IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v21y2017icp201-205.html
   My bibliography  Save this article

Impact of persistent bad returns and volatility on retirement outcomes

Author

Listed:
  • Basu, Anup K.
  • Wiafe, Osei K.

Abstract

We examine wealth outcomes and risk of ruin faced by retirees due to persistent bad returns and high volatility in equity markets occurring at different stages of their retirement. Our results show poor equity returns persisting over long periods can put retirement security to serious risk but volatile market conditions actually have the opposite impact. The timing of such persistent bad returns and volatility (early or late stages of retirement) is critical and has differing effects on retirement outcomes. The results are robust to varying portfolio allocations to equities although the precise impacts are different.

Suggested Citation

  • Basu, Anup K. & Wiafe, Osei K., 2017. "Impact of persistent bad returns and volatility on retirement outcomes," Finance Research Letters, Elsevier, vol. 21(C), pages 201-205.
    • Handle: RePEc:eee:finlet:v:21:y:2017:i:c:p:201-205
    DOI: 10.1016/j.frl.2016.12.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612316303981
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2016.12.011?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. Ronald Newley & Nick Ingram & Veronic Livera & Sheridan Thompson, 2007. "Who's afraid of the big bad bear? Or, why investing in equities for retirement is not scary and why investing without equities is scary," Chapters, in: Hazel Bateman (ed.), Retirement Provision in Scary Markets, chapter 2, Edward Elgar Publishing.
    2. G. William Schwert, 2011. "Stock Volatility during the Recent Financial Crisis," European Financial Management, European Financial Management Association, vol. 17(5), pages 789-805, November.
    3. Dimitris Politis & Halbert White, 2004. "Automatic Block-Length Selection for the Dependent Bootstrap," Econometric Reviews, Taylor & Francis Journals, vol. 23(1), pages 53-70.
    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. Jin, Xiaoye, 2015. "Volatility transmission and volatility impulse response functions among the Greater China stock markets," Journal of Asian Economics, Elsevier, vol. 39(C), pages 43-58.
    2. Chendi Ni & Yuying Li & Peter A. Forsyth, 2023. "Neural Network Approach to Portfolio Optimization with Leverage Constraints:a Case Study on High Inflation Investment," Papers 2304.05297, arXiv.org, revised May 2023.
    3. Lu Wang & Feng Ma & Guoshan Liu, 2020. "Forecasting stock volatility in the presence of extreme shocks: Short‐term and long‐term effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 797-810, August.
    4. Siyi Liu & Xin Liu & Chuancai Zhang & Lingli Zhang, 2023. "Institutional and individual investors' short‐term reactions to the COVID‐19 crisis in China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 4333-4355, December.
    5. Palm, Franz C. & Smeekes, Stephan & Urbain, Jean-Pierre, 2011. "Cross-sectional dependence robust block bootstrap panel unit root tests," Journal of Econometrics, Elsevier, vol. 163(1), pages 85-104, July.
    6. Shankhajyoti De & Arabin Kumar Dey & Deepak Kumar Gouda, 2022. "Construction of Confidence Interval for a Univariate Stock Price Signal Predicted Through Long Short Term Memory Network," Annals of Data Science, Springer, vol. 9(2), pages 271-284, April.
    7. Paulo M. D. C. Parente & Richard J. Smith, 2021. "Quasi‐maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 377-405, July.
    8. Geert Bekaert & Eric C. Engstrom & Nancy R. Xu, 2022. "The Time Variation in Risk Appetite and Uncertainty," Management Science, INFORMS, vol. 68(6), pages 3975-4004, June.
    9. Tiwari, Aviral Kumar & Aye, Goodness C. & Gupta, Rangan & Gkillas, Konstantinos, 2020. "Gold-oil dependence dynamics and the role of geopolitical risks: Evidence from a Markov-switching time-varying copula model," Energy Economics, Elsevier, vol. 88(C).
    10. Shaen Corbet & Cian Twomey, 2014. "Quantifying the Effects of the Inclusion and Segregation of Contracts for Difference in Australian Equity Markets," International Journal of Economics and Financial Issues, Econjournals, vol. 4(2), pages 411-426.
    11. E. Ramos-P'erez & P. J. Alonso-Gonz'alez & J. J. N'u~nez-Vel'azquez, 2020. "Forecasting volatility with a stacked model based on a hybridized Artificial Neural Network," Papers 2006.16383, arXiv.org, revised Aug 2020.
    12. Kumar, Satish & Khalfaoui, Rabeh & Tiwari, Aviral Kumar, 2021. "Does geopolitical risk improve the directional predictability from oil to stock returns? Evidence from oil-exporting and oil-importing countries," Resources Policy, Elsevier, vol. 74(C).
    13. Fricke, Christoph & Menkhoff, Lukas, 2014. "Financial conditions, macroeconomic factors and (un)expected bond excess returns," Discussion Papers 35/2014, Deutsche Bundesbank.
    14. Choi, Ji-Eun & Shin, Dong Wan, 2019. "Moving block bootstrapping for a CUSUM test for correlation change," Computational Statistics & Data Analysis, Elsevier, vol. 135(C), pages 95-106.
    15. Orkun ÇELİK & Deniz ERER & Elif ERER, 2018. "2008 Küresel Krizinin Bireysel Emeklilik Fonları Oynaklığı Üzerindeki Etkisi: Türkiye Örneği," Sosyoekonomi Journal, Sosyoekonomi Society, issue 26(35).
    16. Hampl, Filip & Vágnerová Linnertová, Dagmar & Horváth, Matúš, 2024. "Crypto havens during war times? Evidence from the Russian invasion of Ukraine," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    17. Nucera, Federico & Valente, Giorgio, 2013. "Carry trades and the performance of currency hedge funds," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 407-425.
    18. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
    19. Fulli-Lemaire, Nicolas, 2013. "Alternative inflation hedging strategies for ALM," MPRA Paper 43755, University Library of Munich, Germany.
    20. Bryan Kelly & Alexander Ljungqvist, 2012. "Testing Asymmetric-Information Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1366-1413.

    More about this item

    Keywords

    Retirement; Probability of shortfall; Ruin risk; Equity allocation; Volatility;
    All these keywords.

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • J26 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Retirement; Retirement Policies
    • J32 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Nonwage Labor Costs and Benefits; Retirement Plans; Private Pensions

    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:finlet:v:21:y:2017:i:c:p:201-205. 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/frl .

    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.