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Anders Wilhelmsson

Personal Details

First Name:Anders
Middle Name:
Last Name:Wilhelmsson
Suffix:
RePEc Short-ID:pwi135
https://sites.google.com/site/andersvilhelmsson777/

Affiliation

Nationalekonomiska Institutionen
Ekonomihögskolan
Lunds Universitet

Lund, Sweden
http://www.nek.lu.se/
RePEc:edi:delunse (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Dí­az & Menachem Abudy & Tobi, 2021. "Non-Standard Errors," Working Papers 2021-31, Faculty of Economics and Statistics, Universität Innsbruck.
  2. Vilhelmsson, Anders, 2020. "Macro news and long-run volatility expectations," Knut Wicksell Working Paper Series 2020/1, Lund University, Knut Wicksell Centre for Financial Studies.
  3. Asgharian, Hossein & Krygier, Dominika & Vilhelmsson, Anders, 2019. "Systemic Risk and Centrality Revisited: The Role of Interactions," Working Papers 2019:4, Lund University, Department of Economics.
  4. Jankensgård, Håkan & Vilhelmsson, Anders, 2016. "Ownership Determinants of Stock Return Volatility," Knut Wicksell Working Paper Series 2016/3, Lund University, Knut Wicksell Centre for Financial Studies.
  5. Lundqvist, Sara & Vilhelmsson, Anders, 2016. "Enterprise Risk Management and Default Risk: Evidence from the Banking Industry," Knut Wicksell Working Paper Series 2016/2, Lund University, Knut Wicksell Centre for Financial Studies.
  6. Lundtofte, Frederik & Wilhelmsson, Anders, 2011. "Idiosyncratic Risk and Higher-Order Cumulants," Working Papers 2011:33, Lund University, Department of Economics.
  7. Christophe Pérignon & Laurent Fresard & Anders Wilhelmsson, 2011. "The Pernicious Effects of Contaminated Data in Risk Management," Post-Print hal-00630301, HAL.

Articles

  1. Hilling, Axel & Lundtofte, Frederik & Sandell, Niklas & Sonnerfeldt, Amanda & Vilhelmsson, Anders, 2021. "Tax avoidance and state ownership — The case of Sweden," Economics Letters, Elsevier, vol. 208(C).
  2. Håkan Jankensgård & Anders Vilhelmsson, 2018. "The Shareholder Base Hypothesis of Stock Return Volatility: Empirical Evidence," Financial Management, Financial Management Association International, vol. 47(1), pages 55-79, March.
  3. Sara A. Lundqvist & Anders Vilhelmsson, 2018. "Enterprise Risk Management and Default Risk: Evidence from the Banking Industry," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 85(1), pages 127-157, March.
  4. Hilling Axel & Sandell Niklas & Vilhelmsson Anders, 2017. "Tax Planning in Partner-owned Close Corporations," Nordic Tax Journal, Sciendo, vol. 2017(1), pages 108-120, January.
  5. Lundtofte, Frederik & Wilhelmsson, Anders, 2013. "Risk premia: Exact solutions vs. log-linear approximations," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4256-4264.
  6. Anders Wilhelmsson, 2013. "Density Forecasting with Time‐Varying Higher Moments: A Model Confidence Set Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(1), pages 19-31, January.
  7. Frésard, Laurent & Pérignon, Christophe & Wilhelmsson, Anders, 2011. "The pernicious effects of contaminated data in risk management," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2569-2583, October.
  8. Peter Nyberg & Anders Wilhelmsson, 2010. "Volatility Risk Premium, Risk Aversion, and the Cross‐Section of Stock Returns," The Financial Review, Eastern Finance Association, vol. 45(4), pages 1079-1100, November.
  9. Peter Nyberg & Anders Wilhelmsson, 2009. "Measuring Event Risk," Journal of Financial Econometrics, Oxford University Press, vol. 7(3), pages 265-287, Summer.
  10. Anders Wilhelmsson, 2009. "Value at Risk with time varying variance, skewness and kurtosis--the NIG-ACD model," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 82-104, March.
  11. Anders Wilhelmsson, 2006. "Garch forecasting performance under different distribution assumptions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(8), pages 561-578.

