IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/118978.html
   My bibliography  Save this paper

An information based one-factor asset pricing model

Author

Listed:
  • Ghosh, Anisha
  • Julliard, Christian
  • Taylor, Alex

Abstract

Given a set of asset returns, an information-theoretic approach is used to estimate non-parametrically the pricing kernel to price the given cross-section out-of-sample. Compared to leading factor models, this information SDF delivers smaller pricing errors and better cross-sectional fit, and identifies the maximum Sharpe ratio portfolio out-of-sample. Moreover, it extracts novel pricing information not captured by Fama-French and momentum factors, leading to an ‘information anomaly.' A tradable information portfolio that mimics this kernel has a very high out-of-sample Sharpe ratio, outperforming both the 1/N benchmark and the Value and Momentum strategies combined. These results hold for a wide cross-section of assets.

Suggested Citation

  • Ghosh, Anisha & Julliard, Christian & Taylor, Alex, 2016. "An information based one-factor asset pricing model," LSE Research Online Documents on Economics 118978, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:118978
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/118978/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 2013. "Uncertainty Outside and Inside Economic Models," Nobel Prize in Economics documents 2013-7, Nobel Prize Committee.
    2. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    3. Lewellen, Jonathan & Nagel, Stefan & Shanken, Jay, 2010. "A skeptical appraisal of asset pricing tests," Journal of Financial Economics, Elsevier, vol. 96(2), pages 175-194, May.
    4. Donald E. Brown & Robert L. Smith, 1990. "A correspondence principle for relative entropy minimization," Naval Research Logistics (NRL), John Wiley & Sons, vol. 37(2), pages 191-202, April.
    5. Shanken, Jay, 1985. "Multivariate tests of the zero-beta CAPM," Journal of Financial Economics, Elsevier, vol. 14(3), pages 327-348, September.
    6. Christian Julliard & Anisha Ghosh, 2012. "Can Rare Events Explain the Equity Premium Puzzle?," The Review of Financial Studies, Society for Financial Studies, vol. 25(10), pages 3037-3076.
    7. Jackwerth, Jens Carsten & Rubinstein, Mark, 1996. "Recovering Probability Distributions from Option Prices," Journal of Finance, American Finance Association, vol. 51(5), pages 1611-1632, December.
    8. Fernando Alvarez & Urban J. Jermann, 2005. "Using Asset Prices to Measure the Persistence of the Marginal Utility of Wealth," Econometrica, Econometric Society, vol. 73(6), pages 1977-2016, November.
    9. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    10. R. David Mclean & Jeffrey Pontiff, 2016. "Does Academic Research Destroy Stock Return Predictability?," Journal of Finance, American Finance Association, vol. 71(1), pages 5-32, February.
    11. Frederic S. Mishkin & Eugene N. White, 2002. "U.S. Stock Market Crashes and Their Aftermath: Implications for Monetary Policy," NBER Working Papers 8992, National Bureau of Economic Research, Inc.
    12. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    13. Kitamura, Yuichi & Stutzer, Michael, 2002. "Connections between entropic and linear projections in asset pricing estimation," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 159-174, March.
    14. Stock, James H., 1991. "Confidence intervals for the largest autoregressive root in U.S. macroeconomic time series," Journal of Monetary Economics, Elsevier, vol. 28(3), pages 435-459, December.
    15. Steve Ross, 2015. "The Recovery Theorem," Journal of Finance, American Finance Association, vol. 70(2), pages 615-648, April.
    16. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    17. P. M. Robinson, 1991. "Consistent Nonparametric Entropy-Based Testing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 437-453.
    18. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    19. Lars Peter Hansen, 2014. "Nobel Lecture: Uncertainty Outside and Inside Economic Models," Journal of Political Economy, University of Chicago Press, vol. 122(5), pages 945-987.
