advanced-algorithmic-trading

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"""
Size the order to reflect the dollar-weighting of the
current equity account size based on pre-specified
ticker weights.
"""
ticker = initial_order.ticker
if initial_order.action == "EXIT":
# Obtain current quantity and liquidate
cur_quantity = portfolio.positions[ticker].quantity
if cur_quantity > 0:
initial_order.action = "SLD"
initial_order.quantity = cur_quantity
elif cur_quantity < 0:
initial_order.action = "BOT"
initial_order.quantity = cur_quantity
else:
initial_order.quantity = 0
else:
weight = self.ticker_weights[ticker]
# Determine total portfolio value, work out dollar weight
# and finally determine integer quantity of shares to purchase
price = portfolio.price_handler.tickers[ticker]["adj_close"]
price /= PriceParser.PRICE_MULTIPLIER
equity = portfolio.equity / PriceParser.PRICE_MULTIPLIER
dollar_weight = weight * equity
weighted_quantity = int(floor(dollar_weight / price))
# Update quantity
initial_order.quantity = weighted_quantity
return initial_order
25.4.3 Backtest Interface
In order to streamline the generation of multiple separate portfolios without excessive code
duplication a new file called monthly_rebalance_run.py has been created. This contains the
backtesting "boilerplate" code necessary to carry out a monthly full liquidation and rebalanced
backtest. The full file listing can be found at the end of the chapter.
To generate the separate portfolio backtests for this chapter the function run_monthly_rebalance
is imported from monthly_rebalance_run.py. It is then called with the benchmark ticker
(SPY), the ticker_weights dictionary containing the ETF proportions, the tearsheet title
text, start/end dates and account equity.
This makes it extremely straightforward to modify portfolio composition assuming availability
of the pricing data. As an example the code for the 60/40 US equities/bond mix is given by:
# equities_bonds_60_40_etf_portfolio_backtest.py
import datetime