nep-mst New Economics Papers
on Market Microstructure
Issue of 2015‒04‒19
seven papers chosen by
Thanos Verousis

  1. The Long Memory of Order Flow in the Foreign Exchange Spot Market By Martin D. Gould; Mason A. Porter; Sam D. Howison
  2. "The SIML Estimation of Integrated Covariance and Hedging Coefficient under Round-off Errors, Micro-market Price Adjustments and Random Sampling" By Naoto Kunitomo; Hiroumi Misaki; Seisho Sato
  3. Liquidity crises on different time scales By Francesco Corradi; Andrea Zaccaria; Luciano Pietronero
  4. First to “Read” the News: News Analytics and Institutional Trading By Keim, Donald B; Massa, Massimo; von Beschwitz, Bastian
  5. Fire Sales and Information Advantage: When Informed Investor Helps By Massa, Massimo; Zhang, Lei
  6. Are Fundamentals Enough? Explaining Price Variations in the German Day-Ahead and Intraday Power Market By Christian Pape; Christoph Weber
  7. What Are The Macroeconomic Effects of High-Frequency Uncertainty Shocks? By Laurent Ferrara; Pierre Guérin

  1. By: Martin D. Gould; Mason A. Porter; Sam D. Howison
    Abstract: We study the long memory of order flow for each of three liquid currency pairs on a large electronic trading platform in the foreign exchange (FX) spot market. Due to the extremely high levels of market activity on the platform, and in contrast to existing empirical studies of other markets, our data enables us to perform statistically stable estimation without needing to aggregate data from different trading days. We find strong evidence of long memory, with a Hurst exponent of approximately 0.7, for each of the three currency pairs and on each trading day in our sample. We repeat our calculations using data that spans different trading days, and we find no significant differences in our results. We test and reject the hypothesis that the apparent long memory of order flow is an artefact caused by structural breaks, in favour of the alternative hypothesis of true long memory. We therefore conclude that the long memory of order flow in the FX spot market is a robust empirical property that persists across daily boundaries.
    Date: 2015–04
  2. By: Naoto Kunitomo (Faculty of Economics, The University of Tokyo); Hiroumi Misaki (Research Center for Advanced Science and Technology, The University of Tokyo); Seisho Sato (Faculty of Economics, The University of Tokyo)
    Abstract: For estimating the integrated volatility and covariance by using high frequency data, Kunitomo and Sato (2011, 2013) have proposed the Separating Information Maximum Likelihood (SIML) method when there are micro-market noises. The SIML estimator has reasonable nite sample properties and asymptotic properties when the sample size is large when the hidden efficient price process follow a Brownian semi-martingale. We shall show that the SIML estimation is useful for estimating the integrated covariance and hedging coefficient when we have round-off errors, micro-market price adjustments, noises and high-frequency data are randomly sampled. The SIML estimation is consistent, asymptotically normal in the stable convergence sense under a set of reasonable assumptions and it has reasonable nite sample properties with these effects. --
    Date: 2015–03
  3. By: Francesco Corradi; Andrea Zaccaria; Luciano Pietronero
    Abstract: We present an empirical analysis of the microstructure of financial markets and, in particular, of the static and dynamic properties of liquidity. We find that on relatively large time scales (15 minutes) large price fluctuations are connected to the failure of the subtle mechanism of compensation between the flows of market and limit orders: in other words, the missed revelation of the latent order book breaks the dynamical equilibrium between the flows, triggering the large price jumps. On smaller time scales (30 seconds), instead, the static depletion of the limit order book is an indicator of an intrinsic fragility of the system, which is related to a strongly non linear enhancement of the response. In order to quantify this phenomenon we introduce a measure of the liquidity imbalance present in the book and we show that it is correlated to both the sign and the magnitude of the next price movement. These findings provide a quantitative definition of the effective liquidity, which results to be strongly dependent on the considered time scales.
    Date: 2015–04
  4. By: Keim, Donald B; Massa, Massimo; von Beschwitz, Bastian
    Abstract: We investigate whether providers of high frequency news analytics affect the stock market. As identification, we exploit a unique experiment based on differences in news event classifications between different product releases of a major provider of news analytics. We document a causal effect of news analytics on the market, irrespective of the informational content of the news. Coverage in news analytics speeds up the market reaction in terms of stock price response and trading volume, and increases illiquidity immediately after the article. Furthermore, we document that traders learn dynamically about the precision of news analytics.
    Keywords: Information; Institutional Trading; Stock Price Reaction; Textual Analysis
    JEL: G10 G12 G14
    Date: 2015–04
  5. By: Massa, Massimo; Zhang, Lei
    Abstract: We study the relation between information and fire sales during a crisis. We argue that the reinforcing effect of funding liquidity on market liquidity is weaker when investors have more information about the assets facing sudden price drops (Brunnermeier and Pedersen, 2009). We focus on the affiliation of international asset managers with banking conglomerates. We document that bank affiliation provides an informational advantage. We show that (informed) bank-affiliated foreign ownership before the crisis predicts higher stock liquidity, lower extreme negative return realizations, lower short-selling demand, lower comovement (R2) with the market and higher price informativeness during the crisis.
    Keywords: bank-affiliation; fire sales; global asset managers; international crisis; international liquidity.; transmission
    JEL: G10 G15 G21
    Date: 2015–04
  6. By: Christian Pape (Chair for Management Sciences and Energy Economics, University of Duisburg-Essen); Christoph Weber (Chair for Management Sciences and Energy Economics, University of Duisburg-Essen)
    Abstract: European electricity market participants are encouraged to balance intraday deviations from their day-ahead schedules via trades in the intraday market. Together with the increasing production of variable renewable energy sources, the intraday market is gaining importance. We investigate the explanatory power of a fundamental modeling approach explicitly accounting for must-run operations of combined heat and power plants (CHP) and intraday peculiarities such as a shortened intraday supply stack. The fundamental equilibria between every hour’s supply stack and aggregated demand in 2012 and 2013 are modeled to yield hourly price estimates. The major benefits of a fundamental modeling approach are the ability to account for non-linearities in the supply stack and the ability to combine time-varying information consistently. The empirical results show that fundamental modeling explains a considerable share of spot price variance. How-ever, differences between the fundamental and actual prices persist and are explored using regression models. The main differences can be attributed to (avoided) start up-costs, market states and trading behavior.
    Keywords: Intraday market for electricity, fundamental price modeling
    JEL: Q41
    Date: 2015–03
  7. By: Laurent Ferrara; Pierre Guérin
    Abstract: Following the Great Recession, econometric models that better account for un certainty have gained increased attention, and an increasing number of works evaluate the effects of uncertainty shocks. In this paper, we evaluate the impact of high-frequency uncertainty shocks on a set of low-frequency macroeconomic variables representative of the U.S. economy. Rather than estimating models at the same common low-frequency, we use recently developed econometric methodology that allows us to avoid aggregating high-frequency data before estimating models. The impulse response analysis uncovers various salient facts. First, in line with the existing literature, high-frequency uncertainty shocks are associated with a broad-based decline in economic activity. Second, we find that credit and labor market variables react the most to uncertainty shocks. Third, we show that the responses of macroeconomic variables to uncertainty shocks are relatively similar across single-frequency and mixed-frequency data models, suggesting that the temporal aggregation bias is not acute in this context. Finally, we find that some macroeconomic variables exhibit an asymmetric response to uncertainty shocks over the different phases of the business cycle.
    Keywords: MIDAS model, Mixed-frequency VAR, Uncertainty.
    JEL: E32 E44 C32
    Date: 2015

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