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This paper provides a comprehensive analysis of the nonlinear properties of multifactor pricing models. Beginning with the generalized geometric Brownian motion, we develop a method whereby the log returns of a set of d-assets or portfolios admit a scale mixture model. This is followed by an...
Persistent link: https://www.econbiz.de/10009444682
heteroskedasticity) in latent class models. Our modelling approach compares two different representations of heteroskedasticity …
Persistent link: https://www.econbiz.de/10010879096
and heteroskedasticity. We propose a Two-Step Nonlinear Least Square estimator that satisfactorily deals with both …
Persistent link: https://www.econbiz.de/10010916663
Quantifying the relationship between expenditure for a commodity and household income (Engel analysis) has focused on the use of classical functional forms with few rigorous procedures available for selecting the most appropriate function We employ flexible functional forms {Box-Cox curves} to...
Persistent link: https://www.econbiz.de/10010919581
, non-normality, skewness, heteroskedasticity, autocorrelation. …
Persistent link: https://www.econbiz.de/10005460298
In structural vector autoregressive analysis identifying the shocks of interest via heteroskedasticity has become a … standard tool. Unfortunately, the approaches currently used for modelling heteroskedasticity all have drawbacks. For instance … used conventional identification schemes in this context are rejected by the data if heteroskedasticity is allowed for …
Persistent link: https://www.econbiz.de/10010361372
mechanism and multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models. Using changes in volatility …
Persistent link: https://www.econbiz.de/10010233639
mechanism and multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models. Using changes in volatility …
Persistent link: https://www.econbiz.de/10010233991
In structural vector autoregressive analysis identifying the shocks of interest via heteroskedasticity has become a … standard tool. Unfortunately, the approaches currently used for modelling heteroskedasticity all have drawbacks. For instance … used conventional identification schemes in this context are rejected by the data if heteroskedasticity is allowed for …
Persistent link: https://www.econbiz.de/10010364697
panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error … heteroskedasticity of unknown form in the idiosyncratic error component. Finally, we derive a robust Hausman-test of the spatial random …
Persistent link: https://www.econbiz.de/10010367382