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Nonparametric inference for second order stochastic dominance

Schmid, Friedrich; Trede, Mark - 1996

This paper deals with nonparametric inference for second order stochastic dominance of two random variables. If their distribution functions are unknown they have to be inferred from observed realizations. Thus, any results on stochastic dominance are influenced by sampling errors. We establish...

Persistent link: https://www.econbiz.de/10008992397

Nonparametric Specification Testing in Nonlinear and Nonstationary Time Series Models : Theory and Practice

Chen, Jia - 2013

general semiparametric local alternatives. The asymptotic theory developed in this paper differs from existing work on … illustrate the proposed theory and methodology …

Persistent link: https://www.econbiz.de/10013084965

A Tale of Two Time Scales : Applications in Nonparametric Hawkes Processes With Ito Semimartingale Baseline

Yu, Seunghyeon; Potiron, Yoann - 2022

statistics. As a byproduct, we provide estimation and feasible limit theory of the branching ratio (i.e. the L1-norm of the … estimates and truncated Two Scales Realized Volatility of these estimates, together with its central limit theory and feasible …-varying baseline, and for the absence of Brownian diffusion in the baseline. Simulation studies corroborate the theory, and document …

Persistent link: https://www.econbiz.de/10013403725

Efficient Estimation of a Multivariate Multiplicative Volatility Model

Hafner, Christian M. - 2010

-based estimation procedures for the parametric and nonparametric components, and derive the asymptotic properties thereof. For the …

Persistent link: https://www.econbiz.de/10013148178

Bandwidth Selection for Estimators of Time-Varying Stochastic Coefficient Models

Grivas, Charisios; Psaradakis, Zacharias - 2023

A recent strand of the literature has proposed stochastic time-varying coefficient models for modelling structural change in the macroeconomy under both exogeneity and endogeneity. Subsequently, a new class of kernel based non-parametric estimators has been introduced for these models. These...

Persistent link: https://www.econbiz.de/10014356833

Sensitivity of University Rankings : Implications of Stochastic Dominance Efficiency Analysis

Pinar, Mehmet; Milla, Joniada; Stengos, Thanasēs - 2018

To create their rankings, university-ranking agencies usually combine multiple performance measures into a composite index. However, both rankings and index scores are sensitive to the weights assigned to performance measures. This paper uses a stochastic dominance efficiency methodology to...

Persistent link: https://www.econbiz.de/10014112285

Nonparametric change-point analysis of volatility

Bibinger, Markus; Jirak, Moritz; Vetter, Mathias - 2015

This work develops change-point methods for statistics of high-frequency data. The main interest is the volatility of an Itô semi-martingale, which is discretely observed over a fixed time horizon. We construct a minimax-optimal test to discriminate different smoothness classes of the...

Persistent link: https://www.econbiz.de/10010477582

Investors' behavior in alternative asset classes

Papavasiliou, Ellie; Topaloglou, Nikolas; Tsomidis, Georgios - In: Spoudai : journal of economics and business 72 (2022) 3/4, pp. 3-55

investor personae in the Behavioral Finance literature, namely, the Cumulative Prospect Theory, the Markowitz and the Loss …

Persistent link: https://www.econbiz.de/10014246136

Estimation and testing in a perturbed multivariate long memory framework

Less, Vivien; Sibbertsen, Philipp - 2022

We propose a semiparametric multivariate estimator and a multivariate score-type testing procedure under a perturbed multivariate fractional process. The estimator is based on the periodogram and uses a local Whittle criterion function which is generalised by an additional constant to capture...

Persistent link: https://www.econbiz.de/10014247836

The Stochastic Inequality Test - a Test for a Directional Treatment Effect

Schlag, Karl H.; Tremewan, James - 2022

The stochastic inequality test is an exact non-parametric test that can be used to infer whether values in one random sample tend to be higher than in another. In addition it can be used to derive a confidence interval around an intuitive measure of effect size that is readily interpretable...

Persistent link: https://www.econbiz.de/10013281266