In the common nonparametric regression model we consider the problem of constructing optimal designs, if the unknown curve is estimated by a smoothing spline. A new basis for the space of natural splines is derived, and the local minimax property for these splines is used to derive two...

We propose a completely kernel based method of estimating the call price function or the state price density of options. The new estimator of the call price function fulfills the constraints like monotonicity and convexity given in Breeden and Litzenberger (1978) without necessarily estimating...

This paper considers the empirical assessment of the relationship between prices and number of firms in local markets in geographic or, more generally, characteristic space and its use as evidence in merger cases. It outlines a structural, semi-nonparametric econometric model of competition in...

This paper considers the empirical assessment of the relationship between prices and number of firms in local markets in geographic or, more generally, characteristic space and its use as evidence in merger cases. It outlines a structural, semi-nonparametric econometric model of competition in...

Many economic and econometric applications require the integration of functions lacking a closed form antiderivative, which is therefore a task that can only be solved by numerical methods. We propose a new family of probability densities that can be used as substitutes and have the property of...

We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are assumed to follow multivariate dynamics and are...