IDEAS home Printed from https://ideas.repec.org/a/spr/decfin/v44y2021i1d10.1007_s10203-020-00300-z.html
   My bibliography  Save this article

Managing liquidity with portfolio staleness

Author

Listed:
  • Giuseppe Buccheri

    (Universitá degli Studi di Roma Tor Vergata)

  • Davide Pirino

    (Universitá degli Studi di Roma Tor Vergata)

  • Luca Trapin

    (Universitá di Bologna)

Abstract

Liquidity is a risk factor of primary relevance that can significantly affect the asset allocation decisions of investors. In this paper, we introduce the concept of portfolio staleness and propose a simple framework to manage portfolio liquidity, intended as the cost needed to liquidate the portfolio. Within this framework, the traditional minimum variance problem is solved under the additional constraint that portfolio staleness must be smaller than a given threshold. We show that a dynamic asset allocation strategy based on the staleness constrained portfolio can significantly enhance portfolio liquidity over the standard minimum variance solution. Meanwhile, the increase in portfolio risk is limited, generating large liquidity gains per unit of risk.

Suggested Citation

  • Giuseppe Buccheri & Davide Pirino & Luca Trapin, 2021. "Managing liquidity with portfolio staleness," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 215-239, June.
    • Handle: RePEc:spr:decfin:v:44:y:2021:i:1:d:10.1007_s10203-020-00300-z
    DOI: 10.1007/s10203-020-00300-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10203-020-00300-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10203-020-00300-z?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. Jean-Luc Vila & Dimitri Vayanos, 1999. "Equilibrium interest rate and liquidity premium with transaction costs," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 13(3), pages 509-539.
    2. Acharya, Viral V. & Pedersen, Lasse Heje, 2005. "Asset pricing with liquidity risk," Journal of Financial Economics, Elsevier, vol. 77(2), pages 375-410, August.
    3. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1683, August.
    4. Gromb, Denis & Vayanos, Dimitri, 2002. "Equilibrium and welfare in markets with financially constrained arbitrageurs," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 361-407.
    5. Victor DeMiguel & Lorenzo Garlappi & Francisco J. Nogales & Raman Uppal, 2009. "A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms," Management Science, INFORMS, vol. 55(5), pages 798-812, May.
    6. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    7. Amihud, Yakov & Mendelson, Haim, 1986. "Asset pricing and the bid-ask spread," Journal of Financial Economics, Elsevier, vol. 17(2), pages 223-249, December.
    8. Chiu, Junmao & Chung, Huimin & Ho, Keng-Yu & Wang, George H.K., 2012. "Funding liquidity and equity liquidity in the subprime crisis period: Evidence from the ETF market," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2660-2671.
    9. Laurie Simon Hodrick & Pamela C. Moulton, 2009. "Liquidity: Considerations of a Portfolio Manager," Financial Management, Financial Management Association International, vol. 38(1), pages 59-74, March.
    10. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    11. Allaudeen Hameed & Wenjin Kang & S. Viswanathan, 2010. "Stock Market Declines and Liquidity," Journal of Finance, American Finance Association, vol. 65(1), pages 257-293, February.
    12. Oh, Dong Hwan & Patton, Andrew J., 2016. "High-dimensional copula-based distributions with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 349-366.
    13. Canner, Niko & Mankiw, N Gregory & Weil, David N, 1997. "An Asset Allocation Puzzle," American Economic Review, American Economic Association, vol. 87(1), pages 181-191, March.
    14. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1684, August.
    15. Scharfstein, David S & Stein, Jeremy C, 1990. "Herd Behavior and Investment," American Economic Review, American Economic Association, vol. 80(3), pages 465-479, June.
    16. Bazgour, Tarik & Heuchenne, Cedric & Sougné, Danielle, 2016. "Conditional portfolio allocation: Does aggregate market liquidity matter?," Journal of Empirical Finance, Elsevier, vol. 35(C), pages 110-135.
    17. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics," Econometrica, Econometric Society, vol. 72(3), pages 885-925, May.
    18. Ghysels, Eric & Pereira, João Pedro, 2008. "Liquidity and conditional portfolio choice: A nonparametric investigation," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 679-699, September.
    19. Federico M. Bandi & Davide Pirino & Roberto Renò, 2017. "EXcess Idle Time," Econometrica, Econometric Society, vol. 85(6), pages 1793-1846, November.
    20. Vayanos, Dimitri, 1998. "Transaction Costs and Asset Prices: A Dynamic Equilibrium Model," Review of Financial Studies, Society for Financial Studies, vol. 11(1), pages 1-58.
    21. Jeff Fleming & Chris Kirby & Barbara Ostdiek, 2001. "The Economic Value of Volatility Timing," Journal of Finance, American Finance Association, vol. 56(1), pages 329-352, February.
    22. George M. Constantinides, 2005. "Capital Market Equilibrium with Transaction Costs," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 7, pages 207-227, World Scientific Publishing Co. Pte. Ltd..
    23. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    24. Jorion, Philippe, 1985. "International Portfolio Diversification with Estimation Risk," The Journal of Business, University of Chicago Press, vol. 58(3), pages 259-278, July.
    25. Bertsimas, Dimitris & Lo, Andrew W., 1998. "Optimal control of execution costs," Journal of Financial Markets, Elsevier, vol. 1(1), pages 1-50, April.
    26. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2003. "The economic value of volatility timing using "realized" volatility," Journal of Financial Economics, Elsevier, vol. 67(3), pages 473-509, March.
    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. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
    2. Li, Jian & He, Zhou & Wang, Shouyang, 2022. "A survey of supply chain operation and finance with Fintech: Research framework and managerial insights," International Journal of Production Economics, Elsevier, vol. 247(C).

