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on Market Microstructure |
| By: | Charles S. Bos (VU University Amsterdam) |
| Abstract: | When analysing the volatility related to high frequency financial data, mostly non-parametric approaches based on realised or bipower variation are applied. This article instead starts from a continuous time diffusion model and derives a parametric analog at high frequency for it, allowing simultaneously for microstructure effects, jumps, missing observations and stochastic volatility. Estimation of the model delivers measures of daily variation outperforming their non-parametric counterparts. Both with simulated and actual exchange rate data, the feasibility of this novel approach is shown. The parametric setting is used to estimate the intra-day trend in the Euro/U.S. Dollar exchange rate. |
| Keywords: | High frequency; integrated variation; intra-day; jump diffusions; microstructure noise; stochastic volatility; exchange rates |
| JEL: | C11 C14 D53 E44 |
| Date: | 2008–01–22 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:20080011&r=mst |
| By: | Visser, Marcel P. |
| Abstract: | Estimation of the parameters of Garch models for financial data is typically based on daily close-to-close returns. This paper shows that the efficiency of the parameter estimators may be greatly improved by using volatility proxies based on intraday data. The paper develops a Garch quasi maximum likelihood estimator (QMLE) based on these proxies. Examples of such proxies are the realized volatility and the intraday high-low range. Empirical analysis of the S&P 500 index tick data shows that the use of a suitable proxy may reduce the variances of the estimators of the Garch autoregression parameters by a factor 20. |
| Keywords: | volatility estimation; quasi maximum likelihood; volatility proxy; Gaussian QMLE; log-Gaussian QMLE; autoregressive conditional heteroscedasticity |
| JEL: | C51 G1 C14 C22 |
| Date: | 2008–06–10 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:9076&r=mst |