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A time-scale analysis of systematic risk: wavelet-based approach

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  • Khalfaoui Rabeh, K
  • Boutahar Mohamed, B

Abstract

The paper studies the impact of different time-scales on the market risk of individual stock market returns and of a given portfolio in Paris Stock Market by applying the wavelet analysis. To investigate the scaling properties of stock market returns and the lead/lag relationship between them at different scales, wavelet variance and crosscorrelations analyses are used. According to wavelet variance, stock returns exhibit long memory dynamics. The wavelet cross-correlation analysis shows that comovements between stock returns are stronger at higher scales (lower frequencies); scales corresponding to period of 4 months and longer, i.e. scales 7 and 8. The wavelet analysis of systematic risk shows that all individual assets and the diversified portfolio have a multi-scale behavior, which indicates that the systematic risk measured by Beta in the market model is not stable over time. The analysis of VaR at different time scales shows that risk is more concentrated at higher frequencies dynamics (lower time scales) of the data.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 31938.

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Date of creation: 28 Jun 2011
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Handle: RePEc:pra:mprapa:31938

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Keywords: Wavelets; Systematic risk; Value-at-Risk;

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  1. Durai, S. Raja Sethu & Bhaduri, Saumitra N., 2009. "Stock prices, inflation and output: Evidence from wavelet analysis," Economic Modelling, Elsevier, vol. 26(5), pages 1089-1092, September.
  2. In, Francis & Kim, Sangbae, 2006. "Multiscale hedge ratio between the Australian stock and futures markets: Evidence from wavelet analysis," Journal of Multinational Financial Management, Elsevier, vol. 16(4), pages 411-423, October.
  3. Gencay, Ramazan & Selcuk, Faruk & Whitcher, Brandon, 2005. "Multiscale systematic risk," Journal of International Money and Finance, Elsevier, vol. 24(1), pages 55-70, February.
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  5. 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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  7. 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.
  8. Fatma Sine Tepe & Xiaodong Du & David A. Hennessy, 2009. "Impact of Biofuels Policy on Agribusiness Stock Prices, The," Midwest Agribusiness Trade Research and Information Center (MATRIC) Publications 09-wp497, Midwest Agribusiness Trade Research and Information Center (MATRIC) at Iowa State University.
  9. Xiaodong Du & Dermot J. Hayes & Cindy L. Yu, 2010. "Dynamics of Biofuel Stock Prices: A Bayesian Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(2), pages 418-425.
  10. Luisa Tibiletti & Simone Farinelli, 2003. "Upside and downside risk with a benchmark," Atlantic Economic Journal, International Atlantic Economic Society, vol. 31(4), pages 387-387, December.
  11. Boubaker Heni & Boutahar Mohamed, 2011. "A wavelet-based approach for modelling exchange rates," Statistical Methods and Applications, Springer, vol. 20(2), pages 201-220, June.
  12. Sharkasi, Adel & Crane, Martin & Ruskin, Heather J. & Matos, Jose A., 2006. "The reaction of stock markets to crashes and events: A comparison study between emerging and mature markets using wavelet transforms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 368(2), pages 511-521.
  13. 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.
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