Volatilnost kriptovaluta
| Autor: | Branimir Cvitko Cicvarić |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Notitia-časopis za ekonomske, poslovne i društvene teme Volume 6 Issue 1 |
| ISSN: | 1849-9066 |
| Popis: | Many models have been developed to model, estimate and forecast financial time series volatility, amongst which are the most popular autoregressive conditional heteroscedasticity (ARCH) model introduced by Engle (1982) and generalized autoregressive conditional heteroscedasticity (GARCH) model introduced by Bollerslev (1986). The aim of this paper is to determine which type of ARCH/GARCH models can fit the best following cryptocurrencies: Ethereum, Neo, Ripple, Litecoin, Dash, Zcash and Dogecoin. It is found that the EGARCH model is the best fitted model for Ethereum, Zcash and Neo, PARCH model is the best fitted model for Ripple, while for Litecoin, Dash and Dogecoin it depends on the selected distribution and information criterion. Brojni modeli su razvijeni kako bi se modelirala, procijenila i predvidjela volatilnost financijskih vremenskih serija, među kojima su najpopularniji autoregresijski model uvjetne heteroskedastičnosti (ARCH) kojega je osmislio Engle (1982) i generalizirani model uvjetne heteroskedastičnosti (GARCH) kojega je osmislio Bollerslev (1986). Cilj ovog rada je odrediti koji oblik ARCH/GARCH modela najbolje odgovara sljedećim kriptovalutama: Ethereumu, Neu, Rippleu, Litecoinu, Dashu, Zcashu i Dogecoinu. Utvrđeno je kako EGARCH model najbolje odgovara Ethereumu, Zcashu i Neu, PARCH model najbolje odgovara Rippleu, dok za Litecoin, Dash i Dogecoin izbor najboljeg modela ovisi o odabranoj distribuciji i informacijskom kriteriju. |
| Databáze: | OpenAIRE |
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