IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v17y2013i2p211-220n6.html
   My bibliography  Save this article

Noncausality and asset pricing

Author

Listed:
  • Lof Matthijs

    (University of Helsinki)

Abstract

Misspecification of agents’ information sets or expectation formation mechanisms may lead to noncausal autoregressive representations of asset prices. Within the class of linear (vector) autoregressions, annual US stock prices are found to be best described by noncausal models, implying that agents’ expectations are not revealed to an outside observer such as an econometrician observing only realized market data. A simulation study shows that noncausal asset prices are observed when the data are generated by asset-pricing models featuring heterogeneous expectations.

Suggested Citation

  • Lof Matthijs, 2013. "Noncausality and asset pricing," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(2), pages 211-220, April.
    • Handle: RePEc:bpj:sndecm:v:17:y:2013:i:2:p:211-220:n:6
    DOI: 10.1515/snde-2012-0035
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/snde-2012-0035
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/snde-2012-0035?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2012. "Optimal forecasting of noncausal autoregressive time series," International Journal of Forecasting, Elsevier, vol. 28(3), pages 623-631.
    3. Parke, William R. & Waters, George A., 2007. "An evolutionary game theory explanation of ARCH effects," Journal of Economic Dynamics and Control, Elsevier, vol. 31(7), pages 2234-2262, July.
    4. Markku Lanne & Arto Luoma & Jani Luoto, 2012. "Bayesian Model Selection And Forecasting In Noncausal Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 812-830, August.
    5. Campbell, John Y & Shiller, Robert J, 1987. "Cointegration and Tests of Present Value Models," Journal of Political Economy, University of Chicago Press, vol. 95(5), pages 1062-1088, October.
    6. Forni, Mario & Giannone, Domenico & Lippi, Marco & Reichlin, Lucrezia, 2009. "Opening The Black Box: Structural Factor Models With Large Cross Sections," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1319-1347, October.
    7. Lanne, Markku & Saikkonen, Pentti, 2013. "Noncausal Vector Autoregression," Econometric Theory, Cambridge University Press, vol. 29(3), pages 447-481, June.
    8. Meitz, Mika & Saikkonen, Pentti, 2013. "Maximum likelihood estimation of a noninvertible ARMA model with autoregressive conditional heteroskedasticity," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 227-255.
    9. Kenneth Kasa & Todd B. Walker & Charles H. Whiteman, 2014. "Heterogeneous Beliefs and Tests of Present Value Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(3), pages 1137-1163.
    10. Markku Lanne & Pentti Saikkonen, 2011. "GMM Estimation with Non‐causal Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 581-592, October.
    11. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2011. "Non‐Fundamentalness in Structural Econometric Models: A Review," International Statistical Review, International Statistical Institute, vol. 79(1), pages 16-47, April.
    12. John Y. Campbell, Robert J. Shiller, 1988. "The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors," The Review of Financial Studies, Society for Financial Studies, vol. 1(3), pages 195-228.
    13. Lanne Markku & Saikkonen Pentti, 2011. "Noncausal Autoregressions for Economic Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(3), pages 1-32, October.
    14. repec:zbw:bofrdp:2009_018 is not listed on IDEAS
    15. Townsend, Robert M, 1983. "Forecasting the Forecasts of Others," Journal of Political Economy, University of Chicago Press, vol. 91(4), pages 546-588, August.
    16. Breid, F. Jay & Davis, Richard A. & Lh, Keh-Shin & Rosenblatt, Murray, 1991. "Maximum likelihood estimation for noncausal autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 36(2), pages 175-198, February.
    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. Lof, Matthijs, 2013. "Essays on Expectations and the Econometrics of Asset Pricing," MPRA Paper 59064, University Library of Munich, Germany.
    2. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    3. Frédéric BEC & Alain GUAY, 2020. "A simple unit root test consistent against any stationary alternative," Working Papers 2020-28, Center for Research in Economics and Statistics.
    4. Nyberg, Henri & Saikkonen, Pentti, 2014. "Forecasting with a noncausal VAR model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 536-555.
    5. Lanne Markku, 2015. "Noncausality and inflation persistence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 469-481, September.
    6. Markku Lanne & Henri Nyberg, 2015. "Nonlinear dynamic interrelationships between real activity and stock returns," CREATES Research Papers 2015-36, Department of Economics and Business Economics, Aarhus University.
    7. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    8. Frédérique Bec & Heino Bohn Nielsen & Sarra Saïdi, 2020. "Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1413-1428, December.
    9. Maynard, Alex & Ren, Dongmeng, 2019. "The finite sample power of long-horizon predictive tests in models with financial bubbles," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 418-430.
    10. Lanne, Markku & Saikkonen, Pentti, 2013. "Noncausal Vector Autoregression," Econometric Theory, Cambridge University Press, vol. 29(3), pages 447-481, June.
    11. Matthijs Lof, 2015. "Rational Speculators, Contrarians, and Excess Volatility," Management Science, INFORMS, vol. 61(8), pages 1889-1901, August.
    12. Kindop, Igor, 2021. "Ubiquitous multimodality in mixed causal-noncausal processes," MPRA Paper 109594, University Library of Munich, Germany, revised 04 Sep 2021.
    13. Frederique Bec & Alain Guay, 2020. "A Simple Unit Root Test Consistent Against Any Stationary Alternative," Working Papers 20-20, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    14. Alain Hecq & Daniel Velasquez-Gaviria, 2022. "Spectral estimation for mixed causal-noncausal autoregressive models," Papers 2211.13830, arXiv.org.
    15. Karapanagiotidis, Paul, 2013. "Empirical evidence for nonlinearity and irreversibility of commodity futures prices," MPRA Paper 56801, University Library of Munich, Germany.
    16. Nyholm, Juho, 2017. "Residual-based diagnostic tests for noninvertible ARMA models," MPRA Paper 81033, University Library of Munich, Germany.
    17. Karapanagiotidis, Paul, 2014. "Dynamic modeling of commodity futures prices," MPRA Paper 56805, University Library of Munich, Germany.
    18. Cerruti, Gianluca & Lombardini, Simone, 2022. "Financial bubbles as a recursive process lead by short-term strategies," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 555-568.
    19. Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
    20. Jean-Baptiste MICHAU, 2019. "Helicopter Drops of Money under Secular Stagnation," Working Papers 2019-10, Center for Research in Economics and Statistics.

