IDEAS home Printed from https://ideas.repec.org/a/eee/jfinec/v147y2023i3p550-572.html
   My bibliography  Save this article

Volatility and informativeness

Author

Listed:
  • Dávila, Eduardo
  • Parlatore, Cecilia

Abstract

This paper studies the relation between volatility and informativeness in financial markets. We identify two channels (noise-reduction and equilibrium-learning) that determine the volatility-informativeness relation. When informativeness is sufficiently high (low), volatility and informativeness positively (negatively) comove in equilibrium. We identify conditions on primitives that guarantee that volatility and informativeness comove positively or negatively. We introduce the comovement score, a statistic that measures the distance of a given asset to the positive/negative comovement regions. Empirically, comovement scores (i) have trended downwards over the last decades, (ii) are positively related to value and idiosyncratic volatility and negatively to size and institutional ownership.

Suggested Citation

  • Dávila, Eduardo & Parlatore, Cecilia, 2023. "Volatility and informativeness," Journal of Financial Economics, Elsevier, vol. 147(3), pages 550-572.
  • Handle: RePEc:eee:jfinec:v:147:y:2023:i:3:p:550-572
    DOI: 10.1016/j.jfineco.2022.12.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304405X22002495
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jfineco.2022.12.005?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. Xavier Vives, 2017. "Endogenous Public Information and Welfare in Market Games," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(2), pages 935-963.
    2. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    3. Gadi Barlevy & Pietro Veronesi, 2000. "Information Acquisition in Financial Markets," Review of Economic Studies, Oxford University Press, vol. 67(1), pages 79-90.
    4. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    5. Elias Albagli & Christian Hellwig & Aleh Tsyvinski, 2023. "Imperfect Financial Markets and Investment Inefficiencies," American Economic Review, American Economic Association, vol. 113(9), pages 2323-2354, September.
    6. Masahiro Watanabe, 2008. "Price Volatility and Investor Behavior in an Overlapping Generations Model with Information Asymmetry," Journal of Finance, American Finance Association, vol. 63(1), pages 229-272, February.
    7. Jiang Wang, 1993. "A Model of Intertemporal Asset Prices Under Asymmetric Information," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(2), pages 249-282.
    8. Laura L. Veldkamp, 2011. "Information Choice in Macroeconomics and Finance," Economics Books, Princeton University Press, edition 1, number 9621.
    9. Bai, Jennie & Philippon, Thomas & Savov, Alexi, 2016. "Have financial markets become more informative?," Journal of Financial Economics, Elsevier, vol. 122(3), pages 625-654.
    10. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    11. Biais, Bruno & Glosten, Larry & Spatt, Chester, 2005. "Market microstructure: A survey of microfoundations, empirical results, and policy implications," Journal of Financial Markets, Elsevier, vol. 8(2), pages 217-264, May.
    12. Spiegel, Matthew, 1998. "Stock Price Volatility in a Multiple Security Overlapping Generations Model," Review of Financial Studies, Society for Financial Studies, vol. 11(2), pages 419-447.
    13. John Y. Campbell & Martin Lettau & Burton Malkiel & Yexiao Xu, 2023. "Idiosyncratic Equity Risk Two Decades Later," Critical Finance Review, now publishers, vol. 12(1-4), pages 203-223, August.
    14. Christian Hellwig & Aleh Tsyvinski & Elias Albagli, 2014. "Dynamic Dispersed Information and the Credit Spread Puzzle," 2014 Meeting Papers 808, Society for Economic Dynamics.
    15. Bradyn Breon-Drish, 2015. "On Existence and Uniqueness of Equilibrium in a Class of Noisy Rational Expectations Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(3), pages 868-921.
    16. Diamond, Douglas W. & Verrecchia, Robert E., 1981. "Information aggregation in a noisy rational expectations economy," Journal of Financial Economics, Elsevier, vol. 9(3), pages 221-235, September.
    17. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    18. Eduardo Dávila & Cecilia Parlatore, 2021. "Trading Costs and Informational Efficiency," Journal of Finance, American Finance Association, vol. 76(3), pages 1471-1539, June.
    19. Eduardo Dávila & Cecilia Parlatore, 2018. "Identifying Price Informativeness," NBER Working Papers 25210, National Bureau of Economic Research, Inc.
    20. Marcin Kacperczyk & Savitar Sundaresan & Tianyu Wang, 2018. "Do Foreign Investors Improve Market Efficiency?," NBER Working Papers 24765, National Bureau of Economic Research, Inc.
    21. Hellwig, Martin F., 1980. "On the aggregation of information in competitive markets," Journal of Economic Theory, Elsevier, vol. 22(3), pages 477-498, June.
    22. Manzano, Carolina & Vives, Xavier, 2011. "Public and private learning from prices, strategic substitutability and complementarity, and equilibrium multiplicity," Journal of Mathematical Economics, Elsevier, vol. 47(3), pages 346-369.
    23. Bergemann, Dirk & Heumann, Tibor & Morris, Stephen, 2015. "Information and volatility," Journal of Economic Theory, Elsevier, vol. 158(PB), pages 427-465.
    24. Lee, Dong Wook & Liu, Mark H., 2011. "Does more information in stock price lead to greater or smaller idiosyncratic return volatility?," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1563-1580, June.
    25. Jayant Vivek Ganguli & Liyan Yang, 2009. "Complementarities, Multiplicity, and Supply Information," Journal of the European Economic Association, MIT Press, vol. 7(1), pages 90-115, March.
    26. Georgy Chabakauri & Kathy Yuan & Konstantinos E Zachariadis, 2022. "Multi-asset Noisy Rational Expectations Equilibrium with Contingent Claims [A Noisy Rational Expectations Equilibrium for Multi-asset Securities Markets]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(5), pages 2445-2490.
    27. Elias Albagli & Christian Hellwig & Aleh Tsyvinski, 2017. "Imperfect Financial Markets and Shareholder Incentives in Partial and General Equilibrium," NBER Working Papers 23419, National Bureau of Economic Research, Inc.
    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. Jorge Pérez-Rodríguez & Emilio Gómez-Déniza & Simón Sosvilla-Rivero, 2019. "“Testing for private information using trade duration models with unobserved market heterogeneity: The case of Banco Popular”," IREA Working Papers 201907, University of Barcelona, Research Institute of Applied Economics, revised Apr 2019.
    2. Pérez-Rodríguez, Jorge V. & Gómez-Déniz, Emilio & Sosvilla-Rivero, Simón, 2021. "Testing unobserved market heterogeneity in financial markets: The case of Banco Popular," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 151-160.

