- edoc-Server Home
- Browsing by Author
Browsing by Author "Spokoiny, Vladimir"
Now showing items 1-20 of 27
-
2005-09-16BuchAdaptive Estimation for a Time Inhomogeneous Stochastic-Volatility Model Härdle, Wolfgang Karl; Teyssière, Gilles; Spokoiny, Vladimir
-
2008-01-07BuchAdaptive pointwise estimation in time-inhomogeneous time-series models Cizek, Pavel; Härdle, Wolfgang Karl; Spokoiny, VladimirThis paper offers a new method for estimation and forecasting of the linear and nonlinear time series when the stationarity assumption is violated. Our general local parametric approach particularly applies to general ...
-
1999-01-01BuchAn adaptive, rate-optimal test of a parametric model against a nonparametric alternative Horowitz, Joel L.; Spokoiny, VladimirWe develop a new test of a parametric model of a conditional mean function against a nonparametric alternative. The test adapts to the unknown smoothness of the alternative model and is uniformly consistent against ...
-
2014-11-17BuchBootstrap confidence setsunder modelmisspecification Spokoiny, Vladimir; Zhilova, MayyaA multiplier bootstrap procedure for construction of likelihood-based congidence sets is considered for ginite samples and a possible model misspecification. Theoretical results justify the bootstrap consistency for a small ...
-
2006-06-07BuchComponent Analysis for Additive Models Härdle, Wolfgang Karl; Sperlich, Stefan; Spokoiny, VladimirWe consider the component analysis problem for a regression model with an additive structure. The problem is to check the hypothesis of linearity for each component without specifying the structure of the remaining components. ...
-
2005-09-09BuchDeviation Probability Bound for Martingales with Applications to Statistical Estimation Liptser, R.; Spokoiny, Vladimir
-
2006-01-19BuchEstimation of a Function with Discontinuities via Local Polynomial Fit with an Adaptive Window Choice Spokoiny, VladimirWe propose a method of adaptive estimation of a regression function and which is near optimal in the classical sense of the mean integrated error. At the same time, the estimator is shown to be very sensitive to discontinuities ...
-
2006-05-02BuchForward and reverse representations for Markov chains Milstein, Grigori; Schoenmakers, John; Spokoiny, VladimirIn this paper we carry over the concept of reverse probabilistic representations developed in Milstein, Schoenmakers, Spokoiny (2004) for diffusion processes, to discrete time Markov chains. We outline the construction of ...
-
2006-11-16BuchGHICA - Risk Analysis with GH Distributions and Independent Components Chen, Ying; Härdle, Wolfgang Karl; Spokoiny, VladimirOver recent years, study on risk management has been prompted by the Basel committeefor regular banking supervisory. There are however limitations of some widely-used riskmanagement methods that either calculate risk ...
-
2006-01-27BuchImage Denoising Polzehl, Jörg; Spokoiny, VladimirThe paper is concerned with the problem of image denoising for the case of grey-scale images. Such images consist of a finite number of regions with smooth boundaries and the image value is assumed piecewise constant within ...
-
2006-05-02BuchIn Search of Non-Gaussian Components of a High-Dimensional Distribution Blanchard, Gilles; Kawanabe, Motoaki; Sugiyama, Masashi; Spokoiny, Vladimir; Müller, Klaus-RobertFinding non-Gaussian components of high-dimensional data is an important preprocessing step for effcient information processing. This article proposes a new linear method to identify the ``non-Gaussian subspace´´ within a ...
-
2006-11-14BuchInhomogeneous Dependency Modelling with Time Varying Copulae Giacomini, Enzo; Härdle, Wolfgang Karl; Ignatieva, Ekaterina; Spokoiny, VladimirMeasuring dependence in a multivariate time series is tantamount to modelling its dynamicstructure in space and time. In the context of a multivariate normally distributed time series,the evolution of the covariance (or ...
-
2011-01-03BuchLocal Quantile Regression Härdle, Wolfgang Karl; Spokoiny, Vladimir; Wang, WeiningConditional quantile curves provide a comprehensive picture of a response contingent on explanatory variables. Quantile regression is a technique to estimate such curves. In a flexible modeling framework, a specific form ...
-
2011-11-10BuchMartingale approach in pricing and hedging Milstein, Grigori N.; Spokoiny, VladimirThe paper focuses on the problem of pricing and hedging a European contingent claim for an incomplete market model, in which evolution of price processes for a saving account and stocks depends on an observable Markov ...
-
1999-01-01BuchMultiscale Testing of Qualitative Hypotheses Dümbgen, Lutz; Spokoiny, Vladimir
-
2006-03-16BuchOn Estimating a dynamic function of a stochastic system with averaging Liptser, R.; Spokoiny, VladimirWe consider a two-scaled diffusion system, when drift and diffusion parameters of the “slow” component are contaminated by the “ fast” unobserved component. The goal is to estimate the dynamic function which is defined by ...
-
2011-11-16BuchParametric estimation Spokoiny, VladimirThe paper aims at reconsidering the famous Le Cam LAN theory. The main features of the approach which make it different from the classical one are: (1) the study is non-asymptotic, that is, the sample size is fixed and ...
-
2005-12-15BuchPortfolio Value at Risk Based on Independent Components Analysis Chen, Ying; Härdle, Wolfgang Karl; Spokoiny, VladimirRisk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks ...
-
2006-07-06BuchRegression methods in pricing American and Bermudan options using consumption processes Belomestny, Denis; Milstein, Grigori; Spokoiny, VladimirHere we develop methods for e±cient pricing multidimensional discrete-time American and Bermudan options by using regression based algorithms together with a new approach towards constructing upper bounds for the price of ...
-
2007-01-16BuchRobust Risk Management Chen, Ying; Spokoiny, VladimirIn the ideal Black-Scholes world, financial time series are assumed 1) stationary (time homogeneous) and 2) having conditionally normal distribution given the past. These two assumptions have been widely-used in many methods ...
