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National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Yield curve dynamics: Co-movements of latent global and Czech yield curves
 Šimáně, Jaromír ; Šopov, Boril (advisor) ; Novák, Jiří (referee)
This thesis focus on a yield curve modelling. It estimates unobserved "global" yield curve factors which drives changes in individual real yield curves. Yield curves of USD, GBP, JPY and EUR are considered and global factors are able to explain substantial part of their variances. The method is built on the Nelson-Siegel model which is implemented in a state-space form to be able to extract the unobserved yield factors. The estimated global yield factors are further used for explaining the evolution of the Czech yield curve. Their impact to the Czech yield curve is estimated in a time-varying regression which results show that the impact of the global factors is stronger during the years of the interventions of the Czech National Bank and thus suggests that the interventions help to transmit the global low interest rates to the Czech economy.
Detailed record
Yield curve dynamics: Co-movements of latent global and Czech yield curves
 Šimáně, Jaromír ; Šopov, Boril (advisor) ; Novák, Jiří (referee)
This thesis focus on a yield curve modelling. It estimates unobserved "global" yield curve factors which drives changes in individual real yield curves. Yield curves of USD, GBP, JPY and EUR are considered and global factors are able to explain substantial part of their variances. The method is built on the Nelson-Siegel model which is implemented in a state-space form to be able to extract the unobserved yield factors. The estimated global yield factors are further used for explaining the evolution of the Czech yield curve. Their impact to the Czech yield curve is estimated in a time-varying regression which results show that the impact of the global factors is stronger during the years of the interventions of the Czech National Bank and thus suggests that the interventions help to transmit the global low interest rates to the Czech economy.
Detailed record
Forecasting Term Structure of Crude Oil Markets Using Neural Networks
 Malinská, Barbora ; Baruník, Jozef (advisor) ; Polák, Petr (referee)
This thesis enhances rare literature focusing on modeling and forecasting of term structure of crude oil markets. Using dynamic Nelson-Siegel model, crude oil term structure is decomposed to three latent factors, which are further forecasted using both parametric and dynamic neural network approaches. In-sample fit using Nelson-Siegel model brings encouraging results and proves its applicability on crude oil futures prices. Forecasts obtained by focused time-delay neural network are in general more accurate than other benchmark models. Moreover, forecast error is decreasing with increasing time to maturity.
Detailed record

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