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Bakhodir Ergashev

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Personal Details

First Name:Bakhodir
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Last Name:Ergashev
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RePEc Short-ID:per72
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Research output

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Jump to: Working papers Articles

Working papers

  1. Bakhodir A Ergashev, 2004. "Sequential Detection of US Business Cycle Turning Points: Performances of Shiryayev-Roberts, CUSUM and EWMA Procedures," Econometrics 0402001, University Library of Munich, Germany, revised 16 Mar 2004.
  2. Bakhodir A Ergashev, 2003. "On a CAPM monitoring based on the EWMA process control," Computing in Economics and Finance 2003 283, Society for Computational Economics.
  3. Bakhodir Ergashev, 2002. "On valuing corporate debt with the volatility of corporate assets evolving according to an Ornstein-Uhlenbeck process," Finance 0206002, University Library of Munich, Germany.
  4. Bakhodir A Ergashev, 2002. "A note on a generalized Black-Scholes formula," Finance 0203006, University Library of Munich, Germany.

Articles

  1. Bakhodir Ergashev & Konstantin Pavlikov & Stan Uryasev & Evangelos Sekeris, 2016. "Estimation of Truncated Data Samples in Operational Risk Modeling," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(3), pages 613-640, September.
  2. Azamat Abdymomunov & Sharon Blei & Bakhodir Ergashev, 2015. "Integrating Stress Scenarios into Risk Quantification Models," Journal of Financial Services Research, Springer;Western Finance Association, vol. 47(1), pages 57-79, February.
  3. Bakhodir Ergashev, 2012. "A Theoretical Framework for Incorporating Scenarios into Operational Risk Modeling," Journal of Financial Services Research, Springer;Western Finance Association, vol. 41(3), pages 145-161, June.
  4. Chib, Siddhartha & Ergashev, Bakhodir, 2009. "Analysis of Multifactor Affine Yield Curve Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1324-1337.

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

    Sorry, no citations of working papers recorded.

Articles

  1. Bakhodir Ergashev & Konstantin Pavlikov & Stan Uryasev & Evangelos Sekeris, 2016. "Estimation of Truncated Data Samples in Operational Risk Modeling," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(3), pages 613-640, September.

    Cited by:

    1. Daoping Yu & Vytaras Brazauskas, 2017. "Model Uncertainty in Operational Risk Modeling Due to Data Truncation: A Single Risk Case," Risks, MDPI, vol. 5(3), pages 1-17, September.
    2. Giuricich, Mario Nicoló & Burnecki, Krzysztof, 2019. "Modelling of left-truncated heavy-tailed data with application to catastrophe bond pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 498-513.
    3. J. D. Opdyke, 2014. "Estimating Operational Risk Capital with Greater Accuracy, Precision, and Robustness," Papers 1406.0389, arXiv.org, revised Nov 2014.
    4. Maria-Teresa Bosch-Badia & Joan Montllor-Serrats & Maria-Antonia Tarrazon-Rodon, 2020. "Risk Analysis through the Half-Normal Distribution," Mathematics, MDPI, vol. 8(11), pages 1-27, November.
    5. J. D. Opdyke, 2016. "Fast, Accurate, Straightforward Extreme Quantiles of Compound Loss Distributions," Papers 1610.03718, arXiv.org, revised Jul 2017.

  2. Azamat Abdymomunov & Sharon Blei & Bakhodir Ergashev, 2015. "Integrating Stress Scenarios into Risk Quantification Models," Journal of Financial Services Research, Springer;Western Finance Association, vol. 47(1), pages 57-79, February.

    Cited by:

    1. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2015. "The Spectral Stress VaR (SSVaR)," Documents de travail du Centre d'Economie de la Sorbonne 15052, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    2. Colin Ellis, 2017. "Scenario-based stress tests: are they painful enough?," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 11(2), June.
    3. Dominique Gu�gan & Bertrand Hassani & Kehan Li, 2015. "The Spectral Stress VaR (SSVaR)," Working Papers 2015:17, Department of Economics, University of Venice "Ca' Foscari".
    4. Zi-Yi Guo, 2017. "A Model of Plausible, Severe and Useful Stress Scenarios for VIX Shocks," Applied Economics and Finance, Redfame publishing, vol. 4(3), pages 155-163, May.
    5. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2015. "The Spectral Stress VaR (SSVaR)," Post-Print halshs-01169537, HAL.
    6. Dominique Guegan & Bertrand K. Hassani & Kehan Li, 2015. "The Spectral Stress VaR (SSVaR)," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01169537, HAL.
    7. Azamat Abdymomunov & Filippo Curti, 2020. "Quantifying and Stress Testing Operational Risk with Peer Banks’ Data," Journal of Financial Services Research, Springer;Western Finance Association, vol. 57(3), pages 287-313, June.
    8. Pavel Kapinos & Oscar A. Mitnik, 2016. "A Top-down Approach to Stress-testing Banks," Journal of Financial Services Research, Springer;Western Finance Association, vol. 49(2), pages 229-264, June.

