New Economics Papers
on Market Microstructure
Issue of 2013‒04‒27
five papers chosen by
Thanos Verousis

  1. Analysis of Realized Volatility in Two Trading Sessions of the Japanese Stock Market By Tetsuya Takaishi; Ting Ting Chen; Zeyu Zheng
  2. A Fokker-Planck description for the queue dynamics of large tick stocks By A. Gareche; G. Disdier; J. Kockelkoren; J. -P. Bouchaud
  3. Information Acquisition in Ostensibly Efficient Markets By Alasdair Brown
  4. Modeling dynamic diurnal patterns in high frequency financial data By Ito, Ryoko
  5. Forecasting with Mixed Frequency Samples: The Case of Common Trends By Peter Fuleky; Carl S. Bonham

  1. By: Tetsuya Takaishi; Ting Ting Chen; Zeyu Zheng
    Abstract: We analyze realized volatilities constructed using high-frequency stock data on the Tokyo Stock Exchange. In order to avoid non-trading hours issue in volatility calculations we define two realized volatilities calculated separately in the two trading sessions of the Tokyo Stock Exchange, i.e. morning and afternoon sessions. After calculating the realized volatilities at various sampling frequencies we evaluate the bias from the microstructure noise as a function of sampling frequency. Taking into account of the bias to realized volatility we examine returns standardized by realized volatilities and confirm that price returns on the Tokyo Stock Exchange are described approximately by Gaussian time series with time-varying volatility, i.e. consistent with a mixture of distributions hypothesis.
    Date: 2013–04
  2. By: A. Gareche; G. Disdier; J. Kockelkoren; J. -P. Bouchaud
    Abstract: Motivated by empirical data, we develop a statistical description of the queue dynamics for large tick assets based on a two-dimensional Fokker-Planck (diffusion) equation, that explicitly includes state dependence, i.e. the fact that the drift and diffusion depends on the volume present on both sides of the spread. "Jump" events, corresponding to sudden changes of the best limit price, must also be included as birth-death terms in the Fokker-Planck equation. All quantities involved in the equation can be calibrated using high-frequency data on best quotes. One of our central finding is the the dynamical process is approximately scale invariant, i.e., the only relevant variable is the ratio of the current volume in the queue to its average value. While the latter shows intraday seasonalities and strong variability across stocks and time periods, the dynamics of the rescaled volumes is universal. In terms of rescaled volumes, we found that the drift has a complex two-dimensional structure, which is a sum of a gradient contribution and a rotational contribution, both stable across stocks and time. This drift term is entirely responsible for the dynamical correlations between the ask queue and the bid queue.
    Date: 2013–04
  3. By: Alasdair Brown (University of East Anglia)
    Abstract: Grossman and Stiglitz (1980) famously proposed that if markets are efficient, then traders will neglect to acquire information or monitor markets, thereby inadvertently rendering these markets inefficient. In this paper we use data from a simple asset market - Betfair trading on the Wimbledon Tennis Championships between 2008 and 2012 - to investigate whether traders indeed cease to collect information when a market is ostensibly efficient. In this market, risk-free arbitrage opportunities arise frequently during matches (as new information arrives and asynchronously shifts prices), but seldom arise before matches (when there is little or no new information to move prices). Arbitrageurs therefore have good reason to believe that the pre-match market is already efficient, and consequently have less reason to monitor the market at this time. As a result, we find that on the few occasions that arbitrage opportunities do arise before matches, they last substantially and significantly longer than average. This suggests, more generally, that traders will neglect to acquire information (i.e. carry out research, or watch markets) if they believe that markets are already efficient. This neglect, in turn, makes markets inefficient.
    Date: 2013–04
  4. By: Ito, Ryoko
    Abstract: A spline-DCS model is developed to forecast the conditional distribution of high-frequency financial data with periodic behavior. The dynamic cubic spline of Harvey and Koopman (1993) is applied to allow diurnal patterns to evolve stochastically over time. An empirical application illustrates the practicality and impressive predictive performance of the model.
    Keywords: outlier; robustness, score, calendar effect, spline, trade volume.
    JEL: C22
    Date: 2013–04–19
  5. By: Peter Fuleky (UHERO and Department of Economics, University of Hawaii at Manoa); Carl S. Bonham (Department of Economics, University of Hawaii at Manoa)
    Abstract: We analyze the forecasting performance of small mixed frequency factor models when the observed variables share stochastic trends. The indicators are observed at various frequencies and are tied together by cointegration so that valuable high fre- quency information is passed to low frequency series through the common factors. Dierencing the data breaks the cointegrating link among the series and some of the signal leaks out to the idiosyncratic components, which do not contribute to the trans- fer of information among indicators. We nd that allowing for common trends improves forecasting performance over a stationary factor model based on dierenced data. The \common-trends factor model" outperforms the stationary factor model at all analyzed forecast horizons. Our results demonstrate that when mixed frequency variables are cointegrated, modeling common stochastic trends improves forecasts.
    Keywords: Dynamic Factor Model, Mixed Frequency Samples, Common Trends, Forecasting
    JEL: E37 C32 C53 L83
    Date: 2013–04

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