New Economics Papers
on Market Microstructure
Issue of 2012‒02‒15
four papers chosen by
Thanos Verousis


  1. Determinants of immediate price impacts at the trade level in an emerging order-driven market By Wei-Xing Zhou
  2. Portfolio liquidation in dark pools in continuous time By Peter Kratz; Torsten Sch\"oneborn
  3. Realized wavelet-based estimation of integrated variance and jumps in the presence of noise By Jozef Barunik; Lukas Vacha
  4. On return-volatility correlation in financial dynamics By J. Shen; B. Zheng

  1. By: Wei-Xing Zhou (ECUST)
    Abstract: The common wisdom argues that, in general, large trades cause large price changes, while small trades cause small price changes. However, for extremely large price changes, the trade size and news play a minor role, while the liquidity (especially price gaps on the limit order book) is a more influencing factor. Hence, there might be other influencing factors of immediate price impacts of trades. In this paper, through mechanical analysis of price variations before and after a trade of arbitrary size, we identify that the trade size, the bid-ask spread, the price gaps and the outstanding volumes at the bid and ask sides of the limit order book have impacts on the changes of prices. We propose two regression models to investigate the influences of these microscopic factors on the price impact of buyer-initiated partially filled trades, seller-initiated partially filled trades, buyer-initiated filled trades, and seller-initiated filled trades. We find that they have quantitatively similar explanation powers and these factors can account for up to 44% of the price impacts. Large trade sizes, wide bid-ask spreads, high liquidity at the same side and low liquidity at the opposite side will cause a large price impact. We also find that the liquidity at the opposite side has a more influencing impact than the liquidity at the same side. Our results shed new lights on the determinants of immediate price impacts.
    Date: 2012–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1201.5448&r=mst
  2. By: Peter Kratz; Torsten Sch\"oneborn
    Abstract: We consider an illiquid financial market where a risk-averse investor has to liquidate a large portfolio within a finite time horizon [0,T] and can trade continuously at a traditional exchange (the "primary venue") and in a dark pool. At the primary venue, trading yields a linear price impact. In the dark pool, no price impact costs arise but order execution is uncertain, modeled by a multi-dimensional Poisson process. We characterize the costs of trading by a linear-quadratic functional which incorporates both the price impact costs of trading at the primary exchange and the market risk of the position. The liquidation constraint implies a singularity of the value function of the resulting minimization problem at the terminal time T. Via the HJB equation and a quadratic ansatz, we obtain a candidate for the value function which is the limit of a sequence of solutions of initial value problems for a matrix differential equation. Although the differential equation is not a Riccati equation, we are able to show that this limit exists by using an appropriate matrix inequality and a comparison result for Riccati equations. Additionally, we obtain upper and lower bounds of the solutions of the initial value problems, which allow us to prove a verification theorem. If a single asset position is to be liquidated, the investor slowly trades out of her position at the primary venue, with the remainder being placed in the dark pool at any point in time. For multi-asset liquidations this is generally not optimal, and the optimal strategy depends strongly on the correlation of the assets.
    Date: 2012–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1201.6130&r=mst
  3. By: Jozef Barunik; Lukas Vacha
    Abstract: This paper proposes generalization of the popular realized volatility framework by allowing its measurement in the time-frequency domain and bringing robustness to both noise as well as jumps. Based on the generalization of Fan and Wang (2007) approach using smooth wavelets and Maximum Overlap Discrete Wavelet Transform, we present new, general theory for wavelet decomposition of integrated variance. Using wavelets, we not only gain decomposition of the realized variance into several investment horizons, but we are also able to estimate the jumps consistently. Basing our estimator in the two-scale realized variance framework of Zhang et al. (2005), we are able to utilize all available data and get unbiased estimator in the presence of noise as well. The theory is also tested in a large numerical study of the small sample performance of the estimators and compared to other popular realized variation estimators under different simulation settings with changing noise as well as jump level. The results reveal that our wavelet-based estimator is able to estimate and forecast the realized measures with the greatest precision. Another notable contribution lies in the application of the presented theory. Our time-frequency estimators not only produce more efficient estimates, but also decompose the realized variation into arbitrarily chosen investment horizons. The results thus provide a better understanding of the dynamics of stock markets.
    Date: 2012–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1202.1854&r=mst
  4. By: J. Shen; B. Zheng
    Abstract: With the daily and minutely data of the German DAX and Chinese indices, we investigate how the return-volatility correlation originates in financial dynamics. Based on a retarded volatility model, we may eliminate or generate the return-volatility correlation of the time series, while other characteristics, such as the probability distribution of returns and long-range time-correlation of volatilities etc., remain essentially unchanged. This suggests that the leverage effect or anti-leverage effect in financial markets arises from a kind of feedback return-volatility interactions, rather than the long-range time-correlation of volatilities and asymmetric probability distribution of returns. Further, we show that large volatilities dominate the return-volatility correlation in financial dynamics.
    Date: 2012–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1202.0342&r=mst

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