Search Results - subject:"Mixture Models"

Bayesian option pricing using mixed normal heteroskedasticity models

ROMBOUTS, Jeroen V.K.; STENTOFT, Lars - Center for Operations Research and Econometrics (CORE), … - 2009

pricing, finite mixture models, out-ofsample prediction, GARCH models. JEL Classification: C11, C15, C22, G13 … mixture models, which are convex combinations of densities, are becoming a stan- dard tool in financial econometrics. They are … mixture models. Boothe and Glassman (1987), Tucker and Pond (1988), and Pan, Chan, and Fok (1995) use mixtures of normals to …

Persistent link: https://www.econbiz.de/10008494365

Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models

Rombouts, Jeroen V.K.; Stentoft, Lars - Centre Interuniversitaire sur le Risque, les Politiques … - 2009

While stochastic volatility models improve on the option pricing error when compared to the Black-Scholes-Merton model, mispricings remain. This paper uses mixed normal heteroskedasticity models to price options. Our model allows for significant negative skewness and time varying higher order...

Persistent link: https://www.econbiz.de/10008528563

Some Composite ExponentialPareto Models for Actuarial Prediction

Teodorescu, Sandra; Vernic, Raluca - In: Journal for Economic Forecasting (2009) 4, pp. 82-100

Prediction is a very important and not so easy task for an actuary. An insurance company needs predictions of the future claims in order to evaluate premiums, to assess its financial situation, probabilities of ruin, etc. Therefore, modeling the claims distribution is of great importance, but...

Persistent link: https://www.econbiz.de/10008561100

Did Globalization Lead to Segmentation? Identifying Cross-Country Growth Regimes in the Long-Run

Di Vaio, Gianfranco; Enflo, Kerstin - Dipartimento di Economia e Finanza (DEF), Libera … - 2009

Economic historians have stressed that income convergence was a key feature of the OECD-club and that globalization was among the accelerating forces of this process in the long-run. This view has however been challenged, since it suffers from an ad hoc selection of countries. In the paper, a...

Persistent link: https://www.econbiz.de/10008839258

Forecasting Macroeconomic Time Series With Locally Adaptive Signal Extraction

Giordani, Paolo; Villani, Mattias - Sveriges Riksbank - 2009

We introduce a non-Gaussian dynamic mixture model for macroeconomic forecasting. The Locally Adaptive Signal Extraction and Regression (LASER) model is designed to capture relatively persistent AR processes (signal) contaminated by high frequency noise. The distribution of the innovations in...

Persistent link: https://www.econbiz.de/10008469621

Frailty models and frailty-mixture models for recurrent event times

Xu, Ying; Cheung, Yin Bun - In: Stata Journal 15 (2015) 1, pp. 135-154

The analysis of recurrent event times faces three challenges: betweensubject heterogeneity (frailty), within-subject event dependence, and the possibility of a cured fraction. Frailty can be handled by including a latent random-effects term in a Cox-type model. Event dependence may be considered...

Persistent link: https://www.econbiz.de/10011265709

Convergence of the EM algorithm for continuous mixing distributions

Chung, Yeojin; Lindsay, Bruce G. - In: Statistics & Probability Letters 96 (2015) C, pp. 190-195

is often used in mixture models, density estimation, and signal recovery problems. We prove the convergence of the EM in …

Persistent link: https://www.econbiz.de/10011115951

Log-concavity of a mixture of beta distributions

Mu, Xiaosheng - In: Statistics & Probability Letters 99 (2015) C, pp. 125-130

We provide a sufficient condition for a mixture of Beta distributions to have log-concave density. This is true whenever the Beta distributions to be mixed together have constant parameter sum and the mixing weights are themselves log-concave. The result has applications in economics and...

Persistent link: https://www.econbiz.de/10011208319

Model based clustering of high-dimensional binary data

Tang, Yang; Browne, Ryan P.; McNicholas, Paul D. - In: Computational Statistics & Data Analysis 87 (2015) C, pp. 84-101

A mixture of latent trait models with common slope parameters for model-based clustering of high-dimensional binary data, a data type for which few established methods exist, is proposed. Recent work on clustering of binary data, based on a d-dimensional Gaussian latent variable, is extended by...

Persistent link: https://www.econbiz.de/10011209621

A Bayesian hierarchical model for estimating and partitioning Bernstein polynomial density functions

Gard, Charlotte C.; Brown, Elizabeth R. - In: Computational Statistics & Data Analysis 87 (2015) C, pp. 73-83

A Bayesian hierarchical model for simultaneously estimating and partitioning probability density functions is presented. Individual density functions are flexibly modeled using Bernstein densities, which are mixtures of beta densities whose parameters depend only on the number of mixture...

Persistent link: https://www.econbiz.de/10011209622