New Economics Papers
on Market Microstructure
Issue of 2013‒08‒16
two papers chosen by
Thanos Verousis

  1. An analysis of commodity markets: What gain for investors? By Paresh Kumar Narayan; Seema Narayan; Susan S Sharma
  2. Herding in financial markets: Bridging the gap between theory and evidence By Christopher Boortz; Simon Jurkatis; Stephanie Kremer; Dieter Nautz

  1. By: Paresh Kumar Narayan (Deakin University); Seema Narayan (RMIT); Susan S Sharma (Deakin University)
    Abstract: In this paper we study whether the commodity futures market predicts the commodity spot market. Using historical daily data on four commodities—oil, gold, platinum, and silver—we find that they do. We then show how investors can use this information on the futures market to devise trading strategies and make profits. In particular, dynamic trading strategies based on a mean-variance investor framework produce somewhat different results compared with those based on technical trading rules. Dynamic trading strategies suggest that all commodities are profitable and profits are dependent on structural breaks. The most recent global financial crisis marked a period in which commodity profits were the weakest.
    Keywords: Commodity Futures; Commodity Spot; Trading Strategies; Profits
    JEL: C22 G11 G17
  2. By: Christopher Boortz; Simon Jurkatis; Stephanie Kremer; Dieter Nautz
    Abstract: Due to data limitations and the absence of testable, model-based predictions, theory and evidence on herd behavior are only loosely connected. This paper attempts to close this gap in the herding literature. From a theoretical perspective, we use numerical simulations of a herd model to derive new, theory-based predictions for aggregate herding intensity. From an empirical perspective, we employ high-frequency, investor-specic trading data to test the theory-implied impact of information risk and market stress on herding. Conrming model predictions, our results show that herding intensity increases with information risk. In contrast, herding measures estimated for the nancial crisis period cannot be explained by the herd model. This suggests that the correlation of trades observed during the crisis is mainly due to the common reaction of investors to new public information and should not be misinterpreted as herd behavior.
    Keywords: Herd Behavior, Institutional Trading, Model Simulation
    JEL: G11 G24
    Date: 2013–07

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