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On detecting and modeling periodic correlation in financial data

Broszkiewicz-Suwaj, Ewa; Makagon, Andrzej; Weron, Rafal; … - EconWPA - 2005

For many economic problems standard statistical analysis, based on the notion of stationarity, is not adequate. These include modeling seasonal decisions of consumers, forecasting business cycles and - as we show in the present article - modeling wholesale power market prices. We apply standard...

Persistent link: https://www.econbiz.de/10005407946

Formula I(1) and I(2): Race tracks for likelihood maximization algorithms of I(1) and I(2) cointegrated VAR models

Doornik, Jurgen A.; Mosconi, Rocco; Paruolo, Paolo - In: Econometrics 5 (2017) 4, pp. 1-30

This paper provides some test cases, called circuits, for the evaluation of Gaussian likelihood maximization algorithms of the cointegrated vector autoregressive model. Both I(1) and I(2) models are considered. The performance of algorithms is compared first in terms of effectiveness, defined as...

Persistent link: https://www.econbiz.de/10011995197

State-space models on the Stiefel manifold with a new approach to nonlinear filtering

Yang, Yukai; Bauwens, Luc - In: Econometrics 6 (2018) 4, pp. 1-22

We develop novel multivariate state-space models wherein the latent states evolve on the Stiefel manifold and follow a conditional matrix Langevin distribution. The latent states correspond to time-varying reduced rank parameter matrices, like the loadings in dynamic factor models and the...

Persistent link: https://www.econbiz.de/10011995230

Likelihood ratio tests of restrictions on common trends loading matrices in I(2) VAR Systems

Boswijk, H. Peter; Paruolo, Paolo - In: Econometrics 5 (2017) 3, pp. 1-17

Persistent link: https://www.econbiz.de/10011995238

Asymptotic theory for cointegration analysis when the cointegration rank is deficient

Bernstein, David H.; Nielsen, Bent - In: Econometrics 7 (2019) 1, pp. 1-24

We consider cointegration tests in the situation where the cointegration rank is deficient. This situation is of … interest in finite sample analysis and in relation to recent work on identification robust cointegration inference. We derive … asymptotic theory for tests for cointegration rank and for hypotheses on the cointegrating vectors. The limiting distributions …

Persistent link: https://www.econbiz.de/10012696221

Dynamic panel modeling of climate change

Phillips, Peter C. B. - In: Econometrics 8 (2020) 3, pp. 1-28

standard dynamic panel regression and cointegration techniques that have been used in earlier research. The findings reveal …

Persistent link: https://www.econbiz.de/10012696293

Return and risk of pairs trading using a simulation-based Bayesian procedure for predicting stable ratios of stock prices

Ardia, David; Gatarek, Lukasz T.; Hoogerheide, Lennart; … - In: Econometrics 4 (2016) 1, pp. 1-19

. A simulation-based Bayesian procedure is introduced for predicting stable stock price ratios, defined in a cointegration …

Persistent link: https://www.econbiz.de/10011755321

Unit root tests: The role of the univariate models implied by multivariate time series

Cappuccio, Nunzio; Lubian, Diego - In: Econometrics 4 (2016) 2, pp. 1-11

In cointegration analysis, it is customary to test the hypothesis of unit roots separately for each single time series …

Persistent link: https://www.econbiz.de/10011755326

Maximum likelihood estimation of the I(2) model under linear restrictions

Doornik, Jurgen A. - In: Econometrics 5 (2017) 2, pp. 1-20

Estimation of the I(2) cointegrated vector autoregressive (CVAR) model is considered. Without further restrictions, estimation of the I(1) model is by reduced-rank regression (Anderson (1951)). Maximum likelihood estimation of I(2) models, on the other hand, always requires iteration. This paper...

Persistent link: https://www.econbiz.de/10011755375

State Space Modelling of Cointegrated Systems using Subspace Algorithms

Izquierdo, Segismundo; Cesï¿½reo Hernï¿½ndez; … - EconWPA - 2005

The use of subspace algorithms for the identification of non-stationary cointegrated stochastic systems is a promising technique that is currently under discussion. A revision of the literature provides two distinct algorithms: State Space Aoki Time Series (SSATS) identification algorithm (Aoki...

Persistent link: https://www.econbiz.de/10005407877

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