IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1004.4822.html
   My bibliography  Save this paper

Modelling Information Flows in Financial Markets

Author

Listed:
  • Dorje C. Brody
  • Lane P. Hughston
  • Andrea Macrina

Abstract

This paper presents an overview of information-based asset pricing. In this approach, an asset is defined by its cash-flow structure. The market is assumed to have access to "partial" information about future cash flows. Each cash flow is determined by a collection of independent market factors called X-factors. The market filtration is generated by a set of information processes, each of which carries information about one of the X-factors, and eventually reveals the X-factor. Each information process has two terms, one of which contains a "signal" about the associated X-factor, and the other of which represents "market noise". The price of an asset is given by the expectation of the discounted cash flows in the risk-neutral measure, conditional on the information provided by the market. When the market noise is modelled by a Brownian bridge one is able to construct explicit formulae for asset prices, as well as semi-analytic expressions for the prices and greeks of options and derivatives. In particular, option price data can be used to determine the information flow-rate parameters implicit in the definitions of the information processes. One consequence of the modelling framework is a specific scheme of stochastic volatility and correlation processes. Instead of imposing a volatility and correlation model upon the dynamics of a set of assets, one is able to deduce the dynamics of the volatilities and correlations of the asset price movements from more primitive assumptions involving the associated cash flows. The paper concludes with an examination of situations involving asymmetric information. We present a simple model for informed traders and show how this can be used as a basis for so-called statistical arbitrage. Finally, we consider the problem of price formation in a heterogeneous market with multiple agents.

Suggested Citation

  • Dorje C. Brody & Lane P. Hughston & Andrea Macrina, 2010. "Modelling Information Flows in Financial Markets," Papers 1004.4822, arXiv.org.
  • Handle: RePEc:arx:papers:1004.4822
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1004.4822
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    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. Piekunko-Mantiuk Iwona, 2019. "Parameterized Trade on the Futures Market on the WIG20," Folia Oeconomica Stetinensia, Sciendo, vol. 19(1), pages 114-125, June.
    2. Harrison Hong & Terence Lim & Jeremy C. Stein, 2000. "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies," Journal of Finance, American Finance Association, vol. 55(1), pages 265-295, February.
    3. Berg, Joyce E. & Rietz, Thomas A., 2019. "Longshots, overconfidence and efficiency on the Iowa Electronic Market," International Journal of Forecasting, Elsevier, vol. 35(1), pages 271-287.
    4. Syamsul Idul Adha & A. Sakir, 2021. "Effect of Minimum Tick Size Policy on Price Efficiency and Execution Cost," Capital Markets Review, Malaysian Finance Association, vol. 29(2), pages 29-41.
    5. Mohammad Reza TAVAKOLI BAGHDADABAD & Afsaneh NOORI HOUSHYAR, 2014. "Productivity and Efficiency Evaluation of US Mutual Funds," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(2), pages 120-143, March.
    6. David Easley & Soeren Hvidkjaer & Maureen O'Hara, 2002. "Is Information Risk a Determinant of Asset Returns?," Journal of Finance, American Finance Association, vol. 57(5), pages 2185-2221, October.
    7. Rajkamal Iyer & Asim Ijaz Khwaja & Erzo F. P. Luttmer & Kelly Shue, 2016. "Screening Peers Softly: Inferring the Quality of Small Borrowers," Management Science, INFORMS, vol. 62(6), pages 1554-1577, June.
    8. Merl, Robert & Stöckl, Thomas & Palan, Stefan, 2023. "Insider trading regulation and shorting constraints. Evaluating the joint effects of two market interventions," Journal of Banking & Finance, Elsevier, vol. 154(C).
    9. Enrique Sentana, 2005. "Least Squares Predictions and Mean-Variance Analysis," Journal of Financial Econometrics, Oxford University Press, vol. 3(1), pages 56-78.
    10. Qian, Xiaolin & Tam, Lewis H.K. & Zhang, Bohui, 2014. "Systematic liquidity and the funding liquidity hypothesis," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 304-320.
    11. Oxelheim, Lars & Rafferty, Michael, 2005. "On the static efficiency of secondary bond markets," Journal of Multinational Financial Management, Elsevier, vol. 15(2), pages 117-135, April.
    12. Charles Cao & Grant Farnsworth & Hong Zhang, 2021. "The Economics of Hedge Fund Startups: Theory and Empirical Evidence," Journal of Finance, American Finance Association, vol. 76(3), pages 1427-1469, June.
    13. Joshua S. Gans, 2023. "Artificial intelligence adoption in a competitive market," Economica, London School of Economics and Political Science, vol. 90(358), pages 690-705, April.
    14. Diane Del Guercio & Jonathan Reuter, 2014. "Mutual Fund Performance and the Incentive to Generate Alpha," Journal of Finance, American Finance Association, vol. 69(4), pages 1673-1704, August.
    15. Antonello D’Agostino & Kieran Mcquinn & Karl Whelan, 2012. "Are Some Forecasters Really Better Than Others?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(4), pages 715-732, June.
    16. Jezek, M., 2009. "Passive Investors, Active Traders and Strategic Delegation of Price Discovery," Cambridge Working Papers in Economics 0951, Faculty of Economics, University of Cambridge.
    17. 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.
    18. Chung, Kee H. & Kim, Oliver & Lim, Steve C. & Yang, Sean, 2019. "An analytical measure of market underreaction to earnings news," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 612-624.
    19. Walker, M. Mark & Hatfield, Gay B., 1996. "Professional stock analysts' recommendations: Implications for individual investors," Financial Services Review, Elsevier, vol. 5(1), pages 13-29.
    20. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric loss functions and the rationality of expected stock returns," International Journal of Forecasting, Elsevier, vol. 27(2), pages 413-437.

    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:1004.4822. 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.