IDEAS home Printed from https://ideas.repec.org/p/edj/ceauch/219.html
   My bibliography  Save this paper

Portfolio management implications of volatility shifts: Evidence from simulated data

Author

Listed:
  • Viviana Fernandez
  • Brian M Lucey

Abstract

Based on weekly data of the Dow Jones Country Titans, the CBT-municipal bond, spot and futures prices of commodities for the period 1992-2005, we analyze the implications for portfolio management of accounting for conditional heteroskedasticity and structural breaks in long-term volatility. In doing so, we first proceed to utilize the ICSS algorithm to detect volatility shifts, and incorporate that information into PGARCH models fitted to the returns series. At the next stage, we simulate returns series and compute a wavelet-based value at risk, which takes into consideration the investor’s time horizon. We repeat the same procedure for artificial data generated from distribution functions fitted to the returns by a semi-parametric procedure, which accounts for fat tails. Our estimation results show that neglecting GARCH effects and volatility shifts may lead us to overestimate financial risk at different time horizons. In addition, we conclude that investors benefit from holding commodities as their low or even negative correlation with stock indices contribute to portfolio diversification.

Suggested Citation

  • Viviana Fernandez & Brian M Lucey, 2006. "Portfolio management implications of volatility shifts: Evidence from simulated data," Documentos de Trabajo 219, Centro de Economía Aplicada, Universidad de Chile.
  • Handle: RePEc:edj:ceauch:219
    as

