nep-mst New Economics Papers
on Market Microstructure
Issue of 2018‒11‒12
seven papers chosen by
Thanos Verousis

  1. A tale of one exchange and two order books: Effects of fragmentation in the absence of competition By Bernales, Alejandro; Garrido, Nicolás; Sagade, Satchit; Valenzuela, Marcela; Westheide, Christian
  2. Fixing the Fix? Assessing the Effectiveness of the 4pm Fix Benchmark By Martin D. D. Evans; Peter O'Neill; Dagfinn Rime; Jo Saakvitne
  3. Forecasting of Jump Arrivals in Stock Prices: New Attention-based Network Architecture using Limit Order Book Data By Milla M\"akinen; Juho Kanniainen; Moncef Gabbouj; Alexandros Iosifidis
  4. Agent- based model of intra-day financial markets dynamics By Jacopo Staccioli; Mauro Napoletano
  5. Early Birds and Second Mice in the Stock Market By Julio A. Crego; Jin Huang
  6. Option market (in)efficiency and implied volatility dynamics after return jumps By Juho Kanniainen; Martin Magris
  7. Short Selling Ban and Intraday Dynamics By Julio A. Crego

  1. By: Bernales, Alejandro; Garrido, Nicolás; Sagade, Satchit; Valenzuela, Marcela; Westheide, Christian
    Abstract: Exchanges nowadays routinely operate multiple, almost identically structured limit order markets for the same security. We study the effects of such fragmentation on market performance using a dynamic model where agents trade strategically across two identically-organized limit order books. We show that fragmented markets, in equilibrium, offer higher welfare to intermediaries at the expense of investors with intrinsic trading motives, and lower liquidity than consolidated markets. Consistent with our theory, we document improvements in liquidity and lower profits for liquidity providers when Euronext, in 2009, consolidated its order flow for stocks traded across two country-specific and identically-organized order books into a single order book. Our results suggest that competition in market design, not fragmentation, drives previously documented improvements in market quality when new trading venues emerge; in the absence of such competition, market fragmentation is harmful.
    Keywords: Fragmentation,Competition,Liquidity,Price Efficiency
    JEL: G10 G12
    Date: 2018
  2. By: Martin D. D. Evans (Department of Economics, Georgetown University); Peter O'Neill; Dagfinn Rime; Jo Saakvitne
    Abstract: We examine the design and effectiveness of the 4pm Fix, the most important benchmark in FX markets, using a unique dataset of trader identified order book data from an inter- dealer venue. We propose and examine new measures of benchmark quality and examine changes to market liquidity and trader behaviour. Benchmark quality, measured as price efficiency and robustness, improves after the lengthening of the fix window to 5 minutes, but comes at the cost of a significant increase in tracking error for users of the benchmark. We also find that quoted spreads and price impact increase following the window lengthening, with HFTs trading more aggressively during the fix.
    Keywords: Foreign Exchange, Trading, Fix Benchmark
    JEL: F3 F4 G1
    Date: 2018–10–23
  3. By: Milla M\"akinen; Juho Kanniainen; Moncef Gabbouj; Alexandros Iosifidis
    Abstract: The existing literature provides evidence that limit order book data can be used to predict short-term price movements in stock markets. This paper proposes a new neural network architecture for predicting return jump arrivals in equity markets with high-frequency limit order book data. This new architecture, based on Convolutional Long Short-Term Memory with Attention, is introduced to apply time series representation learning with memory and to focus the prediction attention on the most important features to improve performance. The data set consists of order book data on five liquid U.S. stocks. The use of the attention mechanism makes it possible to analyze the importance of the inclusion limit order book data and other input variables. By using this mechanism, we provide evidence that the use of limit order book data was found to improve the performance of the proposed model in jump prediction, either clearly or marginally, depending on the underlying stock. This suggests that path-dependence in limit order book markets is a stock specific feature. Moreover, we find that the proposed approach with an attention mechanism outperforms the multi-layer perceptron network as well as the convolutional neural network and Long Short-Term memory model.
    Date: 2018–10
  4. By: Jacopo Staccioli (Scuola Superiore Sant'Anna); Mauro Napoletano (Observatoire français des conjonctures économiques)
    Abstract: We build an agent-based model of a financial market that is able to jointly reproduce many of the stylized facts at different time-scales. These include properties related to returns (leptokurtosis, absence of linear autocorrelation, volatility clustering), trading volumes (volume clustering, correlation between volume and volatility), and timing of trades (number of price changes, autocorrelation of durations between subsequent trades, heavy tail in their distribution, order-side clustering). With respect to previous contributions we introduce a strict event scheduling borrowed from the EURONEXT exchange, and an endogenous rule for traders participation. We show that such a rule is crucial to match stylized facts.
    Keywords: Intra-day financial dynamics; Stylized facts; Agent-based artificial stock markets; Market microstructure; High frequency trading
    JEL: C63 E12 E22 E32 O4
    Date: 2018–10
  5. By: Julio A. Crego (Tilburg University); Jin Huang (New York University Shanghai)
    Abstract: This paper studies learning in the stock market. Our contribution is to propose a model to illustrate the endogenous timing decision on trading, taking into account the incentive of learning from others about the fundamental value. The model is similar to Easley and O’Hara (1992), except that we introduce less-informed traders whose private information is inferior to fully-informed traders, but superior to that of random noise traders, and a zero-profit market maker. We also allow both types of informed traders to optimize timing of trading. We show that fully-informed traders act as early birds because it is optimal for them to buy or sell at the earliest possible time; meanwhile, less-informed traders could be better off as second mice by delaying transactions to learn from previous trades. The greater information asymmetry between the less-informed traders and the market maker, the larger profits the former could make even though the latter is learning from all trades.
    Keywords: Market microstructure, insider trading, learning, strategic timing.
    JEL: D83 G12 G14
    Date: 2017–11
  6. By: Juho Kanniainen; Martin Magris
    Abstract: In informationally efficient financial markets, option prices and this implied volatility should immediately be adjusted to new information that arrives along with a jump in underlying's return, whereas gradual changes in implied volatility would indicate market inefficiency. Using minute-by-minute data on S&P 500 index options, we provide evidence regarding delayed and gradual movements in implied volatility after the arrival of return jumps. These movements are directed and persistent, especially in the case of negative return jumps. Our results are significant when the implied volatilities are extracted from at-the-money options and out-of-the-money puts, while the implied volatility obtained from out-of-the-money calls converges to its new level immediately rather than gradually. Thus, our analysis reveals that the implied volatility smile is adjusted to jumps in underlying's return asymmetrically. Finally, it would be possible to have statistical arbitrage in zero-transaction-cost option markets, but under actual option price spreads, our results do not imply abnormal option returns.
    Date: 2018–10
  7. By: Julio A. Crego (Tilburg University)
    Abstract: Since September 2008 regulators from different countries, motivated by suspicions regarding an increase in investors' aggressiveness, have implemented several temporary short selling restrictions. In this paper, I study the effect of such policies in the context of the 2012 Spanish short selling ban. The results of this paper highlight an important policy trade-off: on the one hand, I provide evidence that, in line with regulator beliefs, investor aggressiveness is extremely high prior to the ban and, it reverts just after the ban implementation. On the other hand, using a novel identification strategy, I find that this policy increases the bid-ask spread. The causal interpretation of these results is obtained using intraday data under the assumption that the exact time of the implementation is random. The results obtained under this methodology are much smaller than the ones found in previous literature.
    Keywords: Short selling, market quality, Hawkes process, aggressiveness.
    JEL: G14 G18 C58
    Date: 2017–11

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