nep-mst New Economics Papers
on Market Microstructure
Issue of 2018‒11‒26
five papers chosen by
Thanos Verousis

  1. FX Trading and Exchange Rate Disconnect Puzzle By Martin D. D. Evans
  2. The Bias of Realized Volatility By Becker, Janis; Leschinski, Christian
  3. Algorithmic Trading, What if It is Just an Illusion? Evidence from Experimental Financial Markets By Sandrine Jacob Leal; Nobuyuki Hanaki
  4. Dealer behaviour in the Euro money market during times of crisis By Fecht, Falko; Reitz, Stefan
  5. How does information disclosure affect liquidity? Evidence from an Emerging Market By Diego A. Agudelo; Ignacio Arango

  1. By: Martin D. D. Evans (Department of Economics, Georgetown University)
    Abstract: This paper examines how trading in the FX market carries the information that drives movements in currency prices over minutes, days and weeks; and now those movements are connected to interest rates. The paper first presents a model of FX trading in a Limit Order Book (LOB) that identifies how information from outside the market is reflected in FX prices and trading patterns. I then empirically examine this transmission process with the aid of a structural VAR estimated on 13 years of LOB trading data for the EURUSD, the world's most heavily traded currency pair. The VAR estimates reveal several new findings: first, they show that shocks from outside the LOB affect FX prices through both liquidity and information channel; and that the importance of these channels varies according to the source of the shock. Liquidity effects on FX prices are temporary, lasting between two and ten minutes, while information effects of shocks on prices are permanent. Second, the contemporaneous correlation between price changes and order flows varies across the shocks. Some shocks produce a positive correlation (as in standard trading models), while others produce a negative correlation. Third, the model estimates imply that intraday variations in FX prices are overwhelmingly driven by one type of shock, it accounts for 87% of hour-by-hour changes in the FX prices. The second part of the paper examines the connection between the shocks in the trading model and the macroeconomy. For this purpose, I use the VAR estimates to decompose intraday FX price changes and order flows into separate components driven by different shocks. I then aggregate these components into daily and weekly series. I find that one component of daily order flow is strongly correlated with changes in the long-term interest differentials between US and EUR rates. This suggests that the intraday shocks driving this order flow component carry news about future short-term interest rates which is embedded into FX prices. I find that intraday shocks carrying interest-rate information account for on average 56% of the variance in daily EURUSD depreciation rate between 2003 and 2015, but their variance contributions before 2007 and after 2011 are over 80%. These findings indicate that the EURUSD depreciation rate is relatively well-connected to macro fundamentals via a particular component of order flow. Finally, I show that flows embedding liquidity risk have forecasting power for daily and weekly EURUSD depreciation rates.
    Keywords: Foreign Exchange Trading, Microstructure, Order Flow, Exchange-Rate Determination
    JEL: F31 F32 F34
    Date: 2018–11–05
  2. By: Becker, Janis; Leschinski, Christian
    Abstract: Realized volatility underestimates the variance of daily stock index returns by an average of 14 percent. This is documented for a wide range of international stock indices, using the fact that the average of realized volatility and that of squared returns should be the same over longer time horizons. It is shown that the magnitude of this bias cannot be explained by market microstructure noise. Instead, it can be attributed to correlation between the continuous components of intraday returns and correlation between jumps and previous/subsequent continuous price movements.
    Keywords: Return Volatility; Realized Volatility; Squared Returns
    JEL: G11 G12 G17
    Date: 2018–11
  3. By: Sandrine Jacob Leal (ICN Business School, France; Université de Lorraine; CEREFIGE); Nobuyuki Hanaki (Université Côte d'Azur; CNRS, GREDEG; IUF)
    Abstract: This work investigates whether the perception of algorithmic trading (AT) and their potential presence in financial markets by human traders change their price forecasts, trading activities, and ultimately market dynamics. We consider two different types of trading strategies commonly employed by high-frequency traders, layering/spoofing and market making. The former has been associated with market manipulation, and the latter is often seen as providing liquidity to markets. We run artificial trading experiments to examine the effect of their potential presence. From these experiments, we find that (1) the potential presence of AT induces larger initial price forecasts deviations from the fundamental value, (2) the differences in perception of AT have an impact on subjects' initial bids, and (3) the potential presence of AT seems to slow down the convergence of market prices to fundamental value.
    Keywords: Market volatility, Market efficiency, Computer traders, Experiments, Asset markets
    JEL: C90 G14 D84 G01
    Date: 2018–11
  4. By: Fecht, Falko; Reitz, Stefan
    Abstract: This article shows how the recent money market disruptions with elevated counterparty risks and uncertainty about the fundamental value of liquidity influenced the trading behaviour of a key dealer in the Euro money market. The complete trading record in the unsecured segment of the money market for 2007 and 2008 is used to estimate a stylized pricing model, which explicitly accounts for the over-the-counter structure. The empirical results suggest that the market maker learns from order flow, but this information aggregation was increasingly hampered as the crisis unfolded.
    Keywords: Euro money market,financial crisis,market microstructure,pricing behaviour
    JEL: E43 G15 C32
    Date: 2018
  5. By: Diego A. Agudelo; Ignacio Arango
    Abstract: Cross-sectional models positively relate firm information disclosure with stock liquidity, but dynamic models in news releases days show an opposite relation. We address this puzzle by studying the effects of information arrival on liquidity and its determinants. We use trade and quote data from Colombia for 2015 and 2016, along with the complete database of news releases as reported by companies to the regulator. The results of Panel data and PVAR models suggest that news releases increase both informed and uninformed trading. All in all, the temporal negative effect of news releases on liquidity is explained by increasing asymmetric information.
    Keywords: Liquidity, Asymmetric Information, Informed Trading, News releases, Emerging Markets.
    JEL: G10 G15 G19
    Date: 2017–12–10

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.
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.