multiplier(sid)
if math.fabs(self.cumulative_capital_used) > self.max_capital_used:
self.max_capital_used = math.fabs(self.cumulative_capital_used)
# We want to conveye a level, rather than a precise figure.
# round to the nearest 5,000 to keep the number easy on the eyes
self.max_capital_used = self.round_to_nearest(
self.max_capital_used,
base=5000
)
# we're adding a 10% cushion to the capital used.
self.max_leverage = 1.1 * \
self.max_capital_used / self.starting_mav
# add transaction to the list of processed transactions
if self.keep_transactions:
self.processed_transactions[txn.dt].append(txn)
def execute_transaction(self, txn):
# Update Position
# ----------------
if 'contract' in txn.__dict__:
sid = (txn.sid, txn.contract)
else:
sid = txn.sid
position = self.positions[sid]
position.update(txn)
self.ensure_position_index(sid)
self._position_amounts[sid] = position.amount
# Max Leverage
# ---------------
# Calculate the maximum capital used and maximum leverage
transaction_cost = txn.price * txn.amount
self.cumulative_capital_used += transaction_cost
# * #
# now we update ending_mav and ending_total_value such that the performance tracker doesn't think we
# profited when in fact we just entered another position.
# how? just put a negative balance into cash_adjustment equal to the value of the position entered
self.cash_adjustment -= txn.price * txn.amount * get_multiplier(sid)
if math.fabs(self.cumulative_capital_used) > self.max_capital_used:
self.max_capital_used = math.fabs(self.cumulative_capital_used)
# We want to conveye a level, rather than a precise figure.
# round to the nearest 5,000 to keep the number easy on the eyes
self.max_capital_used = self.round_to_nearest(
self.max_capital_used, base=5000)
# we're adding a 10% cushion to the capital used.
self.max_leverage = 1.1 * \
self.max_capital_used / self.starting_mav
# add transaction to the list of processed transactions
if self.keep_transactions:
self.processed_transactions[txn.dt].append(txn)
def calculate_positions_value(self):
multipliers = [get_multiplier(symbol) for symbol in self._position_amounts.keys()]
result = 0
for amount, price, multiplier in zip(self._position_amounts, self._position_last_sale_prices, multipliers):
result += amount * price * multiplier
return result
