This week in Machine Learning for Trading I've implemented an optimizer using SciPy that takes any number of stock symbols and most effectively allocates one's portfolio among the provided options based upon previous data in a given date range. The metric for evaluating the profitability of a portfolio is based upon the Sharpe Ratio, which adjusts a stock's income against its risk.
This work correlates to work I'd done using optimizers to find the optimal behavior for a multi-agent system in the Reinforcement Learning class.
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