New Economics Papers
on Market Microstructure
Issue of 2013‒07‒15
seven papers chosen by
Thanos Verousis


  1. Learning and Information Dissemination in Limit Order Markets By Lijian Wei; Wei Zhang; Xue-Zhong He; Yongjie Zhang
  2. Does More Frequent Trading Increase the Volatility? ? Theoretical Evidence at Asset and Portfolio Level By KiHoon Jimmy Hong
  3. "On Robust Properties of the SIML Estimation of Volatility under Micro-market noise and Random Sampling" By Hiroumi Misaki; Naoto Kunitomo
  4. "The SIML Estimation of Integrated Covariance and Hedging Coefficient under Micro-market noise and Random Sampling" By Naoto Kunitomo; Hiroumi Misaki
  5. The Fragility of Limit Order Markets By Alasdair Brown
  6. Estimating Stochastic Volatility Models using Prediction-based Estimating Functions By Asger Lunde; Anne Floor Brix
  7. The intra-day impact of communication on euro-dollar volatility and jumps By Hans DEWACHTER; Deniz ERDEMLIOGLU; Jean-Yves GNABO; Christelle LECOURT

  1. By: Lijian Wei (Finance Discipline Group, UTS Business School, University of Technology, Sydney); Wei Zhang (College of Management and Economics, Tianjin University); Xue-Zhong He (Finance Discipline Group, UTS Business School, University of Technology, Sydney); Yongjie Zhang (College of Management and Economics, Tianjin University)
    Abstract: What can traders learn and how does learning affect the market? When information is asymmetric, short-lived, and uninformed traders learn, we present an artificial limit order market model to examine the effect of learning, information value, and order aggressiveness on information dissemination efficiency, bid-ask spread, order submission, and order profit of traders. We find that learning helps the uninformed traders to acquire private information more effectively and hence improves market information dissemination. Also the informed traders in general consume liquidity while the uninformed traders mainly supply liquidity. More interestingly, due to the learning and short-lived information, the bid-ask spread and its volatility are positively related to the probability of informed trading. The results help us to understand the behavior of uninformed traders and provide substantial insight and intuition into the trading process.
    Keywords: Limit order book; continuous double auction; learning; information dissemination; order aggressiveness; bid-ask spread
    JEL: G14 C63 D82
    Date: 2013–06–01
    URL: http://d.repec.org/n?u=RePEc:uts:rpaper:333&r=mst
  2. By: KiHoon Jimmy Hong (Finance Discipline Group, UTS Business School, University of Technology, Sydney)
    Abstract: This paper investigates the sensitivity of asset and portfolio price volatility with respect to the minimum available trading interval that the price is quoted. The objective of the study is to find the theoretical impact of high frequency trading on asset and portfolio volatilities, using a simple stochastic model. The paper finds that if high frequency trading is available, both asset and portfolio price volatility tend to decrease. The result suggests that the regulators who are concerned with the volatility induced by high frequency trading should concentrate the regulatory effort on the behavioral aspect of the high frequency traders rather than on how frequent they trade.
    Keywords: High Frequency Trading; Volatility; Technical Analysis; Time Series Momentum
    JEL: G10 G18
    Date: 2013–05–01
    URL: http://d.repec.org/n?u=RePEc:uts:rpaper:332&r=mst
  3. By: Hiroumi Misaki (Research Center for Advanced Science and Technology, University of Tokyo); Naoto Kunitomo (Faculty of Economics, University of Tokyo)
    Abstract:    For estimating the integrated volatility and covariance by using high frequency data, Kunitomo and Sato (2008, 2011) have proposed the Separating Information Maximum Likelihood (SIML) method when there are micro-market noises. The SIML estimator has reasonable finite sample properties and asymptotic properties when the sample size is large under general conditions with non-Gaussian processes or volatility models. We shall show that the SIML estimator has the asymptotic robustness property in the sense that it is consistent and has the stable convergence (i.e. the asymptotic normality in the deterministic case) when there are micro-market noises and the observed high-frequency data are sampled randomly with the underlying (continuous time) stochastic process. The SIML estimation has also reasonable finite sample properties with these effects.
    Date: 2013–06
    URL: http://d.repec.org/n?u=RePEc:tky:fseres:2013cf892&r=mst
  4. By: Naoto Kunitomo (Faculty of Economics, University of Tokyo); Hiroumi Misaki (Research Center for Advanced Science and Technology, University of Tokyo)
