IDEAS home Printed from https://ideas.repec.org/a/wsi/ijtafx/v06y2003i01ns0219024903001797.html
   My bibliography  Save this article

Why The Return Notion Matters

Author

Listed:
  • GREGOR DORFLEITNER

    (Institut für Statistik und Mathematische Wirtschaftstheorie Augsburg, Universität Augsburg, D-86135 Augsburg, Germany)

Abstract

Returns can be defined as log returns or as simple returns. Whereas on a numerical level the difference between these two terms is small as long as the return values are close to zero, there can be non-negligible differences if we look at expected values and (co)variances in a stochastic context. This paper examines the consequences of mixing up the two return terms when variances and convariances are considered. Three applications show that these consequences can be severe in the sense of suboptimal portfolio selection or invalid betas. The paper argues that more awareness of the suited return term is necessary.

Suggested Citation

  • Gregor Dorfleitner, 2003. "Why The Return Notion Matters," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 73-86.
  • Handle: RePEc:wsi:ijtafx:v:06:y:2003:i:01:n:s0219024903001797
    DOI: 10.1142/S0219024903001797
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219024903001797
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S0219024903001797?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. Dale J. Poirier, 1995. "Intermediate Statistics and Econometrics: A Comparative Approach," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262161494, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. M. Reza Bradrania & Maurice Peat & Stephen Satchell, 2022. "Liquidity Costs, Idiosyncratic Volatility and Expected Stock Returns," Papers 2211.04695, arXiv.org.
    2. Gregor Dorfleitner & Carina Lung, 2018. "Cryptocurrencies from the perspective of euro investors: a re-examination of diversification benefits and a new day-of-the-week effect," Journal of Asset Management, Palgrave Macmillan, vol. 19(7), pages 472-494, December.
    3. Reza Bradrania, M. & Peat, Maurice & Satchell, Stephen, 2015. "Liquidity costs, idiosyncratic volatility and expected stock returns," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 394-406.
    4. Christian Klein & Bernhard Zwergel & Sebastian Heiden, 2009. "On the existence of sports sentiment: the relation between football match results and stock index returns in Europe," Review of Managerial Science, Springer, vol. 3(3), pages 191-208, November.
    5. Svetlozar Rachev & Nancy Asare Nyarko & Blessing Omotade & Peter Yegon, 2023. "Bachelier's Market Model for ESG Asset Pricing," Papers 2306.04158, arXiv.org.
    6. Pedro Antonio Martín-Cervantes & María del Carmen Valls Martínez, 2023. "Unraveling the relationship between betas and ESG scores through the Random Forests methodology," Risk Management, Palgrave Macmillan, vol. 25(3), pages 1-29, September.
    7. Asparouhova, Elena & Bessembinder, Hendrik & Kalcheva, Ivalina, 2010. "Liquidity biases in asset pricing tests," Journal of Financial Economics, Elsevier, vol. 96(2), pages 215-237, May.
    8. Michael C. Nwogugu, 2020. "Decision-Making, Sub-Additive Recursive "Matching" Noise And Biases In Risk-Weighted Stock/Bond Index Calculation Methods In Incomplete Markets With Partially Observable Multi-Attribute Pref," Papers 2005.01708, arXiv.org.

    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. Fang, Hao Audrey, 2008. "A discrete-continuous model of households' vehicle choice and usage, with an application to the effects of residential density," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 736-758, November.
    2. Davide Pettenuzzo & Francesco Ravazzolo, 2016. "Optimal Portfolio Choice Under Decision‐Based Model Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1312-1332, November.
    3. Jan R. Magnus & Wendun Wang & Xinyu Zhang, 2016. "Weighted-Average Least Squares Prediction," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1040-1074, June.
    4. Poirier, Dale J., 1997. "Comparing and choosing between two models with a third model in the background," Journal of Econometrics, Elsevier, vol. 78(2), pages 139-151, June.
    5. Antonio Gargano & Davide Pettenuzzo & Allan Timmermann, 2019. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Management Science, INFORMS, vol. 65(2), pages 508-540, February.
    6. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    7. Tai-Hsin Huang & Yi-Huang Chiu & Chih-Ying Mao, 2021. "Imposing Regularity Conditions to Measure Banks’ Productivity Changes in Taiwan Using a Stochastic Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(2), pages 273-303, June.
    8. Roger Hartley & Gauthier Lanot & Ian Walker, 2014. "Who Really Wants To Be A Millionaire? Estimates Of Risk Aversion From Gameshow Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(6), pages 861-879, September.
    9. Rodney W. Strachan & Herman K. Van Dijk, 2013. "Evidence On Features Of A Dsge Business Cycle Model From Bayesian Model Averaging," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(1), pages 385-402, February.
    10. Yee Loon, 2011. "Model uncertainty, performance persistence and flows," Review of Quantitative Finance and Accounting, Springer, vol. 36(2), pages 153-205, February.
    11. Yong Li & Xiaobin Liu & Jun Yu & Tao Zeng, 2018. "A New Wald Test for Hypothesis Testing Based on MCMC outputs," Papers 1801.00973, arXiv.org.
    12. Koop, Gary & Dijk, Herman K. Van, 2000. "Testing for integration using evolving trend and seasonals models: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 97(2), pages 261-291, August.
    13. Li Mingliang & Tobias Justin L, 2006. "Bayesian Analysis of Structural Effects in an Ordered Equation System," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(4), pages 1-24, December.
    14. Gianluigi Pelloni & Wolfgang Polasek, 2003. "Macroeconomic Effects of Sectoral Shocks in Germany, The U.K. and, The U.S. A VAR-GARCH-M Approach," Computational Economics, Springer;Society for Computational Economics, vol. 21(1), pages 65-85, February.
    15. Paul Hofmarcher & Jesús Crespo Cuaresma & Bettina Grün & Kurt Hornik, 2015. "Last Night a Shrinkage Saved My Life: Economic Growth, Model Uncertainty and Correlated Regressors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 133-144, March.
    16. Kim, Chang-Jin & Nelson, Charles R, 2001. "A Bayesian Approach to Testing for Markov-Switching in Univariate and Dynamic Factor Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(4), pages 989-1013, November.
    17. Gordon, Stephen & St-Amour, Pascal, 1997. "Asset Prices with Contingent Preferences," Cahiers de recherche 9712, Université Laval - Département d'économique, revised 08 Jun 1998.
    18. Stephen Gordon & Michel Truchon, 2008. "Social choice, optimal inference and figure skating," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 30(2), pages 265-284, February.
    19. Mohit Batham & Soudeh Mirghasemi & Mohammad Arshad Rahman & Manini Ojha, 2021. "Modeling and Analysis of Discrete Response Data: Applications to Public Opinion on Marijuana Legalization in the United States," Papers 2109.10122, arXiv.org, revised May 2023.
    20. Sögner, Leopold, 2015. "Learning, convergence and economic constraints," Mathematical Social Sciences, Elsevier, vol. 75(C), pages 27-43.

    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:wsi:ijtafx:v:06:y:2003:i:01:n:s0219024903001797. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ijtaf/ijtaf.shtml .

    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.