Stuetzle and Mittal (1979) for ordinary nonparametric kernel regression and Kauermann and Tutz (1996) for nonparametric generalized linear model kernel regression constructed estimators with lower order bias than the usual estimators, without the need for devices such as second derivative...

A new methodology is proposed to estimate theoretical prices of financial contin- gent claims whose values are dependent on some other underlying financial assets. In the literature, the preferred choice of estimator is usually maximum likelihood (ML). ML has strong asymptotic justification but...

In this paper, we introduce a new, computationally attractive estimator of long memory by taking a weighted average of the GPH or local Whittle estimator over different bandwidths. We show that the new estimator can be designed to have the same asymptotic bias properties as the bias-reduced...

One of the most studied questions in economics and finance is whether equity returns or premiums can be predicted by empirical models. While many authors favor the historical mean or other simple parametric methods, this article focuses on nonlinear relationships. A straightforward...

This paper introduces a new class of generalized flat-top realized kernels for estimation of quadratic variation in the presence of market microstructure noise that is allowed to exhibit a non-trivial dependence structure and to be correlated with the efficient price process. The estimators in...

This paper extends the class of generalized at-top realized kernels, introduced in Varneskov (2011), to the multivariate case, where quadratic covariation of non-synchronously observed asset prices is estimated in the presence of market microstructure noise that is allowed to exhibit serial...

It is well-known that maximum likelihood (ML) estimation of the autoregressive parameter of a dynamic panel data model with .xed eects is inconsistent under .xed time series sample size (T) and large cross section sample size (N) asymptotics. The estimation bias is particularly relevant in...

This paper overviews maximum likelihood and Gaussian methods of estimating continuous time models used in finance. Since the exact likelihood can be constructed only in special cases, much attention has been devoted to the development of methods designed to approximate the likelihood. These...

A new methodology is proposed to estimate theortical prices of financial contingent-claims whose values are dependent on some other underlying financial assets. In the literature the preferred choice of estimator is usually maximum likelihood (ML). ML has strong asymptotic justification but is...