New Economics Papers
on Market Microstructure
Issue of 2014‒01‒17
three papers chosen by
Thanos Verousis

  1. Does mood affect trading behavior? By Kaustia, Markku; Rantapuska, Elias
  2. Realized volatility risk By David E. Allen; Michael McAleer; Marcel Scharth
  3. Competition/fragmentation in equities markets: A literature survey By Gomber, Peter; Sagade, Satchit; Theissen, Erik; Weber, Moritz Christian; Westheide, Christian

  1. By: Kaustia, Markku; Rantapuska, Elias
    Abstract: We test whether investor mood affects trading with data on all stock market transactions in Finland, utilizing variation in daylight and local weather. We find some evidence that environmental mood variables (local weather, length of day, daylight saving and lunar phase) affect investors' direction of trade and volume. The effect magnitudes are roughly comparable to those of classical seasonals, such as the Monday effect. The statistical significance of the mood variables is weak in many cases, however. Only very little of the day-to-day variation in trading is collectively explained by all mood variables and calendar effects, but lower frequency variation seems connected to holiday seasons. --
    Keywords: mood,seasonal affective disorder (SAD),weather,trading behavior,stock market
    JEL: D03 G11 G12
    Date: 2013
  2. By: David E. Allen (School of Accounting, Finance and Economics Edith Cowan University, Australia.); Michael McAleer (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute, The Netherlands, Department of Quantitative Economics, Complutense University of Madrid, and Institute of Economic Research, Kyoto University.); Marcel Scharth (Department of Econometrics Faculty of Economics and Business Administration VU University Amsterdam De Boelelaan 1105 1081 HV Amsterdam The Netherlands)
    Abstract: In this paper we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly gaussian, this unpredictability brings considerably more uncertainty to the empirically relevant ex ante distribution of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility model, which incorporates the fact that realized volatility series are systematically more volatile in high volatility periods. Returns in this framework display time varying volatility, skewness and kurtosis. We provide a detailed account of the empirical advantages of the model using data on the S&P 500 index and eight other indexes and stocks.
    Keywords: Realized volatility, volatility of volatility, volatility risk, value-at-risk, forecasting, conditional heteroskedasticity.
    Date: 2013
  3. By: Gomber, Peter; Sagade, Satchit; Theissen, Erik; Weber, Moritz Christian; Westheide, Christian
    Abstract: Advances in technology and several regulatory initiatives have led to the emergence of a competitive but fragmented equity trading landscape in the US and Europe. While these changes have brought about several benefits like reduced transaction costs, regulators and market participants have also raised concerns about the potential adverse effects associated with increased execution complexity and the impact on market quality of new types of venues like dark pools. In this article we review the theoretical and empirical literature examining the economic arguments and motivations underlying market fragmentation, as well as the resulting implications for investors' welfare. We start with the literature that views exchanges as natural monopolies due to presence of network externalities, and then examine studies which challenge this view by focusing on trader heterogeneity and other aspects of the microstructure of equity markets. --
    Keywords: Market Structure,Competition,Fragmentation,Liquidity,Market Quality
    JEL: G10
    Date: 2013

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