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. Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Dí­az & Menachem Abudy & Tobi, 2021. "Non-Standard Errors," Working Papers 2021-31, Faculty of Economics and Statistics, Universität Innsbruck.

    Cited by:

    1. Fišar, Miloš & Greiner, Ben & Huber, Christoph & Katok, Elena & Ozkes, Ali & Collaboration, Management Science Reproducibility, 2023. "Reproducibility in Management Science," OSF Preprints mydzv, Center for Open Science.
    2. Christoph Huber & Christian König-Kersting, 2022. "Experimenting with Financial Professionals," Working Papers 2022-07, Faculty of Economics and Statistics, Universität Innsbruck.
    3. Müller, Isabella & Noth, Felix & Tonzer, Lena, 2022. "A note on the use of syndicated loan data," IWH Discussion Papers 17/2022, Halle Institute for Economic Research (IWH).

  2. Lundqvist, Sara & Vilhelmsson, Anders, 2016. "Enterprise Risk Management and Default Risk: Evidence from the Banking Industry," Knut Wicksell Working Paper Series 2016/2, Lund University, Knut Wicksell Centre for Financial Studies.

    Cited by:

    1. Bashir, Taqadus & Khalid, Shujaat & Iqbal Khan, Kanwal & Javed, Saman, 2019. "Interest Rate Risk Management by Financial Engineering in Pakistani Non-Financial Firms," MPRA Paper 96426, University Library of Munich, Germany.
    2. Evan M. Eastman & Jianren Xu, 2021. "Market reactions to enterprise risk management adoption, incorporation by rating agencies, and ORSA Act passage," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 24(2), pages 151-180, June.
    3. Ben Kajwang, 2022. "Theoretical review of enterprise risk management culture drivers for insurance firms in Kenya," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 11(5), pages 210-217, July.
    4. Sorin Gabriel Anton & Anca Elena Afloarei Nucu, 2020. "Enterprise Risk Management: A Literature Review and Agenda for Future Research," JRFM, MDPI, vol. 13(11), pages 1-22, November.
    5. Yun, Jiyeon, 2023. "The effect of enterprise risk management on corporate risk management," Finance Research Letters, Elsevier, vol. 55(PB).
    6. Hasan Dinçer & Serhat Yüksel & Fatih Pınarbaşı & Mehmet Ali Alhan, 2020. "Risky Financial Assets in Financial Integration and the Impacts of Derivatives on Banking Returns," World Scientific Book Chapters, in: Stéphane Goutte & Khaled Guesmi (ed.), Risk Factors and Contagion in Commodity Markets and Stocks Markets, chapter 6, pages 133-159, World Scientific Publishing Co. Pte. Ltd..
    7. Alessandra Allini & Raffaela Casciello & Marco Maffei & Martina Prisco, 2022. "The national culture as a determinant of ERM quality: Empirical evidence in the European banking context," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(1), pages 79-102.

  3. Christophe Pérignon & Laurent Fresard & Anders Wilhelmsson, 2011. "The Pernicious Effects of Contaminated Data in Risk Management," Post-Print hal-00630301, HAL.

    Cited by:

    1. Christophe Boucher & Jon Danielsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk models-at-risk," Post-Print hal-02312332, HAL.
    2. Gilbert Colletaz & Christophe Hurlin & Christophe Pérignon, 2012. "The Risk Map: A New Tool for Validating Risk Models," Working Papers halshs-00746273, HAL.
    3. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    4. Ralf Sabiwalsky, 2012. "Does Basel II Pillar 3 Risk Exposure Data help to Identify Risky Banks?," SFB 649 Discussion Papers SFB649DP2012-008, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

Articles

  1. Håkan Jankensgård & Anders Vilhelmsson, 2018. "The Shareholder Base Hypothesis of Stock Return Volatility: Empirical Evidence," Financial Management, Financial Management Association International, vol. 47(1), pages 55-79, March.