    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. Lof, Matthijs, 2013. "Essays on Expectations and the Econometrics of Asset Pricing," MPRA Paper 59064, University Library of Munich, Germany.
    2. Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
    3. Pentti Saikkonen & Rickard Sandberg, 2016. "Testing for a Unit Root in Noncausal Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(1), pages 99-125, January.
    4. Lanne, Markku & Luoto, Jani, 2013. "Autoregression-based estimation of the new Keynesian Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 561-570.
    5. Nyberg, Henri & Saikkonen, Pentti, 2014. "Forecasting with a noncausal VAR model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 536-555.
    6. Lanne Markku, 2015. "Noncausality and inflation persistence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(4), pages 469-481, September.
    7. Pentti Saikkonen & Rickard Sandberg, 2016. "Testing for a Unit Root in Noncausal Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(1), pages 99-125, January.
    8. Lanne, Markku & Saikkonen, Pentti, 2013. "Noncausal Vector Autoregression," Econometric Theory, Cambridge University Press, vol. 29(3), pages 447-481, June.
    9. Lanne, Markku & Nyberg, Henri & Saarinen, Erkka, 2011. "Forecasting U.S. Macroeconomic and Financial Time Series with Noncausal and Causal AR Models: A Comparison," MPRA Paper 30254, University Library of Munich, Germany.
    10. Christian Gourieroux & Joann Jasiak, 2016. "Filtering, Prediction and Simulation Methods for Noncausal Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 405-430, May.
    11. repec:zbw:bofrdp:2013_026 is not listed on IDEAS
    12. Alain Hecq & Elisa Voisin, 2023. "Predicting Crashes in Oil Prices During The Covid-19 Pandemic with Mixed Causal-Noncausal Models," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 209-233, Emerald Group Publishing Limited.
    13. Alain Hecq & Li Sun, 2019. "Identification of Noncausal Models by Quantile Autoregressions," Papers 1904.05952, arXiv.org.
    14. Frédérique Bec & Heino Bohn Nielsen & Sarra Saïdi, 2020. "Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1413-1428, December.
    15. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    16. Gourieroux, Christian & Jasiak, Joann, 2018. "Misspecification of noncausal order in autoregressive processes," Journal of Econometrics, Elsevier, vol. 205(1), pages 226-248.
    17. Lanne, Markku & Luoto, Jani, 2012. "Has US inflation really become harder to forecast?," Economics Letters, Elsevier, vol. 115(3), pages 383-386.
    18. Christian Gourieroux & Joann Jasiak & Michelle Tong, 2021. "Convolution‐based filtering and forecasting: An application to WTI crude oil prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1230-1244, November.
    19. Markku Lanne & Henri Nyberg, 2015. "Nonlinear dynamic interrelationships between real activity and stock returns," CREATES Research Papers 2015-36, Department of Economics and Business Economics, Aarhus University.
    20. Francesco Giancaterini & Alain Hecq, 2020. "Inference in mixed causal and noncausal models with generalized Student's t-distributions," Papers 2012.01888, arXiv.org, revised Nov 2022.
    21. Hecq, A.W. & Lieb, L.M. & Telg, J.M.A., 2015. "Identification of Mixed Causal-Noncausal Models : How Fat Should We Go?," Research Memorandum 035, Maastricht University, Graduate School of Business and Economics (GSBE).

    More about this item

    Keywords

    Noncausal Autoregression; Nonfundamentalness; Stock prices;
    All these keywords.

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C59 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Other

    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:bpj:sndecm:v:17:y:2013:i:2:p:211-220:n:6. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.