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Ingmar Nolte

Personal Details

First Name:Ingmar
Middle Name:
Last Name:Nolte
Suffix:
RePEc Short-ID:pno71
http://www.lancs.ac.uk/staff/nolte/
Terminal Degree:2008 Fachbereich Wirtschaftswissenschaften; Universität Konstanz (from RePEc Genealogy)

Affiliation

Department of Accounting and Finance
Management School
Lancaster University

Lancaster, United Kingdom
http://www.lancaster.ac.uk/lums/our-departments/accounting-and-finance/

:

LANCASTER LA1 4YX
RePEc:edi:dflanuk (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Vasios, Michalis & Payne, Richard & Nolte, Ingmar, 2015. "Profiting from Mimicking Strategies in Non-Anonymous Markets," MPRA Paper 61710, University Library of Munich, Germany.
  2. Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
  3. Sandra Lechner & Ingmar Nolte, 2009. "Customer Trading in the Foreign Exchange Market: Empirical Evidence from an Internet Trading Platform," Working Papers wp09-01, Warwick Business School, Finance Group.
  4. Ingmar Nolte & Valeri Voev, 2009. "Least Squares Inference on Integrated Volatility and the Relationship between Efficient Prices and Noise," CREATES Research Papers 2009-16, Department of Economics and Business Economics, Aarhus University.
  5. Ingmar Nolte & Valeri Voev, 2008. "Estimating High-Frequency Based (Co-) Variances: A Unified Approach," CREATES Research Papers 2008-31, Department of Economics and Business Economics, Aarhus University.
  6. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2006. "Estimating liquidity using information on the multivariate trading process," Working Papers 10, Department of Applied Econometrics, Warsaw School of Economics.

Articles

  1. Ingmar Nolte & Sandra Nolte, 2016. "The information content of retail investors' order flow," The European Journal of Finance, Taylor & Francis Journals, vol. 22(2), pages 80-104, January.
  2. Nolte, Ingmar & Xu, Qi, 2015. "The economic value of volatility timing with realized jumps," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 45-59.
  3. Nolte, Ingmar & Nolte, Sandra & Vasios, Michalis, 2014. "Sell-side analysts’ career concerns during banking stresses," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 424-441.
  4. Ingmar Nolte, 2012. "A detailed investigation of the disposition effect and individual trading behavior: a panel survival approach," The European Journal of Finance, Taylor & Francis Journals, vol. 18(10), pages 885-919, November.
  5. Ingmar Nolte & Sandra Nolte, 2012. "How do individual investors trade?," The European Journal of Finance, Taylor & Francis Journals, vol. 18(10), pages 921-947, November.
  6. Ingmar Nolte & Valeri Voev, 2011. "Least Squares Inference on Integrated Volatility and the Relationship Between Efficient Prices and Noise," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 94-108, April.
  7. Mark Britten-Jones & Anthony Neuberger & Ingmar Nolte, 2011. "Improved Inference in Regression with Overlapping Observations," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(5-6), pages 657-683, June.
  8. Adam-Müller, Axel F.A. & Nolte, Ingmar, 2011. "Cross hedging under multiplicative basis risk," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2956-2964, November.
  9. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2011. "An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(4), pages 669-707, June.
  10. Ingmar Nolte, 2008. "Modeling a Multivariate Transaction Process," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(1), pages 143-170, Winter.
  11. Nolte, Ingmar & Pohlmeier, Winfried, 2007. "Using forecasts of forecasters to forecast," International Journal of Forecasting, Elsevier, vol. 23(1), pages 15-28.
  12. Roman Liesenfeld & Ingmar Nolte & Winfried Pohlmeier, 2006. "Modelling financial transaction price movements: a dynamic integer count data model," Empirical Economics, Springer, vol. 30(4), pages 795-825, January.

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.

Wikipedia mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2011. "An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(4), pages 669-707, June.

    Mentioned in:

    1. An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics (JAE 2011) in ReplicationWiki ()

Working papers

  1. Vasios, Michalis & Payne, Richard & Nolte, Ingmar, 2015. "Profiting from Mimicking Strategies in Non-Anonymous Markets," MPRA Paper 61710, University Library of Munich, Germany.

    Cited by:

    1. Benos, Evangelos & Payne, Richard & Vasios, Michalis, 2016. "Centralized trading, transparency and interest rate swap market liquidity: evidence from the implementation of the Dodd-Frank Act," Bank of England working papers 580, Bank of England.

