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Asymmetric Information in Fads Models

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  • Paolo Guasoni

    (Boston University
    Università di Pisa)

Abstract

Fads models were introduced by Shiller (Am Econ Rev 71:421–436, 1981) and Summers (J Finance 41:591–601, 1986) as plausible alternatives to the efficient markets/constant expected returns assumptions. Under these models, logarithms of asset prices embody both a martingale component, with permanent shocks, and a stationary component, with temporary shocks. We study a continuous-time version of these models both from the point of view of informed agents, who observe both fundamental and market values, and from that of uninformed agents, who only observe market prices. We specify the asset price in the larger filtration of the informed agent, and then derive its decomposition in the smaller filtration of the uninformed agent using the Hitsuda representation of Gaussian processes. For uninformed agents we obtain a non-Markovian dynamics, which justifies the use of technical analysis in optimal trading strategies. For both types of agents, we solve the problem of maximization of expected logarithmic utility from terminal wealth, and obtain an explicit formula for the additional logarithmic utility of informed agents. Finally, we apply the decomposition result to the problem of testing the presence of fads from market data. An application to the NYSE-AMEX indices from the CRSP database shows that, if the fads component prevails, then the mean-reversion speed must be slow.

Suggested Citation

  • Paolo Guasoni, 2006. "Asymmetric Information in Fads Models," Finance and Stochastics, Springer, vol. 10(2), pages 159-177, April.
  • Handle: RePEc:spr:finsto:v:10:y:2006:i:2:d:10.1007_s00780-006-0006-4
    DOI: 10.1007/s00780-006-0006-4
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    References listed on IDEAS

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    Cited by:

    1. Buckley, Winston & Long, Hongwei & Perera, Sandun, 2014. "A jump model for fads in asset prices under asymmetric information," European Journal of Operational Research, Elsevier, vol. 236(1), pages 200-208.
    2. Buckley, Winston & Long, Hongwei & Marshall, Mario, 2016. "Numerical approximations of optimal portfolios in mispriced asymmetric Lévy markets," European Journal of Operational Research, Elsevier, vol. 252(2), pages 676-686.
    3. Elisa Luciano & Antonella Tolomeo, 2016. "Are information and portfolio diversification substitutes or complements?," Carlo Alberto Notebooks 456, Collegio Carlo Alberto.
    4. Bernardo D'Auria & Jos'e Antonio Salmer'on, 2017. "Valuing the anticipative information on the stochastic short interest rates," Papers 1711.03642, arXiv.org, revised Nov 2021.
    5. Buckley, Winston S. & Long, Hongwei, 2015. "A discontinuous mispricing model under asymmetric information," European Journal of Operational Research, Elsevier, vol. 243(3), pages 944-955.
    6. Huy N. Chau & Miklos Rasonyi, 2016. "On optimal investment with processes of long or negative memory," Papers 1608.00768, arXiv.org, revised Mar 2017.
    7. Chau, Huy N. & Rásonyi, Miklós, 2018. "On optimal investment with processes of long or negative memory," Stochastic Processes and their Applications, Elsevier, vol. 128(4), pages 1095-1113.
    8. D'Auria, Bernardo & García Martí, Dolores & Salmerón Garrido, José Antonio, 2017. "Optimal portfolio with insider information on the stochastic interest rate," DES - Working Papers. Statistics and Econometrics. WS 25819, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Buckley, Winston S. & Brown, Garfield O. & Marshall, Mario, 2012. "A mispricing model of stocks under asymmetric information," European Journal of Operational Research, Elsevier, vol. 221(3), pages 584-592.
    10. Winston Buckley & Sandun Perera, 2019. "Optimal demand in a mispriced asymmetric Carr–Geman–Madan–Yor (CGMY) economy," Annals of Finance, Springer, vol. 15(3), pages 337-368, September.
    11. Sebastian Jaimungal & Xiaofei Shi, 2024. "The Price of Information," Papers 2402.11864, arXiv.org, revised Mar 2024.

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