Národní úložiště šedé literatury Nalezeno 3 záznamů.  Hledání trvalo 0.00 vteřin. 
An Empirical Testing of CAPM Model on Crypto Currency Market
Bařina, Petr-Lev ; Michalíková, Eva (oponent) ; Doubravský, Karel (vedoucí práce)
This master’s thesis explores the application of the Capital Asset Pricing Model (CAPM) to the cryptocurrency market. It investigates the feasibility of CAPM in this emerging market, focusing on constructing the efficient frontier, tangency portfolio, minimum variance portfolio, and beta coefficient testing. Utilising quantitative methods, the thesis evaluates the linearity of beta coefficients and the influence of non-systematic risk on returns and assesses the validity of CAPM assumptions. The evidence is tested using a market portfolio and benchmark portfolio for the construction of the model and compare the findings. This empirical analysis contributes to understanding traditional financial models’ adaptability to digital asset markets.
Bitcoin volatility estimation
Bařina, Petr-Lev ; Pavláková Dočekalová, Marie (oponent) ; Luňáček, Jiří (vedoucí práce)
This bachelor thesis focuses on econometrics modelling and prediction of bitcoin volatility. The first part of the thesis is the theory of statistical properties of time series and models interpreting these properties. The practical part focuses on modelling, prediction, and evaluation of the accuracy of the predictions. The Key models are the Moving average model, the Autoregressive model, ARCH and the GARCH. The last part is a summary of results and proposals for improvement.
Bitcoin volatility estimation
Bařina, Petr-Lev ; Pavláková Dočekalová, Marie (oponent) ; Luňáček, Jiří (vedoucí práce)
This bachelor thesis focuses on econometrics modelling and prediction of bitcoin volatility. The first part of the thesis is the theory of statistical properties of time series and models interpreting these properties. The practical part focuses on modelling, prediction, and evaluation of the accuracy of the predictions. The Key models are the Moving average model, the Autoregressive model, ARCH and the GARCH. The last part is a summary of results and proposals for improvement.

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