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Applying VaR to REITs: A comparison of alternative methods

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  • Chiuling Lu
  • Sheng‐Ching Wu
  • Lan‐Chih Ho

Abstract

This study employs five methods to calculate the VaR of twelve REITs portfolios and evaluates the accuracy of these methods. Firstly, we find that the VaR varies among individual portfolios. The Hotel REITs has consistently the largest VaR. The low‐leveraging portfolio tends to have the largest VaR measured by the parametric methods, while the high leveraging portfolio has the largest VaR calculated by the non‐parametric methods. Secondly, each method performs differently at different confidence levels, and no method dominates the others. At the 95% confidence level, the EWMA method performs relatively well. The EQWMA and the two non‐parametric methods perform equivalently and slightly overestimate VaRs. The EQWMAT method ranks the bottom and significantly overestimates VaRs for all portfolios. At the 99% confidence level, the EQWMA method performs the best. The EQWMAT and the two non‐parametric methods perform equivalently and may overestimate VaR for all portfolios. The EWMA method turns out to be the worst and tends to underestimate the VaR. These findings may provide more insights for institutional real estate investors.

Suggested Citation

  • Chiuling Lu & Sheng‐Ching Wu & Lan‐Chih Ho, 2009. "Applying VaR to REITs: A comparison of alternative methods," Review of Financial Economics, John Wiley & Sons, vol. 18(2), pages 97-102, April.
    • Handle: RePEc:wly:revfec:v:18:y:2009:i:2:p:97-102
    DOI: 10.1016/j.rfe.2008.03.001
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    1. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    2. Chris Brooks & Gita Persand, 2000. "Value at Risk and Market Crashes," ICMA Centre Discussion Papers in Finance icma-dp2000-01, Henley Business School, University of Reading.
    3. Vlaar, Peter J. G., 2000. "Value at risk models for Dutch bond portfolios," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1131-1154, July.
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