Project 2: Optimize Something Documentation

optimization.py

 

optimize_portfolio(sd=datetime.datetime(2008, 1, 1, 0, 0), ed=datetime.datetime(2009, 1, 1, 0, 0), syms=[‘GOOG’, ‘AAPL’, ‘GLD’, ‘XOM’], gen_plot=False)

This function should find the optimal allocations for a given set of stocks. You should optimize for maximum Sharpe
Ratio. The function should accept as input a list of symbols as well as start and end dates and return a list of
floats (as a one-dimensional numpy array) that represents the allocations to each of the equities. You can take
advantage of routines developed in the optional assess portfolio project to compute daily portfolio value and
statistics.

Parameters

• sd (datetime) – A datetime object that represents the start date, defaults to 1/1/2008
• ed (datetime) – A datetime object that represents the end date, defaults to 1/1/2009
• syms (list) – A list of symbols that make up the portfolio (note that your code should support any
  symbol in the data directory)
• gen_plot (bool) – If True, optionally create a plot named plot.png. The autograder will always call your
  code with gen_plot = False.

Returns

A tuple containing the portfolio allocations, cumulative return, average daily returns,
standard deviation of daily returns, and Sharpe ratio

Return type

tuple

test_code()

This function WILL NOT be called by the auto grader.