There is a growing literature on the realized volatility (RV) forecasting of asset returns using high-frequency data. We explore the possibility of forecasting RV with factor analysis; once considering the significant jumps. A real high-frequency financial data application suggests that the...

This paper develops new model selection criteria for regression with heteroskedastic and autocorrelated errors. We prove the selection consistency of the introduced criteria and evaluate their performance by simulation. The results suggest that the new criteria may bring significant improvement...

This paper proposes a model selection criterion for models defined by a set of moment conditions that are possibly nonsmooth and discontinuous. The model selection criterion is based on an asymptotically unbiased approximation of the Kullback–Leibler Information Criterion (KLIC), using the...

This paper suggests using a unit t-value criterion in imposing restrictions on lags to formulate a subset vector autoregressive (VAR) model for the purpose of point forecasts. Among any other alternative models nested to the initial VAR model, this less restrictive modeling strategy produces the...

Using a statistical methodology guided by a genetic algorithm, we select the best econometric model for explaining the severity of the 2008 crisis, with the main determinant being the percentage of bank claims on private sector over deposits in the year 2006.