New Economics Papers
on Market Microstructure
Issue of 2009‒01‒24
three papers chosen by
Thanos Verousis
  1. Predicting Stock Volatility Using After-Hours Information By Chun-Hung Chen; Wei-Choun Yu; Eric Zivot
  2. Profitability of Technical Trading Rules on the Baltic Stock Markets By Lönnbark, Carl; Soultanaeva, Albina
  3. The influence of seller learning and time constraints on sequential bargaining in an artificial perishable goods market By Sonia Moulet; Juliette Rouchier
  1. By: Chun-Hung Chen (KPMG); Wei-Choun Yu (Winona State University); Eric Zivot (University of Washington)
    Abstract: We use realized volatilities based on after hours high frequency returns to predict next day volatility. We extend GARCH and long-memory forecasting models to include additional information: the whole night, the preopen, the postclose realized variance, and the overnight squared return. For four NASDAQ stocks (MSFT, AMGN, CSCO, and YHOO) we find that the inclusion of the preopen variance can improve the out-of-sample forecastability of the next day conditional day volatility. Additionally, we find that the postclose variance and the overnight squared return do not provide any predictive power for the next day conditional volatility. Our findings support the results of prior studies that traders trade for non-information reasons in the postclose period and trade for information reasons in the preopen period.
    Date: 2009–01
    URL: http://d.repec.org/n?u=RePEc:udb:wpaper:uwec-2009-01&r=mst
  2. By: Lönnbark, Carl (Department of Economics, Umeå University); Soultanaeva, Albina (Department of Economics, Umeå University)
    Abstract: In this note we study whether simple technical trading rules are profitable on the three Baltic stock markets. To statistically assess our findings we consider the conventional t-test and a block-bootstrap procedure. The two evaluation methods give conflicting results. The t-test supports some of the rules, while the block-bootstrap does not.
    Keywords: Baltic stock markets; technical trading rules; block bootstrap
    JEL: G10 G14
    Date: 2009–01–14
    URL: http://d.repec.org/n?u=RePEc:hhs:umnees:0761&r=mst
  3. By: Sonia Moulet (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille II - Université Paul Cézanne - Aix-Marseille III - Ecole des Hautes Etudes en Sciences Sociales - CNRS : UMR6579); Juliette Rouchier (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille II - Université Paul Cézanne - Aix-Marseille III - Ecole des Hautes Etudes en Sciences Sociales - CNRS : UMR6579)
    Abstract: This paper investigates the formation of prices in a perishable goods market where agents bargain repeatedly through pair-wise interactions. After extensive field observations, we chose to focus on two aspects that seem important to actors of this market : the passage of time and update in judgement when gathering information. The main feature of the market is that a seller bargaining with a buyer has incomplete information about buyer’s willingness to pay and is not sure how her trading partner will evaluate an offer or compare it with other options. On the other hand, buyers have limited time to look for good sand cannot meet all possible sellers before making a decision. Hence agents cannot calculate the best price to offer but receive information through limited interactions, and use this information to choose their actions. An agent-based model was built to represent a frame work that mimics the observed market institution and where agent’s possible behaviours and learning was made as consistent as possible with gathered data. Simulations were run, first for sensitivity analysis concerning main parameters, then to test the dependence of agents’learning to (a) the time buyers can spend on the market and (b) the frequency of update in learning by sellers. To validate the model, features produced by the simulated market are compared to the stylized facts gathered for negotiation about four goods. We reproduce the main features of the data on the dynamics of offers, transaction prices and agents’behavior during the bargaining phases.
    Keywords: agent-based model, bargaining, perishable goods, pair-wise interac-tion, decentralized market
    Date: 2009–01–15
    URL: http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-00353505_v1&r=mst
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