Reporting Analytics in Financial Markets

3.0 credits

The objective of this course is to intro­duce students to the concepts and meth­odologies of financial reporting-based data analytics from a USER-driven rather than a producer-driven mindset. It is NOT to train students to become data scien­tists or data analysts, but rather to train business managers to utilize new types of data and techniques to solve business problems more effectively. The primary focus will be to build pre­dictive models using financial statement information that can predict future out­comes of interest such as future earnings; future stock prices; future economic growth etc. The first part will focus on traditional models based on sales, earn­ings per share etc., while the latter part will expand the repertoire to non-quan­titative data such as textual analysis of annual reports. The learning objectives are (i) bringing students up-to-date with the latest developments in the field of predic­tive analytics (as it pertains to financial reporting); and (ii) demonstrating how students can design and implement prediction models built on economic theory that harness the power of modern tools to more effectively solve business problems. Students will be taught to use these tools from the perspective of a business manager who uses the data once these are made available rather than a data analyst who creates the data and delivers them. The course will be general enough to be interesting to the wider student pool irre­spective of career tracks – but it is more likely to be chosen by students who have an interest in financial markets.