Showing 1 - 10 of 155
We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semi-martingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance...
Persistent link: https://www.econbiz.de/10011277282
partner from car industry, combines classical tests and nonparametric smoothing techniques to detect trends in the process of … resampling methods borrowed from nonparametric smoothing. The aim of the analysis is to find a reliable technical solution which …
Persistent link: https://www.econbiz.de/10005677929
This paper proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental variables which are independent of response given potential outcomes. A nonparametric testing procedure based on integrated squared distance is proposed. The statistic’s...
Persistent link: https://www.econbiz.de/10011212947
factor loadings via proper orthogonal decomposition. Simulation study and real data analysis show that the 3D Image FPCA …
Persistent link: https://www.econbiz.de/10011261760
asymptotic normality. Simulation evidence strongly corroborates with the asymptotic theory. …
Persistent link: https://www.econbiz.de/10008861891
In 2007 and 2008 world food markets observed a significant price boom. Crop failures simultaneously occurring in some of the world’s major production regions have been quoted as one factor among others for the price boom. Against this background, we analyse the stochasticity of crop yields in...
Persistent link: https://www.econbiz.de/10008868032
A Lévy process is observed at time points of distance delta until time T. We construct an estimator of the Lévy-Khinchine characteristics of the process and derive optimal rates of convergence simultaneously in T and delta. Thereby, we encompass the usual low- and high-frequency assumptions...
Persistent link: https://www.econbiz.de/10008629514
This paper studies the performance of nonparametric quantile regression as a tool to predict Value at Risk (VaR). The approach is flexible as it requires no assumptions on the form of return distributions. A monotonized double kernel local linear estimator is applied to estimate moderate (1%)...
Persistent link: https://www.econbiz.de/10008629520
This study analyses credit default risk for firms in the Asian and Pacific region by applying two methodologies: a Support Vector Machine (SVM) and a logistic regression (Logit). Among different financial ratios suggested as predictors of default, leverage ratios and the company size display a...
Persistent link: https://www.econbiz.de/10009021755
A nonparametric procedure for quantile regression, or more generally nonparametric M-estimation, is proposed which is completely data-driven and adapts locally to the regularity of the regression function. This is achieved by considering in each point M-estimators over different local...
Persistent link: https://www.econbiz.de/10009024914