    Cited by:

    1. Chia, Yee-Ee & Lim, Kian-Ping & Goh, Kim-Leng, 2020. "More shareholders, higher liquidity? Evidence from an emerging stock market," Emerging Markets Review, Elsevier, vol. 44(C).
    2. Neukirchen, Daniel & Engelhardt, Nils & Krause, Miguel & Posch, Peter N., 2023. "The value of (private) investor relations during the COVID-19 crisis," Journal of Banking & Finance, Elsevier, vol. 147(C).
    3. Chen, Zhongdong & Craig, Karen Ann, 2023. "Active attention, retail investor base, and stock returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    4. Umar Butt & Trevor William Chamberlain, 2023. "Blockholdings, Dividend Policy, Stock Returns and Return Volatility: Evidence from the UAE," IJFS, MDPI, vol. 11(4), pages 1-13, October.

  2. Sara A. Lundqvist & Anders Vilhelmsson, 2018. "Enterprise Risk Management and Default Risk: Evidence from the Banking Industry," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 85(1), pages 127-157, March.
    See citations under working paper version above.
  3. Lundtofte, Frederik & Wilhelmsson, Anders, 2013. "Risk premia: Exact solutions vs. log-linear approximations," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4256-4264.

    Cited by:

    1. Abootaleb Shirvani & Stefan Mittnik & W. Brent Lindquist & Svetlozar T. Rachev, 2021. "Bitcoin Volatility and Intrinsic Time Using Double Subordinated Levy Processes," Papers 2109.15051, arXiv.org, revised Aug 2023.
    2. Fischer, Thomas & Lundtofte , Frederik, 2018. "Unequal Returns: Using the Atkinson Index to Measure Financial Risk," Working Papers 2018:25, Lund University, Department of Economics.
    3. Abootaleb Shirvani & Stoyan V. Stoyanov & Frank J. Fabozzi & Svetlozar T. Rachev, 2021. "Equity premium puzzle or faulty economic modelling?," Review of Quantitative Finance and Accounting, Springer, vol. 56(4), pages 1329-1342, May.

  4. Anders Wilhelmsson, 2013. "Density Forecasting with Time‐Varying Higher Moments: A Model Confidence Set Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(1), pages 19-31, January.

    Cited by:

    1. Gianluca Cubadda & Barbara Guardabascio, 2017. "Representation, Estimation and Forecasting of the Multivariate Index-Augmented Autoregressive Model," CEIS Research Paper 397, Tor Vergata University, CEIS, revised 13 Jul 2018.
    2. Kaeck, Andreas & Rodrigues, Paulo & Seeger, Norman J., 2018. "Model Complexity and Out-of-Sample Performance: Evidence from S&P 500 Index Returns," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 1-29.

  5. Frésard, Laurent & Pérignon, Christophe & Wilhelmsson, Anders, 2011. "The pernicious effects of contaminated data in risk management," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2569-2583, October.
    See citations under working paper version above.
  6. Peter Nyberg & Anders Wilhelmsson, 2010. "Volatility Risk Premium, Risk Aversion, and the Cross‐Section of Stock Returns," The Financial Review, Eastern Finance Association, vol. 45(4), pages 1079-1100, November.

    Cited by:

    1. Tim Bollerslev & Hao Zhou, 2006. "Expected stock returns and variance risk premia," Finance and Economics Discussion Series 2007-11, Board of Governors of the Federal Reserve System (U.S.).

  7. Peter Nyberg & Anders Wilhelmsson, 2009. "Measuring Event Risk," Journal of Financial Econometrics, Oxford University Press, vol. 7(3), pages 265-287, Summer.

