nep-mst New Economics Papers
on Market Microstructure
Issue of 2012‒02‒27
five papers chosen by
Thanos Verousis
Bangor University

  1. Order book dynamics in liquid markets: limit theorems and diffusion approximations By Rama Cont; Adrien De Larrard
  2. Performance metrics for algorithmic traders By Rosenthal, Dale W.R.
  3. The pitch rather than the pit: investor inattention during FIFA World Cup matches By Michael Ehrmann; David-Jan Jansen
  4. A simple microstructure return model explaining microstructure noise and Epps effects By A. Saichev; D. Sornette
  5. Stocks repurchase and sophistication of individual investors By Camille Magron; Maxime Merli

  1. By: Rama Cont (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - CNRS : UMR7599 - Université Paris VI - Pierre et Marie Curie - Université Paris VII - Paris Diderot); Adrien De Larrard (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - CNRS : UMR7599 - Université Paris VI - Pierre et Marie Curie - Université Paris VII - Paris Diderot)
    Abstract: We propose a model for the dynamics of a limit order book in a liquid market where buy and sell orders are submitted at high frequency. We derive a functional central limit theorem for the joint dynamics of the bid and ask queues and show that, when the frequency of order arrivals is large, the intraday dynamics of the limit order book may be approximated by a Markovian jump-diffusion process in the positive orthant, whose characteristics are explicitly described in terms of the statistical properties of the underlying order flow. This result allows to obtain tractable analytical approximations for various quantities of interest, such as the probability of a price increase or the distribution of the duration until the next price move, conditional on the state of the order book. Our results allow for a wide range of distributional assumptions and temporal dependence in the order flow and apply to a wide class of stochastic models proposed for order book dynamics, including models based on Poisson point processes, self-exciting point processes and models of the ACD-GARCH family.
    Keywords: limit order book ; queueing systems ; heavy traffic limit ; functional central limit theorem ; diffusion approximation ; high-frequency data ; market microstructure ; point process
    Date: 2011
  2. By: Rosenthal, Dale W.R.
    Abstract: Portfolio traders may split large orders into smaller orders scheduled over time to reduce price impact. Since handling many orders is cumbersome, these smaller orders are often traded in an automated (“algorithmic”) manner. We propose metrics using these orders to help measure various trading-related skills with low noise. Managers may use these metrics to assess how separate parts of the trading process contribute execution, market timing, and order scheduling skills versus luck. These metrics could save 4 basis points in cost per trade yielding a 15% reduction in expenses and saving $7.3 billion annually for US-domiciled equity mutual funds alone. The metrics also allow recovery of parameters for a price impact model with lasting and ephemeral effects. Some metrics may help evaluate external intermediaries, test for possible front-running, and indicate sloppy or overly passive trading.
    Keywords: trading skill; short term market timing; order scheduling; luck versus skill
    JEL: G14 G12 G23 G24
    Date: 2009–06–22
  3. By: Michael Ehrmann; David-Jan Jansen
    Abstract: At the 2010 FIFA World Cup in South Africa, many soccer matches were played during stock market trading hours, providing us with a natural experiment to analyze fluctuations in investor attention. Using minute-by-minute trading data for fifteen international stock exchanges, we present three key findings. First, when the national team was playing, the number of trades dropped by 45%, while volumes were 55% lower. Second, market activity was influenced by match events. For instance, a goal caused an additional drop in trading activity by 5%. The magnitude of this reduction resembles what is observed during lunchtime, and as such might not be indicative for shifts in attention. However, our third finding is that the comovement between national and global stock market returns decreased by over 20% during World Cup matches, whereas no comparable decoupling can be found during lunchtime. We conclude that stock markets were following developments on the soccer pitch rather than in the trading pit, leading to a changed price formation process.
    Keywords: investor inattention; stock markets; trading volume; high-frequency data; soccer
    JEL: G12 G14 G15
    Date: 2012–02
  4. By: A. Saichev; D. Sornette
    Abstract: We present a simple microstructure model of financial returns that combines (i) the well-known ARFIMA process applied to tick-by-tick returns, (ii) the bid-ask bounce effect, (iii) the fat tail structure of the distribution of returns and (iv) the non-Poissonian statistics of inter-trade intervals. This model allows us to explain both qualitatively and quantitatively important stylized facts observed in the statistics of microstructure returns, including the short-ranged correlation of returns, the long-ranged correlations of absolute returns, the microstructure noise and Epps effects. According to the microstructure noise effect, volatility is a decreasing function of the time scale used to estimate it. Paradoxically, the Epps effect states that cross correlations between asset returns are increasing functions of the time scale at which the returns are estimated. The microstructure noise is explained as the result of the negative return correlations inherent in the definition of the bid-ask bounce component (ii). In the presence of a genuine correlation between the returns of two assets, the Epps effect is due to an average statistical overlap of the momentum of the returns of the two assets defined over a finite time scale in the presence of the long memory process (i).
    Date: 2012–02
  5. By: Camille Magron (LaRGE Research Center, Université de Strasbourg); Maxime Merli (LaRGE Research Center, Université de Strasbourg)
    Abstract: In this article, we stress the impact of sophistication on stocks repurchase behavior by individual investors. By analyzing a large database of 8’072’016 trades by 84’500 individual French investors from 1999 to 2006, we evidence at aggregated and individual level that investors prefer to repurchase stocks they previously sold for a gain and stocks that have lost value since being sold. These patterns of repurchase emphasize the role played by anticipated and experienced regret in trading decisions. Based on direct measures of sophistication (trading of foreign assets, derivative assets and bonds) and an indirect one (wealth), we demonstrate that less sophisticated investors are more prone to these biases in repurchase behavior. Besides, we show that portfolio performance of investors are not directly related to these repurchase preferences.
    Keywords: Stock Repurchase, Individual Investor, Trading Behavior.
    JEL: G11
    Date: 2012

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