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Andrey L. Vasnev

Personal Details

First Name:Andrey
Middle Name:L.
Last Name:Vasnev
Suffix:
RePEc Short-ID:pva556
[This author has chosen not to make the email address public]
http://sydney.edu.au/business/staff/andreyv

Affiliation

(50%) Business School
University of Sydney

Sydney, Australia
http://sydney.edu.au/business/

: +61 2 9351 8083


RePEc:edi:sbsydau (more details at EDIRC)

(50%) Discipline of Business Analytics
Business School
University of Sydney

Sydney, Australia
http://sydney.edu.au/business/business_analytics

: + 61 2 9351 6584
+ 61 2 9351 6409
Sydney, NSW 2006
RePEc:edi:dxusyau (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Christopher G. Gibbs & Andrey L. Vasnev, 2017. "Conditionally Optimal Weights and Forward-Looking Approaches to Combining Forecasts," Discussion Papers 2017-10, School of Economics, The University of New South Wales.
  2. Gerlach, R & Sutton, M & Vasnev, A, 2015. "Generalized Variance: A Robust Estimator of Stock Price Volatility," Working Papers 2015-02, University of Sydney Business School, Discipline of Business Analytics.
  3. Gerda Claeskens & Jan Magnus & Andrey Vasnev & Wendun Wang, 2014. "The Forecast Combination Puzzle: A Simple Theoretical Explanation," Tinbergen Institute Discussion Papers 14-127/III, Tinbergen Institute.
  4. Pauwels, Laurent & Vasnev, Andrey, 2013. "Practical considerations for optimal weights in density forecast combi nation," Working Papers 01/2013, University of Sydney Business School, Discipline of Business Analytics.
  5. Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 02/2013, University of Sydney Business School, Discipline of Business Analytics.
  6. Magnus, Jan R & Vasnev, Andrey, 2013. "Practical use of sensitivity in econometrics with an illustration to forecast combinations," Working Papers 2013-04, University of Sydney Business School, Discipline of Business Analytics.
  7. Gerlach, Richard & Vasnev, Andrey & Watkins, John, 2012. "Multiple Event Incidence and Duration Analysis for Credit Data Incorporating Non-Stochastic Loan Maturity," Working Papers 03/2013, University of Sydney Business School, Discipline of Business Analytics.
  8. Pauwels, Laurent & Vasnev, Andrey, 2011. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Working Papers 11/2011, University of Sydney Business School, Discipline of Business Analytics.
  9. Gerlach, Richard & Vasnev, Andrey & Watkins, John, 2009. "Survival Analysis for Credit Scoring: Incidence and Latency," Working Papers 03/2009, University of Sydney Business School, Discipline of Business Analytics.
  10. Vasnev, A.L., 2006. "Local sensitivity in econometrics," Other publications TiSEM 789cc7a5-57da-4c5c-b5af-2, Tilburg University, School of Economics and Management.
  11. Magnus, J.R. & Vasnev, A.L., 2004. "Local Sensitivity and Diagnostic Tests," Discussion Paper 2004-105, Tilburg University, Center for Economic Research.

Articles

  1. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
  2. Claeskens, Gerda & Magnus, Jan R. & Vasnev, Andrey L. & Wang, Wendun, 2016. "The forecast combination puzzle: A simple theoretical explanation," International Journal of Forecasting, Elsevier, vol. 32(3), pages 754-762.
  3. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
  4. Magnus, Jan R. & Vasnev, Andrey L., 2015. "Interpretation and use of sensitivity in econometrics, illustrated with forecast combinations," International Journal of Forecasting, Elsevier, vol. 31(3), pages 769-781.
  5. Pauwels, Laurent & Vasnev, Andrey, 2014. "Forecast combination for U.S. recessions with real-time data," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 138-148.
  6. John G. T. Watkins & Andrey L. Vasnev & Richard Gerlach, 2014. "Multiple Event Incidence And Duration Analysis For Credit Data Incorporating Non‐Stochastic Loan Maturity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(4), pages 627-648, June.
  7. Andrey Vasnev & Margaret Skirtun & Laurent Pauwels, 2013. "Forecasting Monetary Policy Decisions in Australia: A Forecast Combinations Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(2), pages 151-166, March.
  8. Vasnev, Andrey L., 2010. "Sensitivity of GLS estimators in random effects models," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1252-1262, May.
  9. Magnus, Jan R. & Vasnev, Andrey L., 2008. "Using Macro Data To Obtain Better Micro Forecasts," Econometric Theory, Cambridge University Press, vol. 24(02), pages 553-579, April.
  10. Jan R. Magnus & Andrey L. Vasnev, 2007. "Local sensitivity and diagnostic tests," Econometrics Journal, Royal Economic Society, vol. 10(1), pages 166-192, March.
  11. Stanislav Anatolyev & Andrey Vasnev, 2002. "Markov chain approximation in bootstrapping autoregressions," Economics Bulletin, AccessEcon, vol. 3(19), pages 1-8.