    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. Eduardo Dávila & Cecilia Parlatore, 2021. "Trading Costs and Informational Efficiency," Journal of Finance, American Finance Association, vol. 76(3), pages 1471-1539, June.
    2. Albagli, Elias & Hellwig, Christian & Tsyvinski, Aleh, 2021. "Information Aggregation with Asymmetric Asset Payoffs," TSE Working Papers 21-1172, Toulouse School of Economics (TSE), revised Apr 2023.
    3. Elias Albagli & Christian Hellwig & Aleh Tsyvinski, 2021. "Dispersed Information and Asset Prices," Working Papers hal-03118639, HAL.
    4. Lou, Youcheng & Parsa, Sahar & Ray, Debraj & Li, Duan & Wang, Shouyang, 2019. "Information aggregation in a financial market with general signal structure," Journal of Economic Theory, Elsevier, vol. 183(C), pages 594-624.
    5. Zhifeng Cai, 2020. "Dynamic information acquisition and time-varying uncertainty," Departmental Working Papers 202002, Rutgers University, Department of Economics.
    6. Elias Albagli & Christian Hellwig & Aleh Tsyvinski, 2011. "A Theory of Asset Prices Based on Heterogeneous Information," Cowles Foundation Discussion Papers 1827, Cowles Foundation for Research in Economics, Yale University.
    7. Maryam Farboodi & Laura Veldkamp, 2018. "Long Run Growth of Financial Data Technology," Working Papers 18-09, New York University, Leonard N. Stern School of Business, Department of Economics.
    8. Veldkamp, Laura & Farboodi, Maryam, 2018. "Long Run Growth of Financial Data Technology," CEPR Discussion Papers 13278, C.E.P.R. Discussion Papers.
    9. Pavan, Alessandro & Vives, Xavier, 2015. "Information, Coordination, and Market Frictions: An Introduction," Journal of Economic Theory, Elsevier, vol. 158(PB), pages 407-426.
    10. Avdis, Efstathios, 2016. "Information tradeoffs in dynamic financial markets," Journal of Financial Economics, Elsevier, vol. 122(3), pages 568-584.
    11. Jordi Mondria & Xavier Vives & Liyan Yang, 2022. "Costly Interpretation of Asset Prices," Management Science, INFORMS, vol. 68(1), pages 52-74, January.
    12. Markus K Brunnermeier & Michael Sockin & Wei Xiong, 2022. "China’s Model of Managing the Financial System [Beauty Contests and Iterated Expectations in Asset Markets]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(6), pages 3115-3153.
    13. Angeletos, G.-M. & Lian, C., 2016. "Incomplete Information in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1065-1240, Elsevier.
    14. Matthijs Breugem & Adrian Buss, 2017. "Institutional Investors and Information Acquisition: Implications for Asset Prices and Informational Efficiency," Carlo Alberto Notebooks 524, Collegio Carlo Alberto.
    15. Peress, Joel & Schmidt, Daniel, 2021. "Noise traders incarnate: Describing a realistic noise trading process," Journal of Financial Markets, Elsevier, vol. 54(C).
    16. Luca Bernardinelli & Paolo Guasoni & Eberhard Mayerhofer, 2022. "Informational efficiency and welfare," Mathematics and Financial Economics, Springer, volume 16, number 2, June.
    17. Maryam Farboodi & Laura Veldkamp, 2017. "Long Run Growth of Financial Technology," NBER Working Papers 23457, National Bureau of Economic Research, Inc.
    18. Markus K. Brunnermeier & Michael Sockin & Wei Xiong, 2020. "China’s Model of Managing the Financial System," Working Papers 2020-45, Princeton University. Economics Department..
    19. Mäkinen, Taneli & Ohl, Björn, 2015. "Information acquisition and learning from prices over the business cycle," Journal of Economic Theory, Elsevier, vol. 158(PB), pages 585-633.
    20. Vayanos, Dimitri & Wang, Jiang, 2013. "Market Liquidity—Theory and Empirical Evidence ," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1289-1361, Elsevier.

    More about this item

    Keywords

    Price informativeness; Price volatility; Learning; Information aggregation; Comovement score;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:jfinec:v:147:y:2023:i:3:p:550-572. 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/inca/505576 .

    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.