  2. Sandra Lechner & Ingmar Nolte, 2009. "Customer Trading in the Foreign Exchange Market: Empirical Evidence from an Internet Trading Platform," Working Papers wp09-01, Warwick Business School, Finance Group.

    Cited by:

    1. Peter Gomber & Jascha-Alexander Koch & Michael Siering, 2017. "Digital Finance and FinTech: current research and future research directions," Journal of Business Economics, Springer, vol. 87(5), pages 537-580, July.
    2. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    3. Michael R. King & Carol Osler & Dagfinn Rime, 2011. "Foreign exchange market structure, players and evolution," Working Paper 2011/10, Norges Bank.
    4. Carol Osler & Xuhang Wang, 2012. "The Microstructure of Currency Markets," Working Papers 49, Brandeis University, Department of Economics and International Businesss School.

  3. Ingmar Nolte & Valeri Voev, 2009. "Least Squares Inference on Integrated Volatility and the Relationship between Efficient Prices and Noise," CREATES Research Papers 2009-16, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Yuta Koike, 2013. "Limit Theorems for the Pre-averaged Hayashi-Yoshida Estimator with Random Sampling," Global COE Hi-Stat Discussion Paper Series gd12-276, Institute of Economic Research, Hitotsubashi University.
    2. Roxana Halbleib & Valeri Voev, 2011. "Forecasting Covariance Matrices: A Mixed Frequency Approach," CREATES Research Papers 2011-03, Department of Economics and Business Economics, Aarhus University.
    3. Selma Chaker, 2013. "Volatility and Liquidity Costs," Staff Working Papers 13-29, Bank of Canada.
    4. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 14(2), pages 383-417.

  4. Ingmar Nolte & Valeri Voev, 2008. "Estimating High-Frequency Based (Co-) Variances: A Unified Approach," CREATES Research Papers 2008-31, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Kim Christensen & Roel Oomen & Mark Podolskij, 2009. "Realised Quantile-Based Estimation of the Integrated Variance," CREATES Research Papers 2009-27, Department of Economics and Business Economics, Aarhus University.
    2. Roxana Halbleib & Valeri Voev, 2011. "Forecasting Covariance Matrices: A Mixed Frequency Approach," CREATES Research Papers 2011-03, Department of Economics and Business Economics, Aarhus University.
    3. Varneskov, Rasmus & Voev, Valeri, 2013. "The role of realized ex-post covariance measures and dynamic model choice on the quality of covariance forecasts," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 83-95.
    4. Valeri Voev, 2009. "On the Economic Evaluation of Volatility Forecasts," CREATES Research Papers 2009-56, Department of Economics and Business Economics, Aarhus University.
    5. Roxana Halbleib & Valeri Voev, 2016. "Forecasting Covariance Matrices: A Mixed Approach," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 14(2), pages 383-417.

Articles

  1. Nolte, Ingmar & Xu, Qi, 2015. "The economic value of volatility timing with realized jumps," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 45-59.

    Cited by:

    1. Omura, Akihiro & Li, Bin & Chung, Richard & Todorova, Neda, 2018. "Convenience yield, realised volatility and jumps: Evidence from non-ferrous metals," Economic Modelling, Elsevier, vol. 70(C), pages 496-510.

  2. Nolte, Ingmar & Nolte, Sandra & Vasios, Michalis, 2014. "Sell-side analysts’ career concerns during banking stresses," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 424-441.

    Cited by:

    1. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    2. Bernard Herskovic & Joao Ramos, 2016. "Acquiring information through peers," 2016 Meeting Papers 248, Society for Economic Dynamics.

  3. Ingmar Nolte, 2012. "A detailed investigation of the disposition effect and individual trading behavior: a panel survival approach," The European Journal of Finance, Taylor & Francis Journals, vol. 18(10), pages 885-919, November.

    Cited by:

    1. Urs Fischbacher & Gerson Hoffmann & Simeon Schudy, 2014. "The Causal Effect of Stop-Loss and Take-Gain Orders on the Disposition Effect," Working Paper Series of the Department of Economics, University of Konstanz 2014-10, Department of Economics, University of Konstanz.
    2. Maiko Koga, 2016. "Momentum trading behavior in the FX market: Evidence from Japanese retail investors," Economics Bulletin, AccessEcon, vol. 36(1), pages 92-96.
    3. Richards, Daniel W. & Willows, Gizelle D., 2018. "Who trades profusely? The characteristics of individual investors who trade frequently," Global Finance Journal, Elsevier, vol. 35(C), pages 1-11.
    4. Richards, Daniel W. & Fenton-O'Creevy, Mark & Rutterford, Janette & Kodwani, Devendra G., 2018. "Is the disposition effect related to investors’ reliance on System 1 and System 2 processes or their strategy of emotion regulation?," Journal of Economic Psychology, Elsevier, vol. 66(C), pages 79-92.
    5. Li, Jianbiao & Niu, Xiaofei & Li, Dahui & Cao, Qian, 2018. "Using Non-Invasive Brain Stimulation to Test the Role of Self-Control in Investor Behavior," EconStor Preprints 177890, ZBW - German National Library of Economics.

