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Department of Economics and Business Economics

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Papers in peer-reviewed journals

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Franchi, M. & Johansen, S. (2017). Improved inference on cointegrating vectors in the presence of a near unit root using adjusted quantiles. Econometrics, 5(2). https://doi.org/10.3390/econometrics5020025

Petrova, D., Koopman, S. J. M., Ballester, J. & Rodó, X. (2017). Improving the long-lead predictability of El Niño using a novel forecasting scheme based on a dynamic components model. Climate Dynamics, 48(3), 1249–1276. https://doi.org/10.1007/s00382-016-3139-y

Christensen, K., Podolskij, M., Thamrongrat, N. & Veliyev, B. (2017). Inference from high-frequency data: A subsampling approach. Journal of Econometrics, 197(2), 245–272. https://doi.org/10.1016/j.jeconom.2016.07.010

Koopman, S. J. M., Lit, R. & Lukas, A. (2017). Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model. Journal of the American Statistical Association, 112(520), 1490-1503. https://doi.org/10.1080/01621459.2017.1302878

Ozturk, S. R., van der Wel, M. & van Dijk, D. (2017). Intraday price discovery in fragmented markets. Journal of Financial Markets, 32, 28-48. https://doi.org/10.1016/j.finmar.2016.10.001

Barra, I., Hoogerheide, L. & Koopman, S. J. M. (2017). Joint Bayesian Analysis of Parameters and States in Nonlinear non-Gaussian State Space Models. Journal of Applied Econometrics, 32(5), 1003–1026. https://doi.org/10.1002/jae.2533

Haldrup, N. & Vera-Valdés, E. (2017). Long memory, fractional integration, and cross sectional aggregation. Journal of Econometrics, 199(1), 1-11. https://doi.org/10.1016/j.jeconom.2017.03.001

Christensen, B. J. & Varneskov, R. T. (2017). Medium Band Least Squares Estimation of Fractional Cointegration in the Presence of Low-Frequency Contamination. Journal of Econometrics, 197(2), 218-244. https://doi.org/10.1016/j.jeconom.2016.07.009

Callot, L., Kock, A. B. & Medeiros, M. (2017). Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice. Journal of Applied Econometrics, 32(1), 140-158. https://doi.org/10.1002/jae.2512

Amado, C., Silvennoinen, A. & Terasvirta, T. (2017). Modelling and forecasting WIG20 daily returns. Central European Journal of Economic Modelling and Econometrics, 9(3), 173-200. http://cejeme.org/publishedarticles/2017-17-29-636423094307656250-5104.pdf

Podolskij, M., Schmidt, C. & Vetter, M. (2017). On U- and V-statistics for discontinuous Ito semimartingales. Annales de l'Institut Henri Poincaré, Probabilités et Statistiques, 53(3), 1007-1050. https://doi.org/10.1214/16-AIHP744

Podolskij, M. & Basse-O'Connor, A. (2017). On critical cases in limit theory for stationary increments Levy driven moving averages. Stochastics: An International Journal of Probability and Stochastic Processes , 89(1), 360-383. https://doi.org/10.1080/17442508.2016.1191493

Cavaliere, G., Nielsen, H. B. & Rahbek, A. (2017). On the Consistency of Bootstrap Testing for a Parameter on the Boundary of the Parameter Space. Journal of Time Series Analysis, 38(4), 513-534. https://doi.org/10.1111/jtsa.12214

Sauri, O. & Veraart, A. (2017). On the class of distributions of subordinated Lévy processes and bases. Stochastic Processes and Their Applications, 127(2), 475-496. https://doi.org/10.1016/j.spa.2016.06.015

Pakkanen, M., Sottinen, T. & Yazigi, A. (2017). On the conditional small ball property of multivariate Lévy-driven moving average processes. Stochastic Processes and Their Applications, 127(3), 749–782. https://doi.org/10.1016/j.spa.2016.06.025

Huang, Z., Wang, T. & Hansen, P. R. (2017). Option Pricing with the Realized GARCH Model: An Analytical Approximation Approach. Journal of Futures Markets, 37(4), 328-358. https://doi.org/10.1002/fut.21821

