nep-mst New Economics Papers
on Market Microstructure
Issue of 2015‒09‒05
seven papers chosen by
Thanos Verousis

  1. Endogenous Formation of Limit Order Books: the Effects of Trading Frequency By Roman Gayduk; Sergey Nadtochiy
  2. Tick Size: Theory and Evidence By Werner, Ingrid M.; Wen, Yuanji; Rindi, Barbara; Consonni, Francesco; Buti, Sabrina
  3. Designating market maker behaviour in Limit Order Book markets By Efstathios Panayi; Gareth W. Peters; Jon Danielsson; Jean-Pierre Zigrand
  4. A reduced-form model for level-1 limit order books By Tzu-Wei Yang; Lingjiong Zhu
  5. Time-dependent scaling patterns in high frequency financial data By Noemi Nava; Tiziana Di Matteo; Tomaso Aste
  6. Return patterns of South Korean stocks following large price shocks By Kolaric, S.; Kiesel, F.; Schiereck, D.
  7. Forecasting stock market returns over multiple time horizons By Kroujiline, Dimitri; Gusev, Maxim; Ushanov, Dmitry; Sharov, Sergey V.; Govorkov, Boris

  1. By: Roman Gayduk; Sergey Nadtochiy
    Abstract: In this work, we present a modeling framework in which the shape and dynamics of a Limit Order Book (LOB) arise endogenously from an equilibrium between multiple market participants (agents). On the one hand, the new framework captures very closely the true, micro-level, mechanics of an auction-style exchange. On the other hand, it uses the standard abstractions of games with continuum of players (in particular, the mean field game theory) to obtain a tractable macro-level description of the LOB. We use the proposed modeling framework to analyze the effects of trading frequency on the liquidity of the market in a very general setting. In particular, we show that the higher trading frequency increases market efficiency if the agents choose to provide liquidity in equilibrium. However, we also show that the higher trading frequency makes markets more fragile, in the following sense: in a high-frequency trading regime, the agents choose to provide liquidity in equilibrium if and only if they are market-neutral (i.e. their beliefs satisfy certain martingale property). The theoretical results are illustrated with numerical examples.
    Date: 2015–08
  2. By: Werner, Ingrid M. (OH State University); Wen, Yuanji (University of Western Australia); Rindi, Barbara (Bocconi University); Consonni, Francesco (Bocconi University); Buti, Sabrina (University of Toronto)
    Abstract: We model a public limit order book where rational traders decide whether to demand or supply liquidity, and where liquidity builds endogenously. The model predicts that a reduction of the tick size will cause spreads and welfare to deteriorate for illiquid but improve for liquid books. We find empirical support for these predictions based on European and U.S. data. The model also generates predictions for volume, but we find less empirical support for these predictions which we attribute to opportunistic High-Frequency-Traders selectively entering the market.
    JEL: G10 G12 G14 G18 G20
    Date: 2015–03
  3. By: Efstathios Panayi; Gareth W. Peters; Jon Danielsson; Jean-Pierre Zigrand
    Abstract: Financial exchanges provide incentives for limit order book (LOB) liquidity provision to certain market participants, termed designated market makers or designated sponsors. While quoting requirements typically enforce the activity of these participants for a certain portion of the day, we argue that liquidity demand throughout the trading day is far from uniformly distributed, and thus this liquidity provision may not be calibrated to the demand. We propose that quoting obligations also include requirements about the speed of liquidity replenishment, and we recommend use of the Threshold Exceedance Duration (TED) for this purpose. We present a comprehensive regression modelling approach using GLM and GAMLSS models to relate the TED to the state of the LOB and identify the regression structures that are best suited to modelling the TED. Such an approach can be used by exchanges to set target levels of liquidity replenishment for designated market makers.
    Date: 2015–08
  4. By: Tzu-Wei Yang; Lingjiong Zhu
    Abstract: One popular approach to model the limit order books dynamics of the best bid and ask at level-1 is to use the reduced-form diffusion approximations. It is well known that the biggest contributing factor to the price movement is the imbalance of the best bid and ask. We investigate the data of the level-1 limit order books of a basket of stocks and study the numerical evidence of drift, correlation, volatility and their dependence on the imbalance. Based on the numerical discoveries, we develop a nonparametric reduced-form model with analytical tractability that is self-consistent with the data.
    Date: 2015–08
  5. By: Noemi Nava; Tiziana Di Matteo; Tomaso Aste
    Abstract: We measure the influence of different time-scales on the dynamics of financial market data. This is obtained by decomposing financial time series into simple oscillations associated with distinct time-scales. We propose two new time-varying measures: 1) an amplitude scaling exponent and 2) an entropy like measure. We apply these measures to intra-day, 30-second sampled prices of various stock indices. Our results reveal intra-day trends where different time-horizons contribute with variable relative amplitudes over the course of the trading day. Our findings indicate that the time series we analysed have a non-stationary multi-fractional nature with predominantly persistent behaviour at the middle of the trading session and anti-persistent behaviour at the open and close. We demonstrate that these deviations are statistically significant and robust.
    Date: 2015–08
  6. By: Kolaric, S.; Kiesel, F.; Schiereck, D.
    Abstract: This study tests the market efficiency of the South Korean stock market by examining returns on stocks of the constituents of the KOSPI 50 from 2000 to 2014 following large 1-month price decreases and increases. An exponential GARCH (EGARCH) event study framework is used to analyse the stock returns. The results show that large price shocks, positive and negative, are likely to be followed by positive market returns. Moreover, the results show an increase in the beta of stocks in the years following a large price shock. The overall results therefore support the Uncertain Information Hypothesis. However, beginning in 2008, return patterns more closely reflect those hypothesised by the Efficient Market Hypothesis, possibly due to increased participation by international investors. The observed returns following large price increases and decreases can be partially explained by changes in the Korean won to US dollar exchange rate and the trading behaviour of foreign investors.
    Date: 2015–08–27
  7. By: Kroujiline, Dimitri; Gusev, Maxim; Ushanov, Dmitry; Sharov, Sergey V.; Govorkov, Boris
    Abstract: In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we further develop the news-driven analytic model of the stock market derived in Gusev et al. (2015). This enables us to capture market dynamics at various timescales and shed light on mechanisms underlying certain market behaviors such as transitions between bull- and bear markets and the self-similar behavior of price changes. We investigate the model and show that the market is nearly efficient on timescales shorter than one day, adjusting quickly to incoming news, but is inefficient on longer timescales, where news may have a long-lasting nonlinear impact on dynamics attributable to a feedback mechanism acting over these horizons. Using the model, we design the prototypes of algorithmic strategies that utilize news flow, quantified and measured, as the only input to trade on market return forecasts over multiple horizons, from days to months. The backtested results suggest that the return is predictable to the extent that successful trading strategies can be constructed to harness this predictability.
    Keywords: stock market dynamics, return predictability, price feedback, market efficiency, news analytics, sentiment evolution, agent-based modeling, Ising, dynamical systems, synchronization, self-similar behavior, regime transitions, news-based strategies, algorithmic trading
    JEL: G02 G12 G14 G17
    Date: 2015–08–18

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