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Frank S. Nielsen

Personal Details

First Name:Frank
Middle Name:S.
Last Name:Nielsen
Suffix:
RePEc Short-ID:pni154
[This author has chosen not to make the email address public]
http://www.econ.au.dk/afn/PhD/nielsenfs.htm

Affiliation

(in no particular order)

Center for Research in Econometric Analysis of Time Series (CREATES)
Institut for Økonomi (Department of Economics and Business)
Aarhus Universitet (University of Aarhus)

Aarhus, Denmark
http://www.creates.au.dk/



Building 1322, DK-8000 Aarhus C
RePEc:edi:creaudk (more details at EDIRC)

School of Economics and Management
Institut for Økonomi (Department of Economics and Business)
Aarhus Universitet (University of Aarhus)

Aarhus, Denmark
http://www.econ.au.dk/

+45 8942 1133
+45 8613 6334
Building 1322, DK-8000 Aarhus C
RePEc:edi:anaaudk (more details at EDIRC)

Research output

as
Jump to: Working papers

Working papers

  1. Frank S. Nielsen, 2009. "Local Whittle estimation of multivariate fractionally integrated processes," CREATES Research Papers 2009-38, Department of Economics and Business Economics, Aarhus University.
  2. Per Frederiksen & Frank S. Nielsen & Morten Ørregaard Nielsen, 2008. "Local polynomial Whittle estimation of perturbed fractional processes," CREATES Research Papers 2008-29, Department of Economics and Business Economics, Aarhus University.
  3. Frank S. Nielsen, 2008. "Local polynomial Whittle estimation covering non-stationary fractional processes," CREATES Research Papers 2008-28, Department of Economics and Business Economics, Aarhus University.
  4. Niels Haldrup & Frank S. Nielsen & Morten Ørregaard Nielsen, 2007. "A Vector Autoregressive Model for Electricity Prices Subject to Long Memory and Regime Switching," CREATES Research Papers 2007-29, Department of Economics and Business Economics, Aarhus University.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Frank S. Nielsen, 2009. "Local Whittle estimation of multivariate fractionally integrated processes," CREATES Research Papers 2009-38, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Niels Haldrup & Robinson Kruse, 2014. "Discriminating between fractional integration and spurious long memory," CREATES Research Papers 2014-19, Department of Economics and Business Economics, Aarhus University.
    2. Kristoufek, Ladislav, 2015. "On the interplay between short and long term memory in the power-law cross-correlations setting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 218-222.
    3. de Truchis, Gilles, 2013. "Approximate Whittle analysis of fractional cointegration and the stock market synchronization issue," Economic Modelling, Elsevier, vol. 34(C), pages 98-105.
    4. Ergemen, Yunus Emre & Haldrup, Niels & Rodríguez-Caballero, Carlos Vladimir, 2016. "Common long-range dependence in a panel of hourly Nord Pool electricity prices and loads," Energy Economics, Elsevier, vol. 60(C), pages 79-96.
    5. Kristoufek, Ladislav, 2013. "Mixed-correlated ARFIMA processes for power-law cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6484-6493.