    Cited by:

    1. Jan Hanousek & Evžen Kočenda & Jan Novotný, 2016. "Shluková analýza skoků na kapitálových trzích [Cluster Analysis of Jumps on Capital Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2016(2), pages 127-144.
    2. Zhou, Chunyang & Wu, Chongfeng & Wang, Yudong, 2019. "Dynamic portfolio allocation with time-varying jump risk," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 113-124.
    3. Chunyang Zhou & Chongfeng Wu & Weidong Xu, 2020. "Incorporating time‐varying jump intensities in the mean‐variance portfolio decisions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(3), pages 460-478, March.
    4. Hanousek Jan & Kočenda Evžen & Novotný Jan, 2012. "The identification of price jumps," Monte Carlo Methods and Applications, De Gruyter, vol. 18(1), pages 53-77, January.
    5. Jan Novotn?? & Jan Hanousek & Ev??en Ko??enda, 2013. "Price Jump Indicators: Stock Market Empirics During the Crisis," William Davidson Institute Working Papers Series wp1050, William Davidson Institute at the University of Michigan.

  8. Anders Wilhelmsson, 2009. "Value at Risk with time varying variance, skewness and kurtosis--the NIG-ACD model," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 82-104, March.

    Cited by:

    1. Grigory Franguridi, 2014. "Higher order conditional moment dynamics and forecasting value-at-risk (in Russian)," Quantile, Quantile, issue 12, pages 69-82, February.
    2. A. Gabrielsen & P. Zagaglia & A. Kirchner & Z. Liu, 2012. "Forecasting Value-at-Risk with Time-Varying Variance, Skewness and Kurtosis in an Exponential Weighted Moving Average Framework," Papers 1206.1380, arXiv.org.
    3. Dark Jonathan Graeme, 2010. "Estimation of Time Varying Skewness and Kurtosis with an Application to Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-50, March.
    4. Wu, Xinyu & Xia, Michelle & Zhang, Huanming, 2020. "Forecasting VaR using realized EGARCH model with skewness and kurtosis," Finance Research Letters, Elsevier, vol. 32(C).
    5. Wentao Hu, 2019. "calculation worst-case Value-at-Risk prediction using empirical data under model uncertainty," Papers 1908.00982, arXiv.org.
    6. Wei Kuang, 2021. "Dynamic VaR forecasts using conditional Pearson type IV distribution," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 500-511, April.
    7. Bujar Huskaj & Marcus Nossman, 2013. "A Term Structure Model for VIX Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(5), pages 421-442, May.
    8. Mike G. Tsionas & Nicholas Apergis, 2023. "Another look at contagion across United States and European financial markets: Evidence from the credit default swaps markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1137-1155, January.
    9. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
    10. Papantonis Ioannis & Tzavalis Elias & Agapitos Orestis & Rompolis Leonidas S., 2023. "Augmenting the Realized-GARCH: the role of signed-jumps, attenuation-biases and long-memory effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(2), pages 171-198, April.
    11. Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tédongap, 2016. "Which parametric model for conditional skewness?," The European Journal of Finance, Taylor & Francis Journals, vol. 22(13), pages 1237-1271, October.
    12. Gong, Xiaoli & Zhuang, Xintian, 2017. "Measuring financial risk and portfolio reversion with time changed tempered stable Lévy processes," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 148-159.
