IDEAS home Printed from https://ideas.repec.org/a/rfb/journl/v08y2016i2p055-060.html
   My bibliography  Save this article

Discrete Portfolio Adjustment with Fixed Transaction Costs

Author

Listed:
  • Linus Wilson

Abstract

This paper presents a closed-form solution to the portfolio adjustment problem in discrete time when an investor faces fixed transaction costs. This transaction cost model assumes a mean-variance investor who wants to adjust her holdings of a risky and risk-free asset. It is shown how this model can be calibrated to be used with a variety of risk models such as life cycle portfolio weights and value at risk (VaR) models. The decision problem can easily be inputted into and calculated in Excel. This paper finds that investors facing lower fixed transaction costs, with higher account balances, and with a greater mismatch between their desired and current allocations will be more eager to rebalance.

Suggested Citation

  • Linus Wilson, 2016. "Discrete Portfolio Adjustment with Fixed Transaction Costs," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 8(2), pages 055-060, December.
  • Handle: RePEc:rfb:journl:v:08:y:2016:i:2:p:055-060
    as

    Download full text from publisher

    File URL: http://rfb.ase.ro/articole/art2_dec_2016.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Maxime Bonelli & Mireille Bossy, 2017. "Portfolio Management with Drawdown Constraint: An Analysis of Optimal Investment," Working Papers hal-02282162, HAL.
    2. Vladimir Cherny & Jan Obłój, 2013. "Portfolio optimisation under non-linear drawdown constraints in a semimartingale financial model," Finance and Stochastics, Springer, vol. 17(4), pages 771-800, October.
    3. Brad M. Barber & Terrance Odean, 2001. "Boys will be Boys: Gender, Overconfidence, and Common Stock Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 261-292.
    4. Zabel, Edward, 1973. "Consumer Choice, Portfolio Decisions, and Transaction Costs," Econometrica, Econometric Society, vol. 41(2), pages 321-335, March.
    5. Vladimir Cherny & Jan Obloj, 2011. "Portfolio optimisation under non-linear drawdown constraints in a semimartingale financial model," Papers 1110.6289, arXiv.org, revised Apr 2013.
    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. Paolo Guasoni & Jan Obłój, 2016. "The Incentives Of Hedge Fund Fees And High-Water Marks," Mathematical Finance, Wiley Blackwell, vol. 26(2), pages 269-295, April.
    2. Stanislaus Maier-Paape & Andreas Platen & Qiji Jim Zhu, 2019. "A General Framework for Portfolio Theory. Part III: Multi-Period Markets and Modular Approach," Risks, MDPI, vol. 7(2), pages 1-31, June.
    3. Wang, Wenyuan & Chen, Ping & Li, Shuanming, 2020. "Generalized expected discounted penalty function at general drawdown for Lévy risk processes," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 12-25.
    4. Baurdoux, E.J. & Palmowski, Z. & Pistorius, M.R., 2017. "On future drawdowns of Lévy processes," Stochastic Processes and their Applications, Elsevier, vol. 127(8), pages 2679-2698.
    5. Ankush Agarwal & Ronnie Sircar, 2017. "Portfolio Benchmarking under Drawdown Constraint and Stochastic Sharpe Ratio," Working Papers hal-01388399, HAL.
    6. Zhang, Gongqiu & Li, Lingfei, 2023. "A general method for analysis and valuation of drawdown risk," Journal of Economic Dynamics and Control, Elsevier, vol. 152(C).
    7. Leonie Violetta Brinker, 2021. "Minimal Expected Time in Drawdown through Investment for an Insurance Diffusion Model," Risks, MDPI, vol. 9(1), pages 1-18, January.
    8. Chen, Xinfu & Landriault, David & Li, Bin & Li, Dongchen, 2015. "On minimizing drawdown risks of lifetime investments," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 46-54.
    9. Long Bai & Peng Liu, 2019. "Drawdown and Drawup for Fractional Brownian Motion with Trend," Journal of Theoretical Probability, Springer, vol. 32(3), pages 1581-1612, September.
    10. Landriault, David & Li, Bin & Li, Shu, 2015. "Analysis of a drawdown-based regime-switching Lévy insurance model," Insurance: Mathematics and Economics, Elsevier, vol. 60(C), pages 98-107.
    11. Ankush Agarwal & Ronnie Sircar, 2016. "Portfolio Benchmarking under Drawdown Constraint and Stochastic Sharpe Ratio," Papers 1610.08558, arXiv.org.
    12. Li, Shu & Zhou, Xiaowen, 2022. "The Parisian and ultimate drawdowns of Lévy insurance models," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 140-160.
    13. David Landriault & Bin Li & Hongzhong Zhang, 2017. "A Unified Approach for Drawdown (Drawup) of Time-Homogeneous Markov Processes," Papers 1702.07786, arXiv.org.
    14. Sergio Ortobelli Lozza & Enrico Angelelli & Alda Ndoci, 2019. "Timing portfolio strategies with exponential Lévy processes," Computational Management Science, Springer, vol. 16(1), pages 97-127, February.
    15. Baurdoux, Erik J. & Palmowski, Z & Pistorius, Martijn R, 2017. "On future drawdowns of Lévy processes," LSE Research Online Documents on Economics 84342, London School of Economics and Political Science, LSE Library.
    16. Berg, Joyce E. & Rietz, Thomas A., 2019. "Longshots, overconfidence and efficiency on the Iowa Electronic Market," International Journal of Forecasting, Elsevier, vol. 35(1), pages 271-287.
    17. Maxime Menuet & Petros G. Sekeris, 2021. "Overconfidence and conflict," Economic Inquiry, Western Economic Association International, vol. 59(4), pages 1483-1499, October.
    18. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    19. Bobba, Matteo & Frisancho, Veronica, 2022. "Self-perceptions about academic achievement: Evidence from Mexico City," Journal of Econometrics, Elsevier, vol. 231(1), pages 58-73.
    20. Jason M. Lindo & Nicholas J. Sanders & Philip Oreopoulos, 2010. "Ability, Gender, and Performance Standards: Evidence from Academic Probation," American Economic Journal: Applied Economics, American Economic Association, vol. 2(2), pages 95-117, April.

    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:rfb:journl:v:08:y:2016:i:2:p:055-060. 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: Tatu Lucian (email available below). General contact details of provider: https://edirc.repec.org/data/ffasero.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.