  2. Per Frederiksen & Frank S. Nielsen & Morten Ørregaard Nielsen, 2008. "Local polynomial Whittle estimation of perturbed fractional processes," CREATES Research Papers 2008-29, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Per Frederiksen & Morten Orregaard Nielsen, 2008. "Bias-Reduced Estimation of Long-Memory Stochastic Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(4), pages 496-512, Fall.
    2. Mccloskey, Adam & Perron, Pierre, 2013. "Memory Parameter Estimation In The Presence Of Level Shifts And Deterministic Trends," Econometric Theory, Cambridge University Press, vol. 29(06), pages 1196-1237, December.
    3. Robinson Kruse & Christian Leschinski & Michael Will, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers 2016-17, Department of Economics and Business Economics, Aarhus University.
    4. Hou, Jie & Perron, Pierre, 2014. "Modified local Whittle estimator for long memory processes in the presence of low frequency (and other) contaminations," Journal of Econometrics, Elsevier, vol. 182(2), pages 309-328.
    5. Sibbertsen, Philipp & Leschinski, Christian & Busch, Marie, 2018. "A multivariate test against spurious long memory," Journal of Econometrics, Elsevier, vol. 203(1), pages 33-49.
    6. Arteche, Josu & Orbe, Jesus, 2016. "A bootstrap approximation for the distribution of the Local Whittle estimator," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 645-660.
    7. Marcel Aloy & Gilles De Truchis, 2015. "Optimal Estimation Strategies for Bivariate Fractional Cointegration Systems and the Co-persistence Analysis of Stock Market Realized Volatilities," Post-Print hal-01410660, HAL.
    8. Wenger, Kai & Leschinski, Christian & Sibbertsen, Philipp, 2017. "The Memory of Volatility," Hannover Economic Papers (HEP) dp-601, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    9. Leschinski, Christian, 2017. "On the memory of products of long range dependent time series," Economics Letters, Elsevier, vol. 153(C), pages 72-76.
    10. Eduardo Rossi & Paolo Santucci de Magistris, 2011. "Estimation of long memory in integrated variance," CREATES Research Papers 2011-11, Department of Economics and Business Economics, Aarhus University.
    11. Frank S. Nielsen, 2008. "Local polynomial Whittle estimation covering non-stationary fractional processes," CREATES Research Papers 2008-28, Department of Economics and Business Economics, Aarhus University.
    12. Busch, Marie & Sibbertsen, Philipp, 2018. "An Overview of Modified Semiparametric Memory Estimation Methods," Hannover Economic Papers (HEP) dp-628, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    13. Gilles de Truchis & Benjamin Keddad, 2014. "On the Risk Comovements between the Crude Oil Market and the U.S. Dollar Exchange Rates," AMSE Working Papers 1421, Aix-Marseille School of Economics, France, revised May 2014.
    14. Gilles de Truchis & Elena Ivona Dumitrescu, 2019. "Narrow-band Weighted Nonlinear Least Squares Estimation of Unbalanced Cointegration Systems," EconomiX Working Papers 2019-14, University of Paris Nanterre, EconomiX.
    15. Torben G. Andersen & Rasmus T. Varneskov, 2018. "Consistent Inference for Predictive Regressions in Persistent VAR Economies," CREATES Research Papers 2018-09, Department of Economics and Business Economics, Aarhus University.
    16. Stelios Arvanitis & Antonis Demos, "undated". "A Class of Indirect Inference Estimators: Higher Order Asymptotics and Approximate Bias Correction (Revised)," DEOS Working Papers 1411, Athens University of Economics and Business, revised 23 Sep 2014.
    17. Per Frederiksen & Frank S. Nielsen, 2008. "Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood," CREATES Research Papers 2008-59, Department of Economics and Business Economics, Aarhus University.
    18. Shi, Wendong & Sun, Jingwei, 2016. "Aggregation and long-memory: An analysis based on the discrete Fourier transform," Economic Modelling, Elsevier, vol. 53(C), pages 470-476.
    19. Gilles de Truchis & Elena Ivona Dumitrescu & Florent Dubois, 2019. "Local Whittle Analysis of Stationary Unbalanced Fractional Cointegration Systems," EconomiX Working Papers 2019-15, University of Paris Nanterre, EconomiX.

  3. Frank S. Nielsen, 2008. "Local polynomial Whittle estimation covering non-stationary fractional processes," CREATES Research Papers 2008-28, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Frank S. Nielsen, 2009. "Local Whittle estimation of multivariate fractionally integrated processes," CREATES Research Papers 2009-38, Department of Economics and Business Economics, Aarhus University.
    2. Eduardo Rossi & Paolo Santucci de Magistris, 2011. "Estimation of long memory in integrated variance," CREATES Research Papers 2011-11, Department of Economics and Business Economics, Aarhus University.
    3. Frank S. Nielsen, 2011. "Local Whittle estimation of multi‐variate fractionally integrated processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(3), pages 317-335, May.
    4. Stelios Arvanitis & Antonis Demos, "undated". "A Class of Indirect Inference Estimators: Higher Order Asymptotics and Approximate Bias Correction (Revised)," DEOS Working Papers 1411, Athens University of Economics and Business, revised 23 Sep 2014.
    5. Lasak, Katarzyna, 2010. "Likelihood based testing for no fractional cointegration," Journal of Econometrics, Elsevier, vol. 158(1), pages 67-77, September.

