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pro vyhledávání: '"Ristig, Alexander"'
We propose methods to infer jumps of a semi-martingale, which describes long-term price dynamics based on discrete, noisy, high-frequency observations. Different to the classical model of additive, centered market microstructure noise, we consider on
Externí odkaz:
http://arxiv.org/abs/2403.00819
Autor:
Okhrin, Ostap, Ristig, Alexander
Publikováno v:
In Journal of Multivariate Analysis May 2024 201
Understanding the structure of financial markets deals with suitably determining the functional relation between financial variables. In this respect, important variables are the trading activity, defined here as the number of trades $N$, the traded
Externí odkaz:
http://arxiv.org/abs/1803.04892
This note complements the inspiring work on dimensional analysis and market microstructure by Kyle and Obizhaeva [18]. Following closely these authors, our main result shows by a similar argument as usually applied in physics the following remarkable
Externí odkaz:
http://arxiv.org/abs/1702.05434
Akademický článek
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Autor:
Pohl, Mathias1 (AUTHOR) mathias.pohl@univie.ac.at, Ristig, Alexander1,2 (AUTHOR), Schachermayer, Walter2 (AUTHOR), Tangpi, Ludovic3 (AUTHOR)
Publikováno v:
Mathematical Programming. Jun2020, Vol. 181 Issue 2, p405-434. 30p.
Financial contagion and systemic risk measures are commonly derived from conditional quantiles by using imposed model assumptions such as a linear parametrization. In this paper, we provide model free measures for contagion and systemic risk which ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______133::d40178470cc24638872bef36c0368122
http://edoc.hu-berlin.de/18452/5247
http://edoc.hu-berlin.de/18452/5247
We propose an iterative procedure to efficiently estimate models with complex log-likelihood functions and the number of parameters relative to the observations being potentially high. Given consistent but inefficient estimates of sub-vectors of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9931e26b8d9105ebf9c11355aedefd62
http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/33146
http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/33146
We propose an iterative procedure to efficiently estimate models with complex log-likelihood functions and the number of parameters relative to the observations being potentially high. Given consistent but inefficient estimates of sub-vectors of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______133::5d515997055e20a54bcf054d709a5c97
http://edoc.hu-berlin.de/18452/5149
http://edoc.hu-berlin.de/18452/5149
Multiplicative error models (MEM) became a standard tool for modeling conditional durations of intraday transactions, realized volatilities and trading volumes. The parametric estimation of the corresponding multivariate model, the so-called vector M
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______133::c4767cf5c7cbedf192e1d6cf85ac6414
http://edoc.hu-berlin.de/18452/5080
http://edoc.hu-berlin.de/18452/5080