In this paper, I model the intraday trading activity based on volume durations, i.e. the waiting time until a predetermined volume is absorbed by the market. Since this concept measures the trading volume per time it is strongly related to market liquidity. I focus on volumes measured...

This paper analyzes the interday stability of the price process using transaction data. While the vast majority of empirical studies on the microstructure of financial markets rests on the tacit assumption that observed prices are generated by a time-invariant price process, we question this...

This paper presents structural estimates for a bargaining model which nests the right-to-manage, the efficient wage bargaining, the seniority and the standard neoclassical labor demand model as special cases. In contrast to most existing models, our approach accounts for heterogeneous skill...

This paper proposes a semiparametric approach by introducing a smooth scale function into the standard GARCH model so that conditional heteroskedasticity and scale change in a financial time series can be modelled simultaneously. An estimation procedure combining kernel estimation of the scale...

The recent availability of large data sets covering single transactions on financial markets has created a new branch of econometrics which has opened up a new door of looking at the microstructure of financial markets and its dynamics. The specific nature of transaction data such as the...

We consider two sequences of Markov chains inducing equivalent measures on the discrete path space. We establish conditions under which these two measures converge weakly to measures induced on the Wiener space by weak solutions of two SDEs, which are unique in the sense of probability law. We...

This paper considers estimation of the regression function and its derivatives in nonparametric regression with fractional time series errors. We focus on investigating the properties of a kernel dependent function V (delta) in the asymptotic variance and finding closed form formula of it, where...

Modelling and forecasting the covariance of financial return series has always been a challenge due to the so-called "curse of dimensionality". This paper proposes a methodology that is applicable in large dimensional cases and is based on a time series of realized covariance matrices. Some...

Estimation of a nonparametric regression spectrum based on the periodogram is considered. Neither trend estimation nor smoothing of the periodogram are required. Alternatively, for cases where spectral estimation of phase shifts fails and the shift does not depend on frequency, a time domain...

We consider parameter estimation for time-dependent locally stationary long-memory processes. The asymptotic distribution of an estimator based on the local infinite autoregressive representation is derived, and asymptotic formulas for the mean squared error of the estimator, and the...