  3. Bakhodir Ergashev, 2012. "A Theoretical Framework for Incorporating Scenarios into Operational Risk Modeling," Journal of Financial Services Research, Springer;Western Finance Association, vol. 41(3), pages 145-161, June.

    Cited by:

    1. Azamat Abdymomunov & Atanas Mihov, 2019. "Operational Risk and Risk Management Quality: Evidence from U.S. Bank Holding Companies," Journal of Financial Services Research, Springer;Western Finance Association, vol. 56(1), pages 73-93, August.
    2. Babbel, David F., 2010. "A Note on Scenario Analysis in the Measurement of Operational Risk Capital: A Change of Measure Approach," Working Papers 10-26, University of Pennsylvania, Wharton School, Weiss Center.
    3. Azamat Abdymomunov & Sharon Blei & Bakhodir Ergashev, 2015. "Integrating Stress Scenarios into Risk Quantification Models," Journal of Financial Services Research, Springer;Western Finance Association, vol. 47(1), pages 57-79, February.
    4. Azamat Abdymomunov & Filippo Curti, 2020. "Quantifying and Stress Testing Operational Risk with Peer Banks’ Data," Journal of Financial Services Research, Springer;Western Finance Association, vol. 57(3), pages 287-313, June.
    5. Pavel V. Shevchenko & Gareth W. Peters, 2013. "Loss Distribution Approach for Operational Risk Capital Modelling under Basel II: Combining Different Data Sources for Risk Estimation," Papers 1306.1882, arXiv.org.
    6. Sovan Mitra, 2013. "Scenario Generation For Operational Risk," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(3), pages 163-187, July.
    7. Pavel Kapinos & Oscar A. Mitnik, 2016. "A Top-down Approach to Stress-testing Banks," Journal of Financial Services Research, Springer;Western Finance Association, vol. 49(2), pages 229-264, June.

  4. Chib, Siddhartha & Ergashev, Bakhodir, 2009. "Analysis of Multifactor Affine Yield Curve Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1324-1337.

    Cited by:

