This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most...

This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most...

The paper examines the relative performance of Stochastic Volatility (SV) and Generalised Autoregressive Conditional Heteroscedasticity (GARCH) (1,1) models fitted to ten years of daily data for FTSE. As a benchmark, we used the realized volatility (RV) of FTSE sampled at 5 min intervals taken...

We develop theory of a novel fast bootstrap for dependent data. Our scheme deploys i.i.d. resampling of smoothed moment indicators. We characterize the class of parametric and semiparametric estimation problems for which the method is valid. We show the asymptotic re refinements of the new...

A time series model is discussed that incorporates both permanent and transient effects. Estimation techniques are given, and the power of the likelihood ratio test is assessed. When applied to the monthly price/earnings series of the S&P 500 over the period 1871-2013, both permanent and...

The contingency table literature on tests for dependence among discrete multi-category variables is extensive. Existing tests assume, however, that draws are independent, and there are no tests that account for serial dependencies -- a problem that is particularly important in economics and...

In a factor-augmented regression, the forecast of a variable depends on a few factors estimated from a large number of predictors. But how does one determine the appropriate number of factors relevant for such a regression? Existing work has focused on criteria that can consistently estimate the...

We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. We investigate the relative performance of VaR and ES models using daily returns for sixteen stock market indices (eight from developed and eight...

This paper presents new econometric specifications for the Brazilian exports in the period 1995-2009 using data from the Quarterly Accounts and allowing for nonlinearities. In the cointegrating vector, there is evidence of a level shift, but the elasticities have not changed significantly. The...

The HP filter is the most popular filter for extracting the trend and cycle components from an observed time series. Many researchers consider the smoothing parameter e͏̈ = 1600 as something like an universal constant. It is well known that the HP filter is an optimal filter under some...