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Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series analysis. The purpose of...
Persistent link: https://www.econbiz.de/10010484894
We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...
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This article generalises the results of Sadi and Zakoian (2006) to a considerably larger class of nonlinear ARCH models with discontinuities, leverage e ects and robust news impact curves. We propose a new method of proof for the existence of a strictly stationary and phi-mixing solution....
Persistent link: https://www.econbiz.de/10011699508
We propose a semiparametric estimator to determine the effects of explanatory variables on the conditional interquantile expectation (IQE) of the random variable of interest, without specifying the conditional distribution of the underlying random variables. IQE is the expected value of the...
Persistent link: https://www.econbiz.de/10011622915
This paper explores the contagious propagation of jumps among international stock market indices by exploiting a rich panel of stock and options data. We propose a multivariate option pricing model designed to allow for, but not superimpose, time and space amplification of jumps in option...
Persistent link: https://www.econbiz.de/10012650140
This paper develops a semiparametric estimation method that jointly identifies the probability weighting and utility functions implicit in option prices. Our econometric method avoids direct specification of the objective conditional return distributions, which are instead obtained by...
Persistent link: https://www.econbiz.de/10015333127
We propose a Bayesian infinite hidden Markov model to estimate time- varying parameters in a vector autoregressive model. The Markov structure allows for heterogeneity over time while accounting for state-persistence. By modelling the transition distribution as a Dirichlet process mixture model,...
Persistent link: https://www.econbiz.de/10011569148