(in Polish) Analiza fundamentalna i techniczna 2600-IADz2AFT
The course takes students from return analysis and testing the efficient market hypothesis through macroeconomic analysis, financial statements, and valuation, to the technical analysis.
Course coordinators
Learning outcomes
K_W01 – demonstrates advanced knowledge of research methodology and terminology within the discipline of economics and finance, as well as in complementary disciplines (management and quality sciences and legal sciences).
K_W02 – demonstrates advanced knowledge of the principles, procedures, and practices related to investment and data analysis.
K_W03 – demonstrates advanced knowledge of economic theories and models concerning the functioning of organizations and the economy as a whole, particularly in areas related to financial investment and data analysis.
K_W05 – demonstrates advanced knowledge of complex technological, social, political, legal, economic, and environmental processes and phenomena, including fundamental dilemmas of contemporary civilization and their impact on financial decision-making in organizations, the functioning of the economy as a whole, and the development of information systems within organizations.
K_U01 – applies theories from economics and finance, as well as complementary disciplines (management and quality sciences and legal sciences), to identify, diagnose, and solve problems related to financial decision-making in the areas of investment and data analysis.
K_U02 – correctly interprets complex technological, social, political, legal, economic, and environmental processes and phenomena and assesses their impact on financial decision-making in organizations and on the functioning of organizations and the economy as a whole.
K_U03 – appropriately selects sources and adapts existing methods and tools or develops new ones, including advanced information and communication technologies, to identify, diagnose, and solve problems related to financial decision-making in the areas of investment and data analysis.
K_U05 – proposes solutions to problems arising under unpredictable conditions.
K_U08 – plans, organizes, and leads teamwork; collaborates effectively within teams and takes a leading role in team activities.
K_K01 – demonstrates the ability to critically assess complex situations and phenomena related to financial investment and data analysis within organizations.
K_K02 – recognizes the importance and value of scientific knowledge in solving complex problems related to investment and data analysis within organizations and seeks expert advice in this process.
K_K03 – initiates activities that benefit the community, society, or the environment, as well as initiatives aimed at promoting the common good.
Assessment criteria
Empirical project prepared in Python.
Project assessment criteria:
• Accuracy of data collection, cleaning, and aggregation
• Analysis of returns, market efficiency, macroeconomic factors, or sectors
• Quality of fundamental analysis and construction of screening filters
• Accuracy of comparable company valuation or DCF valuation
• Accuracy of technical analysis and definition of trading rules
• Critical assessment of model risk and research limitations
• Quality of code, visualizations, and presentation of results
Practical placement
-
Bibliography
- K. Borowski, Analiza techniczna. Średnie ruchome, wskaźniki i oscylatory, Difin, Warszawa 2017
- K. Borowski, Analiza fundamentalna. Metody wyceny przedsiębiorstwa, Difin, 2014
- W. McKinney, Python w analizie danych. Przetwarzanie danych za pomocą pakietów pandas i NumPy oraz środowiska Jupyter. Wydanie III, Helion, 2023
Notes
|
Term 2026Z:
- |