Alexander Tsyplakov

Personal Details

First Name:	Alexander
Middle Name:
Last Name:	Tsyplakov
Suffix:
RePEc Short-ID:	pts2
	[This author has chosen not to make the email address public]
	Vesenniy proezd, 6 - 44 630090 Novosibirsk Russia
	9139442807

Affiliation

Economics Department
Novosibirsk State University

Novosibirsk, Russia
http://econom.nsu.ru/
RePEc:edi:ednskru (more details at EDIRC)

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. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.

   Cited by:

   1. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
      • Malte Knuppel & Fabian Kruger & Marc-Oliver Pohle, 2022. "Score-based calibration testing for multivariate forecast distributions," Papers 2211.16362, arXiv.org, revised Dec 2023.
   2. Natalia Nolde & Johanna F. Ziegel, 2016. "Elicitability and backtesting: Perspectives for banking regulation," Papers 1608.05498, arXiv.org, revised Feb 2017.
   3. Taylor, James W., 2020. "A strategic predictive distribution for tests of probabilistic calibration," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1380-1388.
   4. Werner Ehm & Tilmann Gneiting & Alexander Jordan & Fabian Krüger, 2016. "Of quantiles and expectiles: consistent scoring functions, Choquet representations and forecast rankings," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 505-562, June.
   5. Johanna F. Ziegel & Fabian Kruger & Alexander Jordan & Fernando Fasciati, 2017. "Murphy Diagrams: Forecast Evaluation of Expected Shortfall," Papers 1705.04537, arXiv.org.
   6. Allen, Sam & Koh, Jonathan & Segers, Johan & Ziegel, Johanna, 2024. "Tail calibration of probabilistic forecasts," LIDAM Discussion Papers ISBA 2024018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
   7. Tobias Fissler & Jana Hlavinov'a & Birgit Rudloff, 2019. "Elicitability and Identifiability of Systemic Risk Measures," Papers 1907.01306, arXiv.org, revised Oct 2019.
   8. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
   9. Ziegel, Johanna F. & Krueger, Fabian & Jordan, Alexander & Fasciati, Fernando, 2017. "Murphy Diagrams: Forecast Evaluation of Expected Shortfall," Working Papers 0632, University of Heidelberg, Department of Economics.

2. Tsyplakov, Alexander, 2013. "Evaluation of Probabilistic Forecasts: Proper Scoring Rules and Moments," MPRA Paper 45186, University Library of Munich, Germany.

   Cited by:

   1. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
   2. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.

3. Tsyplakov, Alexander, 2011. "Evaluating density forecasts: a comment," MPRA Paper 31184, University Library of Munich, Germany.

   Cited by:

   1. Taillardat, Maxime & Fougères, Anne-Laure & Naveau, Philippe & de Fondeville, Raphaël, 2023. "Evaluating probabilistic forecasts of extremes using continuous ranked probability score distributions," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1448-1459.
   2. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
      • Malte Knuppel & Fabian Kruger & Marc-Oliver Pohle, 2022. "Score-based calibration testing for multivariate forecast distributions," Papers 2211.16362, arXiv.org, revised Dec 2023.
   3. Taylor, James W., 2020. "A strategic predictive distribution for tests of probabilistic calibration," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1380-1388.
   4. Knüppel, Malte, 2011. "Evaluating the calibration of multi-step-ahead density forecasts using raw moments," Discussion Paper Series 1: Economic Studies 2011,32, Deutsche Bundesbank.
      • Malte Knüppel, 2015. "Evaluating the Calibration of Multi-Step-Ahead Density Forecasts Using Raw Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 270-281, April.
   5. Tsyplakov, Alexander, 2012. "Assessment of probabilistic forecasts: Proper scoring rules and moments," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 27(3), pages 115-132.
   6. Allen, Sam & Koh, Jonathan & Segers, Johan & Ziegel, Johanna, 2024. "Tail calibration of probabilistic forecasts," LIDAM Discussion Papers ISBA 2024018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
   7. Hajo Holzmann & Matthias Eulert, 2014. "The role of the information set for forecasting - with applications to risk management," Papers 1404.7653, arXiv.org.
   8. Marc-Oliver Pohle, 2020. "The Murphy Decomposition and the Calibration-Resolution Principle: A New Perspective on Forecast Evaluation," Papers 2005.01835, arXiv.org.
   9. Tsyplakov, Alexander, 2014. "Theoretical guidelines for a partially informed forecast examiner," MPRA Paper 55017, University Library of Munich, Germany.

