Second article in two-part series on stock data analysis with Python released

WEST JORDAN, Utah - Sept. 26, 2016 - PRLog -- Curtis Miller released online his second article in a two-part series on stock market data analysis with Python. The article was released on September 26th, 2016 at 9:00 AM MDT.

The first article in the series, released last week, described obtaining and visualizing stock market data along with computing moving averages in Python. This was the most popular article on Curtis Miller's website to date, and was circulated on many other popular Python sites.

The second part in the series discusses developing and analyzing trading strategies, based on moving average crossover strategies. This includes defining rules for a trading strategy, developing methods for signal detection, backtesting, evaluation of results, and benchmarking. Curtis Miller provides code examples and functions for reproducing and improvising upon his methods.

Additionally, exercises are included at the end of the article to encourage readers to explore ideas not covered in depth in the article, in addition to practicing coding skills. The functions produced by completing these practice exercises are likely to be much more useful in an actual trading environment.

The content of the series was based on a lecture given by Curtis Miller at the University of Utah in September, 2016. It has been released to the public in blog form.

The article can be accessed at https://ntguardian.wordpress.com/2016/09/19/introduction-...