The application of quantitative methods in finance

The aim of this subject is to show practical aspects of using quantitative methods in finance based on time series, cross-sectional data, panel data. The students will be familiarized with: the fundamentals of statistics and testing statistical hypotheses, construction of econometric model: linear and non-linear based on time series and panel data. Basic panel models and also models with qualitative variable: logit, probit and tobit. Practical application of the production function, Cobb-Douglas, other production functions. Methods for measuring performance based on regression (SFA) and mathematical programming (DEA), presentation of empirical research. Elements of the financial position of the company: profit and loss (shaping the financial result) and the balance sheet. Methods of measuring the value of the company (the indexing method and the method of MVA, EVA). Model Du Pont. Estimating the primary risk models, credit scoring, logistic regression, discriminant analysis, linear re

The aim of this lecture is to familiarize students with quantitative methods, statistical and econometric analysis used in modeling financial phenomena, with emphasis on models of financial time series and panel data analysis models. Presented issues include the analysis of linear models, nonlinear models in particular production functions, models of varying quality and the access to linear programming. An additional aim of the course is to acquaint students with empirical and practical examples of the application of the presented statistical and econometric models in finance, particularly in banking and finance, and regional analysis.

Literatura podstawowa:

1. D. Baltagi, Econometrics Analysis of Panel Data (3rd ed.), 2005, J. Wiley&Sons.

2. Degryse, H., Kim, M., Ongena, S. (2009). Microeconometrics of banking: Methods, applications and results. Oxford University Press.

3. S. L. Sclove, (2013), A Course on Statistics for Finance, CRC Press, Taylor & Francis Group

Literatura uzupełniająca:

1. Hsiao C. (2003), Analysis of panel data, Second Edition, Cambridge University Press.

2. Van Hoose D. (2010), The Industrial Organization of Banking, Bank Behavior, Market Structure, and Regulation, Springer-Verlag, Berlin Heidelberg.

3. Wooldridge J. (2002), Econometric analysis of cross-section and panel data, The MIT Press.

4. Charnes A., W. Cooper, W. Golany, B. Seiford, A. Y. Lewin (1997), Data Envelopment Analysis, Theory, Methodology and Applications, Kluwer Academic Publishers Boston/Dordrecht/London.

Publikacje własne:

Małgorzata Pawłowska, Aleksandra Staniszewska, Impact of Fintech on the Level of Competition in the EU Banking Sector,W: red. Zied Ftiti , Hachmi Ben Ameur, Waël Louhichi, Financial and Economic Systems : Transformations and New Challenges,2021;

Małgorzata Pawłowska, Techniki cyfrowe w sektorze finansowym : wpływ na strukturę rynku i ryzyko,2022

Kryteria oceniania:

egzamin tradycyjny-pisemny: 0.00%

egzamin testowy: 0.00%

egzamin ustny: 50.00%

kolokwium: 0.00%

referaty/eseje: 50.00%

ocena z ćwiczeń: 0.00%

inne: 0.00%

The aim of this subject is to show practical aspects of using quantitative methods in finance based on time series, cross-sectional data, panel data. The students will be familiarized with: the fundamentals of statistics and testing statistical hypotheses, construction of econometric model: linear and non-linear based on time series and panel data. Basic panel models and also models with qualitative variable: logit, probit and tobit. Practical application of the production function, Cobb-Douglas, other production functions. Methods for measuring performance based on regression (SFA) and mathematical programming (DEA), presentation of empirical research. Elements of the financial position of the company: profit and loss (shaping the financial result) and the balance sheet. Methods of measuring the value of the company (the indexing method and the method of MVA, EVA). Model Du Pont. Estimating the primary risk models, credit scoring, logistic regression, discriminant analysis, linear re

The aim of this lecture is to familiarize students with quantitative methods, statistical and econometric analysis used in modeling financial phenomena, with emphasis on models of financial time series and panel data analysis models. Presented issues include the analysis of linear models, nonlinear models in particular production functions, models of varying quality and the access to linear programming. An additional aim of the course is to acquaint students with empirical and practical examples of the application of the presented statistical and econometric models in finance, particularly in banking and finance, and regional analysis.

Literatura podstawowa:

1. D. Baltagi, Econometrics Analysis of Panel Data (3rd ed.), 2005, J. Wiley&Sons.

2. Degryse, H., Kim, M., Ongena, S. (2009). Microeconometrics of banking: Methods, applications and results. Oxford University Press.

