IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v40y2008i21p2775-2783.html
   My bibliography  Save this article

The payoff and implied pricing kernel in REITs

Author

Listed:
  • Hsiao-Tang Hsu

Abstract

This article explores the hybrid character (i.e. the resemblance of both stock and bond) of Real Estate Investment Trust (REIT) through the implied pricing kernel behind REITs prices. We use the Empirical Pricing kernel method (Rosenberg and Engle, 2002) to explore their Payoff probability density and extract the implied pricing kernel. To estimate payoff probability density, we use asymmetric GARCH model. Results indicate that implied pricing kernels flatten in all ranges of low rate of returns and decrease exponentially in ranges of high rate of returns. This means the REIT pricing kernel resembles a bond when rate of return is low, and a stock when it is high. The pattern is consistent between 1970 and 2000.

Suggested Citation

  • Hsiao-Tang Hsu, 2008. "The payoff and implied pricing kernel in REITs," Applied Economics, Taylor & Francis Journals, vol. 40(21), pages 2775-2783.
  • Handle: RePEc:taf:applec:v:40:y:2008:i:21:p:2775-2783
    DOI: 10.1080/00036840600970344
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/00036840600970344
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00036840600970344?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. James Payne & Hassan Mohammadi, 2004. "The transmission of shocks across real estate investment trust (REIT) markets," Applied Financial Economics, Taylor & Francis Journals, vol. 14(17), pages 1211-1217.
    2. Ait-Sahalia, Yacine & Lo, Andrew W., 2000. "Nonparametric risk management and implied risk aversion," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 9-51.
    3. Chapman, David A, 1997. "Approximating the Asset Pricing Kernel," Journal of Finance, American Finance Association, vol. 52(4), pages 1383-1410, September.
    4. Rosenberg, Joshua V. & Engle, Robert F., 2002. "Empirical pricing kernels," Journal of Financial Economics, Elsevier, vol. 64(3), pages 341-372, June.
    5. Breeden, Douglas T., 1979. "An intertemporal asset pricing model with stochastic consumption and investment opportunities," Journal of Financial Economics, Elsevier, vol. 7(3), pages 265-296, September.
    6. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    7. Jackwerth, Jens Carsten, 2000. "Recovering Risk Aversion from Option Prices and Realized Returns," Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 433-451.
    8. Ling, David C. & Ryngaert, Michael, 1997. "Valuation uncertainty, institutional involvement, and the underpricing of IPOs: The case of REITs," Journal of Financial Economics, Elsevier, vol. 43(3), pages 433-456, March.
    9. James Payne & George Waters, 2007. "Have Equity REITs Experienced Periodically Collapsing Bubbles?," The Journal of Real Estate Finance and Economics, Springer, vol. 34(2), pages 207-224, February.
    10. Ko Wang & John Erickson & George Gau & Su Han Chan, 1995. "Market Microstructure and Real Estate Returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 23(1), pages 85-100, March.
    Full references (including those not matched with items on IDEAS)

    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. Brennan, Michael J & LIU, XIAOQUAN & Xia, Yihong, 2005. "Option Pricing Kernels and the ICAPM," University of California at Los Angeles, Anderson Graduate School of Management qt4d90p8ss, Anderson Graduate School of Management, UCLA.
    2. Vanden, Joel M., 2005. "Equilibrium analysis of volatility clustering," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 374-417, June.
    3. Joshua Rosenberg, 1999. "Empirical Tests of Interest Rate Model Pricing Kernels," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-015, New York University, Leonard N. Stern School of Business-.
    4. Byun, Suk Joon & Jeon, Byoung Hyun & Min, Byungsun & Yoon, Sun-Joong, 2015. "The role of the variance premium in Jump-GARCH option pricing models," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 38-56.
    5. Bakshi, Gurdip & Madan, Dilip & Panayotov, George, 2010. "Returns of claims on the upside and the viability of U-shaped pricing kernels," Journal of Financial Economics, Elsevier, vol. 97(1), pages 130-154, July.
    6. Polkovnichenko, Valery & Zhao, Feng, 2013. "Probability weighting functions implied in options prices," Journal of Financial Economics, Elsevier, vol. 107(3), pages 580-609.
    7. Dominique Guegan & Florian Ielpo, 2008. "Flexible time series models for subjective distribution estimation with monetary policy in view," PSE-Ecole d'économie de Paris (Postprint) halshs-00368356, HAL.
    8. Rosenberg, Joshua V. & Engle, Robert F., 2002. "Empirical pricing kernels," Journal of Financial Economics, Elsevier, vol. 64(3), pages 341-372, June.
    9. Carol Alexander & Emese Lazar, 2009. "Modelling Regime‐Specific Stock Price Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(6), pages 761-797, December.
    10. Xinyu WU & Senchun REN & Hailin ZHOU, 2017. "Empirical Pricing Kernels: Evidence from the Hong Kong Stock Market," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(4), pages 263-278.
    11. Fabio Araujo & Joao Victor Issler, 2005. "Estimating the Stochastic Discount Factor without a Utility Function," Computing in Economics and Finance 2005 202, Society for Computational Economics.
    12. Peter Reinhard Hansen & Chen Tong, 2022. "Option Pricing with Time-Varying Volatility Risk Aversion," Papers 2204.06943, arXiv.org, revised Oct 2022.
    13. Dominique Guegan & Florian Ielpo, 2008. "Flexible time series models for subjective distribution estimation with monetary policy in view," Post-Print halshs-00368356, HAL.
    14. Liao, Wen Ju & Sung, Hao-Chang, 2020. "Implied risk aversion and pricing kernel in the FTSE 100 index," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    15. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    16. Dominique Guégan & Florian Ielpo, 2008. "Flexible time series models for subjective distribution estimation with monetary policy in view," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 51(1), pages 79-103.
    17. Dominique Guegan & Florian Ielpo, 2007. "Flexible time series models for subjective distribution estimation with monetary policy in view," Post-Print halshs-00188247, HAL.
    18. Maria Kyriacou & Jose Olmo & Marius Strittmatter, 2021. "Optimal portfolio allocation using option‐implied information," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 266-285, February.
    19. Han, Bin, 2004. "Limits of Arbitrage, Sentiment and Pricing Kernal: Evidences from Index Options," Working Paper Series 2004-2, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    20. Dietmar P. J. Leisen, 2017. "The shape of small sample biases in pricing kernel estimations," Quantitative Finance, Taylor & Francis Journals, vol. 17(6), pages 943-958, June.

    More about this item

    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:taf:applec:v:40:y:2008:i:21:p:2775-2783. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    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.