European Union Portugal 2020 - Agriculture and Rural Development Foundation for Science and Technology European University Foundation
Suggestions, Compliments, Complaints Terms & Conditions of Use Projects Co-financed by the European Union
©2024 Instituto Politécnico de Coimbra. Todos os direitos reservados.

Search

Financial Satement Analysis

Home / Unidades Curriculares / Financial Satement Analysis

Base Knowledge

It is recommended that there is the knowledge previously acquired in the other curricular units of the course.

Teaching Methodologies

The teaching of the curricular unit is based on recent research materials and the experience obtained through practice. The pedagogy of the course is strongly interactive. It is intended an active participation of the students from the discussion of real cases.

The classes are theoretical-practical, with presence (and active participation) in classes optional, although strongly advised.

Learning Results

This curricular unit offers a broad and integrated approach to the analysis of financial statements of a company from the perspective of its contribution to the evaluation of current performance and financial condition and future. It is structured in order to achieve two main objectives: a) help the student understand the relationship between business decisions – investment, financing and operations – and the financial statements, and b) develop in the student a critical perspective of reading the financial statements from the perspective assessment of a company’s current and future performance and financial condition.

At the same time, the curricular unit introduces the basic principles of financial analysis of other entities, namely of sports corporations.

Program

 

1. Analysis of financial statements: an introduction
2. Supporting documents for company financial analysis
3. Annual report: case studies
4. Solvency and liquidity analysis
5. Profitability and productivity analysis
6. Cash flow analysis
7. Risk analysis
8. Earnings manipulation
9. Insolvency forecasting
10. Measures of financial constraints
11. Measures of economic performance
12. Introduction to analyzing the financial reports of other organizations: the example of SADs

Curricular Unit Teachers

Mário Jorge Sacramento dos Santos

Internship(s)

NAO

Bibliography

Basic:

  1. Carvalho das Neves, J. (2012). Análise e Relato Financeiro – Uma Visão Integrada de Gestão, Texto Editora.

  2. Lourenço, I., P. Ferreira, A. Simões e C. Pais (2013). IFRS Demonstrações Financeiras – Casos para Executivos, Edições Almedina.

  3. Palepu, Krinshna G., Paul M. Healy and Erik Peek (2019). Business Analysis and Valuation, Cengage Learning.

Adittional:

  1. Alexander, David, Anne Britton, Ann Jorissen, Martin Hoogendoorn and Carien Van Mourik (2017). International Financial Reporting and Analysis, Cengage Learning.

  2. Dean, Passard C. (2016). Analyzing and Understanding Annual Reports: Workbook for Financial Analysis, Pearson.

  3. Fridson, M., andF. Alvarez (2011). Financial Statement Analysis – A Practitioner’s Guide, Wiley Finance.

  4. Hawawini, G. e C. Viallet (2022). Finance for Executives – Managing for Value Creation, CENGAGE

  5. Mayes, Timothy R. (2018). Financial Analysis with Microsoft Excel, CENGAGE.

  6. Robinson, T. R., E. Henry, W. L. Pirie, andM. A. Broihahn (2012). International Financial Statement Analysis, Wiley/CFA Investment Series.

  7. Pasewark, William R. (2009). Understanding Corporate Annual Reports: A Financial Analysis Project, McGraw-Hill.
  8. Samuels, J., R. E. Brayshaw, and J. M. Craner (1995). Financial Statement Analysis in Europe, Chapman & Hall.
  9. Vernimmen, Pierre, Pascal Quiry, Maurizio Dallochio, Yann Le Fur, and Antonio Salvi (2014). Corporate Finance, Theory and Practice, Wiley.

Papers

1. Aymen, A., Sourour, B.S., Badreddine, M. (2018). The effect of annual report readability on financial analysts’ behaviour. Journal of Economics, Finance and Accounting (JEFA), V.5(1), p.26-37.
2. Baxamusa, M., A. Jalal and A. JHA (2018), It pays to partner with a firm that writes annual reports well, Journal of Banking and Finance, vol.92, pages 13-34.
3. Barboza, F., Kimura, H. & Altman, E. (2017). Machine learning models and bankruptcy prediction, Expert Systems with Applications, Volume 83, Pages 405-417.
4. Bateni, L., & Asghari, F. (2020). Bankruptcy prediction using logit and genetic algorithm models: A 29 comparative analysis. Computational Economics, 55(1), 335–348.
5. Bentéjac, C., Csörgő, A. & Martínez-Muñoz, G (2021). A comparative analysis of gradient boosting algorithms. Artif. Intell. Rev 54, 1937–1967.
6. Fauver, L., Loureiro, G. and Taboada, A. (2017). The Impact of Regulation on Information Quality and Performance around Seasoned Equity Offerings:
International Evidence. Journal of Corporate Finance. 44, p. 73-98.
7. Hwang, B. H. and H. H. Kim (2017), It pays to write well, Journal of Financial Economics, vol.124, pages 373-394.
8. Jabeur, B., S., Gharib, C., Mefteh-Wali, S. & Arfi, B., W. (2021). CatBoost model and artificial intelligence techniques for corporate failure prediction.
Technological Forecasting and Social Change.
9. Loureiro, Gilberto R. and Silva, Sónia, Earnings Management and Stock Price Crashes Post U.S. Cross-Delistings (March 5, 2021). International Review of Financial Analysis, 2022.
10. Schauer, Catharina & Elsas, Ralf & Breitkopf, Nikolas, 2019. “A new measure of fifinancial constraints applicable to private and public firms,” Journal of Banking & Finance, Elsevier, vol. 101(C), pages 270-295.
11. Shetty, S., Musa, M. & Brédart., X. (2022). Bankruptcy Prediction Using Machine Learning Techniques. Journal of Risk and Financial Management 15, no. 1: 35