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Oliver Blaskowitz

Personal Details

First Name:Oliver
Middle Name:
Last Name:Blaskowitz
Suffix:
RePEc Short-ID:pbl78
[This author has chosen not to make the email address public]

Affiliation

Institut für Statistik und Ökonometrie (ISÖ)
Wirtschaftswissenschaftliche Fakultät
Humboldt-Universität Berlin

Berlin, Germany
http://ise.wiwi.hu-berlin.de/
RePEc:edi:ishubde (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Blaskowitz, Oliver J. & Herwartz, Helmut, 2009. "On economic evaluation of directional forecasts," SFB 649 Discussion Papers 2009-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  2. Blaskowitz, Oliver J. & Herwartz, Helmut, 2008. "A note on the model selection risk for ANOVA based adaptive forecasting of the EURIBOR swap term structure," SFB 649 Discussion Papers 2008-064, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  3. Blaskowitz, Oliver J. & Herwartz, Helmut, 2008. "Testing directional forecast value in the presence of serial correlation," SFB 649 Discussion Papers 2008-073, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  4. Blaskowitz, Oliver J. & Herwartz, Helmut & Cadenas Santiago, Gonzalo de, 2005. "Modeling the FIBOR/EURIBOR swap term structure: An empirical approach," SFB 649 Discussion Papers 2005-024, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  5. Blaskowitz, Oliver J. & Herwartz, Helmut & de Cadenas Santiago, Gonzalo, 2005. "Modeling the FIBOR/EURIBOR Swap Term Structure: An Empirical Approach," Economics Working Papers 2005-04, Christian-Albrechts-University of Kiel, Department of Economics.
  6. Härdle, Wolfgang Karl & Blaskowitz, Oliver J. & Schmidt, Peter, 2004. "Skewness and Kurtosis Trades," Papers 2004,09, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    repec:hum:wpaper:sfb649dp2008-017 is not listed on IDEAS

Articles

  1. Blaskowitz, Oliver & Herwartz, Helmut, 2014. "Testing the value of directional forecasts in the presence of serial correlation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 30-42.
  2. Blaskowitz, Oliver & Herwartz, Helmut, 2011. "On economic evaluation of directional forecasts," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1058-1065, October.
  3. Oliver Blaskowitz & Helmut Herwartz, 2009. "Pca-Based Ex-Ante Forecasting Of Swap Term Structures," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 12(04), pages 465-489.
  4. Oliver Blaskowitz & Helmut Herwartz, 2009. "Adaptive forecasting of the EURIBOR swap term structure," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 575-594.

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. Blaskowitz, Oliver J. & Herwartz, Helmut, 2009. "On economic evaluation of directional forecasts," SFB 649 Discussion Papers 2009-052, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Emilian Dobrescu, 2014. "Attempting to Quantify the Accuracy of Complex Macroeconomic Forecasts," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-21, December.
    2. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.

  2. Blaskowitz, Oliver J. & Herwartz, Helmut, 2008. "Testing directional forecast value in the presence of serial correlation," SFB 649 Discussion Papers 2008-073, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Kajal Lahiri & Liu Yang, 2018. "Confidence Bands for ROC Curves With Serially Dependent Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 115-130, January.
    2. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    3. Bergmeir, Christoph & Costantini, Mauro & Benítez, José M., 2014. "On the usefulness of cross-validation for directional forecast evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 132-143.
    4. Tsuchiya, Yoichi, 2014. "Purchasing and supply managers provide early clues on the direction of the US economy: An application of a new market-timing test," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 599-618.

  3. Blaskowitz, Oliver J. & Herwartz, Helmut & Cadenas Santiago, Gonzalo de, 2005. "Modeling the FIBOR/EURIBOR swap term structure: An empirical approach," SFB 649 Discussion Papers 2005-024, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Blaskowitz, Oliver J. & Herwartz, Helmut, 2008. "Adaptive forecasting of the EURIBOR swap term structure," SFB 649 Discussion Papers 2008-017, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  4. Blaskowitz, Oliver J. & Herwartz, Helmut & de Cadenas Santiago, Gonzalo, 2005. "Modeling the FIBOR/EURIBOR Swap Term Structure: An Empirical Approach," Economics Working Papers 2005-04, Christian-Albrechts-University of Kiel, Department of Economics.

