Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Vasyl Golosnoy"'
Publikováno v:
Metrika. 86:315-342
We focus on estimating daily integrated volatility (IV) by realized measures based on intraday returns following a discrete-time stochastic model with a pronounced intraday periodicity (IP). We demonstrate that neglecting the IP-impact on realized es
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ff0aa51d1869be54e6be3cae59897a5
https://doi.org/10.1007/s00184-022-00875-0
https://doi.org/10.1007/s00184-022-00875-0
Publikováno v:
Econometrics and Statistics. 23:36-52
Diurnal fluctuations in volatility are a well-documented stylized fact of intraday price data. This warrants an investigation how this intraday periodicity (IP) affects both finite sample as well as asymptotic properties of several popular realized e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77595e8a2cc2aed82b5ee09c16785d23
https://doi.org/10.1016/j.ecosta.2021.03.002
https://doi.org/10.1016/j.ecosta.2021.03.002
Publikováno v:
AStA Advances in Statistical Analysis.
We consider a linear measurement error model (MEM) with AR(1) process in the state equation which is widely used in applied research. This MEM could be equivalently re-written as ARMA(1,1) process, where the MA(1) parameter is related to the variance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9fd2ae7f9e11ebbbd39a445fc6fa38c
https://doi.org/10.1007/s10182-022-00462-8
https://doi.org/10.1007/s10182-022-00462-8
Publikováno v:
Applied Stochastic Models in Business and Industry. 37:1060-1079
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9073d3e44f93c66ef1bf809d652c32d5
https://doi.org/10.1002/asmb.2636
https://doi.org/10.1002/asmb.2636
Autor:
Vasyl Golosnoy, Miriam Isabel Seifert
Publikováno v:
Statistics. 55:475-488
We focus on sequential (online) monitoring of changes in the mean vector of high-dimensional persistent VARMA time series by using multivariate control charts. Applying either modified or residual ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::098dc9a0bd0c91dcb7c9d6dff1ede6d3
https://doi.org/10.1080/02331888.2021.1949013
https://doi.org/10.1080/02331888.2021.1949013
Publikováno v:
International Journal of Forecasting. 36:761-780
In many economic applications, it is convenient to model and forecast a variable of interest in logs rather than in levels. However, the reverse transformation from log forecasts to levels introduces a bias. This paper compares different bias correct
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a9d646a29766ace58f27e507207bc62
https://doi.org/10.1016/j.ijforecast.2019.09.001
https://doi.org/10.1016/j.ijforecast.2019.09.001
Publikováno v:
Econometrics and Statistics. 14:49-62
Statistical inferences for weights of the global minimum variance portfolio (GMVP) are of both theoretical and practical relevance for mean-variance portfolio selection. Daily realized GMVP weights depend only on realized covariance matrix computed f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5092a909c3975315ce14c1c93405d297
https://doi.org/10.1016/j.ecosta.2018.08.003
https://doi.org/10.1016/j.ecosta.2018.08.003
Autor:
Jan Vogler, Vasyl Golosnoy
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d19848113a6f4d18341794982bb44b3
https://doi.org/10.2139/ssrn.4077801
https://doi.org/10.2139/ssrn.4077801
Publikováno v:
WIREs Computational Statistics. 14
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5b8b22b1fffe7e10bbad6956837a2c4
https://doi.org/10.1002/wics.1556
https://doi.org/10.1002/wics.1556
Autor:
Vasyl Golosnoy, Bastian Gribisch
Publikováno v:
SSRN Electronic Journal.
We propose direct multiple time series models for predicting high dimensional vectors of observable realized global minimum variance portfolio (GMVP) weights computed based on high-frequency intraday returns. We apply Lasso regression techniques, dev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b42f74743c601d33891bb27dfea3da54
https://doi.org/10.2139/ssrn.3717695
https://doi.org/10.2139/ssrn.3717695