IDEAS home Printed from https://ideas.repec.org/p/hhs/lunewp/2001_016.html
   My bibliography  Save this paper

Empirical Probability Distributions of Real Return from Swedish Stock and Bond Portfolios

Author

Listed:
  • Graflund, Andreas

    (Department of Economics, Lund University)

Abstract

This paper introduces a new non-parametric approach to integrate empirical probability functions of the real return for different investment horizons for five portfolios of Swedish stocks and bonds. In our setting the problem reduces to generating new generalizations from an empirical Markov chain. We find that the stocks yield a real return of about 7.5% and bonds about 3.0%. Our results suggest that an investor ought to avoid bonds in the long run. Finally if the investors goal is to minimize the risk of capital destruction the preferable long-run passive portfolio is a mix of bonds and stocks.

Suggested Citation

  • Graflund, Andreas, 2001. "Empirical Probability Distributions of Real Return from Swedish Stock and Bond Portfolios," Working Papers 2001:16, Lund University, Department of Economics, revised 29 Jan 2002.
  • Handle: RePEc:hhs:lunewp:2001_016
    as

    Download full text from publisher

    File URL: http://project.nek.lu.se/publications/workpap/Papers/WP01_16.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Paparoditis, Efstathios & Politis, Dimitris N., 2001. "A Markovian Local Resampling Scheme For Nonparametric Estimators In Time Series Analysis," Econometric Theory, Cambridge University Press, vol. 17(3), pages 540-566, June.
    2. Fishburn, Peter C, 1977. "Mean-Risk Analysis with Risk Associated with Below-Target Returns," American Economic Review, American Economic Association, vol. 67(2), pages 116-126, March.
    3. repec:bla:scandj:v:99:y:1997:i:2:p:335-50 is not listed on IDEAS
    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. Dipankar Mondal & N. Selvaraju, 2022. "Convexity, two-fund separation and asset ranking in a mean-LPM portfolio selection framework," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 225-248, March.
    2. Wojtek Michalowski & Włodzimierz Ogryczak, 2001. "Extending the MAD portfolio optimization model to incorporate downside risk aversion," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(3), pages 185-200, April.
    3. Ogryczak, Wlodzimierz & Ruszczynski, Andrzej, 1999. "From stochastic dominance to mean-risk models: Semideviations as risk measures," European Journal of Operational Research, Elsevier, vol. 116(1), pages 33-50, July.
    4. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Efficient skewness/semivariance portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 17(5), pages 331-346, September.
    5. Jesus Gonzalo & Jose Olmo, 2014. "Conditional Stochastic Dominance Tests In Dynamic Settings," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 55(3), pages 819-838, August.
    6. Elie Matta & Jean McGuire, 2008. "Too Risky to Hold? The Effect of Downside Risk, Accumulated Equity Wealth, and Firm Performance on CEO Equity Reduction," Organization Science, INFORMS, vol. 19(4), pages 567-580, August.
    7. Luo, Yan & Wang, Xiaohuan & Zhang, Chenyang & Huang, Wei, 2021. "Accounting-based downside risk and expected stock returns: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 78(C).
    8. Brogan, Anita J. & Stidham Jr., Shaler, 2008. "Non-separation in the mean-lower-partial-moment portfolio optimization problem," European Journal of Operational Research, Elsevier, vol. 184(2), pages 701-710, January.
    9. Yao, Haixiang & Huang, Jinbo & Li, Yong & Humphrey, Jacquelyn E., 2021. "A general approach to smooth and convex portfolio optimization using lower partial moments," Journal of Banking & Finance, Elsevier, vol. 129(C).
    10. Roman, Diana & Mitra, Gautam & Zverovich, Victor, 2013. "Enhanced indexation based on second-order stochastic dominance," European Journal of Operational Research, Elsevier, vol. 228(1), pages 273-281.
    11. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    12. Tavakoli Baghdadabad, Mohammad Reza, 2014. "Average drawdown risk reduction and risk tolerances," Research in Economics, Elsevier, vol. 68(3), pages 264-276.
    13. Berg, Ernst & Starp, Michael, 2006. "Farm Level Risk Assessment Using Downside Risk Measures," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25400, International Association of Agricultural Economists.
    14. repec:ecb:ecbdps:202113 is not listed on IDEAS
    15. Tronstad, Russell & McNeill, Thomas J., 1987. "An Alternative Measure of Price Risk on Aggregate Sow Farrowings, 1973-86," 1987 Annual Meeting, August 2-5, East Lansing, Michigan 269961, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. Olmo, José & Sanso-Navarro, Marcos, 2012. "Forecasting the performance of hedge fund styles," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2351-2365.
    17. Veld, Chris & Veld-Merkoulova, Yulia V., 2008. "The risk perceptions of individual investors," Journal of Economic Psychology, Elsevier, vol. 29(2), pages 226-252, April.
    18. Liao Wang & David D. Yao, 2021. "Risk Hedging for Production Planning," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1825-1837, June.
    19. Danielsson, Jon & Jorgensen, Bjorn N. & Sarma, Mandira & de Vries, Casper G., 2006. "Comparing downside risk measures for heavy tailed distributions," Economics Letters, Elsevier, vol. 92(2), pages 202-208, August.
    20. Cotter, John & Dowd, Kevin, 2006. "Extreme spectral risk measures: An application to futures clearinghouse margin requirements," Journal of Banking & Finance, Elsevier, vol. 30(12), pages 3469-3485, December.
    21. Manzan, S. & Zerom, D., 2005. "A Multi-Step Forecast Density," CeNDEF Working Papers 05-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

    More about this item

    Keywords

    Empirical distribution; stock returns; bond returns; real return; markovian bootstrap; MCMC;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hhs:lunewp:2001_016. 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: Iker Arregui Alegria (email available below). General contact details of provider: https://edirc.repec.org/data/delunse.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.