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. Christopher G. Gibbs & Andrey L. Vasnev, 2017. "Conditionally Optimal Weights and Forward-Looking Approaches to Combining Forecasts," Discussion Papers 2017-10, School of Economics, The University of New South Wales.

    Cited by:

    1. Fossati, Sebastian, 2017. "Testing for State-Dependent Predictive Ability," Working Papers 2017-9, University of Alberta, Department of Economics.

  2. Gerda Claeskens & Jan Magnus & Andrey Vasnev & Wendun Wang, 2014. "The Forecast Combination Puzzle: A Simple Theoretical Explanation," Tinbergen Institute Discussion Papers 14-127/III, Tinbergen Institute.

    Cited by:

    1. Blanc, Sebastian M. & Setzer, Thomas, 2016. "When to choose the simple average in forecast combination," Journal of Business Research, Elsevier, vol. 69(10), pages 3951-3962.
    2. Pan, Zhiyuan & Wang, Yudong & Wu, Chongfeng & Yin, Libo, 2017. "Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 130-142.
    3. Davide Pettenuzzo & Zhiyuan Pan & Yudong Wang, 2017. "Forecasting Stock Returns: A Predictor-Constrained Approach," Working Papers 116, Brandeis University, Department of Economics and International Businesss School.
    4. Davide Pettenuzzo & Zhiyuan Pan & Yudong Wang, 2017. "Forecasting Stock Returns: A Predictor-Constrained Approach," Working Papers 116R, Brandeis University, Department of Economics and International Businesss School.
    5. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
    6. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    7. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España;Working Papers Homepage.
    8. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2015. "On the Forecast Combination Puzzle," Papers 1505.00475, arXiv.org.
    9. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2017. "Forecasting the real prices of crude oil using forecast combinations over time-varying parameter models," Energy Economics, Elsevier, vol. 66(C), pages 337-348.
    10. Christopher G. Gibbs & Andrey L. Vasnev, 2017. "Conditionally Optimal Weights and Forward-Looking Approaches to Combining Forecasts," Discussion Papers 2017-10, School of Economics, The University of New South Wales.
    11. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01317974, HAL.
    12. Zhang, Keyi & Gençay, Ramazan & Ege Yazgan, M., 2017. "Application of wavelet decomposition in time-series forecasting," Economics Letters, Elsevier, vol. 158(C), pages 41-46.

  3. Pauwels, Laurent & Vasnev, Andrey, 2013. "Practical considerations for optimal weights in density forecast combi nation," Working Papers 01/2013, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Magnus, Jan R. & Vasnev, Andrey L., 2015. "Interpretation and use of sensitivity in econometrics, illustrated with forecast combinations," International Journal of Forecasting, Elsevier, vol. 31(3), pages 769-781.

  4. Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 02/2013, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Goodness C. Aye & Christina Christou & Luis A. Gil-Alana & Rangan Gupta, 2016. "Forecasting the Probability of Recessions in South Africa: The Role of Decomposed Term-Spread and Economic Policy Uncertainty," Working Papers 201680, University of Pretoria, Department of Economics.
    2. Pirschel, Inske, 2015. "Forecasting Euro Area Recessions in real-time with a mixed-frequency Bayesian VAR," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113031, Verein für Socialpolitik / German Economic Association.

  5. Gerlach, Richard & Vasnev, Andrey & Watkins, John, 2012. "Multiple Event Incidence and Duration Analysis for Credit Data Incorporating Non-Stochastic Loan Maturity," Working Papers 03/2013, University of Sydney Business School, Discipline of Business Analytics.

    Cited by:

    1. Matthew Read & Chris Stewart & Gianni La Cava, 2014. "Mortgage-related Financial Difficulties: Evidence from Australian Micro-level Data," RBA Research Discussion Papers rdp2014-13, Reserve Bank of Australia.
    2. Lore Dirick & Gerda Claeskens & Bart Baesens, 2017. "Time to default in credit scoring using survival analysis: a benchmark study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 652-665, June.
    3. Ewa Wycinka, 2015. "Modelling Time to Default Or Early Repayment as Competing Risks (Modelowanie czasu do zaprzestania splat rat kredytu lub wczesniejszej splaty kredytu jako zdarzen konkurujacych )," Problemy Zarzadzania, University of Warsaw, Faculty of Management, vol. 13(55), pages 146-157.
    4. Dirick, Lore & Claeskens, Gerda & Baesens, Bart, 2015. "An Akaike information criterion for multiple event mixture cure models," European Journal of Operational Research, Elsevier, vol. 241(2), pages 449-457.

