Access the full text.
Sign up today, get unlimited access with DeepDyve Pro!
a measure for the asymmetric response of the variance to positive and negative lagged returns based on the quantile autoregressive (QAR) parameter estimates as well as an estimator for the conditional ...
Abstract Variance estimation is central to many questions in finance and economics. Until now ex post variance estimation has been based on infill asymptotic assumptions that exploit high-frequency ...
estimation refers to inference concerning the parameters θ = (β, σ2, ϕ, τ2) of model (1), whilst prediction refers to inference concerning the realisation of the linear predictor. In MBGapp, estimation uses ...
. For a random sample {Xt}t=1T, one can define the threshold u as a high quantile of the sample.1 Assuming that the asymptotic characterization holds for the exceedances of u, I(Xt>u), an estimate of the extremal ...
confidence intervals for the unknown parameters β (studies [12, 13]). The t−statistic based approaches do not require at all estimation of limiting variances of estimators of interest. As discussed in [11–13 ...
, this assessment depends on the computational techniques used (e.g. sampling or optimization- based ) and end targets of the analysis (e.g. point estimates , set-valued estimates , or distribution-valued estimates ...
defined which require forecasting quantiles deep in the lower tail of the asset return distribution. Traditional parametric methods based on estimation of entire densities are mostly ill-suited ...
that forecast horizons were in fact 5, 12, 19 and 26 days. Submissions were required in a quantile - based format with 23 quantiles of each output measure at levels 0.01, 0.025, 0.05, 0.10, 0.15,…, 0.95, 0.975 ...
fide probability density, that is, it is non-negative and integrates to unity. Semiparametric density estimation methodologies lie in between parametric and nonparametric approaches, combining advantages ...
). Building on Edgeworth expansions for studentized statistics based on the pre‐averaged realized volatility estimator , we also propose confidence intervals for integrated volatility that incorporate ...
Access the full text.
Sign up today, get unlimited access with DeepDyve Pro!