    Cited by:

    1. Blaskowitz, Oliver J. & Herwartz, Helmut, 2008. "Adaptive forecasting of the EURIBOR swap term structure," SFB 649 Discussion Papers 2008-017, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  5. Härdle, Wolfgang Karl & Blaskowitz, Oliver J. & Schmidt, Peter, 2004. "Skewness and Kurtosis Trades," Papers 2004,09, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).

    Cited by:

    1. Katarzyna Kopczewska, 2014. "L-moments skewness and kurtosis as measures of regional convergence and cohesion," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(4), pages 251-266, November.
    2. silvia Muzzioli & Alessio Ruggieri, 2013. "Option Implied Trees and Implied Moments," Department of Economics (DEMB) 0015, University of Modena and Reggio Emilia, Department of Economics "Marco Biagi".
    3. Julian Winkel & Wolfgang Karl Härdle, 2023. "Pricing Kernels and Risk Premia implied in Bitcoin Options," Risks, MDPI, vol. 11(5), pages 1-18, April.
    4. Fengler, Matthias R. & Härdle, Wolfgang & Mammen, Enno, 2003. "Implied volatility string dynamics," SFB 373 Discussion Papers 2003,54, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. Alizadeh, Amir H. & Gabrielsen, Alexandros, 2013. "Dynamics of credit spread moments of European corporate bond indexes," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3125-3144.
    6. Huimin Zhao & Jin E. Zhang & Eric C. Chang, 2013. "The Relation between Physical and Risk-neutral Cumulants," International Review of Finance, International Review of Finance Ltd., vol. 13(3), pages 345-381, September.

Articles

  1. Blaskowitz, Oliver & Herwartz, Helmut, 2014. "Testing the value of directional forecasts in the presence of serial correlation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 30-42.

    Cited by:

    1. Cribari-Neto, Francisco & Scher, Vinícius T. & Bayer, Fábio M., 2023. "Beta autoregressive moving average model selection with application to modeling and forecasting stored hydroelectric energy," International Journal of Forecasting, Elsevier, vol. 39(1), pages 98-109.
    2. Hambuckers, J. & Ulm, M., 2023. "On the role of interest rate differentials in the dynamic asymmetry of exchange rates," Economic Modelling, Elsevier, vol. 129(C).
    3. Casarin, Roberto & Costantini, Mauro & Paradiso, Antonio, 2021. "On the role of dependence in sticky price and sticky information Phillips curve: Modelling and forecasting," Economic Modelling, Elsevier, vol. 105(C).
    4. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
    5. Hartmann, Matthias & Herwartz, Helmut & Ulm, Maren, 2017. "A comparative assessment of alternative ex ante measures of inflation uncertainty," International Journal of Forecasting, Elsevier, vol. 33(1), pages 76-89.
    6. Kladívko, Kamil & Österholm, Pär, 2021. "Do market participants’ forecasts of financial variables outperform the random-walk benchmark?," Finance Research Letters, Elsevier, vol. 40(C).
    7. Kajal Lahiri & Liu Yang, 2018. "Confidence Bands for ROC Curves With Serially Dependent Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 115-130, January.
    8. Christian Pierdzioch & Monique B. Reid & Rangan Gupta, 2014. "On the Directional Accuracy of Inflation Forecasts: Evidence from South African Survey Data," Working Papers 201463, University of Pretoria, Department of Economics.
    9. G. Kontogeorgos & K. Lambrias, 2022. "Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 213-229, March.
    10. Kladivko, Kamil & Österholm, Pär, 2020. "Can Households Predict where the Macroeconomy is Headed?," Working Papers 2020:11, Örebro University, School of Business.
    11. Kiss, Tamás & Kladívko, Kamil & Silfverberg, Oliwer & Österholm, Pär, 2023. "Market participants or the random walk – who forecasts better? Evidence from micro-level survey data," Finance Research Letters, Elsevier, vol. 54(C).
    12. Santamaría-Bonfil, G. & Reyes-Ballesteros, A. & Gershenson, C., 2016. "Wind speed forecasting for wind farms: A method based on support vector regression," Renewable Energy, Elsevier, vol. 85(C), pages 790-809.
    13. Bergmeir, Christoph & Costantini, Mauro & Benítez, José M., 2014. "On the usefulness of cross-validation for directional forecast evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 132-143.
    14. Kontogeorgos, Georgios & Lambrias, Kyriacos, 2019. "An analysis of the Eurosystem/ECB projections," Working Paper Series 2291, European Central Bank.
    15. Constantin Bürgi & Dorine Boumans, 2020. "Categorical Forecasts and Non-Categorical Loss Functions," CESifo Working Paper Series 8266, CESifo.