  6. Vasnev, A.L., 2006. "Local sensitivity in econometrics," Other publications TiSEM 789cc7a5-57da-4c5c-b5af-2, Tilburg University, School of Economics and Management.

    Cited by:

    1. Rooderkerk, R.P., 2007. "Optimizing product lines and assortments," Other publications TiSEM fa544b38-604e-410b-a5da-1, Tilburg University, School of Economics and Management.
    2. Hollander, S., 2007. "The merits and economic consequences of reputation : Three essays," Other publications TiSEM d9932a90-7aac-4b23-bf99-6, Tilburg University, School of Economics and Management.
    3. Eiling, E., 2007. "Essays on International Finance and Asset Pricing," Other publications TiSEM 5f891179-600e-4965-a5eb-0, Tilburg University, School of Economics and Management.

  7. Magnus, J.R. & Vasnev, A.L., 2004. "Local Sensitivity and Diagnostic Tests," Discussion Paper 2004-105, Tilburg University, Center for Economic Research.

    Cited by:

    1. Zhang, Xinyu & Chen, Ti & Wan, Alan T.K. & Zou, Guohua, 2009. "Robustness of Stein-type estimators under a non-scalar error covariance structure," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2376-2388, November.
    2. Hashimoto, Elizabeth M. & Ortega, Edwin M.M. & Cancho, Vicente G. & Cordeiro, Gauss M., 2010. "The log-exponentiated Weibull regression model for interval-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1017-1035, April.
    3. Carrasco, Jalmar M.F. & Ortega, Edwin M.M. & Paula, Gilberto A., 2008. "Log-modified Weibull regression models with censored data: Sensitivity and residual analysis," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 4021-4039, April.
    4. Liu, Shuangzhe & Ma, Tiefeng & Polasek, Wolfgang, 2012. "Spatial System Estimators for Panel Models: A Sensitivity and Simulation Study," Economics Series 294, Institute for Advanced Studies.
    5. Eric Manes, 2009. "Pakistan's Investment Climate : Laying the Foundation for Growth, Volume 2. Annexes," World Bank Other Operational Studies 12411, The World Bank.
    6. Mayston, David, 2009. "The determinants of cumulative endogeneity bias in multivariate analysis," Journal of Multivariate Analysis, Elsevier, vol. 100(6), pages 1120-1136, July.
    7. Magnus, Jan R. & Vasnev, Andrey L., 2015. "Interpretation and use of sensitivity in econometrics, illustrated with forecast combinations," International Journal of Forecasting, Elsevier, vol. 31(3), pages 769-781.
    8. Qin, Huaizhen & Wan, Alan T.K. & Zou, Guohua, 2009. "On the sensitivity of the one-sided t test to covariance misspecification," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1593-1609, September.
    9. Giuseppe De Luca & Jan Magnus & Franco Peracchi, 2015. "On the Ambiguous Consequences of Omitting Variables," Tinbergen Institute Discussion Papers 15-061/III, Tinbergen Institute.
    10. Vasnev, Andrey L., 2010. "Sensitivity of GLS estimators in random effects models," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1252-1262, May.
    11. Cibele Russo & Reiko Aoki & Gilberto Paula, 2012. "Assessment of variance components in nonlinear mixed-effects elliptical models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 519-545, September.

Articles

  1. Claeskens, Gerda & Magnus, Jan R. & Vasnev, Andrey L. & Wang, Wendun, 2016. "The forecast combination puzzle: A simple theoretical explanation," International Journal of Forecasting, Elsevier, vol. 32(3), pages 754-762.
    See citations under working paper version above.
  2. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.

    Cited by:

    1. Li, Jingrui & Wang, Rui & Wang, Jianzhou & Li, Yifan, 2018. "Analysis and forecasting of the oil consumption in China based on combination models optimized by artificial intelligence algorithms," Energy, Elsevier, vol. 144(C), pages 243-264.
    2. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
    3. Antoine Mandel & Amir Sani, 2016. "Learning Time-Varying Forecast Combinations," Documents de travail du Centre d'Economie de la Sorbonne 16036, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    4. Gergely Akos Ganics, 2017. "Optimal density forecast combinations," Working Papers 1751, Banco de España;Working Papers Homepage.
    5. Antoine Mandel & Amir Sani, 2017. "A Machine Learning Approach to the Forecast Combination Puzzle," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01317974, HAL.

