New Economics Papers
on Market Microstructure
Issue of 2010‒12‒11
five papers chosen by
Thanos Verousis

  1. Dynamic Dark Pool Trading Strategies in Limit Order Markets By Sabrina Buti; Barbara Rindi; Ingrid M. Werner
  2. Call auctions: A solution to some difficulties in Indian finance By Susan Thomas
  3. The Price Impact of Order Book Events By Rama Cont; Arseniy Kukanov; Sasha Stoikov
  4. Liquidity Problems in the FX Liquid Market By Vladimir Borgy; Julien Idier; Gaëlle Le Fol
  5. Trading volume and serial correlation in stock returns: a threshold regression approach By Shoko Morimoto; Mototsugu Shintani

  1. By: Sabrina Buti; Barbara Rindi; Ingrid M. Werner
    Abstract: We model a dynamic financial market where traders submit orders either to a limit order book (LOB) or to a Dark Pool (DP). We show that there is a positive liquidity externality in the DP, that orders migrate from the LOB to the DP, but that overall trading volume increases when a DP is introduced. We also demonstrate that DP market share is higher when LOB depth is high, when LOB spread is narrow, when the tick size is large and when traders seek protection from price impact. Further, while inside quoted depth in the LOB always decreases when a DP is introduced, quoted spreads can narrow for liquid stocks and widen for illiquid ones. We also show that traders' interaction with both LOB and DP generates interesting systematic patterns in order ow: di¤erently from Parlour (1998), the probability of a continuation is greater than that of a reversal only for liquid stocks. In addition, when depth decreases on one side of LOB, liquidity is drained from DP. When a DP is added to a LOB, total welfare as well as institutional traders' welfare increase but only for liquid stocks; retail traders' welfare instead always decreases. Finally, when flash orders provide select traders with information about the state of the DP, we show that more orders migrate from the LOB to the DP, and DP welfare effects are enhanced.
    Date: 2010
  2. By: Susan Thomas (Indira Gandhi Institute of Development Research)
    Abstract: The Indian financial system has been revolutionised by the application of a new market design: continuous trading with an anonymous limit order book at NSE and BSE. However, in certain situations, this market design has limitations. Call auctions represent an alternative strategy, where the order flow over a certain time period is pooled, and the market-clearing price obtained through an aggregated supply and demand curve. Call auctions trade off instantaneity of order execution in favour of elimination of impact cost, and can achieve a more trusted price. They can improve the functioning of the market on issues such as market opening, market close, extreme news events, and potentially for illiquid securities including bonds. Call auctions could usefully replace some existing market rules such as `circuit breakers\'. At the same time, there are many subtle elements in making a call auction market work, which require care in market design.
    Keywords: Market microstructure, call auctions, illiquid securities, circuit breakers
    JEL: G10 G19
    Date: 2010
  3. By: Rama Cont; Arseniy Kukanov; Sasha Stoikov
    Abstract: We study the price impact of order book events - limit orders, market orders and cancelations - using the NYSE TAQ data for 50 U.S. stocks. We show that, over short time intervals, price changes are mainly driven by the order flow imbalance, defined as the imbalance between supply and demand at the best bid and ask prices. Our study reveals a linear relation between order flow imbalance and price changes, with a slope inversely proportional to the market depth. These results are shown to be robust to seasonality effects, and stable across time scales and across stocks. We argue that this linear price impact model, together with a scaling argument, implies the empirically observed "square-root" relation between price changes and trading volume. However, the relation between price changes and trade volume is found to be noisy and less robust than the one based on order flow imbalance.
    Date: 2010–11
  4. By: Vladimir Borgy (Banque de France - Banque de France); Julien Idier (Banque de france - Banque de France); Gaëlle Le Fol (DRM - Dauphine Recherches en Management - CNRS : UMR7088 - Université Paris Dauphine - Paris IX)
    Abstract: Even though the FX market is one of the most liquid financial market, it would be an error to consider that it is immune against any liquidity problem. This paper analyzes on a long sample (2000-2009), the all set of quotes and transactions in three main currency pairs (EURJPY, EURUSD, USDJPY) on the EBS platform. To characterize the FX market liquidity, we consider the spread, the traded volume, the number of transactions and the Amihud (2002) statistic for illiquidity. We also propose the computation of a new liquidity indicator, BIL, that solely relies on price series availability. The main benefit of such measure is to be easily calculated on almost any financial market as well as to have a clear interpretation in terms of liquidity costs. Using all these advanced liquidity analyses, we finally test the accuracy of these measures to detect liquidity problems in the FX market. Our analysis, based on a signaling approach, shows that liquidity problems have arisen during specific episodes in the early 2000's and more generally during the recent financial turmoil.
    Keywords: FX market; Liquidity; financial crisis
    Date: 2010
  5. By: Shoko Morimoto (Graduate School of Economics, Osaka University); Mototsugu Shintani (Department of Economics, Vanderbilt University)
    Abstract: We extend the analysis of Campbell et al. (1993) on the relationship between the first-order daily stock return autocorrelation and stock market trading volume by allowing abrupt and smooth transition structures using lagged stock returns as a transition variable. Using U.S. stock market data, we find the evidence supporting the nonlinear relationship characterized by a stronger return reversal effect on a high-volume day combined with low lagged stock returns.
    Keywords: TAR, STAR, Stock return autocorrelation, Trading volume
    JEL: C22 G12
    Date: 2010–12

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