Showing 11 - 20 of 175
We consider a generalization of stochastic bandits where the set of arms, $\cX$, is allowed to be a generic measurable space and the mean-payoff function is ''locally Lipschitz'' with respect to a dissimilarity function that is known to the decision maker. Under this condition we construct an...
Persistent link: https://www.econbiz.de/10009371841
Persistent link: https://www.econbiz.de/10005169135
The calibration of financial models has become rather important topic in recent years mainly because of the need to price increasingly complex options in a consistent way. The choice of the underlying model is crucial for the good performance of any calibration procedure. Recent empirical...
Persistent link: https://www.econbiz.de/10005678048
Persistent link: https://www.econbiz.de/10005598719
Persistent link: https://www.econbiz.de/10005613411
We investigate the problem of calibrating an exponential Lévy model based on market prices of vanilla options. We show that this inverse problem is in general severely ill-posed and we derive exact minimax rates of convergence. The estimation procedure we propose is based on the explicit...
Persistent link: https://www.econbiz.de/10005652730
We are concerned with kernel density estimation on the rotation group SO(3). We prove asymptotically optimal convergence rates for the minimax risk of the mean integrated squared error for different function classes including bandlimited functions, functions with bounded Sobolev norm and...
Persistent link: https://www.econbiz.de/10010678852
The subject of this paper is the estimation of a probability measure on Rd from the data observed with an additive noise, under the Wasserstein metric of order p (with p≥1). We assume that the distribution of the errors is known and belongs to a class of supersmooth distributions, and we give...
Persistent link: https://www.econbiz.de/10011041999
We consider the problem of adaptive estimation of the regression function in a framework where we replace ergodicity assumptions (such as independence or mixing) by another structural assumption on the model. Namely, we propose adaptive upper bounds for kernel estimators with data-driven...
Persistent link: https://www.econbiz.de/10011064962
Persistent link: https://www.econbiz.de/10005395515