    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. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2018. "Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions," Journal of Econometrics, Elsevier, vol. 207(1), pages 71-91.
    2. Vayanos, Dimitri & Wang, Jiang, 2013. "Market Liquidity—Theory and Empirical Evidence ," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1289-1361, Elsevier.
    3. Karstanje, Dennis & Sojli, Elvira & Tham, Wing Wah & van der Wel, Michel, 2013. "Economic valuation of liquidity timing," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5073-5087.
    4. Hautsch, Nikolaus & Voigt, Stefan, 2019. "Large-scale portfolio allocation under transaction costs and model uncertainty," Journal of Econometrics, Elsevier, vol. 212(1), pages 221-240.
    5. Dimitri Vayanos & Jiang Wang, 2012. "Market Liquidity -- Theory and Empirical Evidence," NBER Working Papers 18251, National Bureau of Economic Research, Inc.
    6. Gregory Connor & Lisa R. Goldberg & Robert A. Korajczyk, 2010. "Portfolio Risk Analysis," Economics Books, Princeton University Press, edition 1, number 9224.
    7. Roxana Chiriac & Valeri Voev, 2011. "Modelling and forecasting multivariate realized volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 922-947, September.
    8. Yu‐Sheng Lai, 2022. "High‐frequency data and stock–bond investing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1623-1638, December.
    9. Vassallo, Danilo & Buccheri, Giuseppe & Corsi, Fulvio, 2021. "A DCC-type approach for realized covariance modeling with score-driven dynamics," International Journal of Forecasting, Elsevier, vol. 37(2), pages 569-586.
    10. Cederburg, Scott & O’Doherty, Michael S. & Wang, Feifei & Yan, Xuemin (Sterling), 2020. "On the performance of volatility-managed portfolios," Journal of Financial Economics, Elsevier, vol. 138(1), pages 95-117.
    11. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    12. Vayanos, Dimitri & Wang, Jiang, 2009. "Liquidity and asset prices: a united framework," LSE Research Online Documents on Economics 29303, London School of Economics and Political Science, LSE Library.
    13. Michiel de Pooter & Martin Martens & Dick van Dijk, 2008. "Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data—But Which Frequency to Use?," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 199-229.
    14. Santos, André Alves Portela & Ferreira, Alexandre R., 2017. "On the choice of covariance specifications for portfolio selection problems," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(1), May.
    15. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.
    16. Symitsi, Efthymia & Symeonidis, Lazaros & Kourtis, Apostolos & Markellos, Raphael, 2018. "Covariance forecasting in equity markets," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 153-168.
    17. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    18. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
    19. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2015. "Do High‐Frequency Data Improve High‐Dimensional Portfolio Allocations?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 263-290, March.
    20. Turtle, H.J. & Wang, Kainan, 2016. "The benefits of improved covariance estimation," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 233-246.

    More about this item

    Keywords

    Portfolio liquidity; Investments; Price staleness; HAR;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:spr:decfin:v:44:y:2021:i:1:d:10.1007_s10203-020-00300-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.