I recently got flung into the world of quantum computing and I'm a beginner at coding. I was assigned to do the Portfolio Optimization tutorial of the Qiskit Finance Tutorials and input real data. Truth be told, I'm clueless. It's my understanding that I have to replace the "TICKER" and "RandomDataProvider" parts of the code in order to generate a real-life portfolio.
# Generate expected return and covariance matrix from (random) time-series stocks = [("TICKER%s" % i) for i in range(num_assets)] data = RandomDataProvider(tickers=stocks, start=datetime.datetime(2016,1,1), end=datetime.datetime(2016,1,30)) data.run() mu = data.get_period_return_mean_vector() sigma = data.get_period_return_covariance_matrix() I've imported Quandl and WikipediaDataProvider. I want to keep the number of assets the same, using Microsoft "MSFT", Disney "DIS", Nike "NKE", and Home Depot "HD" stocks. How might I apply this financial from Quandl to the tutorial? I've tried this so far:
num_assets = 4 # Generate expected return and covariance matrix from (random) time-series stocks = [("MSFT%s" , "DIS%s" , "NKE%s" , "HD%s" % i) for i in range(num_assets)] data = WikipediaDataProvider(tickers=stocks, token="xeesvko2fu6Bt9jg-B1T", start=datetime.datetime(2016,1,1), end=datetime.datetime(2016,1,30)) data.run() mu = data.get_period_return_mean_vector() sigma = data.get_period_return_covariance_matrix() But get the error:
--------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-59-19e4d9cde1e3> in <module> 3 # Generate expected return and covariance matrix from (random) time-series 4 stocks = [("MSFT%s" , "DIS%s" , "NKE%s" , "HD%s" % i) for i in range(num_assets)] ----> 5 data = WikipediaDataProvider(tickers=stocks, 6 token="xeesvko2fu6Bt9jg-B1T", 7 start=datetime.datetime(2016,1,1), TypeError: Can't instantiate abstract class WikipediaDataProvider with abstract methods run I apologize for my limited coding skills - I'm very new to all of this! Thank you in advance.