  4. Ingmar Nolte & Sandra Nolte, 2012. "How do individual investors trade?," The European Journal of Finance, Taylor & Francis Journals, vol. 18(10), pages 921-947, November.

    Cited by:

    1. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    2. Vasios, Michalis & Payne, Richard & Nolte, Ingmar, 2015. "Profiting from Mimicking Strategies in Non-Anonymous Markets," MPRA Paper 61710, University Library of Munich, Germany.
    3. Ramazan Gençay & Nikola Gradojevic & Richard Olsen & Faruk Selçuk, 2015. "Informed traders' arrival in foreign exchange markets: Does geography matter?," Post-Print hal-01563055, HAL.
    4. Michael King & Carol Osler & Dagfinn Rime, 2012. "The Market Microstructure Approach to Foreign Exchange: Looking Back and Looking Forward," Working Papers 54, Brandeis University, Department of Economics and International Businesss School.

  5. Ingmar Nolte & Valeri Voev, 2011. "Least Squares Inference on Integrated Volatility and the Relationship Between Efficient Prices and Noise," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 94-108, April.
    See citations under working paper version above.
  6. Mark Britten-Jones & Anthony Neuberger & Ingmar Nolte, 2011. "Improved Inference in Regression with Overlapping Observations," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(5-6), pages 657-683, June.

    Cited by:

    1. Ćorić, Bruno & Pugh, Geoff, 2013. "Foreign direct investment and output growth volatility: A worldwide analysis," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 260-271.
    2. Virginie Coudert & Valérie Mignon, 2013. "The ‘Forward Premium Puzzle’ and the Sovereign Default risk," Post-Print hal-01385839, HAL.
    3. Snaith, Stuart & Termprasertsakul, Santi & Wood, Andrew, 2017. "The exchange rate exposure puzzle: The long and the short of it," Economics Letters, Elsevier, vol. 159(C), pages 204-207.
    4. Yan, Yan & Guan, JianCheng, 2018. "Social capital, exploitative and exploratory innovations: The mediating roles of ego-network dynamics," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 244-258.
    5. Sam Nicholls & David Orsmond, 2015. "The Economic Trends, Challenges and Behaviour of Small Businesses in Australia," RBA Annual Conference Volume,in: Angus Moore & John Simon (ed.), Small Business Conditions and Finance Reserve Bank of Australia.
    6. Charles W. Calomiris & Harry Mamaysky, 2018. "How News and Its Context Drive Risk and Returns Around the World," NBER Working Papers 24430, National Bureau of Economic Research, Inc.
    7. Kucher, Oleg & Kurov, Alexander, 2014. "Business cycle, storage, and energy prices," Review of Financial Economics, Elsevier, vol. 23(4), pages 217-226.
    8. Angelidis, Timotheos & Sakkas, Athanasios & Tessaromatis, Nikolaos, 2015. "Stock market dispersion, the business cycle and expected factor returns," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 265-279.
    9. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, Elsevier.
    10. Heaton, Chris, 2015. "Testing for multiple-period predictability between serially dependent time series," International Journal of Forecasting, Elsevier, vol. 31(3), pages 587-597.

  7. Adam-Müller, Axel F.A. & Nolte, Ingmar, 2011. "Cross hedging under multiplicative basis risk," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2956-2964, November.