    13. André Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
    14. Papantonis, Ioannis & Rompolis, Leonidas & Tzavalis, Elias, 2023. "Improving variance forecasts: The role of Realized Variance features," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1221-1237.
    15. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    16. Owusu Junior, Peterson & Tiwari, Aviral Kumar & Tweneboah, George & Asafo-Adjei, Emmanuel, 2022. "GAS and GARCH based value-at-risk modeling of precious metals," Resources Policy, Elsevier, vol. 75(C).
    17. Alizadeh, Amir H. & Gabrielsen, Alexandros, 2013. "Dynamics of credit spread moments of European corporate bond indexes," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3125-3144.
    18. Sree Vinutha Venkataraman & S. V. D. Nageswara Rao, 2016. "Estimation of dynamic VaR using JSU and PIV distributions," Risk Management, Palgrave Macmillan, vol. 18(2), pages 111-134, August.
    19. Matteo Grigoletto & Francesco Lisi, 2011. "Practical implications of higher moments in risk management," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 487-506, November.
    20. Philipp M. Möller, 2018. "Drawdown Measures And Return Moments," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(07), pages 1-42, November.
    21. Wang, Xiaoyu & Xie, Dejun & Jiang, Jingjing & Wu, Xiaoxia & He, Jia, 2017. "Value-at-Risk estimation with stochastic interest rate models for option-bond portfolios," Finance Research Letters, Elsevier, vol. 21(C), pages 10-20.
    22. He, Xie & Hamori, Shigeyuki, 2021. "Is volatility spillover enough for investor decisions? A new viewpoint from higher moments," Journal of International Money and Finance, Elsevier, vol. 116(C).
    23. Codrut Florin Ivascu & Daniela Serban, 2023. "Value at Risk Estimation for Non-Gaussian Distributions," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 15(2), pages 181-190, December.
    24. Orlando, Giuseppe & Bufalo, Michele, 2022. "Modelling bursts and chaos regularization in credit risk with a deterministic nonlinear model," Finance Research Letters, Elsevier, vol. 47(PA).
    25. Inés Jiménez & Andrés Mora-Valencia & Javier Perote, 2022. "Dynamic selection of Gram–Charlier expansions with risk targets: an application to cryptocurrencies," Risk Management, Palgrave Macmillan, vol. 24(1), pages 81-99, March.
    26. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).
    27. Zhang, Wenting & He, Xie & Hamori, Shigeyuki, 2023. "The impact of the COVID-19 pandemic and Russia-Ukraine war on multiscale spillovers in green finance markets: Evidence from lower and higher order moments," International Review of Financial Analysis, Elsevier, vol. 89(C).
    28. Alexios Ghalanos & Eduardo Rossi & Giovanni Urga, 2015. "Independent Factor Autoregressive Conditional Density Model," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 594-616, May.
    29. Slim, Skander & Koubaa, Yosra & BenSaïda, Ahmed, 2017. "Value-at-Risk under Lévy GARCH models: Evidence from global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 30-53.
    30. Massimiliano Frezza & Sergio Bianchi & Augusto Pianese, 2022. "Forecasting Value-at-Risk in turbulent stock markets via the local regularity of the price process," Computational Management Science, Springer, vol. 19(1), pages 99-132, January.

