This short course will provide an overview of non-parametric statistical techniques. The course will first describe what non-parametric statistics are, when they should be used, and their advantages ...

Mitchell Grant is a self-taught investor with over 5 years of experience as a financial trader. He is a financial content strategist and creative content editor. Timothy Li is a consultant, accountant ...

We provide novel, high-order accurate methods for non-parametric inference on quantile differences between two populations in both unconditional and conditional settings. These quantile differences ...

We use influence functions as a basic tool to study unconditional nonparametric and parametric expected shortfall (ES) estimators with regard to returns data influence, standard errors and coherence.

Value-at-risk (VaR) is one of the most common risk measures used in finance. The correct estimation of VaR is essential for any financial institution, in order to arrive at the accurate capital ...

Abstract: Streamflow disaggregation techniques are used to distribute a single aggregate flow value to multiple sites in both space and time while preserving distributional statistics (i.e., mean, ...

The purpose of this paper is to compare in-sample and out-of-sample performances of three parametric and non-parametric early warning systems (EWS) for currency crises in emerging market economies ...

Journal of the Royal Statistical Society. Series A (Statistics in Society), Vol. 181, No. 3 (2018), pp. 635-647 (13 pages) Statistical agencies are increasingly adopting synthetic data methods for ...