nep-mst New Economics Papers
on Market Microstructure
Issue of 2014‒10‒03
four papers chosen by
Thanos Verousis

  1. A Compound Multifractal Model for High-Frequency Asset Returns By Eric M. Aldrich; Indra Heckenbach; Gregory Laughlin
  2. Market composition and price informativeness in a large market with endogenous order types By Edouard Challe; Edouard Chretien
  3. Factor Structure in Commodity Futures Return and Volatility By Peter Christoffersen; Asger Lunde; Kasper V. Olesen
  4. Information Aggregation and Optimal Market Size By Kei Kawakami

  1. By: Eric M. Aldrich (Department of Economics, University of California Santa Cruz); Indra Heckenbach (Department of Physics, University of California Santa Cruz); Gregory Laughlin (Department of Astronomy and Astrophysics, University of California Santa Cruz)
    Abstract: WThis paper builds a model of high-frequency equity returns in clock time by separately modeling the dynamics of trade-time returns and trade arrivals. Our main contributions are threefold. First, we characterize the distributional behavior of high-frequency asset returns both in clock time and trade time and show that when controlling for pre-scheduled market news events, trade-time returns are well characterized by a Gaussian distribution at very fine time scales. Second, we develop a structured and parsimonious model of clock-time returns by subordinating a trade-time Gaussian distribution with a trade arrival process that is associated with a modified Markov-Switching Multifractal Duration (MSMD) model of Chen et al. (2013). Our modification of the MSMD model provides a much better characterization of high-frequency inter-trade durations than the original model of Chen et al. (2013). Over-dispersion in this distribution of inter-trade durations leads to leptokurtosis and volatility clustering in clock-time returns, even when trade-time returns are Gaussian. Finally, we use our model to extrapolate the empirical relationship between trade rate and volatility in an effort to understand conditions of market failure. Our model finds that physical separation of financial markets maintains a natural ceiling on systemic volatility and promotes market stability.
    Keywords: High-frequency trading, US Equities, News arrival
    JEL: C22 C41 C58 G12 G14 G17
    Date: 2014–08
  2. By: Edouard Challe (Department of Economics, Ecole Polytechnique - CNRS : UMR7176 - Polytechnique - X, CREST - Centre de Recherche en Économie et Statistique - INSEE - École Nationale de la Statistique et de l'Administration Économique, Banque de France - -); Edouard Chretien (CREST - Centre de Recherche en Économie et Statistique - INSEE - École Nationale de la Statistique et de l'Administration Économique)
    Abstract: We analyse the joint determination of price informativeness and the composition of the market by order type in a large asset market with dispersed information. The market microstructure is one in which informed traders may place market orders or full demand schedules and where market makers set the price. Market-order traders trade less aggressively on their information and thus reduce the informativeness of the price; in a full market-order market, price informativeness is bounded, whatever the quality of tradersinformation about the assets dividend. When traders can choose their order type and demand schedules are (even marginally) costlier than market orders, then market-order traders overwhelm the market when the precision of private signals goes to in…nity. This is because demand schedules are substitutes: at high levels of precision, a residual fraction of demand-schedule traders is sufficient to take the trading price close to traders signals, while the latter is itself well aligned with the dividend. Hence, the gain from trading conditional on the price (as demand-schedule traders do) in addition to ones own signal (as all informed traders do) vanishes.
    Date: 2014–09–03
  3. By: Peter Christoffersen (University of Toronto and CREATES); Asger Lunde (Aarhus University and CREATES); Kasper V. Olesen (Aarhus University and CREATES)
    Abstract: Using data on more than 750 million futures trades during 2004-2013, we analyze eight stylized facts of commodity price and volatility dynamics in the post financialization period. We pay particular attention to the factor structure in returns and volatility and to commodity market integration with the equity market. We find evidence of a factor structure in daily commodity futures returns. However, the factor structure in daily commodity futures volatility is even stronger than in returns. When computing model-free realized commodity betas with the stock market we find that they were high during 2008-2010 but have since returned to the pre-crisis level close to zero. The common factor in commodity volatility is nevertheless clearly related to stock market volatility. We conclude that, while commodity markets appear to again be segmented from the equity market when only returns are considered, commodity volatility indicates a nontrivial degree of market integration.
    Keywords: Factor structure, financial volatility, beta, high-frequency data, commodities, financialization
    JEL: G13 Q02
    Date: 2014–09–08
  4. By: Kei Kawakami
    Abstract: This paper studies a rational expectations model of trading where strategic traders face information asymmetries and endowment shocks. We show that negative partici- pation externalities arise due to an endogenous interaction between information aggre-gation and multiple trading motives. Moreover, the negative externalities are strong enough to make optimal market size ?nite. In a decentralized process of market for- mation, multiple markets can survive due to the negative externalities among traders. The model also predicts: (i) that only in a su¢ ciently large market the equilibrium multiplicity due to self-ful?lling trading motives can arise, (ii) that a high correlation in endowment shocks can make markets extremely illiquid.
    Keywords: Asymmetric information, Aggregate shock, Imperfect competition, Market fragmentation, Multiple equilibria, Network externality puzzle, Price impact.
    Date: 2014

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