IDEAS home Printed from https://ideas.repec.org/p/duk/dukeec/10-60.html
   My bibliography  Save this paper

Habit, Long-Run Risks, Prospect? A Statistical Inquiry

Author

Listed:
  • Eric M. Aldrich
  • A. Ronald Gallant

Abstract

We use recently proposed Bayesian statistical methods to compare the habit persistence asset pricing model of Campbell and Cochrane, the long-run risks model of Bansal and Yaron, and the prospect theory model of Barberis, Huang, and Santos. We improve these Bayesian methods so that they can accommodate highly nonlinear models such as the three aforementioned. Our substantive results can be stated succinctly: If one believes that the extreme consumption fluctuations of 1930–1949 can recur, although they have not in the last sixty years even counting the current recession, then the long-run risks model is preferred. Otherwise, the habit model is preferred. We reach this conclusion by undertaking two types of comparisons, relative and absolute, over two sample periods, 1930–2008 and 1950–2008, using real, annual, U.S. data on stock returns, consumption growth, and the price to dividend ratio. Comparisons are conducted using a trivariate series of all three, a bivariate series comprised of consumption growth and stock returns, and a univariate series of stock returns alone. The prior for each model is that the ergodic mean of the real interest rate be 0.896 within ±1 with probability 0.95 together with a preference for model parameters that are near their published values. The prospect theory model is not considered for the trivariate series because it puts all its mass on a two-dimensional subspace thereby violating the regularity conditions of the methods employed. For the trivariate series, in the relative comparison, the long-run risks model dominates the habit model over the 1930–2008 period, while the habit persistence model dominates the long-run risks model over the 1950–2008 period; in the absolute assessment, both models fail over both sample periods. Empirical results for the bivariate series are explored more completely because it has the most substantive relevance. For the bivariate series, in the relative comparison, the long-run risks model dominates over the 1930–2008 period, while the habit persistence model dominates over the 1950–2008 period; in the absolute assessment, the habit model fails in the 1930–2008 period and the prospect theory model fails in the 1950–2008 period. Out-of-sample, the models show interesting differences in their forecasts over the 2009–2013 horizon. In-sample, all three models track the conditional volatility of stock returns about the same. They differ mainly in how they track the conditional volatility of consumption growth and the conditional correlation between consumption growth and stock returns. For the univariate series and for both sample periods, the models perform about the same in the relative comparison and fit the series reasonably well in the absolute assessment. The main value of the univariate series is that the near equal performance of the three models permits exploration of methodological issues.

Suggested Citation

  • Eric M. Aldrich & A. Ronald Gallant, 2010. "Habit, Long-Run Risks, Prospect? A Statistical Inquiry," Working Papers 10-60, Duke University, Department of Economics.
  • Handle: RePEc:duk:dukeec:10-60
    as

    Download full text from publisher

    File URL: http://papers.ssrn.com/abstract=1674030
    File Function: main text
    Download Restriction: no

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Raymond Kan & Cesare Robotti, 2016. "The Exact Distribution of the Hansen–Jagannathan Bound," Management Science, INFORMS, vol. 62(7), pages 1915-1943, July.
    2. Mengel F. & Peeters R.J.A.P., 2015. "Do markets encourage risk-seeking behaviour?," Research Memorandum 042, Maastricht University, Graduate School of Business and Economics (GSBE).
    3. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFS Working Paper Series 572, Center for Financial Studies (CFS).
    4. Grammig, Joachim & Küchlin, Eva-Maria, 2017. "A two-step indirect inference approach to estimate the long-run risk asset pricing model," CFR Working Papers 17-01, University of Cologne, Centre for Financial Research (CFR).
    5. Favero, Carlo A. & Ortu, Fulvio & Tamoni, Andrea & Yang, Haoxi, 2016. "Implications of Return Predictability across Horizons for Asset Pricing Models," CEPR Discussion Papers 11645, C.E.P.R. Discussion Papers.
    6. Gallant, A. Ronald & Jahan-Parvar, Mohammad & Liu, Hening, 2015. "Measuring Ambiguity Aversion," Finance and Economics Discussion Series 2015-105, Board of Governors of the Federal Reserve System (U.S.).
    7. Andrew Y. Chen & Rebecca Wasyk & Fabian Winkler, 2017. "A Likelihood-Based Comparison of Macro Asset Pricing Models," Finance and Economics Discussion Series 2017-024, Board of Governors of the Federal Reserve System (U.S.).

    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:duk:dukeec:10-60. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Department of Economics Webmaster). General contact details of provider: http://econ.duke.edu/ .

    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.

    We have no references for this item. You can help adding them by using 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.