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| Description
| - This paper deals with a conditional volatility GARCH model and model based on realized volatility which is able to account for the main empirical features observed in data in financial markets. Inspired by well-known Heterogeneous Market Hypothesis and by the asymmetric behavior of volatility between long and short time horizons, we used an additive cascade of different volatility components generated by the actions of different types of market participants. This additive volatility cascade leads to a simple AR-type model in the realized volatility with the feature of considering volatilities realized over different time horizons. HAR-RV model successfully achieves the purpose of reproducing the main empirical features of volatility like long memory, fat tails, and self-similarity in a very simple and parsimoniously way. The aim of this paper is to compare estimates got by simple AR(1)-GARCH(1, 1) model and HAR-RV model using data from the Czech stock market represented by PX index. In our paper we work with daily, weekly and monthly returns of mentioned stock index. Preliminary results on the estimation and forecast of the HAR - RV model on PX stock index data show remarkably good in-sample forecasting performance which steadily and substantially outperforms those of standard models represented by AR(1)–GARCH(1, 1) model. There will be also very fruitful to compare results estimated by mentioned models in different time periods. We especially mention an impact of the global financial crisis on Czech stock market volatility. Therefore, in this paper we will investigate pre-crisis, crisis and post-crisis periods.
- This paper deals with a conditional volatility GARCH model and model based on realized volatility which is able to account for the main empirical features observed in data in financial markets. Inspired by well-known Heterogeneous Market Hypothesis and by the asymmetric behavior of volatility between long and short time horizons, we used an additive cascade of different volatility components generated by the actions of different types of market participants. This additive volatility cascade leads to a simple AR-type model in the realized volatility with the feature of considering volatilities realized over different time horizons. HAR-RV model successfully achieves the purpose of reproducing the main empirical features of volatility like long memory, fat tails, and self-similarity in a very simple and parsimoniously way. The aim of this paper is to compare estimates got by simple AR(1)-GARCH(1, 1) model and HAR-RV model using data from the Czech stock market represented by PX index. In our paper we work with daily, weekly and monthly returns of mentioned stock index. Preliminary results on the estimation and forecast of the HAR - RV model on PX stock index data show remarkably good in-sample forecasting performance which steadily and substantially outperforms those of standard models represented by AR(1)–GARCH(1, 1) model. There will be also very fruitful to compare results estimated by mentioned models in different time periods. We especially mention an impact of the global financial crisis on Czech stock market volatility. Therefore, in this paper we will investigate pre-crisis, crisis and post-crisis periods. (en)
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| Title
| - HETEROGENEOUS AUTOREGRESSIVE MODEL OF THE REALIZED VOLATILITY: EVIDENCE FROM CZECH STOCK MARKET
- HETEROGENEOUS AUTOREGRESSIVE MODEL OF THE REALIZED VOLATILITY: EVIDENCE FROM CZECH STOCK MARKET (en)
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| skos:prefLabel
| - HETEROGENEOUS AUTOREGRESSIVE MODEL OF THE REALIZED VOLATILITY: EVIDENCE FROM CZECH STOCK MARKET
- HETEROGENEOUS AUTOREGRESSIVE MODEL OF THE REALIZED VOLATILITY: EVIDENCE FROM CZECH STOCK MARKET (en)
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| skos:notation
| - RIV/61989100:27510/12:86082800!RIV15-MSM-27510___
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| http://linked.open...avai/riv/aktivita
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| http://linked.open...avai/riv/aktivity
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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/61989100:27510/12:86082800
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| http://linked.open...riv/jazykVysledku
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| http://linked.open.../riv/klicovaSlova
| - autoregressive conditional heteroskedasticity, forecast, HAR-RV, heterogeneous market hypothesis, model estimation, realized volatility, stock market (en)
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| http://linked.open.../riv/klicoveSlovo
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| http://linked.open...ontrolniKodProRIV
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| http://linked.open...v/mistoKonaniAkce
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| http://linked.open...i/riv/mistoVydani
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| http://linked.open...i/riv/nazevZdroje
| - Advances in Finance and Accounting : proceedings of the 1st WSEAS International Conference on Finance, Accounting and Auditing (FAA '12) : Tomas Bata University in Zlin, Czech Republic, September 20-22, 2012
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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...UplatneniVysledku
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| http://linked.open...iv/tvurceVysledku
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| http://linked.open...vavai/riv/typAkce
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| http://linked.open.../riv/zahajeniAkce
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| issn
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| number of pages
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| http://purl.org/ne...btex#hasPublisher
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| https://schema.org/isbn
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| http://localhost/t...ganizacniJednotka
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