Database Management in Financial Markets 2600-DIdz1ZBDRF
The analytical reports will cover, among others, the following topics: stock market volatility, the impact of non-financial factors, bond market modeling, and modeling the impact of financial and non-financial factors.
Databases used:
• International databases (e.g., World Bank and International Monetary Fund): Global Financial Development Database, Financial Structure Database, Financial Regulation Database, Deposit Insurance Database, Investor Protection Database, Creditor Protection Database, Macroprudential Policy Instruments Database, Eurostat, Reuters
• Domestic databases: Central Statistical Office (GUS), Polish Financial Supervision Authority (UKNF), National Bank of Poland (NBP).
Students will use linear, nonlinear, and panel models for financial market analysis. The course emphasizes the practical application of models for identifying trends and, under the instructor’s guidance, participation in conducting research on financial markets, in particular the stock and bond markets.
Issues related to sustainable development are also addressed.
Type of course
Course coordinators
Learning outcomes
Upon successful completion of the course, the student:
Knowledge
• Knows and understands quantitative and qualitative research methodologies used in financial market analysis, as well as terminology related to investment advisory and capital markets (K_W01).
• Knows and understands the principles of preparing analytical reports based on national and international databases (e.g., Eurostat, GUS, NBP, IMF, World Bank) (K_W02).
• Knows and understands the impact of social, legal, political, economic, and ecological processes (including ESG factors and sustainable development) on financial decision-making (K_W05).
Skills
• Uses national and international databases to prepare analytical reports on the stock market, bond market, and other financial instruments (K_U01).
• Correctly interprets the results of econometric and statistical analyses, including market volatility, trends, and relationships between variables (K_U02).
• Prepares and presents an analytical report, both written and oral, including critical interpretation of results (K_U03).
Social competences
• Applies critical evaluation to complex situations and phenomena related to investment advisory and capital markets in organizations, including assessing the implications of the Efficient Market Hypothesis (EMH) for investors using appropriate statistical tools, such as variance analysis in portfolio valuation and risk models (K_K01).
Assessment criteria
Written exam (test, open questions, problem-solving tasks), class participation, additional assignments, attendance control, term paper.
Learning outcomes will be continuously assessed through tasks performed by students during classes and finally verified during the course exam.
• Written test – on campus (including open questions, tabular tasks, and closed questions)
• Project
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Grading scale (maximum 100 points):
• 0–50% of points – grade 2 (fail)
• 51–60% of points – grade 3 (satisfactory)
• 61–70% of points – grade 3.5 (satisfactory plus)
• 71–80% of points – grade 4 (good)
• 81–90% of points – grade 4.5 (very good)
• 91–100% of points – grade 5 (excellent)
Practical placement
Not required for course completion
Bibliography
Lander, J. 2018. Język R dla każdego. Zaawansowane analizy i grafika statystyczna, APN Promise
Fabozzi, F. J., & Fabozzi, F. A. (2021). Bond Markets, Analysis, and Strategies (10th ed.). The MIT Press.
Brooks, C. (2019). Introductory Econometrics for Finance (4th ed.). Cambridge University Press.
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Term 2025Z:
• Lander, J. (2018). Język R dla każdego. Zaawansowane analizy i grafika statystyczna. APN Promise. |
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: