New Economics Papers
on Market Microstructure
Issue of 2009‒08‒16
five papers chosen by
Thanos Verousis


  1. Intraday Trading Patterns: The Role of Timing By Katya Malinova; Andreas Park
  2. Dispersion of Information or Market Behaviour: General Public Trading in S&P500 Index Futures By Gerard L. Gannon
  3. The Trading Performance of Dynamic Hedging Models: Time Varying Covariance and Volatility Transmission Effects By Michael T. Chng; Gerard L. Gannon
  4. A Dynamic Analysis of the Microstructure of Moving Average Rules in a Double Auction Market By Carl Chiarella; Xue-Zhong He; Paolo Pellizzari
  5. Bootstrapping the likelihood ratio cointegration test in error correction models with unknown lag order By Christian Kascha; Carsten Trenkler

  1. By: Katya Malinova; Andreas Park
    Abstract: In a dynamic model of financial market trading multiple heterogeneously informed traders choose when to place orders. Better informed traders trade immediately, worse informed delay — even though they expect the public expectation to move against them. This behavior causes distinct intra-day patterns with decreasing (L-shaped) spreads and increasing (reverse L-shaped) volume and probability of informed trading (PIN). Competition increases market participation and causes more pronounced spread and less pronounced volume patterns. Systematic improvements in information increase spreads and volume. Very short-lived private information generates L- or reverse J-shaped volume patterns, which are further enhanced by competition.
    Keywords: intraday patterns, asymmetric information, trade timing, microstructure
    JEL: D82 G12 G14
    Date: 2009–08–01
    URL: http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-365&r=mst
  2. By: Gerard L. Gannon
    Abstract: This paper considers 15 minute records of trading volume and traded prices coinciding with the reporting intervals required by the Commodity Futures Trading Commission. Records are extracted from trade records for two way trade between market makers (CTI1) and the general public (CTI4) from January 1994 to June 2004. Futures price records are matched with S&P500 cash index price records. Simultaneous volatility models are specified and estimated to test trading volume to futures volatility lead/lag effects and also futures volatility to cash index volatility lead/lag effects. There is evidence that existing theoretical models of the general public trading behaviour do not explain such behaviour in these very actively traded markets. These effects can depend more on market conditions than what is suggested in theoretical models.
    Keywords: S&P500 Trade Data, Simultaneous Volatility, Market Makers, General Public, Volume, Lead/Lag Volatility
    JEL: G14
    Date: 2009–08–05
    URL: http://d.repec.org/n?u=RePEc:dkn:acctwp:aef_2009_01&r=mst
  3. By: Michael T. Chng; Gerard L. Gannon
    Abstract: In this paper, we investigate the value of incorporating implied volatility from related option markets in dynamic hedging. We comprehensively model the volatility of all four S&P 500 cash, futures, index option and futures option markets simultaneously. Synchronous half-hourly observations are sampled from transaction data. Special classes of extended simultaneous volatility systems (ESVL) are estimated and used to generate out-of-sample hedge ratios. In a hypothetical dynamic hedging scheme, ESVLbased hedge ratios, which incorporate incremental information in the implied volatilities of the two S&P 500 option markets, generate profits from interim rebalancing of the futures hedging position that are incremental over competing hedge ratios. In addition, ESVL-based hedge ratios are the only hedge ratios that manage to generate sufficient profit during the hedging period to cover losses incurred by the physical portfolio .
    Keywords: volatility transmission, dynamic hedging, optimal hedge ratio, S&P 500
    JEL: G14 G28
    Date: 2009–08–05
    URL: http://d.repec.org/n?u=RePEc:dkn:acctwp:aef_2009_02&r=mst
  4. By: Carl Chiarella (School of Finance and Economics, University of Technology, Sydney); Xue-Zhong He (School of Finance and Economics, University of Technology, Sydney); Paolo Pellizzari (Department of Applied Mathematics, School for Advanced Studies in Venice, Ca? Foscari University)
    Abstract: Inspired by the theoretically oriented dynamic analysis of moving average rules in Chiarella, He and Hommes (CHH) (2006a) model, this paper conducts a dynamic analysis of a microstructure model of continuous double auctions in which the probability of heterogeneous agents to trade is determined by the rules of either fundamentalists mean-reverting to the fundamental or chartists choosing moving average rules based their relative performance. With such a realistic market microstructure, the model is able not only to obtain the results of the CHH model but also to characterise most of the stylized facts including the power-law behaviour of volatility. The results seem to suggest that a comprehensive explanation of several statistical properties of returns is possible in a framework where both behavioral traits and realistic microstructure have a role.
    Keywords: microstructure model; continuous double auctions; heterogeneous agents; stylized facts
    JEL: G12 D53
    Date: 2009–07–01
    URL: http://d.repec.org/n?u=RePEc:uts:rpaper:251&r=mst
  5. By: Christian Kascha (Norges Bank (Central Bank of Norway)); Carsten Trenkler (University of Mannheim)
    Abstract: We investigate the small-sample size and power properties of bootstrapped likelihood ratio systems cointegration tests via Monte Carlo simulations when the true lag order of the data generating process is unknown. A recursive bootstrap scheme is employed. We estimate the order by minimizing different information criteria. In comparison to the standard asymptotic likelihood ratio test based on an estimated lag order we found that the recursive bootstrap procedure can lead to improvements in small samples even when the true lag order is unknown while the power loss is moderate.
    Keywords: Cointegration tests, Bootstrapping, Information criteria
    JEL: C15 C32
    Date: 2009–08–04
    URL: http://d.repec.org/n?u=RePEc:bno:worpap:2009_12&r=mst

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