Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Marwan Izzeldin"'
Autor:
Marwan Izzeldin, Yaz Gülnur Muradoğlu, Vasileios Pappas, Athina Petropoulou, Sheeja Sivaprasad
On February 24, 2022, Russia invaded the Ukraine. In this paper, we analyze the response of European and global stock markets alongside a representative sample of commodities. We compare the war response against the recent Covid-19 pandemic and the n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f062b019fb201819fb823948d36fe4b
https://doi.org/10.1016/j.irfa.2023.102598
https://doi.org/10.1016/j.irfa.2023.102598
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::16437fb6e476ce0f24db0ac1a69ccc7e
https://doi.org/10.2139/ssrn.4342139
https://doi.org/10.2139/ssrn.4342139
This paper introduces a novel class of volatility forecasting models that incorporate market realized (co)variances and semi(co)variances within the framework of a heterogeneous autoregressive (HAR) model. Our empirical analysis shows statistically
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc682b7e7a37920cf92aee49e892227a
This paper shows that generalizing the heterogeneous autoregressive model (HAR) with realized (co)variances and semi-(co)variances from the index leads to more accurate volatility forecasts. To circumvent the effects of the market microstructure nois
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac8e13166a7e1aadafe117b21169db52
https://eprints.lancs.ac.uk/id/eprint/170334/
https://eprints.lancs.ac.uk/id/eprint/170334/
We propose a Bayesian approach for inference in the stochastic ray production frontier (SRPF), which can model multiple-input–multiple-output production technologies even in case of zero output quantities, i.e., if some outputs are not produced by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0ee04018f1e92d8507c107832445a34
https://doi.org/10.1007/s00181-021-02060-0
https://doi.org/10.1007/s00181-021-02060-0
Publikováno v:
SSRN Electronic Journal.
This paper addresses the role of the right jump tail under the risk-neutral measure, as a proxy for fear-of-fear, in the return predictability implicit in the VIX market. A simulation establishes that the right jump tail dominates the left jump tail
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84f75219923b0a90ffe0a7eb41f6aea0
https://doi.org/10.2139/ssrn.4041591
https://doi.org/10.2139/ssrn.4041591
Publikováno v:
International Journal of Forecasting. 35:1318-1331
This paper proposes a cluster HAR-type model that adopts the hierarchical clustering technique to form the cascade of heterogeneous volatility components. In contrast to the conventional HAR-type models, the proposed cluster models are based on the r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0056670e079fced88f51fcf48dc97c2
https://doi.org/10.1016/j.ijforecast.2019.04.017
https://doi.org/10.1016/j.ijforecast.2019.04.017
Publikováno v:
Economics Letters. 181:160-163
We propose a filtration technique for making inference in systems with I ( 0 ) and I ( d ) variables using the fractionally co-integrated vector autoregressive (FCVAR) model with long memory in the co-integrating residuals. Superior predictions for t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::11ef83a57b398cdeef212d9108fea179
https://doi.org/10.1016/j.econlet.2019.05.031
https://doi.org/10.1016/j.econlet.2019.05.031
Publikováno v:
Journal of Forecasting. 39:56-68
Marine transport has grown rapidly as the result of globalization and sustainable world growth rates. Shipping market risks and uncertainty have also grown and need to be mitigated with the development of a more reliable procedure to predict changes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53f6c87ab1b5208cf8ecdf5adb108f13
https://doi.org/10.1002/for.2613
https://doi.org/10.1002/for.2613
Publikováno v:
Journal of the Royal Statistical Society Series A: Statistics in Society. 182:887-917
Summary The paper proposes a multivariate stochastic volatility model where shifts in volatility are endogenously driven by large return shocks. The model proposed generalizes the univariate stochastic volatility model of Dendramis and colleagues to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb5e79a047f00e5bdb54e0827d5eae63
https://doi.org/10.1111/rssa.12443
https://doi.org/10.1111/rssa.12443