Data and Analytics in Finance
- Work easily in R, import data in R, make basic manipulation with it to prepare data for calculations and export results of calculations.
- Apply methods of data analysis and understand their objectives.
- Understand limitation and relevance of the methods.
- Apply skills in data cleaning.
- Demonstrate the ability to work in different software environments for data analysis and to explain the choice of software.
- Make decision in finance on base of data analysis and prove them.
- Master ability of making decision on base of data analysis and proving them.
- Understand basic theories in analysis of financial data, invent and write a code for a particular task in finance data analysis.
- Data wrangling with R
- Optimization problems on financial data
- Fraud detection using machine learning
- 2021/2022 3rd module
- 2021/2022 4th module0.4 * Exam + 0.15 * Self-study students’ work + 0.15 * Seminar activities + 0.15 * Test 1 + 0.15 * Test 2
- Provost, F., & Fawcett, T. (2013). Data Science for Business : What You Need to Know About Data Mining and Data-Analytic Thinking (Vol. 1st ed). Beijing: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=619895
- Tsay, R. S. (2013). An Introduction to Analysis of Financial Data with R. Wiley.