IDEAS home Printed from https://ideas.repec.org/a/taf/jpropr/v16y1999i3p257-270.html
   My bibliography  Save this article

Some implications of the lack of a consensus view of UK property's future risk and return

Author

Listed:
  • Stephen Lee
  • Peter Byrne

Abstract

Surveys of 'experts' have been undertaken to obtain forecasts of the future risk and return relationship of Property with Equities and Bonds in both the USA and the UK. The mean or median values of these forecasts have been used in asset allocation models to justify Property's position in the mixed asset portfolio. The use of these measures as consensus forecasts has been adopted without determining the meaning of Consensus and whether they can be taken as consensual. This paper uses Consensus testing methodology on data from a survey of UK Property professionals to test whether a Consensus exists in their forecasts of the future risk/return of UK property. The results show that for a number of key variables there is substantial disagreement. The implication is that, for individual funds seeking to justify a place for Property in a mixed asset portfolio, it must depend upon their views of the expected risk and return characteristics of the asset classes that form their portfolio, rather than any more general measures of central tendency. In this context the Modern Portfolio approach enables stress testing of assumptions about the level of holding that they wish for Property by developing scenarios given the risk and return expectations of the assets. Results of using such scenarios in this context are shown for the UK Consensus holding (15%).

Suggested Citation

  • Stephen Lee & Peter Byrne, 1999. "Some implications of the lack of a consensus view of UK property's future risk and return," Journal of Property Research, Taylor & Francis Journals, vol. 16(3), pages 257-270, January.
  • Handle: RePEc:taf:jpropr:v:16:y:1999:i:3:p:257-270
    DOI: 10.1080/095999199368148
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/095999199368148
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/095999199368148?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. N. French, 1994. "Property in the context of multi asset portfolios," ERES eres1994_124, European Real Estate Society (ERES).
    2. repec:arz:wpaper:eres1994-124 is not listed on IDEAS
    3. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    4. Bera, Anil K. & Jarque, Carlos M., 1981. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals : Monte Carlo Evidence," Economics Letters, Elsevier, vol. 7(4), pages 313-318.
    5. Winkler, Robert L., 1989. "Combining forecasts: A philosophical basis and some current issues," International Journal of Forecasting, Elsevier, vol. 5(4), pages 605-609.
    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. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    2. Armstrong, J. Scott & Morwitz, Vicki G. & Kumar, V., 2000. "Sales forecasts for existing consumer products and services: Do purchase intentions contribute to accuracy?," International Journal of Forecasting, Elsevier, vol. 16(3), pages 383-397.
    3. Mayr, Johannes, 2010. "Forecasting Macroeconomic Aggregates," Munich Dissertations in Economics 11140, University of Munich, Department of Economics.
    4. Kamstra, Mark & Kennedy, Peter, 1998. "Combining qualitative forecasts using logit," International Journal of Forecasting, Elsevier, vol. 14(1), pages 83-93, March.
    5. Massimo Guidolin & Carrie Fangzhou Na, 2007. "The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns," Working Papers 2006-059, Federal Reserve Bank of St. Louis.
    6. Steffen Henzel & Johannes Mayr, 2009. "The Virtues of VAR Forecast Pooling – A DSGE Model Based Monte Carlo Study," ifo Working Paper Series 65, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    7. Budescu, David V. & Rantilla, Adrian K. & Yu, Hsiu-Ting & Karelitz, Tzur M., 2003. "The effects of asymmetry among advisors on the aggregation of their opinions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 90(1), pages 178-194, January.
    8. Luis Fernando Melo & Héctor Núñez, 2004. "Combinación de Pronósticos de la Inflación en Presencia de cambios Estructurales," Borradores de Economia 286, Banco de la Republica de Colombia.
    9. Karine Bouthevillain, 1993. "La prévision macro-économique : précision relative et consensus," Économie et Prévision, Programme National Persée, vol. 108(2), pages 97-126.
    10. Guo, Zhenhai & Zhao, Jing & Zhang, Wenyu & Wang, Jianzhou, 2011. "A corrected hybrid approach for wind speed prediction in Hexi Corridor of China," Energy, Elsevier, vol. 36(3), pages 1668-1679.
    11. Karine Bouthevillain & Alexandre Mathis, 1995. "Prévisions : mesures, erreurs et principaux résultats," Économie et Statistique, Programme National Persée, vol. 285(1), pages 89-100.
    12. Bacci, Livio Agnew & Mello, Luiz Gustavo & Incerti, Taynara & Paulo de Paiva, Anderson & Balestrassi, Pedro Paulo, 2019. "Optimization of combined time series methods to forecast the demand for coffee in Brazil: A new approach using Normal Boundary Intersection coupled with mixture designs of experiments and rotated fact," International Journal of Production Economics, Elsevier, vol. 212(C), pages 186-211.
    13. Keunkwan Ryu & Kuo-yuan Liang, 1992. "Relationship of Forecast Encompassing to Composite Forecasts with Simulations and an Application," UCLA Economics Working Papers 668, UCLA Department of Economics.
    14. Luis Fernando Melo Velandia & Héctor M. Núñez Amortegui, 2004. "Combinación de pronósticos de la inflación en presencia de cambios estructurales," Borradores de Economia 2153, Banco de la Republica.
    15. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    16. Carlo Altavilla & Paul De Grauwe, 2010. "Forecasting and combining competing models of exchange rate determination," Applied Economics, Taylor & Francis Journals, vol. 42(27), pages 3455-3480.
    17. M. Hashem Pesaran & Paolo Zaffaroni, 2004. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi Asset Volatility Models for Risk Management," CESifo Working Paper Series 1358, CESifo.
    18. Kim, Hyun Hak & Swanson, Norman R., 2018. "Mining big data using parsimonious factor, machine learning, variable selection and shrinkage methods," International Journal of Forecasting, Elsevier, vol. 34(2), pages 339-354.
    19. Fernando M. Duarte & Carlo Rosa, 2015. "The equity risk premium: a review of models," Economic Policy Review, Federal Reserve Bank of New York, issue 2, pages 39-57.
    20. Jakub Nowotarski, 2013. "Short-term forecasting of electricity spot prices using model averaging (Krótkoterminowe prognozowanie spotowych cen energii elektrycznej z wykorzystaniem uśredniania modeli)," HSC Research Reports HSC/13/17, Hugo Steinhaus Center, Wroclaw University of Technology.

    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:jpropr:v:16:y:1999:i:3:p:257-270. 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/RJPR20 .

    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.