3. S. L. Sclove, (2013), A Course on Statistics for Finance, CRC Press, Taylor & Francis Group

Literatura uzupełniająca:

1. Hsiao C. (2003), Analysis of panel data, Second Edition, Cambridge University Press.

2. Van Hoose D. (2010), The Industrial Organization of Banking, Bank Behavior, Market Structure, and Regulation, Springer-Verlag, Berlin Heidelberg.

3. Wooldridge J. (2002), Econometric analysis of cross-section and panel data, The MIT Press.

4. Charnes A., W. Cooper, W. Golany, B. Seiford, A. Y. Lewin (1997), Data Envelopment Analysis, Theory, Methodology and Applications, Kluwer Academic Publishers Boston/Dordrecht/London.

Publikacje własne:

Małgorzata Pawłowska, Techniki cyfrowe w sektorze finansowym : wpływ na strukturę rynku i ryzyko,2022;

Małgorzata Pawłowska, Aleksandra Staniszewska, Impact of Fintech on the Level of Competition in the EU Banking Sector,W: red. Zied Ftiti , Hachmi Ben Ameur, Waël Louhichi, Financial and Economic Systems : Transformations and New Challenges,2021

Kryteria oceniania:

egzamin tradycyjny-pisemny: 0.00%

egzamin testowy: 0.00%

egzamin ustny: 50.00%

kolokwium: 0.00%

referaty/eseje: 50.00%

ocena z ćwiczeń: 0.00%

inne: 0.00%

The aim of this subject is to show practical aspects of using quantitative methods in finance based on time series, cross-sectional data, panel data. The students will be familiarized with: the fundamentals of statistics and testing statistical hypotheses, construction of econometric model: linear and non-linear based on time series and panel data. Basic panel models and also models with qualitative variable: logit, probit and tobit. Practical application of the production function, Cobb-Douglas, other production functions. Methods for measuring performance based on regression (SFA) and mathematical programming (DEA), presentation of empirical research. Elements of the financial position of the company: profit and loss (shaping the financial result) and the balance sheet. Methods of measuring the value of the company (the indexing method and the method of MVA, EVA). Model Du Pont. Estimating the primary risk models, credit scoring, logistic regression, discriminant analysis, linear re

The aim of this lecture is to familiarize students with quantitative methods, statistical and econometric analysis used in modeling financial phenomena, with emphasis on models of financial time series and panel data analysis models. Presented issues include the analysis of linear models, nonlinear models in particular production functions, models of varying quality and the access to linear programming. An additional aim of the course is to acquaint students with empirical and practical examples of the application of the presented statistical and econometric models in finance, particularly in banking and finance, and regional analysis.

Literatura podstawowa:

1. D. Baltagi, Econometrics Analysis of Panel Data (3rd ed.), 2005, J. Wiley&Sons.

2. Degryse, H., Kim, M., Ongena, S. (2009). Microeconometrics of banking: Methods, applications and results. Oxford University Press.

3. S. L. Sclove, (2013), A Course on Statistics for Finance, CRC Press, Taylor & Francis Group

Literatura uzupełniająca:

1. Hsiao C. (2003), Analysis of panel data, Second Edition, Cambridge University Press.

2. Van Hoose D. (2010), The Industrial Organization of Banking, Bank Behavior, Market Structure, and Regulation, Springer-Verlag, Berlin Heidelberg.

3. Wooldridge J. (2002), Econometric analysis of cross-section and panel data, The MIT Press.

4. Charnes A., W. Cooper, W. Golany, B. Seiford, A. Y. Lewin (1997), Data Envelopment Analysis, Theory, Methodology and Applications, Kluwer Academic Publishers Boston/Dordrecht/London.

Publikacje własne:

Małgorzata Pawłowska, Techniki cyfrowe w sektorze finansowym : wpływ na strukturę rynku i ryzyko,2022;

Małgorzata Pawłowska, Aleksandra Staniszewska, Impact of Fintech on the Level of Competition in the EU Banking Sector,W: red. Zied Ftiti , Hachmi Ben Ameur, Waël Louhichi, Financial and Economic Systems : Transformations and New Challenges,2021

Kryteria oceniania:

egzamin tradycyjny-pisemny: 0.00%

egzamin testowy: 0.00%

egzamin ustny: 50.00%

kolokwium: 0.00%

referaty/eseje: 50.00%

ocena z ćwiczeń: 0.00%

inne: 0.00%