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State space modeling of run-off triangles
Kohout, Marek ; Cipra, Tomáš (advisor) ; Mazurová, Lucie (referee)
The main goal of this Diploma thesis is to describe an approach for modeling run-off triangles of nonlife insurance (calculation of IBNR reserve) based on state space models and apply the method to the selected run-off triangles. In difference from (Atherino a kol., 2010) the KFAS package in R software is used for modeling purposes in the numerical study at the end of the thesis. One provides a preview of various possibilities of data and model adjustment applied to the same run-off triangles in order to asses added value of these steps (logartihmic transformation of input data, interventions for outliers etc.). A special attention is devoted to lognormal modification of the basic state space model. An integral part of the numerical study in the thesis is a residual diagnostic of models and simulation approach to IBNR reserves. 1
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Seasonal state space modeling
Suk, Luboš ; Cipra, Tomáš (advisor) ; Zichová, Jitka (referee)
State space modeling represents a statistical framework for exponential smoo- thing methods and it is often used in time series modeling. This thesis descri- bes seasonal innovations state space models and focuses on recently suggested TBATS model. This model includes Box-Cox transformation, ARMA model for residuals and trigonometric representation of seasonality and it was designed to handle a broad spectrum of time series with complex types of seasonality inclu- ding multiple seasonality, high frequency of data, non-integer periods of seasonal components, and dual-calendar effects. The estimation of the parameters based on maximum likelihood and trigonometric representation of seasonality greatly reduce computational burden in this model. The universatility of TBATS model is demonstrated by four real data time series.
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Short-Term Determinants of the Idiosyncratic Sovereign Risk Premium: A Regime-Dependent Analysis for European Credit Default Swaps
Calice, Giovanni ; Miao, RongHui ; Štěrba, Filip ; Vašíček, Bořek
This study investigates the dynamic behavior of the sovereign CDS term premium for a group of European countries. The CDS term premium can be regarded as a forward- looking measure of idiosyncratic sovereign default risk as perceived by financial markets in real time. Using a Markov-switching unobserved component model, we decompose the daily CDS term premium into two unobserved components of statistically different nature (stationary and nonstationary) and study the determinants of their short-term dynamics. Specifically, we link these components in a vector autoregression to various daily observed financial market variables. We find that decomposition into the two components is vital for understanding the short-term dynamics of the entire CDS term premium. The strongest impacts can be attributed to CDS market liquidity, local stock returns, and overall risk aversion. By contrast, the impact of shocks from the sovereign bond market is rather muted. Therefore, the CDS market microstructure effect and investor sentiment play the main roles in sovereign risk evaluation in real time. Moreover, our results suggest that the response of the CDS term premium to shocks to financial variables is regime-dependent and can be ten times stronger during periods of high volatility.
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