Microstructure Models with Short-term Inertia and Stochastic Volatility.

• Author(s) / Creator(s)

  • Kouritzin, Michael

• Partially-observed microstructure models, containing stochastic volatility, dynamic trading noise and short term inertia, are introduced to address the following questions: (1) Do the observed prices exhibit statistically signicant inertia? (2) Is stochastic volatility (SV) still evident in the presence of dynamical trading noise? (3) If so, which SV model matches the observed price data best? Bayes factor methods are chosen for determining best-fit to allow volatility models with very different structures to be considered. Nonlinear filtering techniques are utilized to compute the Bayes factor on tick-by-tick data and to estimate the unknown parameters. Our price data sets all exhibit strong evidence of both inertia and Heston-type stochastic volatility.

• Date created

  2013-06-25

• Subjects / Keywords

  • Counting Process
  • Trading Noise
  • Stochastic Volatility
  • Bayes Factor
  • Microstructure
  • Model Selection
  • Price Inertia
  • Asset Price

• Type of Item

  Article (Draft / Submitted)

• DOI

  https://doi.org/10.7939/R3930P900

• License

  Attribution-NonCommercial-NoDerivatives 3.0 International