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Portfolio management implications of volatility shifts: Evidence from simulated data

  • Viviana Fernandez
  • Brian M Lucey

    ()

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.

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File URL: http://www.dii.uchile.cl/~cea/sitedev/cea/www/download.php?file=documentos_trabajo/ASOCFILE120060522101433.pdf
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Paper provided by Centro de Economía Aplicada, Universidad de Chile in its series Documentos de Trabajo with number 219.

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Date of creation: 2006
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Handle: RePEc:edj:ceauch:219
Contact details of provider: Web page: http://www.dii.uchile.cl/cea/

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  1. 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.
  2. Adriana P. Mattedi & Fernando M. Ramos & Reinaldo R. Rosa & Rosario N. Mantegna, 2004. "Value-at-Risk and Tsallis statistics: risk analysis of the aerospace sector," Papers cond-mat/0402654, arXiv.org, revised Mar 2004.
  3. Viviana Fernandez, 2005. "The International CAPM and a wavelet-based decomposition of Value at Risk," The Institute for International Integration Studies Discussion Paper Series iiisdp075, IIIS.
  4. 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.
  5. 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 225-34, April.
  6. 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.
  7. 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.
  8. 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.
  9. Enrico Capobianco, 2004. "Multiscale Analysis of Stock Index Return Volatility," Computational Economics, Society for Computational Economics, vol. 23(3), pages 219-237, 04.
  10. Giot Pierre & Laurent Sebastien, 2001. "Modelling daily value-at-risk using realized volatility and arch type models," Research Memorandum 014, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  11. Ingve Simonsen, 2001. "Measuring Anti-Correlations in the Nordic Electricity Spot Market by Wavelets," Papers cond-mat/0108033, arXiv.org, revised Apr 2003.
  12. 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.
  13. Aggarwal, Reena & Inclan, Carla & Leal, Ricardo, 1999. "Volatility in Emerging Stock Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(01), pages 33-55, March.
  14. Tan, Abby, 2006. "Long-memory volatility in derivative hedging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(2), pages 689-696.
  15. Antonios Antoniou & Constantinos E. Vorlow, 2004. "Price Clustering and Discreteness: Is there Chaos behind the Noise?," Papers cond-mat/0407471, arXiv.org.
  16. 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.
  17. 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.
  18. Connor Jeff & Rossiter Rosemary, 2005. "Wavelet Transforms and Commodity Prices," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-22, March.
  19. 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.
  20. Szilard Pafka & Imre Kondor, 2001. "Evaluating the RiskMetrics Methodology in Measuring Volatility and Value-at-Risk in Financial Markets," Papers cond-mat/0103107, arXiv.org.
  21. 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.
  22. 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.
  23. 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.
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