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Speculative dynamics

  • Dan Bernhardt

    ()

  • P. Seiler
  • B. Taub

We then characterize analytically and numerically how the characteristics of private information—its quantity, persistence and correlation, and division among speculators—affect trading profits, pricing and trading strategies. In particular, we derive how speculators trade on new information versus old, and on private signals versus prices. We show via a frequency-domain argument that trading strategies emphasize new information versus old.

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File URL: http://hdl.handle.net/10.1007/s00199-009-0456-y
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Article provided by Springer in its journal Economic Theory.

Volume (Year): 44 (2010)
Issue (Month): 1 (July)
Pages: 1-52

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Handle: RePEc:spr:joecth:v:44:y:2010:i:1:p:1-52
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  1. He, Hua & Wang, Jiang, 1995. "Differential Information and Dynamic Behavior of Stock Trading Volume," Review of Financial Studies, Society for Financial Studies, vol. 8(4), pages 919-72.
  2. Foster, F. Douglas & Viswanathan, S., 1994. "Strategic Trading with Asymmetrically Informed Traders and Long-Lived Information," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 29(04), pages 499-518, December.
  3. Minh Chau & Dimitri Vayanos, 2008. "Strong-Form Efficiency with Monopolistic Insiders," Review of Financial Studies, Society for Financial Studies, vol. 21(5), pages 2275-2306, September.
  4. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-68, February.
  5. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-35, November.
  6. Kenneth Kasa, 2000. "Forecasting the Forecasts of Others in the Frequency Domain," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 3(4), pages 726-756, October.
  7. Taub, B., 1997. "Optimal policy in a model of endogenous fluctuations and assets," Journal of Economic Dynamics and Control, Elsevier, vol. 21(10), pages 1669-1697, August.
  8. Dan Bernhardt & Jianjun Miao, 2004. "Informed Trading When Information Becomes Stale," Journal of Finance, American Finance Association, vol. 59(1), pages 339-390, 02.
  9. Back, Kerry & Pedersen, Hal, 1998. "Long-lived information and intraday patterns," Journal of Financial Markets, Elsevier, vol. 1(3-4), pages 385-402, September.
  10. Back, Kerry, 1992. "Insider Trading in Continuous Time," Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 387-409.
  11. Taub, Bart, 1986. "The tradeoff between social insurance and aggregate fluctuations," Information Economics and Policy, Elsevier, vol. 2(4), pages 259-276, December.
  12. Kerry Back & C. Henry Cao & Gregory A. Willard, 2000. "Imperfect Competition among Informed Traders," Journal of Finance, American Finance Association, vol. 55(5), pages 2117-2155, October.
  13. Wang, Jiang, 1993. "A Model of Intertemporal Asset Prices under Asymmetric Information," Review of Economic Studies, Wiley Blackwell, vol. 60(2), pages 249-82, April.
  14. Foster, F Douglas & Viswanathan, S, 1996. " Strategic Trading When Agents Forecast the Forecasts of Others," Journal of Finance, American Finance Association, vol. 51(4), pages 1437-78, September.
  15. Ball, J. A. & Taub, B., 1991. "Factoring spectral matrices in linear-quadratic models," Economics Letters, Elsevier, vol. 35(1), pages 39-44, January.
  16. Joseph G. Pearlman & Thomas J. Sargent, 2005. "Knowing the Forecasts of Others," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 480-497, April.
  17. Whiteman, Charles H., 1985. "Spectral utility, wiener-hopf techniques, and rational expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 9(2), pages 225-240, October.
  18. Lars Peter Hansen & Thomas J. Sargent, 1979. "Formulating and estimating dynamic linear rational expectations models," Working Papers 127, Federal Reserve Bank of Minneapolis.
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