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Vladislav Kargin

Personal Details

First Name:Vladislav
Middle Name:
Last Name:Kargin
Suffix:
RePEc Short-ID:pka58
https://www2.math.binghamton.edu/p/people/kargin/start

Affiliation

Department of Economics
State University of New York-Binghamton (SUNY)

Binghamton, New York (United States)
http://www2.binghamton.edu/economics/
RePEc:edi:debinus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Vladislav Kargin & Alexei Onatski, 2004. "Dynamics of Interest Rate Curve by Functional Auto-Regression," Macroeconomics 0404008, University Library of Munich, Germany, revised 28 Oct 2004.
  2. Vladislav Kargin, 2004. "Coordination Games with Quantum Information," Game Theory and Information 0409006, University Library of Munich, Germany.
  3. Vladislav KArgin, 2004. "Optimal Convergence Trading," Finance 0401003, University Library of Munich, Germany.
  4. Vladislav Kargin, 2003. "Value Investing in Emerging Markets: Risks and Benefits," International Finance 0309005, University Library of Munich, Germany.
  5. Vladislav Kargin, 2003. "Lattice Option Pricing By Multidimensional Interpolation," Finance 0309003, University Library of Munich, Germany, revised 29 Oct 2004.
  6. Vladislav Kargin, 2003. "Uncertainty of the Shapley Value," Game Theory and Information 0309003, University Library of Munich, Germany.
  7. Vladislav Kargin, 2003. "Portfolio Management for a Random Field of Bond Returns," Finance 0310007, University Library of Munich, Germany.
  8. Vladislav Kargin, 2003. "Consistent Estimation of Pricing Kernels from Noisy Price Data," Finance 0311001, University Library of Munich, Germany.
  9. Vladislav Kargin, 2003. "Optimal Asset Allocation with Asymptotic Criteria," Papers math/0304151, arXiv.org.
  10. Vladislav Kargin, 2002. "On Bond Portfolio Management," Papers math/0208130, arXiv.org, revised Mar 2003.

Articles

  1. Kargin, Vladislav, 2016. "On variation of word frequencies in Russian literary texts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 328-334.
  2. Kargin, Vladislav, 2015. "On estimation in the reduced-rank regression with a large number of responses and predictors," Journal of Multivariate Analysis, Elsevier, vol. 140(C), pages 377-394.
  3. Vladislav Kargin, 2011. "On Free Stochastic Differential Equations," Journal of Theoretical Probability, Springer, vol. 24(3), pages 821-848, September.
  4. Kargin, Vladislav, 2011. "Relaxation time is monotone in temperature in the mean-field Ising model," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1094-1097, August.
  5. Vladislav Kargin, 2008. "On coordination games with quantum correlations," International Journal of Game Theory, Springer;Game Theory Society, vol. 37(2), pages 211-218, June.
  6. Kargin, V. & Onatski, A., 2008. "Curve forecasting by functional autoregression," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2508-2526, November.
  7. Vladislav Kargin, 2007. "Berry–Esseen for Free Random Variables," Journal of Theoretical Probability, Springer, vol. 20(2), pages 381-395, June.
  8. Vladislav Kargin, 2005. "Uncertainty Of The Shapley Value," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 7(04), pages 517-529.
  9. Vladislav Kargin, 2005. "Lattice Option Pricing By Multidimensional Interpolation," Mathematical Finance, Wiley Blackwell, vol. 15(4), pages 635-647, October.
  10. Kargin, Vladislav, 2003. "Prevention of herding by experts," Economics Letters, Elsevier, vol. 78(3), pages 401-407, March.
  11. Kargin, Vladislav, 2002. "Value investing in emerging markets: risks and benefits," Emerging Markets Review, Elsevier, vol. 3(3), pages 233-244, September.

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. Vladislav Kargin & Alexei Onatski, 2004. "Dynamics of Interest Rate Curve by Functional Auto-Regression," Macroeconomics 0404008, University Library of Munich, Germany, revised 28 Oct 2004.