  9. Anders Wilhelmsson, 2006. "Garch forecasting performance under different distribution assumptions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(8), pages 561-578.

    Cited by:

    1. Jui-Cheng Hung & Tien-Wei Lou & Yi-Hsien Wang & Jun-De Lee, 2013. "Evaluating and improving GARCH-based volatility forecasts with range-based estimators," Applied Economics, Taylor & Francis Journals, vol. 45(28), pages 4041-4049, October.
    2. Kejin Wu & Sayar Karmakar, 2023. "A model-free approach to do long-term volatility forecasting and its variants," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-38, December.
    3. Lu Wang & Feng Ma & Guoshan Liu, 2020. "Forecasting stock volatility in the presence of extreme shocks: Short‐term and long‐term effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 797-810, August.
    4. Pokhilchuk, K.A. & Savel’ev, S.E., 2016. "On the choice of GARCH parameters for efficient modelling of real stock price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 248-253.
    5. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.
    6. Monday Osagie Adenomon & Richard Adekola Idowu, 2022. "Modelling the Impact of the COVID-19 Pandemic on Some Nigerian Sectorial Stocks: Evidence from GARCH Models with Structural Breaks," FinTech, MDPI, vol. 2(1), pages 1-20, December.
    7. Liu, Yanxin & Li, Johnny Siu-Hang & Ng, Andrew Cheuk-Yin, 2015. "Option pricing under GARCH models with Hansen's skewed-t distributed innovations," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 108-125.
    8. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
    9. Chen, Haojun & Maher, Daniela, 2013. "On the predictive role of large futures trades for S&P500 index returns: An analysis of COT data as an informative trading signal," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 177-201.
    10. Liu, Min, 2022. "The driving forces of green bond market volatility and the response of the market to the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 288-309.
    11. Tran, Thuy Nhung, 2022. "The Volatility of the Stock Market and Financial Cycle: GARCH Family Models," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 56(1), pages 151-168.
    12. Vlad-Cosmin Bulai & Alexandra Horobet & Oana Cristina Popovici & Lucian Belascu & Sofia Adriana Dumitrescu, 2021. "A VaR-Based Methodology for Assessing Carbon Price Risk across European Union Economic Sectors," Energies, MDPI, vol. 14(24), pages 1-21, December.
    13. Kim C. Raath & Katherine B. Ensor, 2023. "Wavelet-L2E Stochastic Volatility Models: an Application to the Water-Energy Nexus," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 150-176, May.
    14. Lu Wang & Feng Ma & Guoshan Liu & Qiaoqi Lang, 2023. "Do extreme shocks help forecast oil price volatility? The augmented GARCH‐MIDAS approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2056-2073, April.
    15. Madziwa, Lawrence & Pillalamarry, Mallikarjun & Chatterjee, Snehamoy, 2023. "Integrating stochastic mine planning model with ARDL commodity price forecasting," Resources Policy, Elsevier, vol. 85(PB).
    16. Matteo Grigoletto & Francesco Lisi, 2011. "Practical implications of higher moments in risk management," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 487-506, November.
    17. Milton Abdul Thorlie & Lixin Song & Muhammad Amin & Xiaoguang Wang, 2015. "Modeling and forecasting of stock index volatility with APARCH models under ordered restriction," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 329-356, August.
    18. Weihuan Huang & Nifei Lin & L. Jeff Hong, 2022. "Monte-Carlo Estimation of CoVaR," Papers 2210.06148, arXiv.org.
    19. Chu, Carlin C.F. & Lam, K.P., 2011. "Modeling intraday volatility: A new consideration," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(3), pages 388-418, July.
    20. Dima, Alina Mihaela & Vasilache, Simona & Agoston, Simona & Ghinea, Valentina & Stamule, Tanase, 2011. "Leadership Challenges In Today’s Academia," MPRA Paper 35019, University Library of Munich, Germany.
    21. Shcherba, Alexandr, 2012. "Market risk valuation modeling for the European countries at the financial crisis of 2008," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 27(3), pages 20-35.
    22. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    23. I‐Ming Jiang & Jui‐Cheng Hung & Chuan‐San Wang, 2014. "Volatility Forecasts: Do Volatility Estimators and Evaluation Methods Matter?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(11), pages 1077-1094, November.
    24. Bouri, Elie, 2015. "A broadened causality in variance approach to assess the risk dynamics between crude oil prices and the Jordanian stock market," Energy Policy, Elsevier, vol. 85(C), pages 271-279.
    25. Liu, Min & Lee, Chien-Chiang, 2021. "Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting," Energy Economics, Elsevier, vol. 103(C).
    26. Min Liu & Wei‐Chong Choo & Chi‐Chuan Lee & Chien‐Chiang Lee, 2023. "Trading volume and realized volatility forecasting: Evidence from the China stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 76-100, January.
    27. Chen, Yan & Yu, Wenqiang, 2020. "Setting the margins of Hang Seng Index Futures on different positions using an APARCH-GPD Model based on extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).

More information

Research fields, statistics, top rankings, if available.

Statistics

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Rankings

This author is among the top 5% authors according to these criteria:
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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 6 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-RMG: Risk Management (2) 2019-03-11 2020-04-27
  2. NEP-BAN: Banking (1) 2019-03-11
  3. NEP-EXP: Experimental Economics (1) 2021-12-06
  4. NEP-MAC: Macroeconomics (1) 2021-02-01
  5. NEP-MON: Monetary Economics (1) 2019-03-11
  6. NEP-NET: Network Economics (1) 2020-04-27
  7. NEP-SEA: South East Asia (1) 2021-12-06
  8. NEP-UPT: Utility Models and Prospect Theory (1) 2011-10-15

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