  2. Blaskowitz, Oliver & Herwartz, Helmut, 2011. "On economic evaluation of directional forecasts," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1058-1065, October.

    Cited by:

    1. Cribari-Neto, Francisco & Scher, Vinícius T. & Bayer, Fábio M., 2023. "Beta autoregressive moving average model selection with application to modeling and forecasting stored hydroelectric energy," International Journal of Forecasting, Elsevier, vol. 39(1), pages 98-109.
    2. Helmut Herwartz & Konstantin A. Kholodilin, 2011. "In-Sample and Out-of-Sample Prediction of Stock Market Bubbles: Cross-Sectional Evidence," Discussion Papers of DIW Berlin 1173, DIW Berlin, German Institute for Economic Research.
    3. Costantini, Mauro & Crespo Cuaresma, Jesus & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Department of Economics Working Paper Series 176, WU Vienna University of Economics and Business.
    4. Herwartz, Helmut, 2017. "Stock return prediction under GARCH — An empirical assessment," International Journal of Forecasting, Elsevier, vol. 33(3), pages 569-580.
    5. Hambuckers, J. & Ulm, M., 2023. "On the role of interest rate differentials in the dynamic asymmetry of exchange rates," Economic Modelling, Elsevier, vol. 129(C).
    6. Casarin, Roberto & Costantini, Mauro & Paradiso, Antonio, 2021. "On the role of dependence in sticky price and sticky information Phillips curve: Modelling and forecasting," Economic Modelling, Elsevier, vol. 105(C).
    7. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
    8. Zhang, Pinyi & Ci, Bicong, 2020. "Deep belief network for gold price forecasting," Resources Policy, Elsevier, vol. 69(C).
    9. Yi Wei, 2021. "Absolute Value Constraint: The Reason for Invalid Performance Evaluation Results of Neural Network Models for Stock Price Prediction," Papers 2101.10942, arXiv.org, revised Mar 2021.
    10. Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova, 2018. "Exchange rate forecasting and the performance of currency portfolios," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 519-540, August.
    11. Christian Pierdzioch & Monique B. Reid & Rangan Gupta, 2014. "On the Directional Accuracy of Inflation Forecasts: Evidence from South African Survey Data," Working Papers 201463, University of Pretoria, Department of Economics.
    12. Ballestra, Luca Vincenzo & Guizzardi, Andrea & Palladini, Fabio, 2019. "Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1250-1262.
    13. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    14. Francisco Javier Eransus & Alfonso Novales Cinca, 2014. "Parameter Estimation Error in Tests of Predictive Performance under Discrete Loss Functions," Documentos de Trabajo del ICAE 2014-22, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    15. Haitham A. Al-Zoubi, 2024. "An affine model for short rates when monetary policy is path dependent," Review of Derivatives Research, Springer, vol. 27(2), pages 151-201, July.
    16. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    17. Santamaría-Bonfil, G. & Reyes-Ballesteros, A. & Gershenson, C., 2016. "Wind speed forecasting for wind farms: A method based on support vector regression," Renewable Energy, Elsevier, vol. 85(C), pages 790-809.
    18. Bergmeir, Christoph & Costantini, Mauro & Benítez, José M., 2014. "On the usefulness of cross-validation for directional forecast evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 132-143.
    19. Ince, Onur & Molodtsova, Tanya, 2017. "Rationality and forecasting accuracy of exchange rate expectations: Evidence from survey-based forecasts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 47(C), pages 131-151.
    20. Döpke, Jörg & Müller, Karsten & Tegtmeier, Lars, 2018. "The economic value of business cycle forecasts for potential investors – Evidence from Germany," Research in International Business and Finance, Elsevier, vol. 46(C), pages 445-461.
    21. Tsuchiya, Yoichi, 2014. "Purchasing and supply managers provide early clues on the direction of the US economy: An application of a new market-timing test," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 599-618.
    22. Constantin Bürgi & Dorine Boumans, 2020. "Categorical Forecasts and Non-Categorical Loss Functions," CESifo Working Paper Series 8266, CESifo.