    Cited by:

    1. B. Li & S. Boubaker & Z. Liu & W. Louhichi & Y. Yao, 2023. "Exploring the Nonlinear Idiosyncratic Volatility Puzzle: Evidence from China," Post-Print hal-04435519, HAL.

  2. Vladislav Kargin, 2004. "Coordination Games with Quantum Information," Game Theory and Information 0409006, University Library of Munich, Germany.

    Cited by:

    1. Adam Brandenburger, 2007. "A Connection Between Correlation in Game Theory and Quantum Mechanics," Levine's Working Paper Archive 122247000000001725, David K. Levine.

  3. Vladislav KArgin, 2004. "Optimal Convergence Trading," Finance 0401003, University Library of Munich, Germany.

    Cited by:

    1. Yingdong Lv & Bernhard K. Meister, 2009. "Application of the Kelly Criterion to Ornstein-Uhlenbeck Processes," Papers 0903.2910, arXiv.org.
    2. Yingdong Lv & Bernhard K. Meister, 2010. "Implication Of The Kelly Criterion For Multi-Dimensional Processes," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 93-112.

  4. Vladislav Kargin, 2003. "Value Investing in Emerging Markets: Risks and Benefits," International Finance 0309005, University Library of Munich, Germany.

    Cited by:

    1. David A. Burnie, 2021. "Democracy, dictatorship, and economic freedom signals in stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 375-390, January.
    2. Hamza, Olfa & Kortas, Mohamed & L'Her, Jean-Francois & Roberge, Mathieu, 2006. "International equity portfolios: Selecting the right benchmark for emerging markets," Emerging Markets Review, Elsevier, vol. 7(2), pages 111-128, June.
    3. Gupta, R. & Donleavy, G.D., 2009. "Benefits of diversifying investments into emerging markets with time-varying correlations: An Australian perspective," Journal of Multinational Financial Management, Elsevier, vol. 19(2), pages 160-177, April.
    4. Tomasz MIZIOLEK & Adam ZAREMBA, 2017. "Fundamental Indexation in European Emerging Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 23-37, March.
    5. Kortas, Mohamed & L'Her, Jean-Francois & Roberge, Mathieu, 2005. "Country selection of emerging equity markets: benefits from country attribute diversification," Emerging Markets Review, Elsevier, vol. 6(1), pages 1-19, April.
    6. Amit Hedau, 2020. "Value Investing: Evidence From Listed Construction And Infrastucture Sector Companies In India," Romanian Economic Business Review, Romanian-American University, vol. 15(4), pages 104-114, december.

  5. Vladislav Kargin, 2003. "Lattice Option Pricing By Multidimensional Interpolation," Finance 0309003, University Library of Munich, Germany, revised 29 Oct 2004.

    Cited by:

    1. Denis Belomestny & Grigori N. Milstein & Vladimir Spokoiny, 2006. "Regression methods in pricing American and Bermudan options using consumption processes," SFB 649 Discussion Papers SFB649DP2006-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Anne Laure Bronstein & Gilles Pagès & Jacques Portès, 2013. "Multi-asset American Options and Parallel Quantization," Methodology and Computing in Applied Probability, Springer, vol. 15(3), pages 547-561, September.
    3. Ivivi J. Mwaniki, 2017. "On skewed, leptokurtic returns and pentanomial lattice option valuation via minimal entropy martingale measure," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1358894-135, January.
    4. François-Heude, Alain & Yousfi, Ouidad, 2013. "A Generalization of Gray and Whaley's Option," MPRA Paper 47908, University Library of Munich, Germany, revised 30 Jun 2013.
    5. David A. Goldberg & Yilun Chen, 2018. "Beating the curse of dimensionality in options pricing and optimal stopping," Papers 1807.02227, arXiv.org, revised Aug 2018.

  6. Vladislav Kargin, 2003. "Uncertainty of the Shapley Value," Game Theory and Information 0309003, University Library of Munich, Germany.

    Cited by:

    1. Stefano Moretti & Fioravante Patrone, 2008. "Transversality of the Shapley value," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(1), pages 1-41, July.
    2. Del Castillo, Maria Fernanda & Dimitrakopoulos, Roussos, 2016. "A multivariate destination policy for geometallurgical variables in mineral value chains using coalition-formation clustering," Resources Policy, Elsevier, vol. 50(C), pages 322-332.
    3. Karl Michael Ortmann, 2016. "The link between the Shapley value and the beta factor," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 39(2), pages 311-325, November.