  3. Pauwels, Laurent & Vasnev, Andrey, 2014. "Forecast combination for U.S. recessions with real-time data," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 138-148.
    See citations under working paper version above.
  4. John G. T. Watkins & Andrey L. Vasnev & Richard Gerlach, 2014. "Multiple Event Incidence And Duration Analysis For Credit Data Incorporating Non‐Stochastic Loan Maturity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(4), pages 627-648, June.
    See citations under working paper version above.
  5. Andrey Vasnev & Margaret Skirtun & Laurent Pauwels, 2013. "Forecasting Monetary Policy Decisions in Australia: A Forecast Combinations Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(2), pages 151-166, March.

    Cited by:

    1. Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 02/2013, University of Sydney Business School, Discipline of Business Analytics.
    2. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
    3. Charalampos Stasinakis & Georgios Sermpinis & Konstantinos Theofilatos & Andreas Karathanasopoulos, 2016. "Forecasting US Unemployment with Radial Basis Neural Networks, Kalman Filters and Support Vector Regressions," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 569-587, April.

  6. Vasnev, Andrey L., 2010. "Sensitivity of GLS estimators in random effects models," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1252-1262, May.

    Cited by:

    1. Magnus, Jan R. & Vasnev, Andrey L., 2015. "Interpretation and use of sensitivity in econometrics, illustrated with forecast combinations," International Journal of Forecasting, Elsevier, vol. 31(3), pages 769-781.

  7. Magnus, Jan R. & Vasnev, Andrey L., 2008. "Using Macro Data To Obtain Better Micro Forecasts," Econometric Theory, Cambridge University Press, vol. 24(02), pages 553-579, April.

    Cited by:

    1. Magnus, Jan R. & Vasnev, Andrey L., 2015. "Interpretation and use of sensitivity in econometrics, illustrated with forecast combinations," International Journal of Forecasting, Elsevier, vol. 31(3), pages 769-781.

  8. Jan R. Magnus & Andrey L. Vasnev, 2007. "Local sensitivity and diagnostic tests," Econometrics Journal, Royal Economic Society, vol. 10(1), pages 166-192, March.
    See citations under working paper version above.
  9. Stanislav Anatolyev & Andrey Vasnev, 2002. "Markov chain approximation in bootstrapping autoregressions," Economics Bulletin, AccessEcon, vol. 3(19), pages 1-8.

    Cited by:

    1. Roy Cerqueti & Paolo Falbo & Cristian Pelizzari & Federica Ricca & Andrea Scozzari, 2012. "A Mixed Integer Linear Programming Approach to Markov Chain Bootstrapping," Working Papers 67-2012, Macerata University, Department of Finance and Economic Sciences, revised Nov 2012.
    2. Cerqueti, Roy & Falbo, Paolo & Guastaroba, Gianfranco & Pelizzari, Cristian, 2013. "A Tabu Search heuristic procedure in Markov chain bootstrapping," European Journal of Operational Research, Elsevier, vol. 227(2), pages 367-384.
    3. Cerqueti, Roy & Falbo, Paolo & Pelizzari, Cristian, 2013. "Relevant States and Memory in Markov Chain Bootstrapping and Simulation," MPRA Paper 46250, University Library of Munich, Germany.
    4. Roy Cerqueti & Paolo Falbo & Cristian Pelizzari & Federica Ricca & Andrea Scozzari, 2017. "A mixed integer linear program to compress transition probability matrices in Markov chain bootstrapping," Annals of Operations Research, Springer, vol. 248(1), pages 163-187, January.

More information

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Statistics

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Co-authorship network on CollEc

Featured entries

This author is featured on the following reading lists, publication compilations or Wikipedia entries:
  1. New Economic School Alumni

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 (6) 2013-10-25 2013-10-25 2014-11-12 2015-04-25 2015-11-21 2017-04-16. Author is listed
  2. NEP-FOR: Forecasting (5) 2013-10-25 2013-10-25 2013-10-25 2015-04-25 2017-04-16. Author is listed
  3. NEP-ETS: Econometric Time Series (4) 2013-10-25 2015-04-25 2015-11-21 2017-04-16
  4. NEP-MAC: Macroeconomics (1) 2013-10-25
  5. NEP-RMG: Risk Management (1) 2015-11-21

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