Evaluation of two-step estimation procedure for a functional model of volatility
(English)Manuscript (Other academic)
A two-step procedure for volatility estimation is evaluated by a simulation study intended to mimic estimation from the Swedish limit order book. To simulate data with varying volatility the Heston stochastic volatility model is used. From the simulated data, the time series of realized quadratic variation (RQV) for a given relative quantity of shares are obtained. These time series are modeled in a functional time series context by fitting an autoregressive moving average model. This model may be estimated in two ways, either by obtaining the raw estimates of the coefficient functions (naive approach) or by smoothing the fitted coefficient functions (two-step approach). Our results show that the risk measures of the smooth coefficient functions are indeed smaller than the corresponding risk measures of the coefficient functions of raw estimates. Consequently, the two-step estimation procedure is considered to be more efficient than the naive approach within this framework.
Computer and Information Science
Research subject Econometrics
IdentifiersURN: urn:nbn:se:umu:diva-18754OAI: oai:DiVA.org:umu-18754DiVA: diva2:174702