Results 151 to 160 of about 5,166,535 (297)
Journal of Management Studies, EarlyView.Abstract While executives vary in attention to the past, present, and future, prior work has largely examined these temporal orientations in isolation or at the individual level, which limits insight into how they jointly configure within top management teams (TMTs) and translate into firm behaviours.
Shi Tang +4 more
wiley +1 more source
Analysis of wet and dry encounters in the Yangtze River Basin based on the Copula function family and research on the probability of floods and droughts occurrence. [PDF]
PLoS OneLi J, Zhao M, Han Y.
europepmc +1 more source
Dynamic stochastic copula models: Estimation, inference and applications [PDF]
We propose a new dynamic copula model where the parameter characterizing dependence follows an autoregressive process. As this model class includes the Gaussian copula with stochastic correlation process, it can be viewed as a generalization of ...
Hafner, Christian M., Manner, Hans
core
A joint model of cost and churn for the insurance industry
Journal of Risk and Insurance, EarlyView.Abstract In insurance markets, claim costs are highly variable, heavy‐tailed, and difficult to predict. At the same time, policyholder retention and lapse behavior (customer churn) are critical determinants of long‐term profitability and solvency. Most existing models in the literature treat claim costs and lapses as independent, overlooking potential ...
Yumo Dong +4 more
wiley +1 more source
Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market [PDF]
This paper develops the method for pricing bivariate contingent claims under General Autoregressive Conditionally Heteroskedastic (GARCH) process. In order to provide a general framework being able to accommodate skewness, leptokurtosis, fat tails as ...
Dominique Guegan, Jing Zhang
core
Robust CDF‐Filtering of a Location Parameter
Journal of Time Series Analysis, EarlyView.ABSTRACT This paper introduces a novel framework for designing robust filters associated with signal plus noise models having symmetric observation density. The filters are obtained by a recursion where the innovation term is a transform of the cumulative distribution function of the residuals.
Leopoldo Catania +2 more
wiley +1 more source
Copula Based Semiparametric Regressive Models
This paper studies the estimation of copula-based semi parametric stationary Markov models. Described models allow us evaluate the parameters of copula, which has the best fit to previously selected model (simple estimators of the marginal distribution ...
Fjodorovs, Jegors, Matvejevs, Andrejs
core
The Shape of the Optimal Hedge Ratio: Modeling Joint Spot-Futures Prices using an Empirical Copula-GARCH Model [PDF]
Commodity cash and futures prices have been rising steadily since 2006. As evidenced by the April 2008 Commodity Futures Trading Commission Agricultural Forum, there is much concern among traditional futures and options market participants that the ...
Power, Gabriel J., Vedenov, Dmitry V.
core
On Testing for Independence Between Generalized Error Models of Several Time Series
Journal of Time Series Analysis, EarlyView.ABSTRACT We define generalized innovations associated with generalized error models having arbitrary distributions, that is, distributions that can be mixtures of continuous and discrete distributions. These models include stochastic volatility models and regime‐switching models with possibly zero‐inflated regimes.
Kilani Ghoudi +2 more
wiley +1 more source
Moving Aggregate Modified Autoregressive Copula‐Based Time Series Models (MAGMAR‐Copulas)
Journal of Time Series Analysis, EarlyView.ABSTRACT Copula‐based time series models can model univariate and stationary time series in a flexible way by decomposing the joint distribution of consecutive observations into a copula and the stationary distribution. Implicitly, this approach assumes a finite Markov order. In reality, a time series may not follow the Markov property.
Sven Pappert
wiley +1 more source