  4. Niels Haldrup & Frank S. Nielsen & Morten Ørregaard Nielsen, 2007. "A Vector Autoregressive Model for Electricity Prices Subject to Long Memory and Regime Switching," CREATES Research Papers 2007-29, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Afanasyev, Dmitriy & Fedorova, Elena, 2015. "The long-term trends on Russian electricity market: comparison of empirical mode and wavelet decompositions," MPRA Paper 62391, University Library of Munich, Germany.
    2. Afanasyev, Dmitriy O. & Fedorova, Elena A. & Popov, Viktor U., 2015. "Fine structure of the price–demand relationship in the electricity market: Multi-scale correlation analysis," Energy Economics, Elsevier, vol. 51(C), pages 215-226.
    3. Luis A. Gil-Alana & Rangan Gupta, 2013. "Persistence and Cycles in Historical Oil Prices Data," Working Papers 201375, University of Pretoria, Department of Economics.
    4. Machin, Stephen & Marie, Olivier & Vujic, Suncica, 2012. "Youth Crime and Education Expansion," IZA Discussion Papers 6582, Institute of Labor Economics (IZA).
    5. Angelica Gianfreda & Luigi Grossi, 2011. "Forecasting Italian Electricity Zonal Prices with Exogenous Variables," Working Papers 01/2011, University of Verona, Department of Economics.
    6. Pircalabu, A. & Benth, F.E., 2017. "A regime-switching copula approach to modeling day-ahead prices in coupled electricity markets," Energy Economics, Elsevier, vol. 68(C), pages 283-302.
    7. Д.О. Афанасьев1 & * & Е.А. Федорова2 & **, 2019. "Краткосрочное Прогнозирование Цены Электроэнергии На Российском Рынке С Использованием Класса Моделей Scarx," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 55(1), pages 68-84, январь.
    8. Nowotarski, Jakub & Tomczyk, Jakub & Weron, Rafał, 2013. "Robust estimation and forecasting of the long-term seasonal component of electricity spot prices," Energy Economics, Elsevier, vol. 39(C), pages 13-27.
    9. António Rua & Paulo M.M. Rodrigues & João Pedro Pereira & Vasco Pesquita, 2016. "Market integration and the persistence of electricity prices," Working Papers w201609, Banco de Portugal, Economics and Research Department.
    10. Eichler, M. & Türk, D., 2013. "Fitting semiparametric Markov regime-switching models to electricity spot prices," Energy Economics, Elsevier, vol. 36(C), pages 614-624.
    11. Nima Nonejad, 2019. "Modeling Persistence and Parameter Instability in Historical Crude Oil Price Data Using a Gibbs Sampling Approach," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1687-1710, April.
    12. Michel Culot & Valérie Goffin & Steve Lawford & Sébastien De Meten & Yves Smeers, 2013. "Practical stochastic modelling of electricity prices," Post-Print hal-01021603, HAL.
    13. Janczura, Joanna & Trueck, Stefan & Weron, Rafal & Wolff, Rodney, 2012. "Identifying spikes and seasonal components in electricity spot price data: A guide to robust modeling," MPRA Paper 39277, University Library of Munich, Germany.
    14. Zachmann, Georg, 2013. "A stochastic fuel switching model for electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 5-13.
    15. Lovcha, Yuliya & Pérez Laborda, Àlex, 2016. "Structural shocks and dinamic elasticities in a long memory model of the US gasoline retail market," Working Papers 2072/261538, Universitat Rovira i Virgili, Department of Economics.
    16. Ergemen, Yunus Emre & Haldrup, Niels & Rodríguez-Caballero, Carlos Vladimir, 2016. "Common long-range dependence in a panel of hourly Nord Pool electricity prices and loads," Energy Economics, Elsevier, vol. 60(C), pages 79-96.
