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Cosma, Antonio; Galli, Fausto - 2014

We carry out a non parametric analysis of financial durations. We make use of an existing algorithm to describe non parametrically the dynamics of the process in terms of its lagged realizations and of a latent variable, its conditional mean. The devices needed to effectively apply the algorithm...

Persistent link: https://www.econbiz.de/10015241268

Adaptive Conformal Inference for computing Market Risk Measures: an Analysis with Four Thousands Crypto-Assets

Fantazzini, Dean - 2024

and daily range models. Despite the substantial volatility observed in the majority of crypto-assets, our findings …

Persistent link: https://www.econbiz.de/10015213597

Beyond Conditional Second Moments: Does Nonparametric Density Modelling Matter to Portfolio Allocation?

Li, Chenxing; Maheu, John M - 2023

This paper investigates the economic importance of nonparametrically/semiparametrically modelling the shape and the change in the unknown distribution of returns in portfolio allocation problems from a Bayesian perspective. Besides parametric multivariate GARCH (MGARCH) benchmark models for...

Persistent link: https://www.econbiz.de/10015214743

An Infinite Hidden Markov Model with GARCH for Short-Term Interest Rates

Li, Chenxing; Yang, Qiao - 2025

Markov model with the volatility persistence captured by the GARCH framework, to effectively model and forecast short … in volatility, thereby enhancing the accuracy of density forecasts compared to existing benchmark models. Out …-of-sample evaluations demonstrate the superior performance of our model in density forecasts and in capturing volatility dynamics due to its …

Persistent link: https://www.econbiz.de/10015214745

Nonparametric approach to portfolio diversification: the case of Australian equity market.

Trofimov, Ivan D. - 2013

This study investigates the portfolio diversification possibilities among Australian sectoral, size and style indexes and between Australian aggregate equity index and selected international indexes. Two analytical methods are used – nonparametric cointegration that appears to be the most...

Persistent link: https://www.econbiz.de/10015256296

Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices

Jin, Xin; Maheu, John M; Yang, Qiao - 2017

This paper introduces a new factor structure suitable for modeling large realized covariance matrices with full likelihood based estimation. Parametric and nonparametric versions are introduced. Due to the computational advantages of our approach we can model the factor nonparametrically as a...

Persistent link: https://www.econbiz.de/10015257776

Identification non paramétrique d’un processus non linéaire hétéroscédastique

CHIKHI, Mohamed - 2009

Cet article vise à identifier un processus non linéaire par la méthode du noyau. Cette identification nécessite une sélection rigoureuse des coefficients de Markov et le choix de la fenêtre qui détermine le degré de lissage de l’estimateur. This paper aims to identify a nonlinear...

Persistent link: https://www.econbiz.de/10015257894

Intensity of default in sovereign bonds: Estimation of an unobservable process

Otero, Karina V. - 2016

This paper proposes a new approach to estimate general stationary diﬀusion processes that describe the evolution of unobserved arrival rates of credit events on sovereign bonds, allowing for arbitrary parametric drift and diﬀusion speciﬁcations. The solutions and transition processes for...

Persistent link: https://www.econbiz.de/10015260419

Consistent Pseudo-Maximum Likelihood Estimators and Groups of Transformations

Gouriéroux, Christian; Monfort, Alain; Zakoian, Jean-Michel - 2018

by examples of systems of nonlinear equations, conditionally heteroskedastic models, stochastic volatility, or models …

Persistent link: https://www.econbiz.de/10015260917

A review of more than one hundred Pareto-tail index estimators

Fedotenkov, Igor - 2018

This paper reviews more than one hundred Pareto (and equivalent) tail index estimators. It focuses on univariate estimators for nontruncated data. We discuss basic ideas of these estimators and provide their analytical expressions. As samples from heavy-tailed distributions are analysed by...

Persistent link: https://www.econbiz.de/10015262087