    Download full text from publisher

    File URL: http://www.cea-uchile.cl/wp-content/uploads/doctrab/ASOCFILE120060522101433.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Giot, Pierre & Laurent, Sebastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
    2. So, Mike K.P. & Kwok, Susanna W.Y., 2006. "A multivariate long memory stochastic volatility model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 450-464.
    3. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    4. Aggarwal, Reena & Inclan, Carla & Leal, Ricardo, 1999. "Volatility in Emerging Stock Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(1), pages 33-55, March.
    5. Lin Shinn-Juh & Stevenson Maxwell, 2001. "Wavelet Analysis of the Cost-of-Carry Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(1), pages 1-17, April.
    6. P. Mattedi, Adriana & M. Ramos, Fernando & Rosa, Reinaldo R. & Mantegna, Rosario N., 2004. "Value-at-risk and Tsallis statistics: risk analysis of the aerospace sector," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(3), pages 554-561.
    7. Ramsey, James B. & Zhang, Zhifeng, 1997. "The analysis of foreign exchange data using waveform dictionaries," Journal of Empirical Finance, Elsevier, vol. 4(4), pages 341-372, December.
    8. Pafka, Szilárd & Kondor, Imre, 2001. "Evaluating the RiskMetrics methodology in measuring volatility and Value-at-Risk in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 305-310.
    9. Simonsen, Ingve, 2003. "Measuring anti-correlations in the nordic electricity spot market by wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 322(C), pages 597-606.
    10. Struzik, Zbigniew R., 2001. "Wavelet methods in (financial) time-series processing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 296(1), pages 307-319.
    11. Fernandez Viviana P, 2005. "The International CAPM and a Wavelet-Based Decomposition of Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-37, December.
    12. Connor Jeff & Rossiter Rosemary, 2005. "Wavelet Transforms and Commodity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-22, March.
    13. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    14. Ingve Simonsen, 2001. "Measuring Anti-Correlations in the Nordic Electricity Spot Market by Wavelets," Papers cond-mat/0108033, arXiv.org, revised Apr 2003.
    15. Antoniou, Antonios & Vorlow, Constantinos E., 2005. "Price clustering and discreteness: is there chaos behind the noise?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 348(C), pages 389-403.
    16. Tan, Abby, 2006. "Long-memory volatility in derivative hedging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(2), pages 689-696.
    17. Tang, Ta-Lun & Shieh, Shwu-Jane, 2006. "Long memory in stock index futures markets: A value-at-risk approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 437-448.
    18. Hammoudeh, Shawkat & Li, Huimin, 2008. "Sudden changes in volatility in emerging markets: The case of Gulf Arab stock markets," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 47-63.
    19. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    20. Enrico Capobianco, 2004. "Multiscale Analysis of Stock Index Return Volatility," Computational Economics, Springer;Society for Computational Economics, vol. 23(3), pages 219-237, April.
    21. Lillo, Fabrizio & Mantegna, Rosario N, 2004. "Dynamics of a financial market index after a crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 125-134.
    22. Antonios Antoniou & Constantinos E. Vorlow, 2004. "Price Clustering and Discreteness: Is there Chaos behind the Noise?," Papers cond-mat/0407471, arXiv.org.
    23. Fernandez, Viviana, 2006. "The impact of major global events on volatility shifts: Evidence from the Asian crisis and 9/11," Economic Systems, Elsevier, vol. 30(1), pages 79-97, March.
    24. Ane, Thierry, 2006. "An analysis of the flexibility of Asymmetric Power GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1293-1311, November.
    25. Fernandez, Viviana, 2006. "The CAPM and value at risk at different time-scales," International Review of Financial Analysis, Elsevier, vol. 15(3), pages 203-219.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Morales, Lucía & Andreosso-O'Callaghan, Bernadette, 2011. "Comparative analysis on the effects of the Asian and global financial crises on precious metal markets," Research in International Business and Finance, Elsevier, vol. 25(2), pages 203-227, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fernandez, Viviana & Lucey, Brian M., 2007. "Portfolio management under sudden changes in volatility and heterogeneous investment horizons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 612-624.
    2. Fernandez, Viviana, 2008. "The war on terror and its impact on the long-term volatility of financial markets," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 1-26.
    3. Fernandez, Viviana, 2007. "A postcard from the past: The behavior of U.S. stock markets during 1871–1938," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 267-282.
    4. Fernandez, Viviana, 2006. "The impact of major global events on volatility shifts: Evidence from the Asian crisis and 9/11," Economic Systems, Elsevier, vol. 30(1), pages 79-97, March.
    5. Corbet, Shaen & Gurdgiev, Constantin & Meegan, Andrew, 2018. "Long-term stock market volatility and the influence of terrorist attacks in Europe," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 118-131.
    6. Fernandez, Viviana, 2009. "The behavior of stock returns in the mining industry following the Iraq war," Research in International Business and Finance, Elsevier, vol. 23(3), pages 274-292, September.
    7. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    8. Viviana Fernandez, 2007. "Stock Market Turmoil: Worldwide Effects of Middle East Conflicts," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 43(3), pages 58-102, June.
    9. Viviana Fernández, 2007. "The behavior of stock returns in the Asia-Pacific mining industry following the Iraq war," Documentos de Trabajo 243, Centro de Economía Aplicada, Universidad de Chile.
    10. Yıldırım, Durmuş Çağrı & Cevik, Emrah Ismail & Esen, Ömer, 2020. "Time-varying volatility spillovers between oil prices and precious metal prices," Resources Policy, Elsevier, vol. 68(C).
    11. Dong, Xiyong & Li, Changhong & Yoon, Seong-Min, 2021. "How can investors build a better portfolio in small open economies? Evidence from Asia’s Four Little Dragons," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    12. Chakrabarty, Anindya & De, Anupam & Gunasekaran, Angappa & Dubey, Rameshwar, 2015. "Investment horizon heterogeneity and wavelet: Overview and further research directions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 45-61.
    13. Rua, António & Nunes, Luis C., 2012. "A wavelet-based assessment of market risk: The emerging markets case," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 84-92.
    14. Maghyereh Aktham Issa & Awartani Basel, 2012. "Modeling and Forecasting Value-at-Risk in the UAE Stock Markets: The Role of Long Memory, Fat Tails and Asymmetries in Return Innovations," Review of Middle East Economics and Finance, De Gruyter, vol. 8(1), pages 1-22, August.
    15. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "How do OPEC news and structural breaks impact returns and volatility in crude oil markets? Further evidence from a long memory process," Energy Economics, Elsevier, vol. 42(C), pages 343-354.
    16. Masih, Mansur & Alzahrani, Mohammed & Al-Titi, Omar, 2010. "Systematic risk and time scales: New evidence from an application of wavelet approach to the emerging Gulf stock markets," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 10-18, January.
    17. David McMillan & Mark Wohar, 2011. "Structural breaks in volatility: the case of UK sector returns," Applied Financial Economics, Taylor & Francis Journals, vol. 21(15), pages 1079-1093.
    18. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
    19. Benhmad, François, 2013. "Bull or bear markets: A wavelet dynamic correlation perspective," Economic Modelling, Elsevier, vol. 32(C), pages 576-591.
    20. Sang Hoon Kang & Seong-Min Yoon, 2009. "Value-at-Risk Analysis for Asian Emerging Markets: Asymmetry and Fat Tails in Returns Innovation," Korean Economic Review, Korean Economic Association, vol. 25, pages 387-411.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:edj:ceauch:219. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/ceuclcl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.