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Alexander Szimayer

is a Professor of Finance in the School of Business, Economics and Social Sciences at University of Hamburg, Germany. He studied Mathematics and Economics in Heidelberg, Munich, and Bonn, and previously held positions as a Professor of Finance in Bonn, Germany, and as Senior Lecturer of Finance at the Australian National University, Canberra, Australia, as well as the University of Western Australia in Perth, Australia. His main research area are Mathematical Finance, Financial Economics, and Applied Probability.


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Christian Hilpert, Stefan Hirth, Alexander Szimayer: Rating Under Asymmetric Information

We study a dynamic signaling game where a firm, by its decision to stay solvent, signals its quality to a rating agency with the rating feeding back into the firm’s cost of capital. Observing the firm’s true cash flow blurred by a persistent measurement error, the error-minimizing rating agency learns dynamically through the firm’s solvency decision. Firms observed with higher measurement error default earlier, inducing directional learning by successively eliminating measurement errors which are too high to be feasible. In a partially separating perfect Bayesian equilibrium in Markov strategies, the firm employs a measurement-error dependent cut-off strategy. We discuss the extensive economic consequences of such a learning mechanism.

Last modified: 2018.11.30.