  3. Oliver Blaskowitz & Helmut Herwartz, 2009. "Pca-Based Ex-Ante Forecasting Of Swap Term Structures," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 12(04), pages 465-489.

    Cited by:

    1. Blaskowitz, Oliver & Herwartz, Helmut, 2011. "On economic evaluation of directional forecasts," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1058-1065, October.

  4. Oliver Blaskowitz & Helmut Herwartz, 2009. "Adaptive forecasting of the EURIBOR swap term structure," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 575-594.

    Cited by:

    1. Cribari-Neto, Francisco & Scher, Vinícius T. & Bayer, Fábio M., 2023. "Beta autoregressive moving average model selection with application to modeling and forecasting stored hydroelectric energy," International Journal of Forecasting, Elsevier, vol. 39(1), pages 98-109.
    2. Costantini, Mauro & Crespo Cuaresma, Jesus & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Department of Economics Working Paper Series 176, WU Vienna University of Economics and Business.
    3. Wellmann, Dennis & Trück, Stefan, 2018. "Factors of the term structure of sovereign yield spreads," Journal of International Money and Finance, Elsevier, vol. 81(C), pages 56-75.
    4. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    5. Dauwe, Alexander & Moura, Marcelo L., 2011. "Forecasting the term structure of the Euro Market using Principal Component Analysis," Insper Working Papers wpe_233, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    6. Casarin, Roberto & Costantini, Mauro & Paradiso, Antonio, 2021. "On the role of dependence in sticky price and sticky information Phillips curve: Modelling and forecasting," Economic Modelling, Elsevier, vol. 105(C).
    7. Chen, Qiwei & Costantini, Mauro & Deschamps, Bruno, 2016. "How accurate are professional forecasts in Asia? Evidence from ten countries," International Journal of Forecasting, Elsevier, vol. 32(1), pages 154-167.
    8. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    9. Blaskowitz, Oliver & Herwartz, Helmut, 2014. "Testing the value of directional forecasts in the presence of serial correlation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 30-42.
    10. Blaskowitz, Oliver & Herwartz, Helmut, 2011. "On economic evaluation of directional forecasts," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1058-1065, October.
    11. Bergmeir, Christoph & Costantini, Mauro & Benítez, José M., 2014. "On the usefulness of cross-validation for directional forecast evaluation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 132-143.

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 1 paper 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-FIN: Finance (1) 2006-08-05
  2. NEP-FMK: Financial Markets (1) 2006-08-05
  3. NEP-FOR: Forecasting (1) 2006-08-05
  4. NEP-MAC: Macroeconomics (1) 2006-08-05
  5. NEP-MON: Monetary Economics (1) 2006-08-05

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