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Realising the future: forecasting with high-frequency-based volatility (HEAVY...
This paper studies in some detail a class of high-frequency-based volatility (HEAVY) models. These models are direct models of daily asset return volatility based on realised... -
Bayesian quantile regression methods (replication data)
This paper is a study of the application of Bayesian exponentially tilted empirical likelihood to inference about quantile regressions. In the case of simple quantiles we show... -
Dating and forecasting turning points by Bayesian clustering with dynamic str...
The information contained in a large panel dataset is used to date historical turning points and to forecast future ones. We estimate groups of series with similar time series... -
Multivariate residual-based finite-sample tests for serial dependence and ARC...
In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR). We focus on tests for serial dependence and ARCH effects with... -
General-interest versus specialty journals: Using intellectual influence of e...
This paper demonstrates the potential problem in using existing economics journal rankings to evaluate the research productivity of scholars by constructing a new ranking of... -
Continuous-time models, realized volatilities, and testable distributional im...
We provide an empirical framework for assessing the distributional properties of daily speculative returns within the context of the continuous-time jump diffusion models...
