New Economics Papers
on Market Microstructure
Issue of 2013‒05‒05
eight papers chosen by
Thanos Verousis

  1. Econometrics of co-jumps in high-frequency data with noise By Markus Bibinger; Lars Winkelmann; ;
  2. The impact of the French Tobin tax By Leonardo Becchetti; Massimo Ferrari
  3. The dynamics of trading duration, volume and price volatility – a vector MEM model By Xu, Yongdeng
  4. Price discovery in the Italian sovereign bonds market: the role of order flow By Alessandro Girardi; Claudio Impenna
  5. Long Memory and Fractional Integration in High Frequency Data on the US Dollar / British Pound Spot Exchange Rate By Guglielmo Maria Caporale; Luis A. Gil-Alana
  6. Semi Markov model for market microstructure By Pietro Fodra; Huyên Pham
  7. Estimating the Quadratic Covariation Matrix from Noisy Observations: Local Method of Moments and Efficiency By Markus Bibinger; Nikolaus Hautsch; Peter Malec; Markus Reiss
  8. Multivariate high-frequency financial data via semi-Markov processes By Guglielmo D'Amico; Filippo Petroni

  1. By: Markus Bibinger; Lars Winkelmann; ;
    Abstract: We establish estimation methods to determine co-jumps in multivariate high-frequency data with nonsynchronous observations and market microstructure noise. The ex-post quadratic covariation of the signal part, which is modeled by an Itˆo-semimartingale, is estimated with a locally adaptive spectral approach. Locally adaptive thresholding allows to disentangle the co-jump and continuous part in quadratic covariation. Our estimation procedure implicitly renders spot (co-)variance estimators. We derive a feasible stable limit theorem for a truncated spectral estimator of integrated covariance. A test for common jumps is obtained with a wild bootstrap strategy. We give an explicit guideline how to implement the method and test the algorithm in Monte Carlo simulations. An empirical application to intra-day tick-data demonstrates the practical value of the approach.
    Keywords: co-jumps, covolatility estimation, jump detection, microstructure noise, non-synchronous observations, quadratic covariation, spectral estimation, truncation
    JEL: C14 G32 E58
    Date: 2013–05
  2. By: Leonardo Becchetti (University of Rome "Tor Vergata"); Massimo Ferrari (University of Rome "Tor Vergata"; Poste Italiane)
    Abstract: We analyse the impact of the introduction of the French Tobin tax on volumes, liquidity and volatility of affected stocks with parametric and non parametric tests on individual stocks, difference in difference tests and other robustness checks controlling for simultaneous month-of-the-year and size effects. Our findings document that the tax has a significant impact in terms of reduction in transaction volumes and intraday volatility. The reduction in volumes traded occurs in similar proportion in non taxed small cap stocks.
    Keywords: Financial Transaction Tax; intraday volatility; liquidity, transaction volumes
    JEL: G18 G12 G14
    Date: 2013–03
  3. By: Xu, Yongdeng
    Abstract: We propose a general form of vector Multiplicative Error Model (MEM) for the dynamics of duration, volume and price volatility. The vector MEM relaxes the two restrictions often imposed by previous empirical work in market microstructure research, by allowing interdependence among the variables and relaxing weak exogeneity restrictions. We further propose a multivariate lognormal distribution for the vector MEM. The model is applied to the trade and quote data from the New York Stock Exchange (NYSE). The empirical results show that the vector MEM captures the dynamics of the trivariate system successfully. We find that times of greater activity or trades with larger size coincide with a higher number of informed traders present in the market. But we highlight that it is unexpected component of trading duration or trading volume that carry the information content. Moreover, our empirical results also suggest a significant feedback effect from price process to trading intensity, while the persistent quote changes and transient quote changes affect trading intensity in different direction, confirming Hasbrouck (1988,1991).
    Keywords: Vector MEM; ACD; GARCH; intraday trading process; duration; volume; volatility
    JEL: C15 C32 C52
    Date: 2013–04
  4. By: Alessandro Girardi (National Institute of Statistics (ISTAT)); Claudio Impenna (Bank of Italy)