Articles

  1. Kargin, Vladislav, 2016. "On variation of word frequencies in Russian literary texts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 328-334.

    Cited by:

    1. Na Kyeong Lee & Yukyeong Han & Wei Xong & Min Song, 2020. "Two layer-based trajectory analysis of the research trend in automotive fuel industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 1701-1719, September.

  2. Kargin, Vladislav, 2015. "On estimation in the reduced-rank regression with a large number of responses and predictors," Journal of Multivariate Analysis, Elsevier, vol. 140(C), pages 377-394.

    Cited by:

    1. Zhao, Li & Xu, Xingzhong, 2017. "Generalized canonical correlation variables improved estimation in high dimensional seemingly unrelated regression models," Statistics & Probability Letters, Elsevier, vol. 126(C), pages 119-126.

  3. Vladislav Kargin, 2008. "On coordination games with quantum correlations," International Journal of Game Theory, Springer;Game Theory Society, vol. 37(2), pages 211-218, June.

    Cited by:

    1. Brandenburger, Adam, 2010. "The relationship between quantum and classical correlation in games," Games and Economic Behavior, Elsevier, vol. 69(1), pages 175-183, May.
    2. Adam Brandenburger, 2008. "The Relationship Between Classical and Quantum Correlation in Games," Levine's Working Paper Archive 122247000000002312, David K. Levine.

  4. Kargin, V. & Onatski, A., 2008. "Curve forecasting by functional autoregression," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2508-2526, November.

    Cited by:

    1. Benatia, David & Carrasco, Marine & Florens, Jean-Pierre, 2017. "Functional linear regression with functional response," Journal of Econometrics, Elsevier, vol. 201(2), pages 269-291.
    2. Sven Otto & Nazarii Salish, 2022. "Approximate Factor Models for Functional Time Series," Papers 2201.02532, arXiv.org, revised Aug 2022.
    3. Blanke, D. & Bosq, D., 2016. "Detecting and estimating intensity of jumps for discretely observed ARMAD(1,1) processes," Journal of Multivariate Analysis, Elsevier, vol. 146(C), pages 119-137.
    4. Atefeh Zamani & Hossein Haghbin & Maryam Hashemi & Rob J. Hyndman, 2022. "Seasonal functional autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(2), pages 197-218, March.
    5. Horváth, Lajos & Husková, Marie & Kokoszka, Piotr, 2010. "Testing the stability of the functional autoregressive process," Journal of Multivariate Analysis, Elsevier, vol. 101(2), pages 352-367, February.
    6. Horváth, Lajos & Liu, Zhenya & Rice, Gregory & Wang, Shixuan, 2020. "A functional time series analysis of forward curves derived from commodity futures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 646-665.
    7. Clive G. Bowsher & Roland Meeks, 2008. "The dynamics of economics functions: modelling and forecasting the yield curve," Working Papers 0804, Federal Reserve Bank of Dallas.
    8. Horváth, Lajos & Hušková, Marie & Rice, Gregory, 2013. "Test of independence for functional data," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 100-119.
    9. Ajroldi, Niccolò & Diquigiovanni, Jacopo & Fontana, Matteo & Vantini, Simone, 2023. "Conformal prediction bands for two-dimensional functional time series," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
    10. Gabrys Robertas & Hörmann Siegfried & Kokoszka Piotr, 2013. "Monitoring the Intraday Volatility Pattern," Journal of Time Series Econometrics, De Gruyter, vol. 5(2), pages 87-116, July.
    11. Haixu Wang & Jiguo Cao, 2023. "Nonlinear prediction of functional time series," Environmetrics, John Wiley & Sons, Ltd., vol. 34(5), August.
    12. Zhang, Xianyang, 2016. "White noise testing and model diagnostic checking for functional time series," Journal of Econometrics, Elsevier, vol. 194(1), pages 76-95.
    13. Devin Didericksen & Piotr Kokoszka & Xi Zhang, 2012. "Empirical properties of forecasts with the functional autoregressive model," Computational Statistics, Springer, vol. 27(2), pages 285-298, June.
    14. Gregory Rice & Han Lin Shang, 2017. "A Plug-in Bandwidth Selection Procedure for Long-Run Covariance Estimation with Stationary Functional Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(4), pages 591-609, July.
    15. Dominique Guegan & Matteo Iacopini, 2018. "Nonparametric forecasting of multivariate probability density functions," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01821815, HAL.
    16. Canale, Antonio & Vantini, Simone, 2016. "Constrained functional time series: Applications to the Italian gas market," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1340-1351.
    17. 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.
    18. Klepsch, J. & Klüppelberg, C., 2017. "An innovations algorithm for the prediction of functional linear processes," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 252-271.
    19. Caio Almeida & Romeu Gomes & André Leite & José Vicente, 2007. "Does Curvature Enhance Forecasting?," Working Papers Series 155, Central Bank of Brazil, Research Department.
    20. Mestre, Guillermo & Portela, José & Rice, Gregory & Muñoz San Roque, Antonio & Alonso, Estrella, 2021. "Functional time series model identification and diagnosis by means of auto- and partial autocorrelation analysis," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
    21. Chen, Yichao & Pun, Chi Seng, 2019. "A bootstrap-based KPSS test for functional time series," Journal of Multivariate Analysis, Elsevier, vol. 174(C).
    22. Alexander Gleim & Nazarii Salish, 2022. "Forecasting Environmental Data: An example to ground-level ozone concentration surfaces," Papers 2202.03332, arXiv.org.
    23. Alexander Aue & Diogo Dubart Norinho & Siegfried Hörmann, 2015. "On the Prediction of Stationary Functional Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 378-392, March.
    24. Bosq, D., 2014. "Computing the best linear predictor in a Hilbert space. Applications to general ARMAH processes," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 436-450.
    25. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2023. "Exploring volatility of crude oil intraday return curves: A functional GARCH-X model," Journal of Commodity Markets, Elsevier, vol. 32(C).
    26. Dominique Guégan & Matteo Iacopini, 2018. "Nonparameteric forecasting of multivariate probability density functions," Documents de travail du Centre d'Economie de la Sorbonne 18012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    27. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2021. "Exploring volatility of crude oil intra-day return curves: a functional GARCH-X Model," MPRA Paper 109231, University Library of Munich, Germany.
    28. Matteo Iacopini & Dominique Guégan, 2018. "Nonparametric Forecasting of Multivariate Probability Density Functions," Working Papers 2018:15, Department of Economics, University of Venice "Ca' Foscari".
    29. Clive Bowsher & Roland Meeks, 2006. "High Dimensional Yield Curves: Models and Forecasting," Economics Series Working Papers 2006-FE-11, University of Oxford, Department of Economics.
    30. Niccol`o Ajroldi & Jacopo Diquigiovanni & Matteo Fontana & Simone Vantini, 2022. "Conformal Prediction Bands for Two-Dimensional Functional Time Series," Papers 2207.13656, arXiv.org, revised Jul 2023.
    31. Goia, Aldo & May, Caterina & Fusai, Gianluca, 2010. "Functional clustering and linear regression for peak load forecasting," International Journal of Forecasting, Elsevier, vol. 26(4), pages 700-711, October.
    32. Rob J. Hyndman & Han Lin Shang, 2008. "Rainbow plots, Bagplots and Boxplots for Functional Data," Monash Econometrics and Business Statistics Working Papers 9/08, Monash University, Department of Econometrics and Business Statistics.
    33. Characiejus, Vaidotas & Rice, Gregory, 2020. "A general white noise test based on kernel lag-window estimates of the spectral density operator," Econometrics and Statistics, Elsevier, vol. 13(C), pages 175-196.
    34. Álvarez-Liébana, J. & Bosq, D. & Ruiz-Medina, M.D., 2017. "Asymptotic properties of a component-wise ARH(1) plug-in predictor," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 12-34.
    35. Daniel R. Kowal & David S. Matteson & David Ruppert, 2019. "Functional Autoregression for Sparsely Sampled Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 97-109, January.
    36. Battey, Heather & Sancetta, Alessio, 2013. "Conditional estimation for dependent functional data," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 1-17.
    37. Almeida, Caio Ibsen Rodrigues de & Vicente, José, 2007. "The role of no-arbitrage on forecasting: lessons from a parametric term structure model," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 657, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    38. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    39. Brendan K. Beare & Juwon Seo & Won-Ki Seo, 2017. "Cointegrated Linear Processes in Hilbert Space," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 1010-1027, November.
    40. Horváth, Lajos & Kokoszka, Piotr & Rice, Gregory, 2014. "Testing stationarity of functional time series," Journal of Econometrics, Elsevier, vol. 179(1), pages 66-82.
    41. Álvarez-Liébana, Javier & Bosq, Denis & Ruiz-Medina, María D., 2016. "Consistency of the plug-in functional predictor of the Ornstein–Uhlenbeck process in Hilbert and Banach spaces," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 12-22.
    42. Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," Papers 1712.07522, arXiv.org, revised Oct 2018.
    43. Butler, Sunil & Kokoszka, Piotr & Miao, Hong & Shang, Han Lin, 2021. "Neural network prediction of crude oil futures using B-splines," Energy Economics, Elsevier, vol. 94(C).
    44. Klepsch, J. & Klüppelberg, C. & Wei, T., 2017. "Prediction of functional ARMA processes with an application to traffic data," Econometrics and Statistics, Elsevier, vol. 1(C), pages 128-149.
    45. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.
    46. Boukhiar, Souad & Mourid, Tahar, 2022. "Resolvent estimators for functional autoregressive processes with random coefficients," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    47. Horváth, Lajos & Reeder, Ron, 2012. "Detecting changes in functional linear models," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 310-334.
    48. Cerovecki, Clément & Hörmann, Siegfried, 2017. "On the CLT for discrete Fourier transforms of functional time series," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 282-295.
    49. Dominique Guegan & Matteo Iacopini, 2018. "Nonparametric forecasting of multivariate probability density functions," Post-Print halshs-01821815, HAL.
    50. Lajos Horváth & Gregory Rice, 2014. "Extensions of some classical methods in change point analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(2), pages 219-255, June.
    51. Xu, Meng & Li, Jialiang & Chen, Ying, 2017. "Varying coefficient functional autoregressive model with application to the U.S. treasuries," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 168-183.
    52. Kada Kloucha, Meryem & Mourid, Tahar, 2019. "Best linear predictor of a C[0,1]-valued functional autoregressive process," Statistics & Probability Letters, Elsevier, vol. 150(C), pages 114-120.