4. Tsyplakov, Alexander, 2010. "The links between inflation and inflation uncertainty at the longer horizon," MPRA Paper 26908, University Library of Munich, Germany.

   Cited by:

   1. O.J. Kehinde & Adegbuyi Omotayo Omotayo & Adegbuyi Abimbola Abidemi, 2018. "Material Management, Information Technology, and Marketing Performance: Implications for Sustainable Business Development in Africa," European Journal of Marketing and Economics Articles, Revistia Research and Publishing, vol. 1, ejme_v1_i.
   2. Göktaş, Pinar, 2016. "Can Unprocessed Food Prices Really Be One of the Main Responsible Causes for not Achieving Inflation Targets in Turkey?," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 16(31), pages 1-16, December.

5. Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.

   Cited by:

   1. Valeria V. Lakshina, 2014. "The Fluke Of Stochastic Volatility Versus Garch Inevitability : Which Model Creates Better Forecasts?," HSE Working papers WP BRP 37/FE/2014, National Research University Higher School of Economics.
   2. Neha Saini & Anil Kumar Mittal, 2019. "On the predictive ability of GARCH and SV models of volatility: An empirical test on the SENSEX index," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(4), pages 1-5.
   3. Márcio Laurini, 2012. "A Hybrid Data Cloning Maximum Likelihood Estimator for Stochastic Volatility Models," IBMEC RJ Economics Discussion Papers 2012-02, Economics Research Group, IBMEC Business School - Rio de Janeiro.
      • Laurini Márcio Poletti, 2013. "A Hybrid Data Cloning Maximum Likelihood Estimator for Stochastic Volatility Models," Journal of Time Series Econometrics, De Gruyter, vol. 5(2), pages 193-229, May.
   4. Valeriya V. Lakshina & Andrey M. Silaev, 2016. "Fluke of stochastic volatility versus GARCH inevitability or which model creates better forecasts?," Economics Bulletin, AccessEcon, vol. 36(4), pages 2368-2380.

6. Tsyplakov Alexander, 2010. "The links between inflation and inflation uncertainty at the longer horizon," EERC Working Paper Series 10/09e, EERC Research Network, Russia and CIS.

   Cited by:

   1. O.J. Kehinde & Adegbuyi Omotayo Omotayo & Adegbuyi Abimbola Abidemi, 2018. "Material Management, Information Technology, and Marketing Performance: Implications for Sustainable Business Development in Africa," European Journal of Marketing and Economics Articles, Revistia Research and Publishing, vol. 1, ejme_v1_i.
   2. Göktaş, Pinar, 2016. "Can Unprocessed Food Prices Really Be One of the Main Responsible Causes for not Achieving Inflation Targets in Turkey?," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 16(31), pages 1-16, December.
   3. Alimi, R. Santos, 2017. "Association between inflation rates and inflation uncertainty in quantile regression," MPRA Paper 79683, University Library of Munich, Germany.

Articles

1. Gaivoronskaia, E. & Tsyplakov, A., 2018. "Using a Modified Erev-Roth Algorithm in an Agent-Based Electricity Market Model," Journal of the New Economic Association, New Economic Association, vol. 39(3), pages 55-83.

   Cited by:

   1. Petrov, Mikhail & Serkov, Leonid & Kozhov, Konstantin, 2021. "Analysis of the spatial features of regional power consumption in the Russian Federation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 61, pages 5-27.

2. Victor Suslov & Tatyana Novikova & Alexander Tsyplakov, 2016. "Simulation of the Role of Government in Spatial Agent-Based Model," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(3), pages 951-965.

   Cited by:

   1. Domozhirov D. A. & Ibragimov N. M. & Melnikova L. V. & Tsyplakov A. A., 2017. "Integration of input–output approach into agent-based modeling. Part 1. Methodological principles," World of economics and management / Vestnik NSU. Series: Social and Economics Sciences, Socionet, vol. 17(1), pages 86-99.
   2. Доможиров Д. А. & Ибрагимов Н. М. & Мельникова Л. В. & Цыплаков А. А., 2017. "Интеграция подхода «затраты – выпуск» в агент-ориентированное моделирование. Часть 1. Методологические основы. Integration of input–output approach into agent-based modeling. Part 1. Methodological pr," Мир экономики и управления // Вестник НГУ. Cерия: Cоциально-экономические науки, Socionet;Новосибирский государственный университет, vol. 17(1), pages 86-99.

