000			01672nam a22002297a 4500
003			ZW-GwMSU
005			20240403082834.0
008			240403b |||||||| |||| 00| 0 eng d
040			_aMSU _bEnglish _cMSU _erda
050	0	0	_aHB139.T52 ECO
100	1		_aFasen, Vicky Maria _eauthor
245	1	0	_aTime series regression on integrated continuous-time processes with heavy and light tails _ccreated by Vicky Fasen
264	1		_aCambridge: _bCambridge University Press, _c2013
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
440			_aEconometric theory _vVolume 29, number 1
520	3		_aThe paper presents a cointegration model in continuous time, where the linear combinations of the integrated processes are modeled by a multivariate Ornstein–Uhlenbeck process. The integrated processes are defined as vector-valued Lévy processes with an additional noise term. Hence, if we observe the process at discrete time points, we obtain a multiple regression model. As an estimator for the regression parameter we use the least squares estimator. We show that it is a consistent estimator and derive its asymptotic behavior. The limit distribution is a ratio of functionals of Brownian motions and stable Lévy processes, whose characteristic triplets have an explicit analytic representation. In particular, we present the Wald and the t-ratio statistic and simulate asymptotic confidence intervals. For the proofs we derive some central limit theorems for multivariate Ornstein–Uhlenbeck processes.
650			_aTime series regression
856			_u10.1017/S0266466612000217
942			_2lcc _cJA
999			_c164629 _d164629