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Analysis of the impact of village funds as fiscal decentratlization policy on reducing poverty level of rural communities in Indonesia
Anam, Choirul ; Plaček, Michal (advisor) ; Nemec, Juraj (referee) ; Vaceková, Gabriela (referee)
Not only does decentralization transfer of powers and functions from central government to local governments, but also about how the people can stimulate rural development to gradually improve their welfare. In fact, not all countries that implement decentralization get the same results in terms of their impact on economic growth and poverty alleviation. This research applies an exploratory approach that is enhanced by structured interviews and field research, as well as an empirical approach that is strengthened by stepwise regression. The aim of this research is to see the interconnection between village funds policies and poverty alleviation in Indonesia. The results show that per capita village funds can reduce poverty even though it may differ between provinces. However, proportional of village funds has the opposite impact if they are overly dependent on the central government transfers. In addition, some of the research findings appear to contradict the theory due to the influence of the unique character and culture of Indonesian people. The village funds program in Indonesia has become a unique and challenging issue for researchers. Therefore, further research can be done by concentrating on the other impacts of village funds in Indonesia than poverty which is essential to enrich the...
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Logistic regression with applications in financial sector
Bílková, Kristýna ; Branda, Martin (advisor) ; Pešta, Michal (referee)
In this bachelor thesis binary logistic regression model is described. Its parameters are estimated by maximum likelihood method. Newton-Raphson's algorithm is used for enumeration of these estimates. There are defined some statistics for testing the significance of the coefficients. Then stepwise regression is desribed. For assessing the quality of the model Pearson's Chi Square Test and Hosmer-Lemeshow's Test of the goodness of fit are defined. Diversification abilitz of the model is illustrated bz the Loreny curve and is quantificated by Gini coefficient, Kolmogorov-Smirnov statistics and generalized coefficient of determination. The theoretical knowledge is applied to insurance area data.
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Risk factor modeling of Hedge Funds' strategies
Radosavčević, Aleksa ; Princ, Michael (advisor) ; Šopov, Boril (referee)
This thesis aims to identify main driving market risk factors of different strategies implemented by hedge funds by looking at correlation coefficients, implementing Principal Component Analysis and analyzing "loadings" for first three principal components, which explain the largest portion of the variation of hedge funds' returns. In the next step, a stepwise regression through iteration process includes and excludes market risk factors for each strategy, searching for the combination of risk factors which will offer a model with the best "fit", based on The Akaike Information Criterion - AIC and Bayesian Information Criterion - BIC. Lastly, to avoid counterfeit results and overcome model uncertainty issues a Bayesian Model Average - BMA approach was taken. Key words: Hedge Funds, hedge funds' strategies, market risk, principal component analysis, stepwise regression, Akaike Information Criterion, Bayesian Information Criterion, Bayesian Model Averaging Author's e-mail: aleksaradosavcevic@gmail.com Supervisor's e-mail: mp.princ@seznam.cz
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Logistic regression with applications in financial sector
Bílková, Kristýna ; Branda, Martin (advisor) ; Pešta, Michal (referee)
In this bachelor thesis binary logistic regression model is described. Its parameters are estimated by maximum likelihood method. Newton-Raphson's algorithm is used for enumeration of these estimates. There are defined some statistics for testing the significance of the coefficients. Then stepwise regression is desribed. For assessing the quality of the model Pearson's Chi Square Test and Hosmer-Lemeshow's Test of the goodness of fit are defined. Diversification abilitz of the model is illustrated bz the Loreny curve and is quantificated by Gini coefficient, Kolmogorov-Smirnov statistics and generalized coefficient of determination. The theoretical knowledge is applied to insurance area data.
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