    Abstract:    For estimating the integrated volatility and covariance by using high frequency data, Kunitomo and Sato (2008, 2011) have proposed the Separating Information Maximum Likelihood (SIML) method when there are micro-market noises. The SIML estimator has reasonable finite sample properties and asymptotic properties when the sample size is large under general conditions with non-Gaussian processes or volatility models. We shall show that the SIML estimation is useful for estimating the integrated covariance and hedging coefficient when we have micro-market noise and financial high frequency data are randomly sampled. The SIML estimation is consistent and has the stable convergence (i.e. the asymptotic normality in the deterministic case) and it has reasonable finite sample properties with these effects.
    Date: 2013–06
    URL: http://d.repec.org/n?u=RePEc:tky:fseres:2013cf893&r=mst
  5. By: Alasdair Brown (University of East Anglia)
    Abstract: Limit order markets - where a subset of traders provide liquidity on a discretionary basis - are the dominant exchange mechanism for financial assets. We analyse the resilience of these markets using Betfair limit order book trading on the Wimbledon Tennis Championships. As matches go inplay, the risk involved in liquidity provision intensifies, as the value of bets can change substantially in a matter of seconds, and, at the end of the match, certain bets are worthless. Our headline result is that liquidity declines by 657% inplay, relative to the pre-match period. Furthermore, a series of difference-in-difference tests reveal this collapse to be disproportionate to the increase in risk. Overall, our results highlight the fragility of limit order markets when discretionary liquidity provision is put under extreme stress.
    Date: 2013–07
    URL: http://d.repec.org/n?u=RePEc:uea:aepppr:2012_48&r=mst
  6. By: Asger Lunde (Aarhus University and CREATES); Anne Floor Brix (Aarhus University and CREATES)
    Abstract: In this paper prediction-based estimating functions (PBEFs), introduced in Sørensen (2000), are reviewed and PBEFs for the Heston (1993) stochastic volatility model are derived. The finite sample performance of the PBEF based estimator is investigated in a Monte Carlo study, and compared to the performance of the GMM estimator based on conditional moments of integrated volatility from Bollerslev and Zhou (2002). The case where the observed log-price process is contaminated by i.i.d. market microstructure (MMS) noise is also investigated. First, the impact of MMS noise on the parameter estimates from the two estimation methods without noise correction are studied. Second, a noise robust GMM estimator is constructed by approximating integrated volatility by a realized kernel instead of realized variance. The PBEFs are also recalculated in the noise setting, and the two estimation methods ability to correctly account for the noise are investigated. Our Monte Carlo study shows that the estimator based on PBEFs outperforms the GMM estimator, both in the setting with and without MMS noise. Finally, an empirical application investigates the possible challenges and general performance of applying the PBEF based estimator in practice.
    Keywords: GMMestimation, Heston model, high-frequency data, integrated volatility, market microstructure noise, prediction-based estimating functions, realized variance, realized kernel
    JEL: C13 C22 C51
    Date: 2013–02–07
    URL: http://d.repec.org/n?u=RePEc:aah:create:2013-23&r=mst
  7. By: Hans DEWACHTER; Deniz ERDEMLIOGLU; Jean-Yves GNABO; Christelle LECOURT
    Abstract: In this paper, we examine the intra-day effects of verbal statements and comments on the FX market uncertainty using two measures: continuous volatility and discontinuous jumps. Focusing on the euro-dollar exchange rate, we provide empirical evidence of how these two sources of uncertainty matter in measuring the short-term reaction of exchange rates to communication events. Talks significantly trigger large jumps or extreme events for approximately an hour after the news release. Continuous volatility starts reacting prior to the news, intensifies around the release time and stays at high levels for several hours. Our results suggest that monetary authorities generally tend to communicate with markets on days when uncertainty is relatively severe, and higher than normal. Disentangling the US and Euro area statements, we also find that abnormal levels of volatility are mostly driven by the communication of the Euro area officials rather than US authorities.
    Date: 2013–03
    URL: http://d.repec.org/n?u=RePEc:ete:ceswps:ces13.04&r=mst

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