Research Commons
      • Browse 
        • Communities & Collections
        • Titles
        • Authors
        • By Issue Date
        • Subjects
        • Types
        • Series
      • Help 
        • About
        • Collection Policy
        • OA Mandate Guidelines
        • Guidelines FAQ
        • Contact Us
      • My Account 
        • Sign In
        • Register
      View Item 
      •   Research Commons
      • University of Waikato Research
      • Management
      • Management Papers
      • View Item
      •   Research Commons
      • University of Waikato Research
      • Management
      • Management Papers
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Time-varying price discovery and autoregressive loading factors: Evidence from S&P 500 cash and e-mini futures markets

      Hou, Yang (Greg); Li, Steven
      Thumbnail
      Files
      Hou - RCP - Time-varying price discovery and autoregressive loading factors.pdf
      Submitted version, 1.169Mb
      Citation
      Export citation
      Hou, Y., & Li, S. (2017). Time-varying price discovery and autoregressive loading factors: Evidence from S&P 500 cash and e-mini futures markets. Presented at the 2017 Global Finance Conference, New York, USA.
      Permanent Research Commons link: https://hdl.handle.net/10289/14348
      Abstract
      The error correction coefficients, known as the loading factors, are a key component for price discovery measurement. So far, the loading factors have always been assumed as static. This paper is the first one to investigate the time-varying loading factors for the price discovery measurement. Based on the minute-by-minute data from the S&P 500 cash and E-mini futures markets, this paper reveals that the loading factors are indeed autoregressive of order 1 (AR(1)) which confirms the self-dependence nature of informed trading. Furthermore, we propose three AR(1) processes for the loading factors and assess their performance in price discovery measurement compared to the static loading factor model. Overall, this research confirms the importance of autoregressive loading factors for the price discovery measurement.
      Date
      2017
      Type
      Conference Contribution
      Rights
      © copyright with the authors
      Collections
      • Management Papers [1135]
      Show full item record  

      Usage

       
       

      Usage Statistics

      For this itemFor all of Research Commons

      The University of Waikato - Te Whare Wānanga o WaikatoFeedback and RequestsCopyright and Legal Statement