Coding 3: Python for Finance

Campus: 
Budapest
Academic Year: 
2019-2020
Term: 
Winter
US Credits: 
0
Course Description: 

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.

Learning Outcomes: 

Core Learning Area

Learning Outcome

Interpersonal Communication Skills

Participate in class discussions and problem solving exercises. Present arguments and findings. Objectively critique findings of fellow students.

Technology Skills

Use of Python with Jupyter notebook in problem solving. Tools needed from Linear algebra and Stochastic calculus are introduced during course.

Cultural Sensitivity and Diversity

Harness international and professional diversity of students in viewing issues and problems from different perspectives.

Quantitative Reasoning

Apply financial models and formulae.

Critical Thinking

Exercise the powers of inquiry, logical thinking and critical analysis. Interpret and evaluate theoretical arguments and empirical evidence.

Ethics and Social Responsibility

Evaluate and discuss challenges related to efficient coding, mathematical modeling and professional behavior.

Management Knowledge and Skills

Attain a broad understanding of the principles of quantitative evidence based financial decision making.

Assessment: 

Grading will be based on the total score out of 100, in line with CEU’s standard grading guidelines.

Minimum pass requirement: ability to apply basic concepts of coding for finance during the final exam.

Prerequisites: 

Successful completion of either of two Fall courses:

Programming Foundations with Python

Python for Beginners

Other courses or other evidence of previous experience in Python will be accepted at the instructors’ discretion. 

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