nep-mst New Economics Papers
on Market Microstructure
Issue of 2017‒03‒05
four papers chosen by
Thanos Verousis
University of Newcastle

  1. High frequency trading and fragility By Cespa, Giovanni; Vives, Xavier
  2. Empirical likelihood for high frequency data By Lorenzo Camponovo; Yukitoshi Matsushita; Taisuke Otsu
  3. Dual decision processes and noise trading By Francesco Cerigioni
  4. The short-term price impact of trades is universal By Bence Toth; Zoltan Eisler; Jean-Philippe Bouchaud

  1. By: Cespa, Giovanni; Vives, Xavier
    Abstract: We show that limited dealer participation in the market, coupled with an informational friction resulting from high frequency trading, can induce demand for liquidity to be upward sloping and strategic complementarities in traders' liquidity consumption decisions: traders demand more liquidity when the market becomes less liquid, which in turn makes the market more illiquid, fostering the initial demand hike. This can generate market instability, where an initial dearth of liquidity degenerates into a liquidity rout (as in a flash crash). While in a transparent market, liquidity is increasing in the proportion of high frequency traders, in an opaque market strategic complementarities can make liquidity U-shaped in this proportion as well as in the degree of transparency. JEL Classification: G10, G12, G14
    Keywords: asymmetric information, flash crash, high frequency trading, market fragmentation
    Date: 2017–02
  2. By: Lorenzo Camponovo; Yukitoshi Matsushita; Taisuke Otsu
    Abstract: With increasing availability of high frequency financial data as a background, various volatility measures and related statistical theory are developed in the recent literature. This paper introduces the method of empirical likelihood to conduct statistical inference on the volatility measures under high frequency data environments. We propose a modified empirical likelihood statistic that is asymptotically pivotal under the infill asymptotics, where the number of high frequency observations in a fixed time interval increases to infinity. Our empirical likelihood approach is extended to be robust to the presence of jumps and microstructure noise. We also provide an empirical likelihood test to detect presence of jumps. Furthermore, we establish Bartlett correction, a higher-order refinement, for a general nonparametric likelihood statistic. Simulation and a real data example illustrate the usefulness of our approach.
    Keywords: High frequency data, Volatility, Empirical likelihood
    JEL: C12 C14 C58
    Date: 2017–02
  3. By: Francesco Cerigioni
    Abstract: Evidence from nancial markets suggests that asset prices can be consistently far from their funda- mental value. Prices seem to underreact to news in the short-run and overreact in the long-run. In this paper, we use Dual Process Theory to describe traders behavior. In particular, a part of traders holds wrong beliefs anytime the market environment does not change suciently. The proportion of traders with wrong beliefs will depend on how similar past market environments are with the present one. We show that such model not only can be seen as a way of endogenizing noise trading, but also provides a justi cation for noise traders' beliefs and it shows that underreaction and overreaction naturally arise in such framework. Finally, we discuss how the model might help understanding the emergence of the equity-premium puzzle and its variation through time.
    Keywords: Asset Pricing, Dual Processes, Noise Trading, Underreaction, Overreaction, Equity-Premium Puzzle
    JEL: G02 G11 G12
    Date: 2016–09
  4. By: Bence Toth; Zoltan Eisler; Jean-Philippe Bouchaud
    Abstract: We analyze a proprietary dataset of trades by a single asset manager, comparing their price impact with that of the trades of the rest of the market. In the context of a linear propagator model we find no significant difference between the two, suggesting that both the magnitude and time dependence of impact are universal. This result is important as optimal execution policies often rely on propagators calibrated on anonymous data. We also find evidence that in the wake of a trade the order flow of other market participants first adds further copy-cat trades enhancing price impact on very short time scales. The induced order flow then quickly inverts, thereby contributing to impact decay.
    Date: 2017–02

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