3. Alexander Tsyplakov, 2011. "An introduction to state space modeling (in Russian)," Quantile, Quantile, issue 9, pages 1-24, July.

   Cited by:

   1. Orlov, D. & Postnikov, E., 2022. "Phillips curve: Inflation and NAIRU in the Russian regions," Journal of the New Economic Association, New Economic Association, vol. 55(3), pages 61-80.

4. Alexander Tsyplakov, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models (in Russian)," Quantile, Quantile, issue 8, pages 69-122, July.

   Cited by:

   1. Maddalena Cavicchioli, 2017. "Estimation and asymptotic covariance matrix for stochastic volatility models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(3), pages 437-452, August.
   2. Neha Saini & Anil Kumar Mittal, 2019. "On the predictive ability of GARCH and SV models of volatility: An empirical test on the SENSEX index," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(4), pages 1-5.

5. Alexander Tsyplakov, 2007. "A guide to the world of instruments (in Russian)," Quantile, Quantile, issue 2, pages 21-47, March.

   Cited by:

   1. Ibragimov Marat & Jovlon Karimov & Elena Permyakova, 2013. "Unemployment and output dynamics in CIS countries: Okun's law revisited," EERC Working Paper Series 13/04e, EERC Research Network, Russia and CIS.
   2. Chepel, S. & Bondarenko, K., 2015. "Is the External Labor Migration an Economic Growth Factor: Econometric Analysis and Policy Implications for the CIS Countries," Journal of the New Economic Association, New Economic Association, vol. 28(4), pages 142-166.
   3. Tendetnik, Pavel & Clayton, Grant & Cathcart, Katy, 2018. "Education and nation-state fragility: Evidence from panel data analysis," International Journal of Educational Development, Elsevier, vol. 62(C), pages 17-26.

6. Alexander Tsyplakov, 2007. "A mini-dictionary of English econometric terminology I (in Russian)," Quantile, Quantile, issue 3, pages 67-72, September.
   • Alexander Tsyplakov, 2014. "A mini-dictionary of English econometric terminology III (in Russian)," Quantile, Quantile, issue 12, pages 45-51, February.
   • Alexander Tsyplakov, 2008. "A mini-dictionary of English econometric terminology II (in Russian)," Quantile, Quantile, issue 5, pages 41-48, September.

   Cited by:

   1. Alexander Tsyplakov, 2007. "A mini-dictionary of English econometric terminology I (in Russian)," Quantile, Quantile, issue 3, pages 67-72, September.
      • Alexander Tsyplakov, 2008. "A mini-dictionary of English econometric terminology II (in Russian)," Quantile, Quantile, issue 5, pages 41-48, September.
      • Alexander Tsyplakov, 2014. "A mini-dictionary of English econometric terminology III (in Russian)," Quantile, Quantile, issue 12, pages 45-51, February.

7. Alexander Tsyplakov, 2006. "Introduction to prediction in classical time series models (in Russian)," Quantile, Quantile, issue 1, pages 3-19, September.

   Cited by:

   1. Tsyplakov, Alexander, 2012. "Assessment of probabilistic forecasts: Proper scoring rules and moments," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 27(3), pages 115-132.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 8 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) 2010-10-09 2013-03-23 2014-04-05 2015-09-11
2. NEP-FOR: Forecasting (4) 2010-12-04 2011-06-11 2013-03-23 2014-04-05
3. NEP-ETS: Econometric Time Series (3) 2010-10-09 2011-06-11 2015-09-11
4. NEP-TRA: Transition Economics (2) 2004-03-14 2015-11-01
5. NEP-CIS: Confederation of Independent States (1) 2004-03-14
6. NEP-CMP: Computational Economics (1) 2015-11-01
7. NEP-HME: Heterodox Microeconomics (1) 2015-11-01
8. NEP-MAC: Macroeconomics (1) 2004-03-14
9. NEP-MON: Monetary Economics (1) 2004-03-14
10. NEP-ORE: Operations Research (1) 2015-09-11
11. NEP-URE: Urban and Real Estate Economics (1) 2015-09-11

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Alexander Tsyplakov 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.