December 2018
Beginner to intermediate
684 pages
21h 9m
English
Content preview from Hands-On Machine Learning for Algorithmic Trading
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Scheduled trading and portfolio rebalancing
We will use the custom MeanReversion factor developed in the last chapter—see the implementation in alpha_factor_zipline_with_trades.py.
The Pipeline created by the compute_factors() method returns a table with a long and a short column for the 25 stocks with the largest negative and positive deviations of their last monthly return from its annual average, normalized by the standard deviation. It also limited the universe to the 500 stocks with the highest average trading volume over the last 30 trading days. before_trading_start() ensures the daily execution of the pipeline and the recording of the results, including the current prices.
The new rebalance() method submits trade orders to the exec_trades() ...