pricing kernel with all underlying risk factors, we decompose the expected stock return into four risk premiums related to the …

This paper examines the extent to which idiosyncratic risk measures explain cross-sectional differences in hedge fund … momentum effects. Idiosyncratic risk is a powerful factor in explaining the cross-sectional variation in hedge fund returns …

We investigate the relationship between hybrid tail covariance risk (HTCR) and expected return over the last four …

We forecast portfolio risk for managing dynamic tail risk protection strategies, based on extreme value theory … for Expected Shortfall, we propose a novel Expected Shortfall (and Value-at-Risk) forecast combination approach, which … the portfolio return distribution. While the associated dynamic risk targeting or portfolio insurance strategies provide …

multiplier bootstrap procedure for estimating the quantiles of the joint distribution of the likelihood ratio statistics, and for … adjusting the confidence level for multiplicity. Theoretical results state the bootstrap validity in the following setting: the …' misspecification is significant, then the bootstrap critical values exceed the true ones and the simultaneous bootstrap confidence set …

iteration. We then extend the NPL estimators to develop one-step NPL bootstrap procedures for discrete Markov decision models … and provide some Monte Carlo evidence based on a machine replacement model of Rust (1987). The proposed one-step bootstrap … expansion ; k-step bootstrap ; maximum pseudo-likelihood estimators ; nested fixed point algorithm ; Newton-Raphson method …

This article provides an introduction to methods and challenges underlying application of the bootstrap in econometric … modelling of economic and financial time series. Validity, or asymptotic validity, of the bootstrap is discussed as this is a … key element in deciding whether the bootstrap is applicable in empirical contexts. That is, as detailed here, bootstrap …

This paper proposes a new bootstrap procedure for mean squared errors of robust smallarea estimators. We formally prove … the asymptotic validity of the proposed bootstrap method and examine its finite sample performance through Monte Carlo … estimation of the total volume and value of cash, debit card and credit card transactions in Canada as well as in its provinces …

bootstrap, in the case of inequality indices. To estimate the parameters of the assumed parametric data generating distribution … inequality index. Its primary advantage is that the scale parameter does not need to be estimated to perform parametric bootstrap … suggest that this feature provides an advantage over the parametric bootstrap using the maximum likelihood estimator. We also …