The aim of the course is to provide a broad understanding of the principles and techniques of finance applications through the use of Python coding in Jupyter notebooks with intuitively visualized output. These objectives will be achieved by an interactive trading game, solving tasks and discussing theory.
Following the introductory class, the course is divided into the following sections. We begin with the fundamentals of data cleaning and reduction applied specifically to financial data with Python libraries (classes 1,2,3). Second, we discuss theory and numerical methods for the pricing of derivatives (classes 4,5,6,7). Third, students participate in a trading game supported by iPython notebooks for calculations (class 8). The course ends with an advanced topic (class 9) and an exam (class 10).
Understanding the problems covered in the course can be important for all students seeking a career in the expanding technology-intensive field of financial engineering. Please see “Further reading” below.