New Economics Papers
on Market Microstructure
Issue of 2013‒03‒16
six papers chosen by
Thanos Verousis

  1. Dynamical Trading Mechanism in Limit Order Markets By Shilei Wang
  2. Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data By Audrino, Francesco; Fengler, Matthias
  3. Limit Theorems for the Pre-averaged Hayashi-Yoshida Estimator with Random Sampling By Yuta Koike
  4. Do High-Frequency Data Improve High-Dimensional Portfolio Allocations? By Nikolaus Hautsch; Lada M. Kyj; Peter Malec;
  5. Competition between stock exchanges and optimal trading. By Kervel, V.L. van
  6. Bootstrapping Realized Multivariate Volatility Measures. By Donovon, Prosper; Goncalves, Silvia; Meddahi, Nour

  1. By: Shilei Wang
    Abstract: This work's purpose is to understand the dynamics of limit order books in order-driven markets. We try to illustrate a dynamical trading mechanism attached to the microstructure of limit order markets. We capture the iterative nature of trading processes, which is critical in the dynamics of bid-ask pairs and the switching laws between different traders' types and their orders. In general, after introducing the atomic trading scheme, we study a general iterated trading process in both combinatorial and stochastic ways, and state a few results on the stability of a dynamical trading system. We also study the controlled dynamics of the spread and the mid-price in an iterated trading system, when their movements, generated from the dynamics of bid-ask pairs, are assumed to be restricted within some extremely small ranges.
    Date: 2013–03
  2. By: Audrino, Francesco; Fengler, Matthias
    Abstract: We suggest a joint analysis of ex-post intra-day variability in an option and its associated underlying asset market as a novel means of validating an option pricing model. For this purpose, we introduce the notion of option realized variance, by which we mean the cumulative variance realized by the sample path of successive option price observations. In concurrently observing the realized path of the underlying asset, we contrast option realized variance with the realized variance that would be implied from the underlying asset price path under certain model assumptions. In the empirical analysis, we focus on the implied volatility compensated Black-Scholes model and the Heston model. We find that neither model reconciles second-order moments in the option and the underlying asset market. The differences point to the existence of additional relevant pricing factors that affect option second-order moments. We thus corroborate findings made in option data of lower frequency.
    Keywords: Option pricing; high frequency data; realized variance; stochastic volatility
    JEL: C52 C58 G13 G17
    Date: 2013–03
  3. By: Yuta Koike
    Abstract: We will focus on estimating the integrated covariance of two diffusion processes observed in a nonsynchronous manner. The observation data is contaminated by some noise, which is possibly correlated with the returns of the diffusion processes, while the sampling times also possibly depend on the observed processes. This situation is much more realistic than those in which both of the noise and the sampling times are independent of the diffusion processes. In a high-frequency setting, we consider a modified version of the pre-averaged Hayashi- Yoshida estimator, and we show that such a kind of estimators has the consistency and the asymptotic mixed normality, and attains the optimal rate of convergence.
    Keywords: Endogenous noise, Hayashi-Yoshida estimator, Integrated covariance, Market microstructure noise, Nonsynchronous observations, Pre-averaging, Stable convergence, Strong predictability
    Date: 2013–01
  4. By: Nikolaus Hautsch; Lada M. Kyj; Peter Malec;
    Abstract: This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. We consider the problem of constructing global minimum variance portfolios based on the constituents of the S&P 500 over a four-year period covering the 2008 financial crisis. HF-based covariance matrix predictions are obtained by applying a blocked realized kernel estimator, different smoothing windows, various regularization methods and two forecasting models. We show that HF-based predictions yield a significantly lower portfolio volatility than methods employing daily returns. Particularly during the volatile crisis period, these performance gains hold over longer horizons than previous studies have shown and translate into substantial utility gains from the perspective of an investor with pronounced risk aversion.
    Keywords: portfolio optimization; spectral decomposition; regularization; blocked realized kernel; covariance prediction
    JEL: G11 G17 C58 C14 C38
    Date: 2013–03
  5. By: Kervel, V.L. van (Tilburg University)
    Abstract: This doctoral thesis focuses on two topics on trading in financial markets: competition between stock exchanges and optimal trading strategies. Chapter one analyzes the effect on the liquidity of a stock when it is traded on multiple trading venues, and distinguishes between competition from transparent and opaque venues. Chapter two demonstrates a strong interaction between the supply and demand of trading activity across trading venues. Chapter three focuses on the optimal strategy to trade a large amount of shares before a deadline. It studies the information asymmetry between informed and uninformed traders, and finds that splitting the large quantity into smaller parts may resolve this friction.
    Date: 2013
  6. By: Donovon, Prosper; Goncalves, Silvia; Meddahi, Nour
    Date: 2013–01

This issue is ©2013 by Thanos Verousis. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.