New Economics Papers
on Market Microstructure
Issue of 2006‒12‒09
four papers chosen by
Thanos Verousis


  1. ENDOGENOUS NOISE TRADERS By Salomonsson, Marcus
  2. Nonparametric Density Estimation for Positive Time Series By Taoufik Bouezmarni; Jeroen V.K. Rombouts
  3. A Search-Based Theory of the On-the-Run Phenomenon By Vayanos, Dimitri; Weill, Pierre-Olivier
  4. The Price Impact of Stock Trades: Evidence from the Prague Stock Exchange By Vít Bubák; Filip Žikeš

  1. By: Salomonsson, Marcus (Dept. of Economic Statistics, Stockholm School of Economics)
    Abstract: We construct a parsimonious model of a financial market where the marginal investor is an endogenous noise trader. Such a trader anticipates that future shocks may force him to exit his position. In compensation he requires a higher return. We show that the original seller of the asset pays the required return. This can only be optimal if the seller has access to an investment opportunity that gives a sufficiently high return, compared to the noise trader's investment opportunities. We also show that, if the noise trader expects to get informative signals, the required return does not necessarily decrease, as claimed in the earlier literature.
    Keywords: Market microstructure; no-trade theorems; adverse selection
    JEL: G14
    Date: 2006–12–05
    URL: http://d.repec.org/n?u=RePEc:hhs:hastef:0644&r=mst
  2. By: Taoufik Bouezmarni; Jeroen V.K. Rombouts (IEA, HEC Montréal)
    Abstract: The Gaussian kernel density estimator is known to have substantial problems for bounded random variables with high density at the boundaries. For i.i.d. data several solutions have been put forward to solve this boundary problem. In this paper we propose the gamma kernel estimator as density estimator for positive data from a stationary ?-mixing process. We derive the mean integrated squared error, almost sure convergence and asymptotic normality. In a Monte Carlo study, where we generate data from an autoregressive conditional duration model and a stochastic volatility model, we find that the gamma kernel outperforms the local linear density estimator. An application to data from financial transaction durations, realized volatility and electricity price data is provided.
    Keywords: Gamma kernel, nonparametric density estimation, mixing process, transaction durations, realised volatility.
    JEL: C11 C22 C52
    Date: 2006–09
    URL: http://d.repec.org/n?u=RePEc:iea:carech:0609&r=mst
  3. By: Vayanos, Dimitri; Weill, Pierre-Olivier
    Abstract: We propose a model in which assets with identical cash flows can trade at different prices. Infinitely-lived agents can establish long positions in a search spot market, or short positions by first borrowing an asset in a search repo market. We show that short-sellers can endogenously concentrate in one asset because of search externalities and the constraint that they must deliver the asset they borrowed. That asset enjoys greater liquidity, measured by search times, and a higher lending fee ('specialness'). Liquidity and specialness translate into price premia that are consistent with no-arbitrage. We derive closed-form solutions for small frictions, and can generate price differentials in line with observed on-the-run premia.
    Keywords: asset pricing; liquidity; on-the-run bonds; search
    JEL: D8 G1
    Date: 2006–11
    URL: http://d.repec.org/n?u=RePEc:cpr:ceprdp:5965&r=mst
  4. By: Vít Bubák (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic); Filip Žikeš (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic; Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague, Czech Republic)
    Abstract: Using high-frequency trade and quote data from the Prague Stock Exchange, this paper investigates the price impact of stock trades using a vector autoregressive model. We find that (a) full impact of a trade on the security price is not felt instantaneously but a with a protracted lag, (b) as a function of trade innovation size, the ultimate impact of the innovation on the quote is non-linear, positive, increasing, and convex, and (c) there is a significant causal pattern (acc. to Grange-Sims) running from lagged quote revisions to trades as well as from trades to quote revisions.
    Keywords: vector autoregressive model; market microstructure; price impact of stock trades
    JEL: G14 G18
    Date: 2006–04
    URL: http://d.repec.org/n?u=RePEc:fau:wpaper:wp2006_19&r=mst

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