    1. Zhang, Guoxiong, 2012. "Bayesian estimation of exchange rate regime choice with spatial effect," Economics Letters, Elsevier, vol. 117(3), pages 604-607.
    2. Hans Dewachter & Leonardo Iania & Marco Lyrio, 2014. "Information in the yield curve: A Macro-Finance approach," Working Paper Research 254, National Bank of Belgium.
    3. Azamat Abdymomunov & Kyu Ho Kang & Ki Jeong Kim, 2014. "Forecasting the Term Structure of Government Bond Yields Using Credit Spreads and Structural Breaks," Working Papers 2014-19, Economic Research Institute, Bank of Korea.
    4. Michael D. Bauer, 2018. "Restrictions on Risk Prices in Dynamic Term Structure Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(2), pages 196-211, April.
    5. Koji Miyawaki & Yasuhiro Omori & Akira Hibiki, 2018. "A discrete/continuous choice model on a nonconvex budget set," Econometric Reviews, Taylor & Francis Journals, vol. 37(2), pages 89-113, February.
    6. Dewachter, Hans & Iania, Leonardo, 2012. "An Extended Macro-Finance Model with Financial Factors," LIDAM Reprints LFIN 2012001, Université catholique de Louvain, Louvain Finance (LFIN).
    7. Kim, Young Min & Kang, Kyu Ho & Ka, Kook, 2020. "Do bond markets find inflation targets credible? Evidence from five inflation-targeting countries," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 66-84.
    8. Michael D. Bauer & Glenn D. Rudebusch, 2014. "The Signaling Channel for Federal Reserve Bond Purchases," International Journal of Central Banking, International Journal of Central Banking, vol. 10(3), pages 233-289, September.
    9. Michael D. Bauer & Glenn D. Rudebusch, 2017. "Interest Rates Under Falling Stars," CESifo Working Paper Series 6571, CESifo.
    10. Dubiel-Teleszynski, Tomasz & Kalogeropoulos, Konstantinos & Karouzakis, Nikolaos, 2024. "Sequential learning and economic benefits from dynamic term structure models," LSE Research Online Documents on Economics 123659, London School of Economics and Political Science, LSE Library.
    11. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    12. Iryna Kaminska & Gabriele Zinna, 2014. "Official Demand for U.S. Debt: Implications for U.S. Real Interest Rates," IMF Working Papers 2014/066, International Monetary Fund.
    13. Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2014. "No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates," CEPR Discussion Papers 9848, C.E.P.R. Discussion Papers.
    14. Hlouskova, Jaroslava & Sögner, Leopold, 2015. "GMM Estimation of Affine Term Structure Models," Economics Series 315, Institute for Advanced Studies.
    15. Tsuyoshi Kunihama & Yasuhiro Omori & Zhengjun Zhang, 2012. "Efficient estimation and particle filter for max‐stable processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(1), pages 61-80, January.
    16. Kaminska, Iryna & Vayanos, Dimitri & Zinna, Gabriele, 2011. "Preferred-habitat investors and the US term structure of real rates," LSE Research Online Documents on Economics 119074, London School of Economics and Political Science, LSE Library.
    17. Januj Amar Juneja, 2022. "A Computational Analysis of the Tradeoff in the Estimation of Different State Space Specifications of Continuous Time Affine Term Structure Models," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 173-220, June.
    18. Mirkov, Nikola, 2012. "International Financial Transmission of the US Monetary Policy: An Empirical Assessment," Working Papers on Finance 1201, University of St. Gallen, School of Finance.
    19. Loria, Francesca & Matthes, Christian & Wang, Mu-Chun, 2022. "Economic theories and macroeconomic reality," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 105-117.
    20. Hong, Zhiwu & Niu, Linlin & Zhang, Chen, 2022. "Affine arbitrage-free yield net models with application to the euro debt crisis," Journal of Econometrics, Elsevier, vol. 230(1), pages 201-220.
    21. Ming Lin & Eric A. Suess & Robert H. Shumway & Rong Chen, 2016. "Bayesian Deconvolution of Signals Observed on Arrays," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 837-850, November.
    22. Taeyoung Doh, 2013. "Long‐Run Risks In The Term Structure Of Interest Rates: Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(3), pages 478-497, April.
    23. Caldeira, João F. & Laurini, Márcio P. & Portugal, Marcelo S., 2010. "Bayesian Inference Applied to Dynamic Nelson-Siegel Model with Stochastic Volatility," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.
    24. Siddhartha Chib & Minchul Shin & Fei Tan, 2023. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.
    25. Andreasen, Martin & Meldrum, Andrew, 2013. "Likelihood inference in non-linear term structure models: the importance of the lower bound," Bank of England working papers 481, Bank of England.
    26. Siddhartha Chib & Srikanth Ramamurthy, 2014. "DSGE Models with Student- t Errors," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 152-171, June.
    27. Siddhartha Chib & Minchul Shin & Fei Tan, 2020. "High-Dimensional DSGE Models: Pointers on Prior, Estimation, Comparison, and Prediction∗," Working Papers 20-35, Federal Reserve Bank of Philadelphia.
    28. Zongwu Cai & Jiazi Chen & Linlin Niu, 2021. "A Semiparametric Model for Bond Pricing with Life Cycle Fundamental," Working Papers 2021-01-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    29. Young Min Kim & Seojin Lee, 2017. "The Role of Unobservable Fundamentals in Korea Exchange Rate Fluctuations: Bayesian Approach," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 23(3), pages 1-22, September.
    30. Abdymomunov Azamat & Kang Kyu Ho, 2015. "The effects of monetary policy regime shifts on the term structure of interest rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 183-207, April.
    31. Meldrum, Andrew & Roberts-Sklar, Matt, 2015. "Long-run priors for term structure models," Bank of England working papers 575, Bank of England.
    32. Abdymomunov, Azamat & Gerlach, Jeffrey, 2014. "Stress testing interest rate risk exposure," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 287-301.
    33. Carlos Lenz, 2010. "Discussion: Reaction of Swiss Term Premia to Monetary Policy Surprises," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 146(I), pages 405-408, March.
    34. Zongwu Cai & Jiazi Chen & Linlin Liu, 2021. "Estimating Impact of Age Distribution on Bond Pricing: A Semiparametric Functional Data Analysis Approach," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202102, University of Kansas, Department of Economics, revised Jan 2021.
    35. Gabriele Zinna, 2014. "Price pressures in the UK index-linked market: an empirical investigation," Temi di discussione (Economic working papers) 968, Bank of Italy, Economic Research and International Relations Area.
    36. Dorota Toczydlowska & Gareth W. Peters, 2018. "Financial Big Data Solutions for State Space Panel Regression in Interest Rate Dynamics," Econometrics, MDPI, vol. 6(3), pages 1-45, July.
    37. Lam, Clifford & Yao, Qiwei, 2012. "Factor modeling for high-dimensional time series: inference for the number of factors," LSE Research Online Documents on Economics 45684, London School of Economics and Political Science, LSE Library.

More information

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Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 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-FIN: Finance (2) 2002-06-13 2003-10-20
  2. NEP-CFN: Corporate Finance (1) 2003-10-20
  3. NEP-ETS: Econometric Time Series (1) 2004-02-08

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