National Repository of Grey Literature 46 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Nové metody ve schvalování úvěrů
Rychnovský, Michal ; Arlt, Josef (advisor) ; Pecáková, Iva (referee) ; Veselý, Petr (referee)
This thesis contributes to the field of applied statistics and financial modeling by analyzing mathematical models used in retail credit underwriting processes. Specifically, it has three goals. First, the thesis aims to challenge the performance criteria used by established statistical approaches and propose focusing on predictive power instead. Secondly, it compares the analytical leverage of the established and other suggested methods according to the newly proposed criteria. Third, the thesis seeks to develop and specify a new comprehensive profitability-based underwriting model and critically reflect on its strengths and weaknesses. In the first chapter I look into the area of probability of default modeling and argue for comparing the predictive power of the models in time rather than focusing on the random testing sample only, as typically suggested in the scholarly literature. For this purpose I use the concept of survival analysis and the Cox model in particular, and apply it to a real Czech banking data sample alongside the commonly used logistic regression model to compare the results using the Gini coefficient and lift characteristics. The Cox model performs comparably on the randomly chosen validation sample and clearly outperforms the logistic regression approach in the predictive power. In the second chapter, in the area of loss given default modeling I introduce two Cox-based models, and compare their predictive power with the standard approaches using the linear and logistic regression on a real data sample. Based on the modified coefficient of determination, the Cox model shows better predictions. Third chapter focuses on estimating the expected profit as an alternative to the risk estimation itself and building on the probability of default and loss given default models, I construct a comprehensive profitability model for fix-term retail loans underwriting. The model also incorporates various related risk-adjusted revenues and costs, allowing more precise results. Moreover, I propose four measures of profitability, including the risk-adjusted expected internal rate of return and return on equity and simulate the impact of the model on each of the measures. Finally, I discuss some weaknesses of these approaches and solve the problem of finding default or fraud concentrations in the portfolio. For this purpose, I introduce a new statistical measure based on a pre-defined expert critical default rate and compare the GUHA method with the classification tree method on a real data sample. While drawing on the comparison of different methods, this work contributes to the debates about survival analysis models used in financial modeling and profitability models used in credit underwriting.
Comparing the effectiveness of selected methods of cancer treatment. Prostate cancer, breast cancer and lung cancer via survival analysis
Šimonková, Karolína ; Šimpach, Ondřej (advisor) ; Pechholdová, Markéta (referee)
This diploma thesis deals with various ways of treatment of selected oncological diseases and the effectiveness of treatment methods and evaluation of the influence of various factors influencing the survival of patients. The activity of individual healing processes is evaluated by survival analysis. The subjects of the study are patients with breast, lung and prostate cancer. The survival analysis considers the sex of the patient, the age and stage of his illness, and other factors to avoid distorted results. The aim of the work is to find out the effects of selected therapeutic procedures on patients' health and to identify factors that have a significant impact on the survival of patients. The data for the diploma thesis was provided by the Institute of Health Information and Statistics of the Czech Republic, the Statistical Office, the National Cancer Register (NOR), the US SEER database and the German Breast Cancer Study.

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