New Economics Papers
on Market Microstructure
Issue of 2007‒06‒02
two papers chosen by
Thanos Verousis

  1. Which market protocols facilitate fair trading? By Marco LiCalzi; Paolo Pellizzari
  2. Estimating the Structural Credit Risk Model When Equity Prices Are Contaminated by Trading Noises By Duan, Jin-Chuan; Fulop, Andras

  1. By: Marco LiCalzi (Department of Applied Mathematics, University of Venice); Paolo Pellizzari (Department of Applied Mathematics, University of Venice)
    Abstract: We study the performance of four market protocols with regard to their ability to equitably distribute the gains from trade among two groups of participants in an exchange economy. We test the protocols by running (computerized) experiments. Assuming Walrasian tatonemment as benchmark, there is a clear-cut ranking from best to worst: batch auction, nondiscretionary dealership, the hybridization of a dealership and a continuous double auction, and finally the pure continuous double auction.
    Keywords: allocative efficiency, allocative fairness, allocative neutrality, comparison of market institutions, market microstructure, performance criteria.
    JEL: D61 D63 D69 G19
    Date: 2007–05
  2. By: Duan, Jin-Chuan (Rotman School of Management, University of Toronto); Fulop, Andras (ESSEC Business School)
    Abstract: The transformed-data maximum likelihood estimation (MLE) method for structural credit risk models developed by Duan (1994) is extended to account for the fact that observed equity prices may have been contaminated by trading noises. With the presence of trading noises, the likelihood function based on the observed equity prices can only be evaluated via some nonlinear filtering scheme. We devise a particle filtering algorithm that is practical for conducting the MLE estimation of the structural credit risk model of Merton (1974). We implement the method on the Dow Jones 30 firms and on 100 randomly selected firms, and find that ignoring trading noises can lead to significantly over-estimating the firm’s asset volatility. The estimated magnitude of trading noise is in line with the direction that a firm’s liquidity will predict based on three common liquidity proxies. A simulation study is then conducted to ascertain the performance of the estimation method.
    Keywords: Credit Risk; Maximum Likelihood; Microstructure; Option Pricing; Particle Filtering
    JEL: C22
    Date: 2006–10

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