• Media type: E-Book
  • Title: Seasonal long memory in intraday volatility and trading volume of Dow Jones stocks
  • Contributor: Voges, Michelle [Author]; Leschinski, Christian [Author]; Sibbertsen, Philipp [Author]
  • Published: [Hannover]: Wirtschaftswissenschaftliche Fakultät der Leibniz Universität Hannover, Jun 2017
  • Published in: Universität Hannover: Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät ; 59900
  • Issue: This version: June 28, 2017
  • Extent: 1 Online-Ressource (circa 21 Seiten); Illustrationen
  • Language: English
  • Identifier:
  • Keywords: Arbeitspapier ; Graue Literatur
  • Origination:
  • Footnote:
  • Description: It is well known that intraday volatilities and trading volumes exhibit strong seasonal features. These seasonalities are usually modeled using dummy variables or deterministic functions. Here, we propose a test for seasonal long memory with a known frequency. Using this test, we show that deterministic seasonality is an accurate model for the DJIA index but not for the component stocks. These still exhibit significant and persistent periodicity after seasonal de-meaning so that more evolved seasonal long memory models are required to model their behavior.
  • Access State: Open Access