nep-mst New Economics Papers
on Market Microstructure
Issue of 2014‒12‒08
five papers chosen by
Thanos Verousis
University of Bath

  1. The Impact of the French Securities Transaction Tax on Market Liquidity and Volatility By Gunther Capelle-Blancard; Olena Havrylchyk
  2. A GARCH analysis of dark-pool trades By Philippe De Peretti; Oren Tapiero
  3. Estimating the spot covariation of asset prices: Statistical theory and empirical evidence By Bibinger, Markus; Hautsch, Nikolaus; Malec, Peter; Reiss, Markus
  4. Asymmetric connectedness of stocks: How does bad and good volatility spill over the U.S. stock market? By Barunik, Jozef; Kočenda, Evžen; Vácha, Lukáš
  5. Strategic Trading in Informationally Complex Environments By Nicolas S. Lambert; Michael Ostrovsky; Mikhail Panov

  1. By: Gunther Capelle-Blancard (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Olena Havrylchyk (Université Paris Ouest Nanterre - Université Paris X - Paris Ouest Nanterre La Défense, CEPII - Centre d'Etudes Prospectives et d'Informations Internationales - Centre d'analyse stratégique)
    Abstract: In this paper, we assess the impact of the securities transaction tax (STT) introduced in France in 2012 on market liquidity and volatility. To identify causality, we rely on the unique design of this tax that is imposed only on large French firms, all listed on Euronext. This provides two reliable control groups (smaller French firms and foreign firms also listed on Euronext) and allows using difference-in-difference methodology to isolate the impact of the tax from other economic changes occuring simultaneously. We find that the STT has reduced trading volume, but we find no effect on theoretically based measures of liquidity, such as price impact, and no significant effect on volatility. The results are robust if we rely on different control groups (German stocks), analyze dynamic effects or construct a control group by propensity score matching.
    Keywords: Financial transaction tax; securities transaction tax; Tobin tax, volatility; liquidity; Euronext
    Date: 2013–12
  2. By: Philippe De Peretti (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne); Oren Tapiero (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne)
    Abstract: The ability to trade in dark-pools without publicly announcing trading orders, concerns regulators and market participants alike. This paper analyzes the information contribution of dark trades to the intraday volatility process. The analysis is conducted by performing a GARCH estimation framework where errors follow the generalized error distribution (GED) and two different proxies for dark trading activity are separately included in the volatility equation. Results indicate that dark trades convey important information on the intraday volatility process. Furthermore, the results highlight the superiority of the proportion of dark trades relative to the proportion of dark volume in affecting the one-step-ahead density forecast
    Keywords: Dark Pools; Density Forecast; Dark Volume; Dark trade
    Date: 2014
  3. By: Bibinger, Markus; Hautsch, Nikolaus; Malec, Peter; Reiss, Markus
    Abstract: We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semi-martingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance estimates. The latter originate from a local method of moments (LMM) which recently has been introduced by Bibinger et al. (2014). We extend the LMM estimator to allow for autocorrelated noise and propose a method to adaptively infer the autocorrelations from the data. We prove the consistency and asymptotic normality of the proposed spot covariance estimator. Based on extensive simulations we provide empirical guidance on the optimal implementation of the estimator and apply it to high-frequency data of a cross-section of NASDAQ blue chip stocks. Employing the estimator to estimate spot covariances, correlations and betas in normal but also extreme-event periods yields novel insights into intraday covariance and correlation dynamics. We show that intraday (co-)variations (i) follow underlying periodicity patterns, (ii) reveal substantial intraday variability associated with (co-)variation risk, (iii) are strongly serially correlated, and (iv) can increase strongly and nearly instantaneously if new information arrives.
    Keywords: local method of moments,spot covariance,smoothing,intraday (co-)variation risk
    JEL: C58 C14 C32
    Date: 2014
  4. By: Barunik, Jozef; Kočenda, Evžen; Vácha, Lukáš
    Abstract: Asymmetries in volatility spillovers are highly relevant to risk valuation and portfolio diversification strategies in financial markets. Yet, the large literature studying information transmission mechanisms ignores the fact that bad and good volatility may spill over at different magnitudes. This paper fills this gap with two contributions. One, we suggest how to quantify asymmetries in volatility spillovers due to bad and good volatility. Two, using high frequency data covering most liquid U.S. stocks in seven sectors, we provide ample evidence of the asymmetric connectedness of stocks. We universally reject the hypothesis of symmetric connectedness at the disaggregate level but in contrast, we document the symmetric transmission of information in an aggregated portfolio. We show that bad and good volatility is transmitted at different magnitudes in different sectors, and the asymmetries sizably change over time. While negative spillovers are often of substantial magnitudes, they do not strictly dominate positive spillovers. We find that the overall intra-market connectedness of U.S. stocks increased substantially with the increased uncertainty of stock market participants during the financial crisis.
    Keywords: volatility,spillovers,semivariance,asymmetric effects,financial markets
    JEL: C18 C58 G15
    Date: 2014
  5. By: Nicolas S. Lambert; Michael Ostrovsky; Mikhail Panov
    Abstract: We study trading behavior and the properties of prices in informationally complex markets. Our model is based on the single-period version of the linear-normal framework of Kyle (1985). We allow for essentially arbitrary correlations among the random variables involved in the model: the value of the traded asset, the signals of strategic traders and competitive market makers, and the demand from liquidity traders. We show that there always exists a unique linear equilibrium, characterize it analytically, and illustrate its properties in a series of examples. We then use this characterization to study the informational efficiency of prices as the number of strategic traders becomes large. If liquidity demand is positively correlated (or uncorrelated) with the asset value, then prices in large markets aggregate all available information. If liquidity demand is negatively correlated with the asset value, then prices in large markets aggregate all information except that contained in liquidity demand.
    JEL: D53 D82 D84 G12 G14
    Date: 2014–09

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