This paper studies determinants of risk premia using a non-parametric term-structure model of the corporate spread. The model, which measures the extra return of defaultable corporate bonds on their government counterparts, involves the rate of inflation, a key macroeconomic variable that is...

In this paper, we are interested in continuous time models in which the index level induces some feedback on the dynamics of its composing stocks. More precisely, we propose a model in which the log-returns of each stock may be decomposed into a systemic part proportional to the log-returns of...

The paper investigates the access of small and medium-sized enterprises to external financing during the recent financial crisis via non-parametric density estimation. The kernel density estimation is applied on a firm-level measure of financing constraints and evaluates its distribution on a...

We propose a sequential learning policy for ranking and selection problems, where we use a non-parametric procedure for estimating the value of a policy. Our estimation approach aggregates over a set of kernel functions in order to achieve a more consistent estimator. Each element in the kernel...

We want to recover the transition kernel P of a Markov chain X when only a sub-sequence of X is available. The time gaps between the observations are iid with unknown distribution. We propose a method to build an estimator of P under the assumption that it has some zero entries. Its asymptotic...

Denecke and Müller (CSDA 55:2724–2738, <CitationRef CitationID="CR2">2011</CitationRef>) presented an estimator for the correlation coefficient based on likelihood depth for Gaussian copula and Denecke and Müller (J Stat Planning Inference 142: 2501–2517, <CitationRef CitationID="CR3">2012</CitationRef>) proved a theorem about the consistency of general estimators based on...</citationref></citationref>