nep-mst New Economics Papers
on Market Microstructure
Issue of 2020‒04‒06
five papers chosen by
Thanos Verousis
University of Essex

  1. Algorithmic trading in a microstructural limit order book model By Frédéric Abergel; Côme Huré; Huyên Pham
  2. High-frequency trading during flash crashes: Walk of fame or hall of shame? By Bellia, Mario; Christensen, Kim; Kolokolov, Aleksey; Pelizzon, Loriana; Renò, Roberto
  3. A closed-form solution for optimal mean-reverting trading strategies By Alexander Lipton; Marcos Lopez de Prado
  4. Retaining Alpha: The Effect of Trade Size and Rebalancing Frequency on FX Strategy Returns By Michael Melvin; Wenqiang Pan; Petra Wikstrom
  5. Centralized vs decentralized markets in the laboratory: The role of connectivity By Alfarano, Simone; Banal-Estanol, Albert; Camacho-Cuena, Eva; Iori, Giulia; Kapar, Burcu

  1. By: Frédéric Abergel (MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec); Côme Huré (LPSM (UMR_8001) - Laboratoire de Probabilités, Statistique et Modélisation - UPD7 - Université Paris Diderot - Paris 7 - SU - Sorbonne Université - CNRS - Centre National de la Recherche Scientifique); Huyên Pham (LPSM (UMR_8001) - Laboratoire de Probabilités, Statistique et Modélisation - UPD7 - Université Paris Diderot - Paris 7 - SU - Sorbonne Université - CNRS - Centre National de la Recherche Scientifique)
    Abstract: We propose a microstructural modeling framework for studying optimal market making policies in a FIFO (first in first out) limit order book (LOB). In this context, the limit orders, market orders, and cancel orders arrivals in the LOB are modeled as Cox point processes with intensities that only depend on the state of the LOB. These are high-dimensional models which are realistic from a micro-structure point of view and have been recently developed in the literature. In this context, we consider a market maker who stands ready to buy and sell stock on a regular and continuous basis at a publicly quoted price, and identifies the strategies that maximize her P&L penalized by her inventory. We apply the theory of Markov Decision Processes and dynamic programming method to characterize analytically the solutions to our optimal market making problem. The second part of the paper deals with the numerical aspect of the high-dimensional trading problem. We use a control randomization method combined with quantization method to compute the optimal strategies. Several computational tests are performed on simulated data to illustrate the efficiency of the computed optimal strategy. In particular, we simulated an order book with constant/ symmet-ric/ asymmetrical/ state dependent intensities, and compared the computed optimal strategy with naive strategies. Some codes are available on
    Keywords: high-dimensional stochastic control,quantization,local regression,Hawkes Process,pure-jump controlled process,Limit order book,Markov Decision Process,high-frequency trading
    Date: 2020
  2. By: Bellia, Mario; Christensen, Kim; Kolokolov, Aleksey; Pelizzon, Loriana; Renò, Roberto
    Abstract: We show that High Frequency Traders (HFTs) are not beneficial to the stock market during flash crashes. They actually consume liquidity when it is most needed, even when they are rewarded by the exchange to provide immediacy. The behavior of HFTs exacerbate the transient price impact, unrelated to fundamentals, typically observed during a flash crash. Slow traders provide liquidity instead of HFTs, taking advantage of the discounted price. We thus uncover a trade-o. between the greater liquidity and efficiency provided by HFTs in normal times, and the disruptive consequences of their trading activity during distressed times.
    Keywords: flash crashes,high-frequency traders (HFTs),liquidity provision,marketmaking
    JEL: G10 G14
    Date: 2020
  3. By: Alexander Lipton; Marcos Lopez de Prado
    Abstract: When prices reflect all available information, they oscillate around an equilibrium level. This oscillation is the result of the temporary market impact caused by waves of buyers and sellers. This price behavior can be approximated through an Ornstein-Uhlenbeck (O-U) process. Market makers provide liquidity in an attempt to monetize this oscillation. They enter a long position when a security is priced below its estimated equilibrium level, and they enter a short position when a security is priced above its estimated equilibrium level. They hold that position until one of three outcomes occur: (1) they achieve the targeted profit; (2) they experience a maximum tolerated loss; (3) the position is held beyond a maximum tolerated horizon. All market makers are confronted with the problem of defining profit-taking and stop-out levels. More generally, all execution traders acting on behalf of a client must determine at what levels an order must be fulfilled. Those optimal levels can be determined by maximizing the trader's Sharpe ratio in the context of O-U processes via Monte Carlo experiments. This paper develops an analytical framework and derives those optimal levels by using the method of heat potentials.
    Date: 2020–03
  4. By: Michael Melvin; Wenqiang Pan; Petra Wikstrom
    Abstract: The literature on currency investing that incorporates transaction costs uses costs relevant for small trade sizes. Using the entire order book of the major electronic brokerages for FX, we compute sweep-to-fill costs for trades of different sizes and illustrate the reduction in post-cost returns as trade size increases. Researchers should consider trade size and frequency to create realistic forecasts of post-tcost returns to gauge the capacity of a strategy. We show how incorporating tcosts in the construction of a portfolio improves performance for both high and low frequency strategies and retains a larger portion of the alpha.
    Keywords: transaction costs, FX microstructure, exchange rates, portfolio construction
    JEL: G15 F31
    Date: 2020
  5. By: Alfarano, Simone; Banal-Estanol, Albert; Camacho-Cuena, Eva; Iori, Giulia; Kapar, Burcu
    Abstract: This paper compares the performance of centralized and decentralized markets experimentally. We constrain trading exchanges to happen on an exogenously predetermined network, representing the trading relationships in markets with differing levels of connectivity. Our experimental results show that, despite having lower trading volumes, decentralized markets are not necessarily less efficient. Although information can propagate quicker through highly connected markets, we show that higher connectivity also induces informed traders to trade faster and exploit further their information advantages before the information becomes fully incorporated into prices. This not only reduces market efficiency, but it also increases wealth inequality. We show that, in more connected markets, informed traders trade not only relatively quicker, but also more, in the right direction, despite not doing it at better prices.
    Keywords: Experiments, financial markets, diffusion of information, decentralized trading.
    JEL: C92 D82 G14
    Date: 2020–02

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