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2013 | 5 | nr 1 | 65--83
Tytuł artykułu

A Long-Run Relationship between Daily Prices on Two Markets: The Bayesian VAR(2)-MSF-SBEKK Model

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
We develop a fully Bayesian framework for analysis and comparison of two competing approaches to modelling daily prices on different markets. The first approach, prevailing in financial econometrics, amounts to assuming that logarithms of prices behave like a multivariate random walk; this approach describes logarithmic returns most often by the VAR(1) model with MGARCH (or sometimes MSV) disturbances. In the second approach, considered here, it is assumed that daily price levels are linked together and, thus, the error correction term is added to the usual VAR(1)-MGARCH or VAR(1)-MSV model for logarithmic returns, leading to a reduced rank VAR(2) specification for logarithms of prices. The model proposed in the paper uses a hybrid MSVMGARCH structure for VAR(2) disturbances. In order to keep cointegration modelling as simple as possible, we restrict to the case of two prices representing two different markets. The aim of the paper is to show how to check if a long-run relationship between daily prices exists and whether taking it into account influences our inference on volatility and short-run relations between returns on different markets. In the empirical example the daily values of the S&P500 index and the WTI oil price in the period 19.12.2005 - 30.09.2011 are jointly modelled. It is shown that, although the logarithms of the values of S&P500 and WTI oil price seem to be cointegrated, neglecting the error correction term leads to practically the same conclusions on volatility and conditional correlation as keeping it in the model. (original abstract)
Rocznik
Tom
5
Numer
Strony
65--83
Opis fizyczny
Twórcy
  • Cracow University of Economics, Poland
Bibliografia
  • [1] Bekiros S. and Diks C. (2008), The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality, Energy Economics 30, 2673-2685.
  • [2] Chang C., Lai J. and Chuang I. (2010), Futures hedging effectiveness under the segmentation of bear/bull energy markets, Energy Economics 32, 442-449.
  • [3] Ji Q. and Fan Y. (2011), A dynamic hedging approach for refineries in multiproduct oil markets, Energy 36, 881-887.
  • [4] Koop G., León-Gonzalez R. and Strachan R. (2009), Efficient posterior simulation for cointegrated models with priors on the cointegration space, Econometric Reviews 29, 224-242.
  • [5] Lenk P. (2009), Simulation pseudo-bias correction to the harmonic mean estimator of integrated likelihoods, Journal of Computational and Graphical Statistics 18, 941-960.
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  • [9] Osiewalski J. and Pajor A. (2009), Bayesian analysis for hybrid MSF- SBEKK models of multivariate volatility. Central European Journal of Economic Modelling and Econometrics 1, 179-202.
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  • [11] Osiewalski K. and Osiewalski J. (2012), Missing observations in daily returns - Bayesian inference within the MSF-SBEKK model. Central European Journal of Economic Modelling and Econometrics 4, 169-197.
  • [12] Pajor A. (2003), Procesy zmienności stochastycznej w bayesowskiej analizie finansowych szeregów czasowych (Stochastic Variance Processes in Bayesian analysis of Financial Time Series), Monografie: Prace Doktorskie Nr 2, Wydawnictwo Akademii Ekonomicznej w Krakowie, Kraków.
  • [13] Pajor A. (2011), A Bayesian analysis of exogeneity in models with latent variables. Central European Journal of Economic Modelling and Econometrics 4, 49-73.
  • [14] Strachan R. (2003), Valid Bayesian estimation of the cointegrating error correction model, Journal of Business & Economic Statistics, vol. 21, p. 185- 195.
  • [15] U.S. Energy Information Administration, Annual Energy Outlook 2013 - Early Release Overview. Available at http://www.eia.gov/forecasts/aeo/er/pdf/ 0383er%282013%29.pdf
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  • [17] Yu B. and Mykland P. (1998), Looking at Markov samplers through cusum path plots: a simple diagnostic idea, Statistics and Computing 8, 275-286.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.ekon-element-000171234689

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