nep-mst New Economics Papers
on Market Microstructure
Issue of 2018‒07‒09
four papers chosen by
Thanos Verousis

  1. Heterogeneous Agent Models in Finance By Roberto Dieci; Xue-Zhong He
  2. Order-book modelling and market making strategies By Xiaofei Lu; Fr\'ed\'eric Abergel
  3. A Deep Learning Based Illegal Insider-Trading Detection and Prediction Technique in Stock Market By Sheikh Rabiul Islam
  4. Foreign Exchange Markets with Last Look By Alvaro Cartea; Sebastian Jaimungal; Jamie Walton

  1. By: Roberto Dieci (University of Bologna); Xue-Zhong He (Finance Discipline Group, UTS Business School, University of Technology Sydney)
    Abstract: This chapter surveys the state-of-art of heterogeneous agent models (HAMs) in finance using a jointly theoretical and empirical analysis, combined with numerical and Monte Carlo analysis from the latest development in computational finance. It provides supporting evidence on the explanatory power of HAMs to various stylized facts and market anomalies through model calibration, estimation, and economic mechanisms analysis. It presents a unified framework in continuous time to study the impact of historical price information on price dynamics, profitability and optimality of fundamental and momentum trading. It demonstrates how HAMs can help to understand stock price co-movements and to build evolutionary CAPM. It also introduces a new HAMs perspective on house price dynamics and an integrate approach to study dynamics of limit order markets. The survey provides further insights into the complexity and efficiency of financial markets and policy implications.
    Keywords: Heterogeneity; bounded rationality; heterogeneous agent-based models; stylized facts; asset pricing; housing bubbles; limit order markets; information efficiency; comovement
    Date: 2018–01–01
  2. By: Xiaofei Lu; Fr\'ed\'eric Abergel
    Abstract: Market making is one of the most important aspects of algorithmic trading, and it has been studied quite extensively from a theoretical point of view. The practical implementation of so-called "optimal strategies" however suffers from the failure of most order book models to faithfully reproduce the behaviour of real market participants. This paper is twofold. First, some important statistical properties of order driven markets are identified, advocating against the use of purely Markovian order book models. Then, market making strategies are designed and their performances are compared, based on simulation as well as backtesting. We find that incorporating some simple non-Markovian features in the limit order book greatly improves the performances of market making strategies in a realistic context.
    Date: 2018–06
  3. By: Sheikh Rabiul Islam
    Abstract: The stock market is a nonlinear, nonstationary, dynamic, and complex system. There are several factors that affect the stock market conditions, such as news, social media, expert opinion, political transitions, and natural disasters. In addition, the market must also be able to handle the situation of illegal insider trading, which impacts the integrity and value of stocks. Illegal insider trading occurs when trading is performed based on non-public (private, leaked, tipped) information (e.g., new product launch, quarterly financial report, acquisition or merger plan) before the information is made public. Preventing illegal insider trading is a priority of the regulatory authorities (e.g., SEC) as it involves billions of dollars, and is very difficult to detect. In this work, we present different types of insider trading approaches, techniques and our proposed approach for detecting and predicting insider trader using a deep-learning based approach combined with discrete signal processing on time series data.
    Date: 2018–07
  4. By: Alvaro Cartea; Sebastian Jaimungal; Jamie Walton
    Abstract: We examine the Foreign Exchange (FX) spot price spreads with and without Last Look on the transaction. We assume that brokers are risk-neutral and they quote spreads so that losses to latency arbitrageurs (LAs) are recovered from other traders in the FX market. These losses are reduced if the broker can reject, ex-post, loss-making trades by enforcing the Last Look option which is a feature of some trading venues in FX markets. For a given rejection threshold the risk-neutral broker quotes a spread to the market so that her expected profits are zero. When there is only one venue, we find that the Last Look option reduces quoted spreads. If there are two venues we show that the market reaches an equilibrium where traders have no incentive to migrate. The equilibrium can be reached with both venues coexisting, or with only one venue surviving. Moreover, when one venue enforces Last Look and the other one does not, counterintuitively, it may be the case that the Last Look venue quotes larger spreads.
    Date: 2018–06

This nep-mst issue is ©2018 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.
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