IDEAS home Printed from https://ideas.repec.org/p/arz/wpaper/eres2001_207.html
   My bibliography  Save this paper

Time Weighted Portfolio Optimisation

Author

Listed:
  • Stephen L. Lee
  • Simon Stevenson

Abstract

In estimating the inputs into the Modern Portfolio Theory (MPT) portfolio optimisation problem it is usual to use equal weighted historic data. Equal weighting of the data, however, does not take account of the current state of the market. Consequently this approach is unlikely to perform well in any subsequent period as the data is still reflecting market conditions that are no longer valid. The need for some return-weighting scheme that gives greater weight to the most recent data would seem desirable. Consequently this study uses returns data which are weighted to give greater weight to the most recent observations to see if such a weighting scheme can offer improved ex ante performance over that based on un-weighted data.

Suggested Citation

  • Stephen L. Lee & Simon Stevenson, 2001. "Time Weighted Portfolio Optimisation," ERES eres2001_207, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2001_207
    as

    Download full text from publisher

    File URL: https://eres.architexturez.net/doc/oai-eres-id-eres2001-207
    Download Restriction: no
    File URL: https://eres.architexturez.net/system/files/pdf/eres2001_207.content.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stephen Lee, 1998. "The Inter-Temporal Stability of Real Estate Returns: An Empirical Investigation," ERES eres1998_141, European Real Estate Society (ERES).
    2. Brailsford, Timothy J. & Faff, Robert W., 1996. "An evaluation of volatility forecasting techniques," Journal of Banking & Finance, Elsevier, vol. 20(3), pages 419-438, April.
    3. Colin Lizieri & Charles Ward, 2000. "Commercial Real Estate Return Distributions: A Review Of Literature And Empirical Evidence," Real Estate & Planning Working Papers rep-wp2000-01, Henley Business School, University of Reading.
    4. repec:arz:wpaper:eres1998-141 is not listed on IDEAS
    5. Stephen Lee & Simon Stevenson, 2000. "Real Estate Portfolio Construction And Estimation Risk," ERES eres2000_070, European Real Estate Society (ERES).
    6. Akgiray, Vedat, 1989. "Conditional Heteroscedasticity in Time Series of Stock Returns: Evidence and Forecasts," The Journal of Business, University of Chicago Press, vol. 62(1), pages 55-80, January.
    7. Satchell, Stephen & Knight, John, 2000. "Return Distributions in Finance," Elsevier Monographs, Elsevier, edition 1, number 9780750647519.
    8. Jobson, J D & Korkie, Bob M, 1981. "Performance Hypothesis Testing with the Sharpe and Treynor Measures," Journal of Finance, American Finance Association, vol. 36(4), pages 889-908, September.
    9. David Walsh & Glenn Yu-Gen Tsou, 1998. "Forecasting index volatility: sampling interval and non-trading effects," Applied Financial Economics, Taylor & Francis Journals, vol. 8(5), pages 477-485.
    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. Ercan Balaban & Asli Bayar & Robert Faff, 2006. "Forecasting stock market volatility: Further international evidence," The European Journal of Finance, Taylor & Francis Journals, vol. 12(2), pages 171-188.
    2. Claudio Giannotti & Gianluca Mattarocci, 2013. "The Role of Risk Measures Choices in Ranking Real Estate Funds: Evidence from the Italian Market," Palgrave Macmillan Studies in Banking and Financial Institutions, in: Alessandro Carretta & Gianluca Mattarocci (ed.), Asset Pricing, Real Estate and Public Finance over the Crisis, chapter 10, pages 165-189, Palgrave Macmillan.
    3. Colin Lizieri & Stephen Satchell & Qi Zhang, 2007. "The Underlying Return‐Generating Factors for REIT Returns: An Application of Independent Component Analysis," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 35(4), pages 569-598, December.
    4. Torben G. Andersen & Tim Bollerslev, 1997. "Answering the Critics: Yes, ARCH Models Do Provide Good Volatility Forecasts," NBER Working Papers 6023, National Bureau of Economic Research, Inc.
    5. Kambouroudis, Dimos S. & McMillan, David G., 2015. "Is there an ideal in-sample length for forecasting volatility?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 114-137.
    6. Stéphane Yen & Ming-Hsiang Chen, 2010. "Open interest, volume, and volatility: evidence from Taiwan futures markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 34(2), pages 113-141, April.
    7. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.
    8. Pandey, Ajay, 2003. "Modeling and Forecasting Volatility in Indian Capital Markets," IIMA Working Papers WP2003-08-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    9. David Walsh & Glenn Yu-Gen Tsou, 1998. "Forecasting index volatility: sampling interval and non-trading effects," Applied Financial Economics, Taylor & Francis Journals, vol. 8(5), pages 477-485.
    10. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, November.
    11. Linlan Xiao, 2013. "Realized volatility forecasting: empirical evidence from stock market indices and exchange rates," Applied Financial Economics, Taylor & Francis Journals, vol. 23(1), pages 57-69, January.
    12. Shiyi Chen & Wolfgang K. Härdle & Kiho Jeong, 2010. "Forecasting volatility with support vector machine-based GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 406-433.
    13. Taufiq Choudhry & Hao Wu, 2008. "Forecasting ability of GARCH vs Kalman filter method: evidence from daily UK time-varying beta," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 670-689.
    14. Bali, Turan G. & Weinbaum, David, 2007. "A conditional extreme value volatility estimator based on high-frequency returns," Journal of Economic Dynamics and Control, Elsevier, vol. 31(2), pages 361-397, February.
    15. Trang Nha Le & Makoto Kakinaka, 2010. "International Transmission Of Stock Returns: Mean And Volatility Spillover Effects In Indonesia And Malaysia," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 4(1), pages 115-131.
    16. Eugenie Hol & Siem Jan Koopman, 2000. "Forecasting the Variability of Stock Index Returns with Stochastic Volatility Models and Implied Volatility," Tinbergen Institute Discussion Papers 00-104/4, Tinbergen Institute.
    17. Asgharian, Hossein & Sikström, Sverker, 2013. "Predicting Stock Price Volatility by Analyzing Semantic Content in Media," Knut Wicksell Working Paper Series 2013/16, Lund University, Knut Wicksell Centre for Financial Studies.
    18. Anupam Dutta & Debojyoti Das, 2022. "Forecasting realized volatility: New evidence from time‐varying jumps in VIX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2165-2189, December.
    19. Maghyereh, Aktham I. & Awartani, Basel & Bouri, Elie, 2016. "The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 57(C), pages 78-93.
    20. Evangelos Drimbetas & Nikolaos Sariannidis & Nicos Porfiris, 2007. "The effect of derivatives trading on volatility of the underlying asset: evidence from the Greek stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 17(2), pages 139-148.

    More about this item

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

    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:arz:wpaper:eres2001_207. 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: Architexturez Imprints (email available below). General contact details of provider: https://edirc.repec.org/data/eressea.html .

    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.