Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Michael Grabchak"'
Autor:
Yunfei Xia, Michael Grabchak
Publikováno v:
Financial Innovation, Vol 10, Iss 1, Pp 1-24 (2024)
Abstract We derive methods for risk-neutral pricing of multi-asset options, when log-returns jointly follow a multivariate tempered stable distribution. These lead to processes that are more realistic than the better known Brownian motion and stable
Externí odkaz:
https://doaj.org/article/9142de24c0b445239a304f8b2d032389
Autor:
Michael Grabchak, Eliana Christou
Publikováno v:
Financial Innovation, Vol 7, Iss 1, Pp 1-16 (2021)
Abstract In this paper we consider the problem of estimating expected shortfall (ES) for discrete time stochastic volatility (SV) models. Specifically, we develop Monte Carlo methods to evaluate ES for a variety of commonly used SV models. This inclu
Externí odkaz:
https://doaj.org/article/749760341edc422da6292602cbdefb3f
Publikováno v:
PLoS ONE, Vol 12, Iss 3, p e0173305 (2017)
Modern measures of diversity satisfy reasonable axioms, are parameterized to produce diversity profiles, can be expressed as an effective number of species to simplify their interpretation, and come with estimators that allow one to apply them to rea
Externí odkaz:
https://doaj.org/article/bb96477c32c747f5a11fbef83fdce6e6
Autor:
Zhiyi Zhang, Michael Grabchak
Publikováno v:
Entropy, Vol 15, Iss 6, Pp 1999-2011 (2013)
Zhang in 2012 introduced a nonparametric estimator of Shannon’s entropy, whose bias decays exponentially fast when the alphabet is finite. We propose a methodology to estimate the bias of this estimator. We then use it to construct a new estimator
Externí odkaz:
https://doaj.org/article/8310c22aa0a04537af30f2ac01d32dd1
Publikováno v:
Entropy, Vol 20, Iss 5, p 371 (2018)
This paper offers sufficient conditions for the Miller–Madow estimator and the jackknife estimator of entropy to have respective asymptotic normalities on countably infinite alphabets.
Externí odkaz:
https://doaj.org/article/857d8bced71d44a8a3f1f966a47e4b1b
Autor:
Michael Grabchak
Publikováno v:
The American Statistician. 77:127-133
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::285b5ff04a33aab797fb68b3cb27c4ee
https://doi.org/10.1080/00031305.2022.2115552
https://doi.org/10.1080/00031305.2022.2115552
Autor:
Lijuan Cao, Michael Grabchak
Publikováno v:
Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e1d9f1f0ecf1aaed02c8483015528032
https://doi.org/10.1145/3545945.3569857
https://doi.org/10.1145/3545945.3569857
Autor:
Michael Grabchak
Publikováno v:
Methodology and Computing in Applied Probability. 24:1877-1890
Discrete tempered stable distributions are a large and flexible class of models for heavy tailed and overdispersed count data. In this paper we derive various properties of these distributions and develop an exact simulation method based on rejection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e8a2f773a9262ec12e849bf555ed2f7
https://doi.org/10.1007/s11009-021-09904-3
https://doi.org/10.1007/s11009-021-09904-3
Autor:
Michael Grabchak, Piergiacomo Sabino
Publikováno v:
Statistics and Computing. 33
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78990ebb8b769db0e63a86875ac0da2c
https://doi.org/10.1007/s11222-022-10165-4
https://doi.org/10.1007/s11222-022-10165-4
Autor:
Michael Grabchak, Isaac M. Sonin
Publikováno v:
Stochastics. 94:680-697
We prove an analogue of the classical zero-one law for both homogeneous and nonhomogeneous Markov chains (MC). Its almost precise formulation is simple: given any event A from the tail σ-algebra of...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c76744c03586c31f214a1c793321a50e
https://doi.org/10.1080/17442508.2021.1980569
https://doi.org/10.1080/17442508.2021.1980569