nep-mst New Economics Papers
on Market Microstructure
Issue of 2015‒08‒30
five papers chosen by
Thanos Verousis

  1. Financial Knudsen number: breakdown of continuous price dynamics and asymmetric buy and sell structures confirmed by high precision order book information By Yoshihiro Yura; Hideki Takayasu; Didier Sornette; Misako Takayasu
  2. Do We Need Ultra-High Frequency Data to Forecast Variances? By Georgiana-Denisa Banulescu; Bertrand Candelon; Christophe Hurlin; Sébastien Laurent
  3. The liquidity premium in CDS transaction prices: Do frictions matter? By Gehde-Trapp, Monika; Gündüz, Yalin; Nasev, Julia
  4. Law on the Market? Evaluating the Securities Market Impact of Supreme Court Decisions By Daniel Martin Katz; Michael J Bommarito II; Tyler Soellinger; James Ming Chen
  5. Something in the Air: Information Density, News Surprises, and Price Jumps By Fuess, Roland; Grabellus, Markus; Mager, Ferdinand; Stein, Michael

  1. By: Yoshihiro Yura; Hideki Takayasu; Didier Sornette; Misako Takayasu
    Abstract: We generalise the description of the dynamics of the order book of financial markets in terms of a Brownian particle embedded in a fluid of incoming, exiting and annihilating particles by presenting a model of the velocity on each side (buy and sell) independently. The improved model builds on the time-averaged number of particles in the inner layer and its change per unit time, where the inner layer is revealed by the correlations between price velocity and change in the number of particles (limit orders). This allows us to introduce the Knudsen number of the financial Brownian particle motion and its asymmetric version (on the buy and sell sides). Not being considered previously, the asymmetric Knudsen numbers are crucial in finance in order to detect asymmetric price changes. The Knudsen numbers allows us to characterise the conditions for the market dynamics to be correctly described by a continuous stochastic process. Not questioned until now for large liquid markets such as the USD/JPY and EUR/USD exchange rates, we show that there are regimes when the Knudsen numbers are so high that discrete particle effects dominate, such as during market stresses and crashes. We document the presence of imbalances of particles depletion rates on the buy and sell sides that are associated with high Knudsen numbers and violent directional price changes. This indicator can detect the direction of the price motion at the early stage while the usual volatility risk measure is blind to the price direction.
    Date: 2015–08
  2. By: Georgiana-Denisa Banulescu (Maastricht University - univ. Maastricht, LEO - Laboratoire d'économie d'Orleans - UO - Université d'Orléans - CNRS); Bertrand Candelon (Maastricht University - univ. Maastricht); Christophe Hurlin (LEO - Laboratoire d'économie d'Orleans - UO - Université d'Orléans - CNRS); Sébastien Laurent (AMU IAE - Institut d'Administration des Entreprises (IAE) - Aix-en-Provence - AMU - Aix-Marseille Université)
    Abstract: In this paper we study various MIDAS models in which the future daily variance is directly related to past observations of intraday predictors. Our goal is to determine if there exists an optimal sampling frequency in terms of volatility prediction. Via Monte Carlo simulations we show that in a world without microstructure noise, the best model is the one using the highest available frequency for the predictors. However, in the presence of microstructure noise, the use of ultra high-frequency predictors may be problematic, leading to poor volatility forecasts. In the application, we consider two highly liquid assets (i.e., Microsoft and S&P 500). We show that, when using raw intraday squared log-returns for the explanatory variable, there is a "high-frequency wall" or frequency limit above which MIDAS-RV forecasts deteriorate. We also show that an improvement can be obtained when using intraday squared log-returns sampled at a higher frequency, provided they are pre-filtered to account for the presence of jumps, intraday periodicity and/or microstructure noise. Finally, we compare the MIDAS model to other competing variance models including GARCH, GAS, HAR-RV and HAR-RV-J models. We find that the MIDAS model provides equivalent or even better variance forecasts than these models, when it is applied on filtered data.
    Date: 2014–10–26
  3. By: Gehde-Trapp, Monika; Gündüz, Yalin; Nasev, Julia
    Abstract: Based on individual CDS transactions cleared by the Depository Trust & Clearing Corporation, we show that illiquidity strongly affects credit default swap premiums. We identify the following effects: First, transaction direction affects prices, as buy (sell) orders lead to premium increases (decreases). Second, larger transactions have a higher price impact. This finding stands in stark contrast to corporate bond markets. Third, traders charge higher premiums as a price for liquidity provision, not as compensation for asymmetric information. Fourth, buyside investors pay significantly higher prices than dealers for demanding liquidity. Last, inventory risk seems to matter little in explaining liquidity premiums.
    Keywords: CDS,illiquidity,temporary price impact,market power,immediacy,DTCC
    JEL: G12 G14
    Date: 2015
  4. By: Daniel Martin Katz; Michael J Bommarito II; Tyler Soellinger; James Ming Chen
    Abstract: Do judicial decisions affect the securities markets in discernible and perhaps predictable ways? In other words, is there "law on the market" (LOTM)? This is a question that has been raised by commentators, but answered by very few in a systematic and financially rigorous manner. Using intraday data and a multiday event window, this large scale event study seeks to determine the existence, frequency and magnitude of equity market impacts flowing from Supreme Court decisions. We demonstrate that, while certainly not present in every case, "law on the market" events are fairly common. Across all cases decided by the Supreme Court of the United States between the 1999-2013 terms, we identify 79 cases where the share price of one or more publicly traded company moved in direct response to a Supreme Court decision. In the aggregate, over fifteen years, Supreme Court decisions were responsible for more than 140 billion dollars in absolute changes in wealth. Our analysis not only contributes to our understanding of the political economy of judicial decision making, but also links to the broader set of research exploring the performance in financial markets using event study methods. We conclude by exploring the informational efficiency of law as a market by highlighting the speed at which information from Supreme Court decisions is assimilated by the market. Relatively speaking, LOTM events have historically exhibited slow rates of information incorporation for affected securities. This implies a market ripe for arbitrage where an event-based trading strategy could be successful.
    Date: 2015–08
  5. By: Fuess, Roland; Grabellus, Markus; Mager, Ferdinand; Stein, Michael
    Abstract: This paper introduces a new information density indicator to provide a more comprehensive understanding of price reactions to news and, more specifically, to the sources of jumps in financial markets. Our information density indicator, which measures the abnormal amount of noisy “ticker” news before scheduled macroeconomic announcements, is significantly related to the likelihood of price jumps and independent of the magnitude of news surprises or pre-announcement trading activity. We therefore interpret this variable as a measure of additional uncertainty in the market, which is resolved by macroeconomic news as “hard” facts.
    Keywords: Information density; jump identification; macroeconomic announcements; noisy information; price discovery process
    JEL: C58 F31 G12 G14 G15
    Date: 2015–08

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