IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to follow this author

Ingmar Nolte

This is information that was supplied by Ingmar Nolte in registering through RePEc. If you are Ingmar Nolte, you may change this information at the RePEc Author Service. Or if you are not registered and would like to be listed as well, register at the RePEc Author Service. When you register or update your RePEc registration, you may identify the papers and articles you have authored.

Personal Details

First Name:Ingmar
Middle Name:
Last Name:Nolte
RePEc Short-ID:pno71
in new window
  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.
  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, 06.
  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, 06.
  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.
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

Most cited item

Most downloaded item (past 12 months)

Access and download statistics for all items

Co-authorship network on CollEc

For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Ingmar Nolte should log into the RePEc Author Service

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.