nep-mst New Economics Papers
on Market Microstructure
Issue of 2017‒10‒29
five papers chosen by
Thanos Verousis
University of Newcastle

  1. Profitability of simple stationary technical trading rules with high-frequency data of Chinese Index Futures By Jing-Chao Chen; Yu Zhou; Xi Wang
  2. Activism, Strategic Trading, and Liquidity By Back, Kerry E.; Collin-Dufresne, Pierre; Fos, Vyacheslav; Li, Tao; Ljungqvist, Alexander P.
  3. Sure Profits via Flash Strategies and the Impossibility of Predictable Jumps By Claudio Fontana; Markus Pelger; Eckhard Platen
  4. Taking Orders and Taking Notes: Dealer Information Sharing in Treasury Markets By Laura Veldkamp; David Lucca; Nina Boyarchenko
  5. Measuring inflation expectations uncertainty using high-frequency data By Joshua C C Chan; Yong Song

  1. By: Jing-Chao Chen; Yu Zhou; Xi Wang
    Abstract: Technical trading rules have been widely used by practitioners in financial markets for a long time. The profitability remains controversial and few consider the stationarity of technical indicators used in trading rules. We convert MA, KDJ and Bollinger bands into stationary processes and investigate the profitability of these trading rules by using 3 high-frequency data(15s,30s and 60s) of CSI300 Stock Index Futures from January 4th 2012 to December 31st 2016. Several performance and risk measures are adopted to assess the practical value of all trading rules directly while ADF-test is used to verify the stationarity and SPA test to check whether trading rules perform well due to intrinsic superiority or pure luck. The results show that there are several significant combinations of parameters for each indicator when transaction costs are not taken into consideration. Once transaction costs are included, trading profits will be eliminated completely. We also propose a method to reduce the risk of technical trading rules.
    Date: 2017–10
  2. By: Back, Kerry E.; Collin-Dufresne, Pierre; Fos, Vyacheslav; Li, Tao; Ljungqvist, Alexander P.
    Abstract: We analyze dynamic trading by an activist investor who can expend costly effort to affect firm value. We obtain the equilibrium in closed form for a general activism technology, including both binary and continuous outcomes. Variation in parameters can produce either positive or negative relations between market liquidity and economic efficiency, depending on the activism technology and model parameters. Two results that contrast with the previous literature are that (a) the relation between market liquidity and economic efficiency is independent of the activist's initial stake for a broad set of activism technologies and (b) an increase in noise trading can reduce market liquidity, because it increases uncertainty about the activist's trades (the activist trades in the opposite direction of noise traders) and thereby increases information asymmetry about the activist's intentions.
    Keywords: activism; continuous time; economic efficiency; Kyle model; liquidity; market depth; price impact; strategic trading
    JEL: G14 G34
    Date: 2017–10
  3. By: Claudio Fontana (Laboratoire de Probabilites et Modeles Aleatoires, Paris Diderot University); Markus Pelger (Management Science and Engineering Department, Stanford University); Eckhard Platen (Finance Discipline Group, UTS Business School, University of Technology, Sydney)
    Abstract: In an arbitrage-free financial market, asset prices should not exhibit jumps of a predictable magnitude at predictable times. We provide a rigorous formulation of this result in a fully general setting, only allowing for buy-and-hold positions and without imposing any semimartingale restriction. We show that asset prices do not exhibit predictable jumps if and only if there is no possibility of obtaining sure profits via high-frequency limits of buy-and-hold trading strategies. Our results imply that, under minimal assumptions, price changes occurring at scheduled dates should only be due to unanticipated information releases.
    Keywords: Absence of arbitrage; predictable time; semimartingale; high-frequency trading
    JEL: C02 G12 G14
    Date: 2017–08–01
  4. By: Laura Veldkamp (New York University); David Lucca (Federal Reserve Bank of New York); Nina Boyarchenko (Federal Reserve Bank of New York)
    Abstract: The use of order flow information by financial firms has come to the forefront of the regulatory debate. A central question is: Should a dealer who acquires information by taking client orders be allowed to use or share that information? We explore how information sharing affects dealers, clients and issuer revenues in U.S. Treasury auctions. Because one cannot observe alternative information regimes, we build a model, calibrate it to auction results data, and use it to quantify counter-factuals. We estimate that yearly auction revenues with full-information sharing (with clients and between dealers) would be $5 billion higher than in a ``Chinese Wall'' regime in which no information is shared. When information sharing enables collusion, the collusion costs revenue, but prohibiting information sharing costs more. For investors, the welfare effects of information sharing depend on how information is shared. Surprisingly, investors benefit when dealers share information with each other, not when they share more with clients. For the market, when investors can bid directly, information sharing creates a new financial accelerator: Only investors with bad news bid through intermediaries, who then share that information with others. Thus, sharing amplifies the effect of negative news. Tests of two model predictions support its key features.
    Date: 2017
  5. By: Joshua C C Chan; Yong Song
    Abstract: Inflation expectations play a key role in determining future economic outcomes. The associated uncertainty provides a direct gauge of how well-anchored the inflation expectations are. We construct a model-based measure of inflation expectations uncertainty by augmenting a standard unobserved components model of inflation with information from noisy and possibly biased measures of inflation expectations obtained from financial markets. This new model-based measure of inflation expectations uncertainty is more accurately estimated and can provide valuable information for policymakers. Using US data, we find significant changes in inflation expectations uncertainty during the Great Recession.
    Keywords: Trend inflation, inflation expectations, stochastic volatility
    JEL: C11 C32 E31
    Date: 2017–10

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.