    17. Girum Dagnachew Abate & Niels Haldrup, 2017. "Space-time modeling of electricity spot prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    18. Wensheng Kang & Ronald A. Ratti & Kyung Hwan Yoon, 2015. "Time-varying effect of oil market shocks on the stock market," CAMA Working Papers 2015-35, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    19. Afanasyev, D. & Fedorova, E., 2018. "External and Internal Determinants on the Electricity Market: A Multi-Scale Adaptive Causal Analysis," Journal of the New Economic Association, New Economic Association, vol. 39(3), pages 33-54.
    20. Eduardo Rossi & Paolo Santucci de Magistris, 2013. "A No‐Arbitrage Fractional Cointegration Model for Futures and Spot Daily Ranges," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(1), pages 77-102, January.
    21. Xu, Weijun & Sun, Qi & Xiao, Weilin, 2012. "A new energy model to capture the behavior of energy price processes," Economic Modelling, Elsevier, vol. 29(5), pages 1585-1591.
    22. Jorge Barrientos Marín & Mónica Toro Martínez, 2017. "Análisis de los fundamentales del precio de la energía eléctrica: evidencia empírica para Colombia," Revista de Economía del Caribe 017148, Universidad del Norte.
    23. Massimiliano Caporin & Fulvio Fontini & Paolo Santucci De Magistris, 2017. "Price convergence within and between the Italian electricity day-ahead and dispatching services markets," "Marco Fanno" Working Papers 0215, Dipartimento di Scienze Economiche "Marco Fanno".
    24. Martin de Lagarde, Cyril & Lantz, Frédéric, 2018. "How renewable production depresses electricity prices: Evidence from the German market," Energy Policy, Elsevier, vol. 117(C), pages 263-277.
    25. Joanna Janczura, 2014. "Pricing electricity derivatives within a Markov regime-switching model: a risk premium approach," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 79(1), pages 1-30, February.
    26. Jorge Barrientos Marín & Mónica Toro Martínez, 2016. "Sobre Los Fundamentales Del Precio De La Energía Eléctrica: Evidencia Empírica Para Colombia," Grupo Microeconomía Aplicada 74, Universidad de Antioquia, Departamento de Economía.
    27. Florian Ziel & Rafal Weron, 2016. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate models," HSC Research Reports HSC/16/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    28. Eduardo Rossi & Paolo Santucci de Magistris, 2009. "A No Arbitrage Fractional Cointegration Analysis Of The Range Based Volatility," CREATES Research Papers 2009-31, Department of Economics and Business Economics, Aarhus University.
    29. Dias, José G. & Ramos, Sofia B., 2014. "Heterogeneous price dynamics in U.S. regional electricity markets," Energy Economics, Elsevier, vol. 46(C), pages 453-463.
    30. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2014. "The effects of sovereign rating drifts on financial return distributions: Evidence from the European Union," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 5-20.
    31. Ziel, Florian & Weron, Rafał, 2018. "Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks," Energy Economics, Elsevier, vol. 70(C), pages 396-420.
    32. Afanasyev, Dmitriy O. & Fedorova, Elena A., 2016. "The long-term trends on the electricity markets: Comparison of empirical mode and wavelet decompositions," Energy Economics, Elsevier, vol. 56(C), pages 432-442.
    33. Sun, Qi & Xu, Weijun & Xiao, Weilin, 2013. "An empirical estimation for mean-reverting coal prices with long memory," Economic Modelling, Elsevier, vol. 33(C), pages 174-181.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 6 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (5) 2008-06-27 2008-06-27 2009-08-22 2009-09-19 2009-10-10. Author is listed
  2. NEP-ETS: Econometric Time Series (4) 2008-06-27 2008-06-27 2009-09-19 2009-10-10
  3. NEP-ENE: Energy Economics (2) 2008-06-27 2009-08-22
  4. NEP-ORE: Operations Research (2) 2008-06-27 2009-10-10

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