• Graduate program
  • Research
  • News
  • Events
    • Summer School
      • Climate Change
      • Gender in Society
      • Inequalities in Health and Healthcare
      • Business Data Science Summer School Program
      • Receive updates
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • Conference: Consumer Search and Markets
    • Annual Tinbergen Institute Conference
  • Summer School
    • Climate Change
    • Gender in Society
    • Inequalities in Health and Healthcare
    • Business Data Science Summer School Program
    • Receive updates
  • Alumni
  • Magazine
Home | Events Archive | Estimation of the Realized High-Order Moments
Seminar

Estimation of the Realized High-Order Moments


  • Series
    Seminars Econometric Institute
  • Speaker(s)
    Ostap Okhrin (TU Dresden, Germany)
  • Field
    Econometrics
  • Location
    Erasmus University Rotterdam, Tinbergen Building, Room H10-31
    Rotterdam
  • Date and time

    November 29, 2018
    16:00 - 17:00

In standard return modelling approaches, returns are often assumed to follow a normal distribution. This assumption implies a zero skewness as well as a zero excess kurtosis. Both of these implications do not correspond to empirical observation and eventually lead to problems e.g. in financial risk management. On the other side, the typical non-parametric estimation of these values require a huge amount of data to be reliable. For this reason, it is advisable to exploit the availability of high frequency data and construct estimators in the fashion of the well-known realized variance. A previous estimation approach is extended to non-martingale price processes. On the basis of Monte Carlo simulations, we show that our estimators are unbiased and consistent when the underlying price process can be modelled as a stochastic volatility jump diffusion process. Distribution properties of the estimators are discussed.

Joint work with: Manuel Schmid (TU Dresden) and Michael Rockinger (Uni Lausanne)