    Cited by:

    1. Koziol, Philipp, 2014. "Inflation and interest rate derivatives for FX risk management: Implications for exporting firms under real wealth," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(4), pages 459-472.
    2. Olaf Korn & Philipp Koziol, 2011. "The Term Structure Of Currency Hedge Ratios," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 14(04), pages 525-557.
    3. Thomas Conlon & John Cotter & Ramazan Gençay, 2016. "Commodity futures hedging, risk aversion and the hedging horizon," The European Journal of Finance, Taylor & Francis Journals, vol. 22(15), pages 1534-1560, December.
    4. Brian Lucey & Britta Berghöfer, 2013. "Fuel Hedging, Operational Hedging and Risk Exposure– Evidence from the Global Airline Industry," The Institute for International Integration Studies Discussion Paper Series iiisdp433, IIIS.
    5. Marcelo J. Villena & Axel A. Araneda, 2014. "Option Pricing of Twin Assets," Papers 1401.6735, arXiv.org.
    6. Kit Wong, 2014. "Hedging and the competitive firm under correlated price and background risk," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(2), pages 329-340, October.
    7. Berghöfer, Britta & Lucey, Brian, 2014. "Fuel hedging, operational hedging and risk exposure — Evidence from the global airline industry," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 124-139.
    8. Bernard, Carole & Kwak, Minsuk, 2016. "Semi-static hedging of variable annuities," Insurance: Mathematics and Economics, Elsevier, vol. 67(C), pages 173-186.
    9. Korn, Olaf & Merz, Alexander, 2016. "How to hedge if the payment date is uncertain?," CFR Working Papers 07-14 [rev.], University of Cologne, Centre for Financial Research (CFR).

  8. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2011. "An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(4), pages 669-707, June.

    Cited by:

    1. Eugenio Miravete, 2014. "Testing for complementarities among countable strategies," Empirical Economics, Springer, vol. 46(4), pages 1521-1544, June.
    2. Pravin Trivedi & David Zimmer, 2017. "A Note on Identification of Bivariate Copulas for Discrete Count Data," Econometrics, MDPI, Open Access Journal, vol. 5(1), pages 1-11, February.
    3. Sucarrat, Genaro & Grønneberg, Steffen, 2016. "Models of Financial Return With Time-Varying Zero Probability," MPRA Paper 68931, University Library of Munich, Germany.
    4. Deb P & Trivedi PK & Zimmer DM, 2009. "Dynamic Cost-offsets of Prescription Drug Expenditures: Panel Data Analysis Using a Copula-based Hurdle Model," Health, Econometrics and Data Group (HEDG) Working Papers 09/15, HEDG, c/o Department of Economics, University of York.
    5. Katarzyna Bień-Barkowska, 2012. "A Bivariate Copula-based Model for a Mixed Binary-Continuous Distribution: A Time Series Approach," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 4(2), pages 117-142, June.
    6. Ruben Loaiza-Maya & Michael Stanley Smith, 2017. "Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series," Papers 1712.09150, arXiv.org, revised Jul 2018.
    7. Gunther Wuyts, 2012. "The impact of aggressive orders in an order-driven market: a simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 18(10), pages 1015-1038, November.

  9. Ingmar Nolte, 2008. "Modeling a Multivariate Transaction Process," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(1), pages 143-170, Winter.

    Cited by:

    1. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    2. Gunther Wuyts, 2012. "The impact of aggressive orders in an order-driven market: a simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 18(10), pages 1015-1038, November.

  10. Nolte, Ingmar & Pohlmeier, Winfried, 2007. "Using forecasts of forecasters to forecast," International Journal of Forecasting, Elsevier, vol. 23(1), pages 15-28.

    Cited by:

    1. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    2. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
    3. Poncela, Pilar & Rodríguez, Julio & Sánchez-Mangas, Rocío & Senra, Eva, 2011. "Forecast combination through dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 27(2), pages 224-237, April.
    4. Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
    5. Panagiotis Papaioannnou & Lucia Russo & George Papaioannou & Constantinos Siettos, 2013. "Can social microblogging be used to forecast intraday exchange rates?," Papers 1310.5306, arXiv.org.
    6. Kunze, Frederik, 2017. "Predicting exchange rates in Asia: New insights on the accuracy of survey forecasts," Center for European, Governance and Economic Development Research Discussion Papers 326, University of Goettingen, Department of Economics.
    7. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    8. Mokinski, Frieder, 2016. "Using time-stamped survey responses to measure expectations at a daily frequency," International Journal of Forecasting, Elsevier, vol. 32(2), pages 271-282.
    9. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
    10. Stolzenburg, Ulrich & Lux, Thomas, 2010. "Identification of a core-periphery structure among participants of a business climate survey," Kiel Working Papers 1659, Kiel Institute for the World Economy (IfW).
    11. Kjellberg, David, 2006. "Measuring Expectations," Working Paper Series 2006:9, Uppsala University, Department of Economics.
    12. Breitung, Jörg & Schmeling, Maik, 2011. "Quantifying survey expectations: What's wrong with the probability approach?," Hannover Economic Papers (HEP) dp-485, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    13. Ullrich Heilemann & Herman O. Stekler, 2010. "Has the Accuracy of German Macroeconomic Forecasts Improved?," Working Papers 2010-001, The George Washington University, Department of Economics, Research Program on Forecasting, revised Feb 2012.
    14. Henry Sabrowski, 2008. "Inflation Expectation Formation of German Consumers: Rational or Adaptive?," Working Paper Series in Economics 100, University of Lüneburg, Institute of Economics.
    15. Panagiotis Papaioannou & Lucia Russo & George Papaioannou & Constantinos Siettos, 2013. "Can social microblogging be used to forecast intraday exchange rates?," Netnomics, Springer, vol. 14(1), pages 47-68, November.