Hillebrand, E. & Proietti, T. (2017). Phase changes and seasonal warming in early instrumental temperature records. Journal of Climate, 30(17), 6795-6821. https://doi.org/10.1175/JCLI-D-16-0747.1

Boudt, K., Laurent, S., Lunde, A., Quaedvlieg, R. & Sauri, O. (2017). Positive semidefinite integrated covariance estimation, factorizations and asynchronicity. Journal of Econometrics, 196(2), 347–367. https://doi.org/10.1016/j.jeconom.2016.09.016

Basse-O'Connor, A., Lachieze-Rey, R. & Podolskij, M. (2017). Power variation for a class of stationary increments Levy driven moving averages. Annals of Probability, 45(6B), 4477-4528. https://doi.org/10.1214/16-AOP1170

Cavaliere, G., Nielsen, M. Ø. & Taylor, A. M. R. (2017). Quasi-maximum likelihood estimation and bootstrap inference in fractional time series models with heteroskedasticity of unknown form. Journal of Econometrics, 198(1), 165-188. https://doi.org/10.1016/j.jeconom.2017.01.008

Christoffersen, P., Du, D. & Elkamhi, R. (2017). Rare disasters, credit, and option market puzzles. Management Science, 63(5), 1341-1364. https://doi.org/10.1287/mnsc.2015.2361

Proietti, T. & Hillebrand, E. (2017). Seasonal changes in central England temperatures. Journal of the Royal Statistical Society, Series A (Statistics in Society), 180(3), 769-791. https://doi.org/10.1111/rssa.12229

Barndorff-Nielsen, O. E., Sauri, O. & Szozda, B. (2017). Selfdecomposable fields. Journal of Theoretical Probability, 30(1), 233-267. https://doi.org/10.1007/s10959-015-0630-z

Callot, L., Caner, M., Kock, A. B. & Riquelme, J. A. (2017). Sharp threshold detection based on sup-norm error rates in high-dimensional models. Journal of Business and Economic Statistics, 35(2), 250-264. https://doi.org/10.1080/07350015.2015.1052461

Terasvirta, T. (2017). Sir Clive Granger's contributions to nonlinear time series and econometrics. European Journal of Pure and Applied Mathematics, 10(1), 104-132. http://www.ejpam.com/index.php/ejpam/article/view/2952/491

Abate, G. D. & Haldrup, N. (2017). Space-time modeling of electricity spot prices. The Energy Journal, 38(5), 175-196. https://doi.org/10.5547/01956574.38.5.gaba

Amado, C. & Teräsvirta, T. (2017). Specification and testing of Multiplicative Time-Varying GARCH models with applications. Econometric Reviews, 36(4), 421-446. https://doi.org/10.1080/07474938.2014.977064

Calvori, F., Creal, D., Koopman, S. J. M. & Lucas, A. (2017). Testing for Parameter Instability across Different Modeling Frameworks. Journal of Financial Econometrics, 15(2), 223-246. https://doi.org/10.1093/jjfinec/nbw008

Kiefer, N. M. & Racine, J. S. (2017). The smooth colonel and the reverend find common ground. Econometric Reviews, 36(1-3), 241-256. https://doi.org/10.1080/07474938.2015.1114304

Dias, G. F. (2017). The time-varying GARCH-in-mean model. Economics Letters, 157, 129-132. https://doi.org/10.1016/j.econlet.2017.06.005

Osterrieder, D. & Schotman, P. C. (2017). The volatility of long-term bond returns: Persistent interest shocks and time-varying risk premiums. Review of Economics and Statistics, 99(5), 884-895. https://doi.org/10.1162/REST_a_00624

Bazzi, M., Blasques, F., Koopman, S. J. M. & Lucas, A. (2017). Time-Varying Transition Probabilities for Markov Regime Switching Models. Journal of Time Series Analysis, 38(3), 458-478. https://doi.org/10.1111/jtsa.12211

Ehlers, L. H., Simonsen, K. B., Jensen, M. B., Rasmussen, G. S. & Olesen, A. V. (2017). Unannounced versus announced hospital surveys: A nationwide cluster-randomized controlled trial. International Journal for Quality in Health Care, 29(3), 406-411. [mzx039]. https://doi.org/10.1093/intqhc/mzx039

