nep-mst New Economics Papers
on Market Microstructure
Issue of 2016‒04‒04
eight papers chosen by
Thanos Verousis

  1. Stepping out of the limit order book: Empirical evidence from the EBS FX market By Yoshida, Yushi; Susai, Masayuki
  2. Market Dynamics vs. Statistics: Limit Order Book Example By Vladislav Gennadievich Malyshkin; Ray Bakhramov
  3. Preference evolution and the dynamics of capital markets By Curatola, Giuliano
  4. Universal trading under proportional transaction costs By Richard J Martin
  5. Time-varying Volatility and the Power Law Distribution of Stock Returns By Warusawitharana, Missaka
  6. Estimating the Integrated Parameter of the Locally Parametric Model in High-Frequency Data By Yoann Potiron
  7. The geometric phase of stock trading By Claudio Altafini
  8. Stock exchange integration and price jump risks - The case of the OMX Nordic exchange mergers By Liu, Yuna

  1. By: Yoshida, Yushi; Susai, Masayuki
    Abstract: Most limit orders exit the market as cancellations or revisions without a transaction. Using the EBS dataset, we can measure how long an individual limit order remains in the foreign exchange (FX) market. Thus, we use the measured lifetimes of canceled limit orders and find that post-order-placement changes in market price and limit order book depth affect cancellations, consistent with optimal behaviors that consider both order placement and order exit. FX dealers cancel their limit orders faster as the depth increases at better quotes. When market prices move away from their submitted quotes, patient dealers exhibit greater forbearance for their worsened position.
    Keywords: Foreign exchange market; Lifetime; Limit order; Market microstructure; Order book.
    JEL: F31 G12 G14 G15
    Date: 2016–03–25
  2. By: Vladislav Gennadievich Malyshkin; Ray Bakhramov
    Abstract: Commonly used limit order book attributes are empirically considered based on NASDAQ ITCH data. It is shown that some of them have the properties drastically different from the ones assumed in many market dynamics study. Because of this difference we propose to make a transition from "Statistical" type of order book study (typical for academics) to "Dynamical" type of study (typical for market practitioners). A computer code, providing full depth order book information and recently executed trades is available from authors [1].
    Date: 2016–03
  3. By: Curatola, Giuliano
    Abstract: This paper introduces endogenous preference evolution into a Lucas-type economy and explores its consequences for investors' trading strategy and the dynamics of asset prices. In equilibrium, investors herd and hold the same portfolio of risky assets which is biased toward stocks of sectors that produce a socially preferred good. Price-dividend ratios, expected returns and return volatility are all time varying. In this way, preference evolution helps rationalize the observed under-performance and local biases of investors' portfolios and many empirical regularities of stock returns such a time variation, the value-growth effect and stochastic volatility.
    Keywords: asset pricing,general equilibrium,heterogeneous investors,interdependent preferences,portfolio choice
    JEL: D51 D91 E20 G12
    Date: 2016
  4. By: Richard J Martin
    Abstract: The theory of optimal trading under proportional transaction costs has been considered from a variety of perspectives. In this paper, we show that all the results can be interpreted using a universal law, illustrating the results in trading algorithm design.
    Date: 2016–03
  5. By: Warusawitharana, Missaka
    Abstract: While many studies find that the tail distribution of high frequency stock returns follow a power law, there are only a few explanations for this finding. This study presents evidence that time-varying volatility can account for the power law property of high frequency stock returns. The power law coefficients obtained by estimating a conditional normal model with nonparametric volatility show a striking correspondence to the power law coefficients estimated from returns data for stocks in the Dow Jones index. A cross-sectional regression of the data coefficients on the model-implied coefficients yields a slope close to one, supportive of the hypothesis that the two sets of power law coefficients are identical. Further, for most of the stocks in the sample taken individually, the model-implied coefficient falls within the 95 percent confidence interval for the coefficient estimated from returns data.
    Keywords: Tail distributions ; high frequency returns ; power laws ; time-varying volatility
    JEL: C58 D30 G12
    Date: 2016–03–18
  6. By: Yoann Potiron
    Abstract: In this paper, we give a general time-varying parameter model, where the multidimensional parameter follows a continuous local martingale. As such, we call it the locally parametric model. The quantity of interest is defined as the integrated value over time of the parameter process $\Theta := T^{-1} \int_0^T \theta_t^* dt$. We provide a local parametric estimator of $\Theta$ based on the original (non time-varying) parametric model estimator and conditions under which we can show consistency and the corresponding limit distribution. We show that the LPM class contains some models that come from popular problems in the high-frequency financial econometrics literature (estimating volatility, high-frequency covariance, integrated betas, leverage effect, volatility of volatility), as well as a new general asset-price diffusion model which allows for endogenous observations and time-varying noise which can be auto-correlated and correlated with the efficient price and the sampling times. Finally, as an example of how to apply the limit theory provided in this paper, we build a time-varying friction parameter extension of the (semiparametric) model with uncertainty zones (Robert and Rosenbaum (2012)), which is noisy and endogenous, and we show that we can verify the conditions for the estimation of integrated volatility.
    Date: 2016–03
  7. By: Claudio Altafini
    Abstract: Geometric phases describe how in a continuous-time dynamical system the displacement of a variable (called phase variable) can be related to other variables (shape variables) undergoing a cyclic motion, according to an area rule. The aim of this paper is to show that geometric phases can exist also for discrete-time systems, and even when the cycles in shape space have zero area. A context in which this principle can be applied is stock trading. A zero-area cycle in shape space represents the type of trading operations normally carried out by high-frequency traders (entering and exiting a position on a fast time-scale), while the phase variable represents the cash balance of a trader. Under the assumption that trading impacts stock prices, even zero-area cyclic trading operations can induce geometric phases, i.e., profits or losses, without affecting the stock quote.
    Date: 2016–03
  8. By: Liu, Yuna (Department of Economics, Umeå University)
    Abstract: The impact of the stock market mergers that took place in the Nordic countries during 2000 – 2007 on the probabilities for stock price jumps, i.e. for relatively extreme price movements, are studied. The main finding is that stock market mergers, on average, reduce the likelihood of observing stock price jumps. The effects are asymmetric in the sense that the probability of sudden price jumps is reduced for large and medium size firms whereas the effect is ambiguous for small size firms. The results also indicate that the market risk has been reduced after the stock market consolidations took place.
    Keywords: Tests for jumps; International financial markets; Market structure; Integration; Common trading platform; Mergers; Acquisitions
    JEL: C22 C51 C58 G15 G34 L10
    Date: 2016–03–16

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