Abstract
In this chapter we study the price response function in presence of liquidity crisis from a theoretical point of view and to appropriately address this problem we introduce a model with a suitable microscopic dynamics.
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References
Daniels, M. G., Farmer, J. D., Gillemot, L., Iori, G., & Smith., E. (2003). Quantitative model of price diffusion and market friction based on trading as a mechanistic random process. Physical Review Letters, 90, 108102.
Smith, E., Farmer, J. D., Gillemot, L., & Krishnamurthy, S. (2003). Statistical theory of the continuous double auction. Quantitative Finance, 3, 481.
Farmer, J. D., Gillemot, L., Lillo, F., Mike, S, & Sen, A. (2004). What really causes large price changes? Quantitative Finance, 4, 383.
Potters, M. & Bouchaud., J.-P. (2003). More statistical properties of order books and price impact. Physica A, 324, 133.
Mike, S., & Farmer, J. D. (2008). An empirical behavioral model of liquidity and volatility. Journal of Economic Dynamics and Control, 32, 200.
Farmer, J. D., Gerig, A., Lillo, F., & Mike., S. (2006). Market efficiency and the long-memory of supply and demand: Is price impact variable and permanent or fixed and temporary. Quantitative Finance, 6, 107.
Bouchaud, J.-P., Kockelkoren, J., & Potters, M. (2004). Random walks, liquidity molasses and critical response in financial markets. Quantitative Finance, 6, 115.
Bouchaud, J.-P., Farmer, J. D., & Lillo, F. (2008). How markets slowly digest changes in supply and demand. Elsevier: Academic Press.
Bouchaud, J.-P., Gefen, Y., Potters, M., & Wyart., M. (2004). Fluctuations and response in financial markets: The subtle nature of random price changes. Quantitative Finance, 4, 176.
Lillo, F., Mike, S., & Farmer, J. D. (2005). Theory for long memory in supply and demand. Physical Review E, 71, 066122.
Plerou, V., Gopikrishnan, P., Gabaix, X., & Stanley., H. E. (2002). Quantifying stock-price response to demand fluctuations. Physical Review E, 324, 66.
Farmer, J. D. & Lillo., F. (2004). On the origin of power law tails in price fluctuations. Quantitative Finance, 4, 7.
Alfi, V., Pietronero, L., & Zaccaria, A. (2009). Europhysics Letters, 86, 58003.
Alfi, V., Cristelli, M., Pietronero, L., & Zaccaria, A. (2009). Minimal agent based model for financial markets. I: Origin and self-organization of stylized facts. European Physical Journal B, 67, 385. arXiv:0808.3562. http://arxiv.org/abs/0808.3562
Alfi, V., Cristelli, M., Pietronero, L., & Zaccaria, A. (2009). Minimal agent based model for financial markets. II: Statistical properties of the linear and multiplicative dynamics. European Physical Journal B, 67, 399. arXiv:0808.3565. http://arxiv.org/abs/0808.3565
Alfi, V., Cristelli, M., Pietronero, L., & Zaccaria, A. (2008). Mechanisms of self-organization and finite size effects in a minimal agents based model. Journal of Statistics (to be published). arXiv:0811.4256.
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Cristelli, M. (2014). Zero Intelligence Model for the Order Book Dynamics. In: Complexity in Financial Markets. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-00723-6_6
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DOI: https://doi.org/10.1007/978-3-319-00723-6_6
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