Kanaya, S. (2017). Uniform Convergence Rates of Kernel-Based Nonparametric Estimators for Continuous Time Diffusion Processes: A Damping Function Approach. Econometric Theory, 33(4), 874–914. https://doi.org/10.1017/S0266466616000219

Hafner, C. M., Laurent, S. & Violante, F. (2017). Weak diffusion limits of dynamic conditional correlation models. Econometric Theory, 33(3), 691-716. https://doi.org/10.1017/S0266466616000128

Boyer, M. M. & Stentoft, L. (2017). Yes We Can (Price Derivatives on Survivor Indices). Risk Management and Insurance Review, 20(1), 37-62. https://doi.org/10.1111/rmir.12073

Pettenuzzo, D., Timmermann, A. & Valkanov, R. (2016). A MIDAS approach to modeling first and second moment dynamics. Journal of Econometrics, 193(2), 315-334. https://doi.org/10.1016/j.jeconom.2016.04.009

Dolatabadi, S., Nielsen, M. Ø. & Xu, K. (2016). A fractionally cointegrated VAR model with deterministic trends and application to commodity futures markets. Journal of Empirical Finance, 38(B), 623–639. https://doi.org/10.1016/j.jempfin.2015.11.005

Hurn, A. S., Silvennoinen, A. & Teräsvirta, T. (2016). A smooth transition logit model of the effects of deregulation in the electricity market. Journal of Applied Econometrics, 31(4), 707-733. https://doi.org/10.1002/jae.2452

Maasoumi, E. & Racine, J. S. (2016). A solution to aggregation and an application to multidimensional 'well-being' frontiers. Journal of Econometrics, 191(2), 374–383. https://doi.org/10.1016/j.jeconom.2015.12.008

Johansen, S. & Nielsen, B. (2016). Analysis of the Forward Search using some new results for martingales and empirical processes. Bernoulli, 22(2), 1131-1183. https://doi.org/10.3150/14-BEJ689

Hansen, N. S. & Lunde, A. (2016). Analyzing Oil Futures with a Dynamic Nelson-Siegel Model. Journal of Futures Markets, 36(2), 153-173. https://doi.org/10.1002/fut.21713

Johansen, S. & Nielsen, B. (2016). Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models. Scandinavian Journal of Statistics, 43(2), 321-348. https://doi.org/10.1111/sjos.12174

Ergemen, Y. E., Haldrup, N. & Rodríguez-Caballero, C. V. (2016). Common long-range dependence in a panel of hourly Nord Pool electricity prices and loads. Energy Economics, 60(November), 79-96. https://doi.org/10.1016/j.eneco.2016.09.008

Kock, A. B. (2016). Consistent and Conservative Model Selection with the Adaptive LASSO in Stationary and Nonstationary Autoregressions. Econometric Theory, 32(1), 243-259. https://doi.org/10.1017/S0266466615000304

Bollerslev, T., Patton, A. J. & Wang, W. (2016). Daily House Price Indices: Construction, Modeling, and Longer-run Predictions. Journal of Applied Econometrics, 31(6), 1005–1025. https://doi.org/10.1002/jae.2471

Christoffersen, P., Jacobs, K. & Li, B. (2016). Dynamic Jump Intensities and Risk Premiums in Crude Oil Futures and Options Markets. Journal of Derivatives, 24(2), 8-30. https://doi.org/10.3905/jod.2016.24.2.008

Lunde, A., Shephard, N. & Sheppard, K. (2016). Econometric analysis of vast covariance matrices using composite realized kernels and their application to portfolio choice. Journal of Business and Economic Statistics, 34(4), 504-518. https://doi.org/10.1080/07350015.2015.1064432

Christensen, B. J., Posch, O. & Van Der Wel, M. (2016). Estimating dynamic equilibrium models using mixed frequency macro and financial data. Journal of Econometrics, 194(1), 116-137. https://doi.org/10.1016/j.jeconom.2016.04.005

Kanaya, S. & Kristensen, D. (2016). Estimation of Stochastic Volatility Models by Nonparametric Filtering. Econometric Theory, 32(4), 861-916. https://doi.org/10.1017/S0266466615000079

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Revised 14.01.2021 -

Solveig Nygaard Sørensen