  11. Roman Liesenfeld & Ingmar Nolte & Winfried Pohlmeier, 2006. "Modelling financial transaction price movements: a dynamic integer count data model," Empirical Economics, Springer, vol. 30(4), pages 795-825, January.

    Cited by:

    1. Großmaß Lidan, 2014. "Liquidity and the Value at Risk," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(5), pages 572-602, October.
    2. Ferriani, Fabrizio, 2010. "Informed and uninformed traders at work: evidence from the French market," MPRA Paper 24487, University Library of Munich, Germany.
    3. Luc Bauwens & Nikolaus Hautsch, 2007. "Modelling Financial High Frequency Data Using Point Processes," SFB 649 Discussion Papers SFB649DP2007-066, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Hellström, Jörgen & Simonsen, Ola, 2006. "Does the Open Limit Order Book Reveal Information About Short-run Stock Price Movements?," Umeå Economic Studies 687, Umeå University, Department of Economics.
    5. Sucarrat, Genaro & Grønneberg, Steffen, 2016. "Models of Financial Return With Time-Varying Zero Probability," MPRA Paper 68931, University Library of Munich, Germany.
    6. Grammig, Joachim & Kehrle, Kerstin, 2008. "A new marked point process model for the federal funds rate target: Methodology and forecast evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2370-2396, July.
    7. Jung, Robert & Kukuk, Martin & Liesenfeld, Roman, 2005. "Time Series of Count Data: Modelling and Estimation," Economics Working Papers 2005-08, Christian-Albrechts-University of Kiel, Department of Economics.
    8. Yousung Park & Hee-Young Kim, 2012. "Diagnostic checks for integer-valued autoregressive models using expected residuals," Statistical Papers, Springer, vol. 53(4), pages 951-970, November.
    9. Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
    10. Claudia Czado & Tilmann Gneiting & Leonhard Held, 2009. "Predictive Model Assessment for Count Data," Biometrics, The International Biometric Society, vol. 65(4), pages 1254-1261, December.
    11. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2010. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," SFB 649 Discussion Papers SFB649DP2010-055, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Dunsmuir, William T. M. & Scott, David J., 2015. "The glarma Package for Observation-Driven Time Series Regression of Counts," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i07).
    13. Magdalena Osinska & Andrzej Dobrzynski & Yochanan Shachmurove, 2016. "Performance Of American And Russian Joint Stock Companies On Financial Market. A Microstructure Perspective," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(4), pages 819-851, December.
    14. Gianbiagio Curato & Fabrizio Lillo, 2013. "Modeling the coupled return-spread high frequency dynamics of large tick assets," Papers 1310.4539, arXiv.org.
    15. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    16. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
    17. Kolassa, Stephan, 2016. "Evaluating predictive count data distributions in retail sales forecasting," International Journal of Forecasting, Elsevier, vol. 32(3), pages 788-803.
    18. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2006. "Estimating liquidity using information on the multivariate trading process," Working Papers 10, Department of Applied Econometrics, Warsaw School of Economics.

More information

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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 5 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 (4) 2008-06-27 2009-05-02 2010-02-05 2011-11-01
  2. NEP-MST: Market Microstructure (3) 2008-06-27 2009-05-02 2010-02-05
  3. NEP-ETS: Econometric Time Series (2) 2008-06-27 2010-02-05
  4. NEP-CBA: Central Banking (1) 2011-11-01
  5. NEP-CFN: Corporate Finance (1) 2008-06-27
  6. NEP-FMK: Financial Markets (1) 2009-05-02
  7. NEP-FOR: Forecasting (1) 2011-11-01
  8. NEP-ICT: Information & Communication Technologies (1) 2010-02-05
  9. NEP-IFN: International Finance (1) 2010-02-05
  10. NEP-ORE: Operations Research (1) 2010-02-05

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