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Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F09%3A00331233%21RIV10-MSM-67985556
rdf:type
skos:Concept n20:Vysledek
dcterms:description
The paper presents an applied study of a multivariate AR(p) process fitted to daily data from U.S. commodity futures markets with the use of Bayesian statistics. In the first part a detailed description of the methods used is given. In the second part two BVAR models are chosen one with assumption of log-normal, the second with normal distribution of prices conditioned on the parameters. For a comparison two simple benchmark models are chosen that are commonly used in todays Financial Mathematics. The article compares the quality of predictions of all the models, tries to find an adequate rate of forgetting of information and questions the validity of Efficient Market Hypothesis in the semi-strong form. The paper presents an applied study of a multivariate AR(p) process fitted to daily data from U.S. commodity futures markets with the use of Bayesian statistics. In the first part a detailed description of the methods used is given. In the second part two BVAR models are chosen one with assumption of log-normal, the second with normal distribution of prices conditioned on the parameters. For a comparison two simple benchmark models are chosen that are commonly used in todays Financial Mathematics. The article compares the quality of predictions of all the models, tries to find an adequate rate of forgetting of information and questions the validity of Efficient Market Hypothesis in the semi-strong form.
dcterms:title
Study of a BVAR(p) process applied to U.S. commodity market data Study of a BVAR(p) process applied to U.S. commodity market data
skos:prefLabel
Study of a BVAR(p) process applied to U.S. commodity market data Study of a BVAR(p) process applied to U.S. commodity market data
skos:notation
RIV/67985556:_____/09:00331233!RIV10-MSM-67985556
n3:aktivita
n8:Z n8:P
n3:aktivity
P(2C06001), Z(AV0Z10750506)
n3:dodaniDat
n10:2010
n3:domaciTvurceVysledku
n12:3832856
n3:druhVysledku
n15:D
n3:duvernostUdaju
n7:S
n3:entitaPredkladatele
n17:predkladatel
n3:idSjednocenehoVysledku
344425
n3:idVysledku
RIV/67985556:_____/09:00331233
n3:jazykVysledku
n16:eng
n3:klicovaSlova
Vector Auto-regression; Forecasting; Financial; Bayesian; Efficient Markets
n3:klicoveSlovo
n6:Efficient%20Markets n6:Bayesian n6:Forecasting n6:Financial n6:Vector%20Auto-regression
n3:kontrolniKodProRIV
[75B7B00469DB]
n3:mistoKonaniAkce
Benátky
n3:mistoVydani
Venice
n3:nazevZdroje
Proceedings of World Academy of Science, Engineering and Technology, WCSET 2009
n3:obor
n13:BB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:projekt
n11:2C06001
n3:rokUplatneniVysledku
n10:2009
n3:tvurceVysledku
Šindelář, Jan
n3:typAkce
n18:WRD
n3:zahajeniAkce
2009-10-28+01:00
n3:zamer
n19:AV0Z10750506
s:issn
2070-3724
s:numberOfPages
12
n14:hasPublisher
Academic Science Research