    Abstract: This paper analyses the price discovery process and the informational role of trading in the Italian wholesale secondary markets for Treasury bonds: the B2B MTS cash and the B2C BondVision trading venues. Using daily data for a representative set of fixed rate government bonds over the period January 2007 - February 2012, we find that the B2C dealer-to-customer market contributes to the process of price formation to a greater extent than the B2B interdealer platform. The informational role of trading is found to be considerable: order flow is a key variable in the process of price formation and appears to continuously act on a cross market basis. Moreover, the explanatory role of order flow turns out to be stronger when liquidity conditions are poorer.
    Keywords: bonds markets, price discovery, order flow, market microstructure, financial crisis
    JEL: G1 G2
    Date: 2013–04
  5. By: Guglielmo Maria Caporale; Luis A. Gil-Alana
    Abstract: This paper analyses the long-memory properties of a high-frequency financial time series dataset. It focuses on temporal aggregation and other features of the data, and how they might affect the degree of dependence of the series. Fractional integration or I(d) models are estimated with a variety of specifications for the error term. In brief, we find evidence that a lower degree of integration is associated with lower data frequencies. In particular, when the data are collected every 10 minutes there are several cases with values of d strictly smaller than 1, implying mean-reverting behaviour; however, for higher data frequencies the unit root null cannot be rejected. This holds for all four series examined, namely Open, High, Low and Last observations for the US dollar / British pound spot exchange rate and for different sample periods.
    Keywords: High frequency data, long memory, volatility persistence, structural breaks
    JEL: C22 F31
    Date: 2013
  6. By: Pietro Fodra (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - CNRS : UMR7599 - Université Paris VI - Pierre et Marie Curie - Université Paris VII - Paris Diderot); Huyên Pham (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - CNRS : UMR7599 - Université Paris VI - Pierre et Marie Curie - Université Paris VII - Paris Diderot)
    Abstract: We introduce a new model for describing the fluctuations of a tick-by-tick single asset price. Our model is based on Markov renewal processes. We consider a point process associated to the timestamps of the price jumps, and marks associated to price increments. By modeling the marks with a suitable Markov chain, we can reproduce the strong mean-reversion of price returns known as microstructure noise. Moreover, by using Markov renewal processes, we can model the presence of spikes in intensity of market activity, i.e. the volatility clustering, and consider dependence between price increments and jump times. We also provide simple parametric and nonparametric statistical procedures for the estimation of our model. We obtain closed-form formula for the mean signature plot, and show the diffusive behavior of our model at large scale limit. We illustrate our results by numerical simulations, and that our model is consistent with empirical data on the Euribor future.
    Keywords: Microstructure noise; Markov renewal process; Signature plot; Scaling limit
    Date: 2013–04–26
  7. By: Markus Bibinger; Nikolaus Hautsch; Peter Malec; Markus Reiss
    Abstract: An efficient estimator is constructed for the quadratic covariation or integrated covolatility matrix of a multivariate continuous martingale based on noisy and non-synchronous observations under high-frequency asymptotics. Our approach relies on an asymptotically equivalent continuous-time observation model where a local generalised method of moments in the spectral domain turns out to be optimal. Asymptotic semiparametric efficiency is established in the Cramér-Rao sense. Main findings are that non-synchronicity of observation times has no impact on the asymptotics and that major efficiency gains are possible under correlation. Simulations illustrate the finite-sample behaviour.
    Keywords: adaptive estimation, asymptotic equivalence, asynchronous observations, integrated covolatility matrix, quadratic covariation, semiparametric efficiency, microstructure noise, spectral estimation
    JEL: C14 C32 C58 G10
    Date: 2013–04
  8. By: Guglielmo D'Amico; Filippo Petroni
    Abstract: In this paper we propose a bivariate generalization of a weighted indexed semi-Markov chains to study the high frequency price dynamics of traded stocks. We assume that financial returns are described by a weighted indexed semi-Markov chain model. We show, through Monte Carlo simulations, that the model is able to reproduce important stylized facts of financial time series like the persistence of volatility and at the same time it can reproduce the correlation between stocks. The model is applied to data from Italian stock market from 1 January 2007 until the end of December 2010.
    Date: 2013–05

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