nep-mst New Economics Papers
on Market Microstructure
Issue of 2019‒01‒21
six papers chosen by
Thanos Verousis

  1. Optimal inventory management and order book modeling By Nicolas Baradel; Bruno Bouchard; David Evangelista; Othmane Mounjid
  2. Another law of small numbers: patterns of trading prices in experimental markets By Tristan Roger; Wael Bousselmi; Patrick Roger; Marc Willinger
  3. The Arrival of News and Return Jumps in Stock Markets: A Nonparametric Approach By Juho Kanniainen; Ye Yue
  4. Emergence of stylized facts during the opening of stock markets By Sebastian M. Krause; Jonas A. Fiegen; Thomas Guhr
  5. Eyes on the Price: Which Power Generation Technologies Set the Market Price? Price Setting in European Electricity Markets: An Application to the Proposed Dutch Carbon Price Floor By Blume-Werry, Eike; Faber, Thomas; Hirth, Lion; Huber, Claus; Everts, Martin
  6. Optimal VWAP execution under transient price impact By Alexander Barzykin; Fabrizio Lillo

  1. By: Nicolas Baradel (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris-Dauphine - CNRS - Centre National de la Recherche Scientifique, ENSAE - Ecole Nationale de la Statistique et de l'Analyse Economique - Ecole Nationale de la Statistique et de l'Analyse Economique); Bruno Bouchard (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris-Dauphine - CNRS - Centre National de la Recherche Scientifique, PSL - PSL Research University); David Evangelista (KAUST - King Abdullah University of Science and Technology); Othmane Mounjid (CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique - X - École polytechnique - CNRS - Centre National de la Recherche Scientifique)
    Abstract: We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14, 20, 21], the MM and the HFT define their trading strategy by optimizing the expected utility of terminal wealth, while the IB has a prescheduled task to sell or buy many shares of the considered asset. We derive the variational partial differential equations that characterize the value functions of the MM and HFT and explain how almost optimal control can be deduced from them. We then provide a first illustration of the interactions that can take place between these different market participants by simulating the dynamic of an order book in which each of them plays his own (optimal) strategy.
    Keywords: Optimal control,Optimal trading,market impact
    Date: 2018
  2. By: Tristan Roger (DRM-Finance - DRM - Dauphine Recherches en Management - Université Paris-Dauphine - CNRS - Centre National de la Recherche Scientifique); Wael Bousselmi (CREST - Centre de Recherche en Economie et Statistique [Bruz] - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz]); Patrick Roger (LARGE - Laboratoire de recherche en gestion et économie - UNISTRA - Université de Strasbourg - L'europe en mutation : histoire, droit, économie et identités culturelles - UNISTRA - Université de Strasbourg - CNRS - Centre National de la Recherche Scientifique); Marc Willinger (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - INRA - Institut National de la Recherche Agronomique - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier)
    Abstract: Conventional finance models indicate that the magnitude of stock prices should not influence portfolio choices or future returns. This view is contradicted, however, by empirical evidence. In this paper, we report the results of an experiment showing that trading prices, in experimental markets, are processed differently by participants, depending on their magnitude. Our experiment has two consecutive treatments. One where the fundamental value is a small number (the small price market) and a second one where the fundamental value is a large number (the large price market). Small price markets exhibit greater mispricing than large price markets. We obtain this result both between-participants and within-participants. Our findings show that price magnitude influences the way people perceive the distribution of future returns. This result is at odds with standard finance theory but is consistent with: (1) a number of observations in the empirical finance and accounting literature; and (2) evidence in neuropsychology on the use of different mental scales for small and large numbers.
    Keywords: behavioral bias,experimental markets,mental scales,number perception,stock price magnitude
    Date: 2018–12–14
  3. By: Juho Kanniainen; Ye Yue
    Abstract: This paper introduces a non-parametric framework to statistically examine how news events, such as company or macroeconomic announcements, contribute to the pre- and post-event jump dynamics of stock prices under the intraday seasonality of the news and jumps. We demonstrate our framework, which has several advantages over the existing methods, by using data for i) the S&P 500 index ETF, SPY, with macroeconomic announcements and ii) Nasdaq Nordic Large-Cap stocks with scheduled and non-scheduled company announcements. We provide strong evidence that non-scheduled company announcements and some macroeconomic announcements contribute jumps that follow the releases and also some evidence for pre-jumps that precede the scheduled arrivals of public information, which may indicate non-gradual information leakage. Especially interim reports of Nordic large-cap companies are found containing important information to yield jumps in stock prices. Additionally, our results show that releases of unexpected information are not reacted to uniformly across Nasdaq Nordic markets, even if they are jointly operated and are based on the same exchange rules.
    Date: 2019–01
  4. By: Sebastian M. Krause; Jonas A. Fiegen; Thomas Guhr
    Abstract: Financial markets show a number of non-stationarities, ranging from volatility fluctuations over ever changing technical and regulatory market conditions to seasonalities. On the other hand, financial markets show various stylized facts which are remarkably stable. It is thus an intriguing question to find out how these stylized facts emerge. As a first example, we here investigate how the bid-ask-spread between best sell and best buy offer for stocks develops during the trading day. For rescaled and properly smoothed data we observe collapsing curves for many different NASDAQ stocks, with a slow power law decline of the spread during the whole trading day. This effect emerges robustly after a highly fluctuating opening period. Some so called large-tick stocks behave differently because of technical boundaries. Their spread closes to one tick shortly after the market opening. We use our findings for identifying the duration of the market opening which we find to vary largely from stock to stock.
    Date: 2018–12
  5. By: Blume-Werry, Eike; Faber, Thomas; Hirth, Lion; Huber, Claus; Everts, Martin
    Abstract: Upon discussion of price setting on electricity wholesale markets, many refer to the so-called merit order model. Conventional wisdom holds that during most hours of the year, coal- or natural gas-fired power plants set the price on European markets. In this context, this paper analyses price setting on European power markets. We use a fundamental electricity market model of interconnected bidding zones to determine hourly price-setting technologies for the year 2020. We find a price-setting pattern that is more complex and nuanced than the conventional wisdom suggests: across all researched countries, coal- and natural gas-fired power plants set the price for only 40 per cent of all hours. Other power generation technologies such as wind, biomass, hydro and nuclear power plants as well as lignite-fired plants set the price during the rest of the year. On some markets, the price setting is characterised by a high level of interconnectivity and thus foreign influence – as illustrated by the example of the Netherlands. During some 75 per cent of hours, foreign power plants set the price on the Dutch market, whilst price setting in other more isolated markets is barely affected by foreign markets. Hence, applying the price setting analysis to the proposed Dutch carbon price floor, we show that different carbon prices have little effect on the technological structure of the price-setting units. In this respect, the impacts of the unilateral initiative are limited. There are, however, considerable changes to be observed in wholesale power prices, import/export balances as well as production volumes and subsequent CO2 outputs of lignite-, coal- and gas-fired power plants.
    Keywords: Resource /Energy Economics and Policy
    Date: 2019–01–14
  6. By: Alexander Barzykin; Fabrizio Lillo
    Abstract: We solve the problem of optimal liquidation with volume weighted average price (VWAP) benchmark when the market impact is linear and transient. Our setting is indeed more general as it considers the case when the trading interval is not necessarily coincident with the benchmark interval: Implementation Shortfall and Target Close execution are shown to be particular cases of our setting. We find explicit solutions in continuous and discrete time considering risk averse investors having a CARA utility function. Finally, we show that, contrary to what is observed for Implementation Shortfall, the optimal VWAP solution contains both buy and sell trades also when the decay kernel is convex.
    Date: 2019–01

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