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Description
| - This contribution focuses on the modelling of volatility of returns in Czech and US stock markets using a two-factor stochastic volatility model, i.e. the volatility process is modeled as a superposition of two autoregressive processes. As the volatility is not observable, the logarithm of the daily range is employed as the proxy. The estimation of parameters and volatility extraction are performed using the Kalman filter. We have obtained a meaningful decomposition of the volatility process into one highly persistent factor and another quickly mean-reverting factor. Moreover, we have shown that although the overall level of the volatility of returns is roughly the same in both markets, the US market exhibits substantially lower volatility of the volatility process.
- This contribution focuses on the modelling of volatility of returns in Czech and US stock markets using a two-factor stochastic volatility model, i.e. the volatility process is modeled as a superposition of two autoregressive processes. As the volatility is not observable, the logarithm of the daily range is employed as the proxy. The estimation of parameters and volatility extraction are performed using the Kalman filter. We have obtained a meaningful decomposition of the volatility process into one highly persistent factor and another quickly mean-reverting factor. Moreover, we have shown that although the overall level of the volatility of returns is roughly the same in both markets, the US market exhibits substantially lower volatility of the volatility process. (en)
- Předkládaný článek se zabývá modelováním volatility výnosů reprezentativních českých a amerických akcií pomocí dvoufaktorového modelu stochastické volatility, kdy proces volatility je modelován jako superpozice dvou nezávislých autoregresních procesů s odlišnou mírou perzistence. Jako proxy pro skutečnou volatilitu je použit logaritmus rozpětí mezi maximální a minimální cenou během obchodního dne. Odhad parametrů modelu a extrakce volatility je proveden pomocí Kalmanova filtru. Porovnání českých a amerických akcií ukazuje, že ačkoli průměrná úroveň volatility je na obou trzích přibližně stejná, variabilita procesu volatility je u českých akcií podstatně vyšší. (cs)
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Title
| - An Empirical Application of a Two-Factor Model of Stochastic Volatility
- An Empirical Application of a Two-Factor Model of Stochastic Volatility (en)
- Empirická aplikace dvoufaktorového modelu stochastické volatility (cs)
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skos:prefLabel
| - An Empirical Application of a Two-Factor Model of Stochastic Volatility
- An Empirical Application of a Two-Factor Model of Stochastic Volatility (en)
- Empirická aplikace dvoufaktorového modelu stochastické volatility (cs)
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skos:notation
| - RIV/67985556:_____/08:00314932!RIV09-GA0-67985556
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
| - P(GA402/07/0465), P(GA402/07/1113), P(LC06075), Z(AV0Z10750506)
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http://linked.open...iv/cisloPeriodika
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/67985556:_____/08:00314932
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - stochastic volatility; Kalman filter (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...odStatuVydavatele
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http://linked.open...ontrolniKodProRIV
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http://linked.open...i/riv/nazevZdroje
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...v/svazekPeriodika
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http://linked.open...iv/tvurceVysledku
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http://linked.open...n/vavai/riv/zamer
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issn
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number of pages
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