New Economics Papers
on Market Microstructure
Issue of 2011‒05‒30
six papers chosen by
Thanos Verousis

  1. On the volatility-volume relationship in energy futures markets using intraday data By Julien Chevallier; Benoît Sévi
  2. Trading Fees and Efficiency in Limit Order Markets By Colliard, Jean-Edouard; Foucault, Thierry
  3. High Frequency Trading, Information, and Takeovers By Humphery-Jenner, M.
  4. Stochastic Price Dynamics Implied By the Limit Order Book By Alex Langnau; Yanko Punchev
  5. Identification of jumps in financial price series By Hellström, Jörgen; Lönnbark, Carl
  6. Dealing with the Inventory Risk By Olivier Gu\'eant; Charles-Albert Lehalle; Joaquin Fernandez Tapia

  1. By: Julien Chevallier; Benoît Sévi
    Abstract: This paper investigates the relationship between trading volume and price volatility in the crude oil and natural gas futures markets when using high-frequency data. By regressing various realized volatility measures (with/without jumps) on trading volume and trading frequency, our results feature a contemporaneous and largely positive relationship. Furthermore, we test whether the volatility-volume relationship is symmetric for energy futures by considering positive and negative realized semivariance. We show that (i) an asymmetric volatility-volume relationship indeed exists, (ii) trading volume and trading frequency significantly affect negative and positive realized semivariance, and (iii) the information content of negative realized semivariance is higher than for positive realized semivariance.
    Keywords: Trading Volume; Price Volatility; Crude Oil Futures; Natural Gas Futures; High-Frequency Data; Realized Volatility; Bipower Variation; Median Realized Volatility; Realised Semivariance; Jump
    JEL: C15 C32 C53 G1 Q4
    Date: 2011
  2. By: Colliard, Jean-Edouard; Foucault, Thierry
    Abstract: We study competition between a dealer (OTC) market and a limit order market. In the limit order market, investors can choose to be "makers" (post limit orders) or "takers" (hit limit orders) whereas in the dealer market they must trade at dealers' quotes. Moreover, in the limit order market, investors pay a trading fee to the operator of this market ("the matchmaker"). We show that an increase in the matchmaker's trading fee can raise investors' ex-ante expected welfare. Actually, it induces makers to post more aggressive offers and thereby it raises the likelihood of a direct trade between investors. For this reason as well, a reduction in the matchmaker's trading fee can counter-intuitively raise the OTC market share. However, entry of a new matchmaker results in an improvement in investors' welfare, despite its negative effect on trading fees. The model has testable implications for the effects of a change in trading fees and their breakdown between makers and takers on various measures of market liquidity.
    Keywords: inter-market competition; Limit order markets; liquidity; make/take fees; OTC markets; trading fees
    JEL: G00 G18 G20 L10
    Date: 2011–05
  3. By: Humphery-Jenner, M. (Tilburg University, Center for Economic Research)
    Abstract: This paper (1) proposes new variables to detect informed high-frequency trading (HFT), (2) shows that HFT can help to predict takeover targets, and (3) shows that HFT in uences target announcement announcement returns. Prior literature suggests that informed trade may occur before takeovers, but has not examined the role of HFT and has relied on monthly measures of informed trade (such as PIN or the spread components). I propose microstructure-based variables to detect HFT that are derived from hazard modeling and from VWAP trading algorithms. I show that these can help predict takeover targets and are significantly related to target announcement returns. This highlights the existence of pre-takeover informed trade and the need to control for it when analyzing takeover returns.
    Keywords: High Frequency Trading;Takeovers;Algorithmic Trading.
    JEL: G12 G14 G18 G34 K22
    Date: 2011
  4. By: Alex Langnau; Yanko Punchev
    Abstract: In this paper we present a novel approach to the determination of fat tails in financial data by studying the information contained in the limit order book. In an order-driven market buyers and sellers may submit limit orders, which are executed when the price touches a pre-specified lower, respectively higher, limit-price. We show that, in equilibrium, the collection of all such orders - the limit order book - implies a volatility smile, similar to observations from option pricing in the Black-Scholes model. We also show how a jump-diffusion process can be explicitly inferred to account for the volatility smile.
    Date: 2011–05
  5. By: Hellström, Jörgen (Umeå School of Business, Umeå University); Lönnbark, Carl (Department of Economics, Umeå University)
    Abstract: The paper outlines and tests, by means of Monte-Carlo simulations, a simple strategy of using existing non-parametric tests for jumps at the daily frequency to identify jumps at higher sampling frequencies. The suggested strategy allow for identification of the number of jumps and jump times during a day, as well as, the size and direction (negative or positive) of the jumps. The method is of importance in order to facilitate detailed empirical studies concerning, for example, causes for jumps in financial price series at finer levels than the daily. The Monte Carlo study reveals that the strategy works reasonably well, particular for lower jump intensities. An application of the studied strategy on the Handelsbanken stock is provided.
    Keywords: Financial econometrics; jumps; realized variance; bipower variation; stock price
    JEL: C14 C15 G12
    Date: 2011–05–20
  6. By: Olivier Gu\'eant; Charles-Albert Lehalle; Joaquin Fernandez Tapia
    Abstract: Market makers have to continuously set bid and ask quotes for the stocks they have under consideration. Hence they face a complex optimization problem in which their return, based on the bid-ask spread they quote and the frequency they indeed provide liquidity, is challenged by the price risk they bear due to their inventory. In this paper, we provide optimal bid and ask quotes and closed-form approximations are derived using spectral arguments.
    Date: 2011–05

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