New Economics Papers
on Market Microstructure
Issue of 2010‒02‒13
five papers chosen by
Thanos Verousis

  1. Beauty Contests and Asset Prices under Asymmetric Information By Ishikawa, Ryuichiro; Kudoh, Noritaka
  2. Impact of the tick-size on financial returns and correlations By Michael C. M\"unnix; Rudi Sch\"afer; Thomas Guhr
  3. Asset returns and volatility clustering in financial time series By Jie-Jun Tseng; Sai-Ping Li
  4. The impact of uncertainties on the pricing of contingent claims By Simone Scotti
  5. A Behavioral Model of Bubbles and Crashes By Kaizoji, Taisei (

  1. By: Ishikawa, Ryuichiro; Kudoh, Noritaka
    Abstract: In this paper, we study a dynamic Gaussian financial market model in which the traders form higher-order expectations about the fundamental value of a single risky asset. Rational uninformed traders are introduced into an otherwise standard differential information economy to investigate the impact of asymmetric information. In a two-period economy, there is a unique linear equilibrium; beauty contests under asymmetric information do not introduce excess volatility driven by self-fulfilling multiple equilibria. Under certain conditions, there is a nonmonotonic relationship between price volatility and the proportion of uninformed traders.
    Keywords: higher-order expectations, asset prices, asymmetric information,
    JEL: D82 D84 G12 G14
    Date: 2010–01–24
  2. By: Michael C. M\"unnix; Rudi Sch\"afer; Thomas Guhr
    Abstract: We demonstrate that the lowest possible price change (tick-size) has a large impact on the structure of financial return distributions. It induces a microstructure as well as it can alter the tail behavior. On small return intervals, the tick-size can distort the calculation of correlations. This especially occurs on small return intervals and thus contributes to the decay of the correlation coefficient towards smaller return intervals (Epps effect). We study this behavior within a model and identify the effect in market data. Furthermore, we present a method to compensate this purely statistical error.
    Date: 2010–01
  3. By: Jie-Jun Tseng; Sai-Ping Li
    Abstract: An analysis of the stylized facts in financial time series is carried out. We find that, instead of the heavy tails in asset return distributions, the slow decay behaviour in autocorrelation functions of absolute returns is actually directly related to the degree of clustering of large fluctuations within the financial time series. We also introduce an index to quantitatively measure the clustering behaviour of fluctuations in these time series and show that big losses in financial markets usually lump more severely than big gains. We further give examples to demonstrate that comparing to conventional methods, our index enables one to extract more information from the financial time series.
    Date: 2010–02
  4. By: Simone Scotti
    Abstract: We study the effect of parameters uncertainties on a stochastic diffusion model, in particular the impact on the pricing of contingent claims, thanks to Dirichlet Forms methods. We apply recent techniques, developed by Bouleau, to hedging procedures in order to compute the sensitivities of SDE trajectories with respect to parameter perturbations. We show that this model can reproduce a bid-ask spread. We also prove that, if the stochastic differential equation admits a closed form representation, also the sensitivities have closed form representations. We exhibit the case of log-normal diffusion and we show that this framework foresees a smiled implied volatility surface coherent with historical data.
    Date: 2010–01
  5. By: Kaizoji, Taisei (
    Abstract: The aim of this paper is to provide one potential theoretical explanation for questions how asset bubbles come about, why it persists, and what caused it to burst. We propose a new model of bubbles and crashes. We divide the risky assets into two classes, the bubble asset and the non-bubble asset, and the risk-free asset. Investors are divided into two groups, the rational investors and the noise traders. The rational investors maximize their expected utility of their wealth in the next period. Noise traders maximize their random utility of binary choice: holding the bubble asset and holding the risk-free asst. We demonstrate that noise-traders’ herd behavior, which follows the behavior getting a majority, occurs when the number of noise-traders increases, and their herd behavior gives cause to a bubble, and their momentum trading prolongs bubble. However, rising stock price slows down as the noise-trader’s behavior approaches to a stationary state, so that the price momentum begins to decrease in the second half of bubble. We demonstrate that decreasing the price momentum lead to market crash.
    Keywords: Bubble; chrash; noise traders; rational investors
    Date: 2010–01–10

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