    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. Anisha Ghosh & Christian Julliard & Alex P. Taylor, 2017. "What Is the Consumption-CAPM Missing? An Information-Theoretic Framework for the Analysis of Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 30(2), pages 442-504.
    2. Sirio Aramonte & Mohammad R. Jahan-Parvar & Samuel Rosen & John W. Schindler, 2022. "Firm-Specific Risk-Neutral Distributions with Options and CDS," Management Science, INFORMS, vol. 68(9), pages 7018-7033, September.
    3. Qiu, Chen & Otsu, Taisuke, 2022. "Information theoretic approach to high dimensional multiplicative models: stochastic discount factor and treatment effect," LSE Research Online Documents on Economics 110494, London School of Economics and Political Science, LSE Library.
    4. DeMiguel, Victor & Martin-Utrera, Alberto & Nogales, Francisco J. & Uppal, Raman, 2017. "A Portfolio Perspective on the Multitude of Firm Characteristics," CEPR Discussion Papers 12417, C.E.P.R. Discussion Papers.
    5. 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.
    6. repec:gnv:wpaper:unige:76321 is not listed on IDEAS
    7. Qi Shi & Bin Li & Adrian (Wai Kong) Cheung & Richard Chung, 2017. "Augmenting the intertemporal CAPM with inflation: Further evidence from alternative models," Australian Journal of Management, Australian School of Business, vol. 42(4), pages 653-672, November.
    8. Cujean, Julien & Andrei, Daniel & Fournier, Mathieu, 2019. "The Low-Minus-High Portfolio and the Factor Zoo," CEPR Discussion Papers 14153, C.E.P.R. Discussion Papers.
    9. Lin, Qi, 2022. "Understanding idiosyncratic momentum in the Chinese stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    10. Pintor, Gabor, 2016. "The macroeconomic shock with the highest price of risk," LSE Research Online Documents on Economics 86225, London School of Economics and Political Science, LSE Library.
    11. Patrick Gagliardini & Elisa Ossola & Olivier Scaillet, 2016. "Time‐Varying Risk Premium in Large Cross‐Sectional Equity Data Sets," Econometrica, Econometric Society, vol. 84, pages 985-1046, May.
    12. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    13. Hollstein, Fabian & Nguyen, Duc Binh Benno & Prokopczuk, Marcel, 2019. "Asset prices and “the devil(s) you know”," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 20-35.
    14. Harvey, Campbell R. & Liu, Yan, 2021. "Lucky factors," Journal of Financial Economics, Elsevier, vol. 141(2), pages 413-435.
    15. Christoffersen, Peter & Fournier, Mathieu & Jacobs, Kris & Karoui, Mehdi, 2021. "Option-Based Estimation of the Price of Coskewness and Cokurtosis Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(1), pages 65-91, February.
    16. Svetlana Bryzgalova & Jiantao Huang & Christian Julliard, 2023. "Bayesian Solutions for the Factor Zoo: We Just Ran Two Quadrillion Models," Journal of Finance, American Finance Association, vol. 78(1), pages 487-557, February.
    17. Sainan Jin & Liangjun Su & Yonghui Zhang, 2015. "Nonparametric testing for anomaly effects in empirical asset pricing models," Empirical Economics, Springer, vol. 48(1), pages 9-36, February.
    18. Weidong Tian & Qing Zhou, 2017. "Asset Pricing Model Uncertainty: A Tradeoff between Bias and Variance," International Review of Finance, International Review of Finance Ltd., vol. 17(2), pages 289-324, June.
    19. Fernando Rubio, 2005. "Eficiencia De Mercado, Administracion De Carteras De Fondos Y Behavioural Finance," Finance 0503028, University Library of Munich, Germany, revised 23 Jul 2005.
    20. Chen Qiu & Taisuke Otsu, 2022. "Information theoretic approach to high‐dimensional multiplicative models: Stochastic discount factor and treatment effect," Quantitative Economics, Econometric Society, vol. 13(1), pages 63-94, January.
    21. Zaremba, Adam, 2019. "Price range and the cross-section of expected country and industry returns," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 174-189.

    More about this item

    Keywords

    pricing kernel; relative entropy; factor models; factor mimicking portfolios; alpha;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:ehl:lserod:118978. 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: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    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.