  5. Vladislav Kargin, 2005. "Uncertainty Of The Shapley Value," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 7(04), pages 517-529.
    See citations under working paper version above.
  6. Vladislav Kargin, 2005. "Lattice Option Pricing By Multidimensional Interpolation," Mathematical Finance, Wiley Blackwell, vol. 15(4), pages 635-647, October.
    See citations under working paper version above.
  7. Kargin, Vladislav, 2002. "Value investing in emerging markets: risks and benefits," Emerging Markets Review, Elsevier, vol. 3(3), pages 233-244, September.
    See citations under working paper version above.

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, Wikipedia, or ReplicationWiki 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 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-CFN: Corporate Finance (3) 2003-09-14 2003-09-14 2003-10-12
  2. NEP-ECM: Econometrics (2) 2003-11-09 2004-04-12
  3. NEP-FIN: Finance (2) 2003-10-12 2004-01-18
  4. NEP-FMK: Financial Markets (2) 2003-10-12 2003-11-09
  5. NEP-RMG: Risk Management (2) 2003-09-14 2003-10-12
  6. NEP-CMP: Computational Economics (1) 2003-09-14
  7. NEP-GTH: Game Theory (1) 2003-09-08
  8. NEP-MAC: Macroeconomics (1) 2004-10-30
  9. NEP-MON: Monetary Economics (1) 2004-10-30

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