IDEAS home Printed from https://ideas.repec.org/a/eee/insuma/v51y2012i3p551-566.html
   My bibliography  Save this article

Optimal investment and consumption when regime transitions cause price shocks

Author

Listed:
  • Lim, Andrew E.B.
  • Watewai, Thaisiri

Abstract

This paper concerns optimal investment and consumption with CRRA utility when there is event risk. Events are modeled by transitions in a finite state Markov chain, but unlike traditional regime switching models, transitions not only change the instantaneous return statistics but are accompanied by jumps in the price at the instant of transition. Optimal investment and consumption policies are characterized using stochastic control methods and computed by solving a system of ordinary differential equations and a convex optimization problem. We show that optimal policies are significantly different from those of traditional regime switching or jump-diffusion problems and that the cost of ignoring transition price shocks can be substantial.

Suggested Citation

  • Lim, Andrew E.B. & Watewai, Thaisiri, 2012. "Optimal investment and consumption when regime transitions cause price shocks," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 551-566.
  • Handle: RePEc:eee:insuma:v:51:y:2012:i:3:p:551-566
    DOI: 10.1016/j.insmatheco.2012.07.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S016766871200090X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.insmatheco.2012.07.011?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. Jun Liu & Francis A. Longstaff & Jun Pan, 2003. "Dynamic Asset Allocation with Event Risk," Journal of Finance, American Finance Association, vol. 58(1), pages 231-259, February.
    2. Yihong Xia, 2001. "Learning about Predictability: The Effects of Parameter Uncertainty on Dynamic Asset Allocation," Journal of Finance, American Finance Association, vol. 56(1), pages 205-246, February.
    3. Kyriakos Chourdakis, 2002. "Continuous Time Regime Switching Models and Applications in Estimating Processes with Stochastic Volatility and Jumps," Working Papers 464, Queen Mary University of London, School of Economics and Finance.
    4. Bjørn Eraker & Michael Johannes & Nicholas Polson, 2003. "The Impact of Jumps in Volatility and Returns," Journal of Finance, American Finance Association, vol. 58(3), pages 1269-1300, June.
    5. Sanjiv Ranjan Das & Raman Uppal, 2004. "Systemic Risk and International Portfolio Choice," Journal of Finance, American Finance Association, vol. 59(6), pages 2809-2834, December.
    6. Robert A. Jarrow & Fan Yu, 2008. "Counterparty Risk and the Pricing of Defaultable Securities," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 20, pages 481-515, World Scientific Publishing Co. Pte. Ltd..
    7. Kyriakos Chourdakis, 2002. "Continuous Time Regime Switching Models and Applications in Estimating Processes with Stochastic Volatility and Jumps," Working Papers 464, Queen Mary University of London, School of Economics and Finance.
    8. Bates, David S., 2000. "Post-'87 crash fears in the S&P 500 futures option market," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 181-238.
    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. Chotipong Charoensom & Thaisiri Watewai, 2022. "Optimal Liquidity Control and Systemic Risk in an Interbank Network with Liquidity Shocks and Regime-dependent Interconnectedness," PIER Discussion Papers 175, Puey Ungphakorn Institute for Economic Research.
    2. Campani, Carlos Heitor & Garcia, René & Lewin, Marcelo, 2021. "Optimal portfolio strategies in the presence of regimes in asset returns," Journal of Banking & Finance, Elsevier, vol. 123(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. Kshatriya, Saranya & Prasanna, Krishna, 2021. "Jump Interdependencies: Stochastic linkages among international stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    2. Jin, Xing & Zhang, Kun, 2013. "Dynamic optimal portfolio choice in a jump-diffusion model with investment constraints," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1733-1746.
    3. Jérôme Detemple, 2014. "Portfolio Selection: A Review," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 1-21, April.
    4. Fulvio Corsi & Davide Pirino & Roberto Renò, 2008. "Volatility forecasting: the jumps do matter," Department of Economics University of Siena 534, Department of Economics, University of Siena.
    5. Christensen, Kim & Oomen, Roel C.A. & Podolskij, Mark, 2014. "Fact or friction: Jumps at ultra high frequency," Journal of Financial Economics, Elsevier, vol. 114(3), pages 576-599.
    6. Li, Chenxu & Chen, Dachuan, 2016. "Estimating jump–diffusions using closed-form likelihood expansions," Journal of Econometrics, Elsevier, vol. 195(1), pages 51-70.
    7. Liu, Jun & Pan, Jun, 2003. "Dynamic derivative strategies," Journal of Financial Economics, Elsevier, vol. 69(3), pages 401-430, September.
    8. Thai Nguyen, 2016. "Optimal investment and consumption with downside risk constraint in jump-diffusion models," Papers 1604.05584, arXiv.org.
    9. Corsi, Fulvio & Pirino, Davide & Renò, Roberto, 2010. "Threshold bipower variation and the impact of jumps on volatility forecasting," Journal of Econometrics, Elsevier, vol. 159(2), pages 276-288, December.
    10. Hong, Yi & Jin, Xing, 2018. "Semi-analytical solutions for dynamic portfolio choice in jump-diffusion models and the optimal bond-stock mix," European Journal of Operational Research, Elsevier, vol. 265(1), pages 389-398.
    11. repec:wyi:journl:002108 is not listed on IDEAS
    12. Branger, Nicole & Kraft, Holger & Meinerding, Christoph, 2009. "What is the impact of stock market contagion on an investor's portfolio choice?," Insurance: Mathematics and Economics, Elsevier, vol. 45(1), pages 94-112, August.
    13. Branger, Nicole & Kraft, Holger & Meinerding, Christoph, 2014. "Partial information about contagion risk, self-exciting processes and portfolio optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 39(C), pages 18-36.
    14. Amaro de Matos, João & Silva, Nuno, 2014. "Consuming durable goods when stock markets jump: A strategic asset allocation approach," Journal of Economic Dynamics and Control, Elsevier, vol. 42(C), pages 86-104.
    15. Oliva, I. & Renò, R., 2018. "Optimal portfolio allocation with volatility and co-jump risk that Markowitz would like," Journal of Economic Dynamics and Control, Elsevier, vol. 94(C), pages 242-256.
    16. Xing Jin & Dan Luo & Xudong Zeng, 2021. "Tail Risk and Robust Portfolio Decisions," Management Science, INFORMS, vol. 67(5), pages 3254-3275, May.
    17. Asgharian, Hossein & Nossman, Marcus, 2011. "Risk contagion among international stock markets," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 22-38, February.
    18. Muck, Matthias, 2010. "Trading strategies with partial access to the derivatives market," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1288-1298, June.
    19. Filipović, Damir & Gourier, Elise & Mancini, Loriano, 2016. "Quadratic variance swap models," Journal of Financial Economics, Elsevier, vol. 119(1), pages 44-68.
    20. Konermann, Patrick & Meinerding, Christoph & Sedova, Olga, 2013. "Asset allocation in markets with contagion: The interplay between volatilities, jump intensities, and correlations," Review of Financial Economics, Elsevier, vol. 22(1), pages 36-46.
    21. Branger, Nicole & Muck, Matthias & Seifried, Frank Thomas & Weisheit, Stefan, 2017. "Optimal portfolios when variances and covariances can jump," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 59-89.

    More about this item

    Keywords

    Event risk; Regime switching; Defaultable bonds; Jump processes; Optimal investment and consumption; Stochastic control;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • 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:eee:insuma:v:51:y:2012:i:3:p:551-566. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505554 .

    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.