IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1709.04070.html
   My bibliography  Save this paper

Multivariate Density Modeling for Retirement Finance

Author

Listed:
  • Christopher J. Rook

Abstract

Prior to the financial crisis mortgage securitization models increased in sophistication as did products built to insure against losses. Layers of complexity formed upon a foundation that could not support it and as the foundation crumbled the housing market followed. That foundation was the Gaussian copula which failed to correctly model failure-time correlations of derivative securities in duress. In retirement, surveys suggest the greatest fear is running out of money and as retirement decumulation models become increasingly sophisticated, large financial firms and robo-advisors may guarantee their success. Similar to an investment bank failure the event of retirement ruin is driven by outliers and correlations in times of stress. It would be desirable to have a foundation able to support the increased complexity before it forms however the industry currently relies upon similar Gaussian (or lognormal) dependence structures. We propose a multivariate density model having fixed marginals that is tractable and fits data which are skewed, heavy-tailed, multimodal, i.e., of arbitrary complexity allowing for a rich correlation structure. It is also ideal for stress-testing a retirement plan by fitting historical data seeded with black swan events. A preliminary section reviews all concepts before they are used and fully documented C/C++ source code is attached making the research self-contained. Lastly, we take the opportunity to challenge existing retirement finance dogma and also review some recent criticisms of retirement ruin probabilities and their suggested replacement metrics.

Suggested Citation

  • Christopher J. Rook, 2017. "Multivariate Density Modeling for Retirement Finance," Papers 1709.04070, arXiv.org.
    • Handle: RePEc:arx:papers:1709.04070
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1709.04070
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christopher J. Rook, 2015. "Optimal Equity Glidepaths in Retirement," Papers 1506.08400, arXiv.org.
    2. Jan Fidrmuc & Peter Huber, 2007. "Introduction," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 34(4), pages 281-286, September.
    3. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    4. G. J. McLachlan, 1987. "On Bootstrapping the Likelihood Ratio Test Statistic for the Number of Components in a Normal Mixture," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(3), pages 318-324, November.
    5. Christopher J. Rook & Mitchell Kerman, 2015. "Approximating the Sum of Correlated Lognormals: An Implementation," Papers 1508.07582, arXiv.org.
    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. Maciejowska, Katarzyna, 2013. "Assessing the number of components in a normal mixture: an alternative approach," MPRA Paper 50303, University Library of Munich, Germany.
    2. Bloom, David E & Canning, David & Sevilla, Jaypee, 2003. "Geography and Poverty Traps," Journal of Economic Growth, Springer, vol. 8(4), pages 355-378, December.
    3. Milan Kumar Das & Anindya Goswami, 2019. "Testing of binary regime switching models using squeeze duration analysis," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-20, March.
    4. RenÈ Garcia, 2002. "Are the Effects of Monetary Policy Asymmetric?," Economic Inquiry, Western Economic Association International, vol. 40(1), pages 102-119, January.
    5. Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020. "Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
    6. Chkili, Walid & Nguyen, Duc Khuong, 2014. "Exchange rate movements and stock market returns in a regime-switching environment: Evidence for BRICS countries," Research in International Business and Finance, Elsevier, vol. 31(C), pages 46-56.
    7. Manuela Goretti, 2005. "The Brazilian currency turmoil of 2002: a nonlinear analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(4), pages 289-306.
    8. David Andolfatto & Paul Gomme, 2003. "Monetary Policy Regimes and Beliefs," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(1), pages 1-30, February.
    9. Valentina Aprigliano & Danilo Liberati, 2021. "Using Credit Variables to Date Business Cycle and to Estimate the Probabilities of Recession in Real Time," Manchester School, University of Manchester, vol. 89(S1), pages 76-96, September.
    10. DAVID E. ALLEN & MICHAEL McALEER & ROBERT J. POWELL & ABHAY K. SINGH, 2018. "Non-Parametric Multiple Change Point Analysis Of The Global Financial Crisis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-23, June.
    11. Menzies Gordon Douglas & Zizzo Daniel John, 2009. "Inferential Expectations," The B.E. Journal of Macroeconomics, De Gruyter, vol. 9(1), pages 1-27, December.
    12. Elyasiani, Elyas & Mansur, Iqbal & Pagano, Michael S., 2007. "Convergence and risk-return linkages across financial service firms," Journal of Banking & Finance, Elsevier, vol. 31(4), pages 1167-1190, April.
    13. Valerie Cerra & Sweta Chaman Saxena, 2008. "Growth Dynamics: The Myth of Economic Recovery," American Economic Review, American Economic Association, vol. 98(1), pages 439-457, March.
    14. Stefano d'Addona & Ilaria Musumeci, 2012. "The British opt-out from the European Monetary Union: empirical evidence from monetary policy rules," CEIS Research Paper 225, Tor Vergata University, CEIS, revised 26 Mar 2012.
    15. Giraitis, Liudas & Kapetanios, George & Marcellino, Massimiliano, 2021. "Time-varying instrumental variable estimation," Journal of Econometrics, Elsevier, vol. 224(2), pages 394-415.
    16. Mariam Camarero & Juan Sapena & Cecilio Tamarit, 2020. "Modelling Time-Varying Parameters in Panel Data State-Space Frameworks: An Application to the Feldstein–Horioka Puzzle," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 87-114, June.
    17. Xi, Xiaojing & Mamon, Rogemar, 2011. "Parameter estimation of an asset price model driven by a weak hidden Markov chain," Economic Modelling, Elsevier, vol. 28(1-2), pages 36-46, January.
    18. repec:dau:papers:123456789/11711 is not listed on IDEAS
    19. Amos Golan & Jeffrey M. Perloff, 2004. "Superior Forecasts of the U.S. Unemployment Rate Using a Nonparametric Method," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 433-438, February.
    20. Caner,M. & Hansen,B.E., 1998. "Threshold autoregression with a near unit root," Working papers 27, Wisconsin Madison - Social Systems.
    21. Anne Morrison Piehl & Suzanne J. Cooper & Anthony A. Braga & David M. Kennedy, 2003. "Testing for Structural Breaks in the Evaluation of Programs," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 550-558, August.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:1709.04070. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.