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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/

: +46 +46 222 0000
+46 +46 2224613
P.O. Box 7082, S-222 07 LUND
RePEc:edi:delunse (more details at EDIRC)

Research output

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Jump to: Working papers Articles

Working papers

  1. Lundtofte, Frederik & Wilhelmsson, Anders, 2011. "Idiosyncratic Risk and Higher-Order Cumulants," Working Papers 2011:33, Lund University, Department of Economics.
  2. Christophe Pérignon & Laurent Fresard & Anders Wilhelmsson, 2011. "The Pernicious Effects of Contaminated Data in Risk Management," Post-Print hal-00630301, HAL.

Articles

  1. Lundtofte, Frederik & Wilhelmsson, Anders, 2013. "Risk premia: Exact solutions vs. log-linear approximations," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4256-4264.
  2. 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.
  3. 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.
  4. 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.
  5. Peter Nyberg & Anders Wilhelmsson, 2009. "Measuring Event Risk," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 7(3), pages 265-287, Summer.
  6. 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.
  7. 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. 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 & Jón Daníelsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk model-at-risk," Post-Print hal-01370130, HAL.
    2. 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.
    3. Gilbert Colletaz & Christophe Hurlin & Christophe Pérignon, 2012. "The Risk Map: A New Tool for Validating Risk Models," Working Papers halshs-00746273, HAL.
    4. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.

Articles

  1. 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.
  2. 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.).

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

    Cited by:

    1. 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.
    2. Jan Hanousek & Evžen Kočenda & Jan Novotný, 2016. "Shluková analýza skoků na kapitálových trzích
      [Cluster Analysis of Jumps on Capital Markets]
      ," Politická ekonomie, University of Economics, Prague, vol. 2016(2), pages 127-144.
    3. 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.

  4. 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. 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.
    2. 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.
    3. 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.
    4. Lucas, André & Zhang, Xin, 2015. "Score Driven Exponentially Weighted Moving Averages and Value-at-Risk Forecasting," Working Paper Series 309, Sveriges Riksbank (Central Bank of Sweden).
    5. 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.
    6. 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.
    7. Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tedongap, 2013. "Which Parametric Model for Conditional Skewness?," Staff Working Papers 13-32, Bank of Canada.
    8. 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).
    9. 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.
    10. 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.
    11. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    12. 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.
    13. 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.
    14. Zi-Yi Guo, 2017. "Heavy-tailed Distributions and Risk Management of Equity Market Tail Events," Journal of Risk & Control, Risk Market Journals, vol. 4(1), pages 31-41.

  5. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Shcherba, Alexandr, 2012. "Market risk valuation modeling for the European countries at the financial crisis of 2008," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 27(3), pages 20-35.
    7. 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.
    8. 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.
    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.

More information

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Statistics

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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 1 paper 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-UPT: Utility Models & Prospect Theory (1) 2011-10-15

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