nep-mst New Economics Papers
on Market Microstructure
Issue of 2017‒07‒16
six papers chosen by
Thanos Verousis

  1. Who supplies liquidity, how and when? By Biais, Bruno; Declerck, Fany; Moinas, Sophie
  2. Dark pools in European equity markets: emergence, competition and implications By Petrescu, Monica; Wedow, Michael
  3. Mean Reversion Trading with Sequential Deadlines andTransaction Costs By Yerkin Kitapbayev; Tim Leung
  4. Trading under Market Impact By Bielagk, Jana; Horst, Ulrich; Moreno-Bromberg, Santiago
  5. Seasonal long memory in intraday volatility and trading volume of Dow Jones stocks By Voges, Michelle; Leschinski, Christian; Sibbertsen, Philipp
  6. The one-trading-day-ahead forecast errors of intra-day realized volatility By Degiannakis, Stavros

  1. By: Biais, Bruno; Declerck, Fany; Moinas, Sophie
    Abstract: Who provides liquidity in modern, electronic limit order book, markets? While agency trading can be constrained by conflicts of interest and information asymmetry between customers and traders, prop traders are likely to be less constrained and thus better positioned to carry inventory risk. Moreover, while slow traders'limit orders may be exposed to severe adverse selection, fast trading technology can improve traders'ability to monitor the market and avoid being picked off. To shed light on these points, we rely on unique data from Euronext and the AMF enabling us to observe the connectivity of traders to the market, and whether they are proprietary traders. We find that proprietary traders, be they fast or slow, provide liquidity with contrarian marketable orders, thus helping the market absorb shocks, even during crisis, and earn profits doing so. Moreover, fast traders provide liquidity by leaving limit orders in the book. Yet, only prop traders can do so without making losses. This suggests that technology is not enough to overcome adverse selection, monitoring incentives are also needed.
    Keywords: Liquidity; high-frequency trading; proprietary trading; adverse selection; electronic limit order book; short-term momentum; contrarian.
    JEL: D82 G1
    Date: 2017–06
  2. By: Petrescu, Monica; Wedow, Michael
    Abstract: This paper considers the growth of dark pools: trading venues for equities without pre-trade transparency. It first documents the emergence and expansion of dark pools in European equity markets in the context of regulatory changes and increased high-frequency trading (HFT). It finds that the market share of trading conducted in dark pools has stabilised below 10% and is similar across groups of stocks from different countries. Second, this paper assesses the nature of competition between dark pools, which is based on price and services offered to clients. It documents a substantial degree of horizontal differentiation among European dark pools, with venues providing different options for placing and processing orders likely to attract different types of traders. The hypothesis that most dark pools are primarily used to shield large orders from information leakage is not supported by evidence. This finding is based on a simple indicator that assesses different dark pools in terms of the level of protection from information leakage due to trading with HFT or predatory traders. Finally, this paper evaluates the benefits and costs of the use of dark pools from the perspective of individual traders as well as for market efficiency and financial stability. Recent evidence appears to reject the notion that dark pools adversely affect volatility in stock markets. JEL Classification: G10, G14, G18
    Keywords: dark pools, equity markets, financial stability, liquidity, market microstructure
    Date: 2017–07
  3. By: Yerkin Kitapbayev; Tim Leung
    Abstract: We study the optimal timing strategies for trading a mean-reverting price process with afinite deadline to enter and a separate finite deadline to exit the market. The price process is modeled by a diffusion with an affine drift that encapsulates a number of well-known models,including the Ornstein-Uhlenbeck (OU) model, Cox-Ingersoll-Ross (CIR) model, Jacobi model,and inhomogeneous geometric Brownian motion (IGBM) model.We analyze three types of trading strategies: (i) the long-short (long to open, short to close) strategy; (ii) the short-long(short to open, long to close) strategy, and (iii) the chooser strategy whereby the trader has the added flexibility to enter the market by taking either a long or short position, and subsequently close the position. For each strategy, we solve an optimal double stopping problem with sequential deadlines, and determine the optimal timing of trades. Our solution methodology utilizes the local time-space calculus of Peskir (2005) to derive nonlinear integral equations of Volterra-type that uniquely characterize the trading boundaries. Numerical implementation ofthe integral equations provides examples of the optimal trading boundaries.
    Date: 2017–07
  4. By: Bielagk, Jana (Humboldt University Berlin); Horst, Ulrich (Humboldt University Berlin); Moreno-Bromberg, Santiago (University of Zurich)
    Abstract: We use a model with agency frictions to analyze the structure of a dealer market that faces competition from a crossing network. Traders are privately informed about their types (e.g. their portfolios), which is something the dealer must take into account when engaging his counterparties. Instead of participating in the dealer market, the traders may take their business to a crossing network. We show that the presence of such a network results in more trader types being serviced by the dealer and that, under certain conditions, the book\'s spread shrinks. We allow for the pricing on the dealer market to determine the structure of the crossing network and show that the same conditions that lead to a reduction of the spread imply the existence of an equilibrium book or crossing network pair.
    Keywords: asymmetric information; crossing networks; dealer markets; non-linear pricing; principal-agent games;
    JEL: D42 D53 G12 G14
    Date: 2017–07–01
  5. By: Voges, Michelle; Leschinski, Christian; Sibbertsen, Philipp
    Abstract: It is well known that intraday volatilities and trading volumes exhibit strong seasonal features. These seasonalities are usually modeled using dummy variables or deterministic functions. Here, we propose a test for seasonal long memory with a known frequency. Using this test, we show that deterministic seasonality is an accurate model for the DJIA index but not for the component stocks. These still exhibit significant and persistent periodicity after seasonal de-meaning so that more evolved seasonal long memory models are required to model their behavior.
    Keywords: Intraday Volatility; Trading Volume; Seasonality; Long Memory
    JEL: C12 C22 C58 G12 G15
    Date: 2017–06
  6. By: Degiannakis, Stavros
    Abstract: Two volatility forecasting evaluation measures are considered; the squared one-day-ahead forecast error and its standardized version. The mean squared forecast error is the widely accepted evaluation function for the realized volatility forecasting accuracy. Additionally, we explore the forecasting accuracy based on the squared distance of the forecast error standardized with its volatility. The statistical properties of the forecast errors point the standardized version as a more appropriate metric for evaluating volatility forecasts. We highlight the importance of standardizing the forecast errors with their volatility. The predictive accuracy of the models is investigated for the FTSE100, DAX30 and CAC40 European stock indices and the exchange rates of Euro to British Pound, US Dollar and Japanese Yen. Additionally, a trading strategy defined by the standardized forecast errors provides higher returns compared to the strategy based on the simple forecast errors. The exploration of forecast errors is paving the way for rethinking the evaluation of ultra-high frequency realized volatility models.
    Keywords: ARFIMA model, HAR model, intra-day data, predictive ability, realized volatility, ultra-high frequency modelling.
    JEL: C14 C32 C50 G11 G15
    Date: 2016–01

This nep-mst issue is ©2017 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.