1 - 7 of 7 articles
We study a new class of conditional skewness models based on conditional quantiles regressions. The approach is much inspired by work of Hal White. To handle multiple horizons I consider quantile MIDAS regressions which amount to direct forecastingas opposed to iterated forecastingconditional...
This article develops an econometric framework to investigate the structure of dependence between random variables and to test whether it changes over time. Our approach is based on the computation—over both a test and a benchmark period—of the conditional probability that a random variable is...
The main contribution of this article is to propose bootstrap methods for realized volatility-like estimators defined on pre-averaged returns. In particular, we focus on the pre-averaged realized volatility estimator proposed by Podolskij and Vetter (2009). This statistic can be written (up to a...
A well-documented empirical result is that market expectations extracted from futures contracts on the federal funds rate are among the best predictors for the future course of monetary policy. We show how this information can be exploited to produce accurate forecasts of bond excess returns and...
We propose a stepwise test, Step-SPA(k), for multiple inequalities testing. This test is analogous to the Step-SPA test of Hsu, Hsu, and Kuan (2010, J. Empirical Econ., 17, 471484) but has asymptotic control of a generalized familywise error rate: the probability of at least k false rejections....
Read and print from thousands of top scholarly journals.
Continue with Facebook
Log in with Microsoft
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Sign Up Log In
To subscribe to email alerts, please log in first, or sign up for a DeepDyve account if you don’t already have one.
To get new article updates from a journal on your personalized homepage, please log in first, or sign up for a DeepDyve account if you don’t already have one.