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 ...

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 ...

Nonparametric methods form an important core of statistical techniques and are typically used when data do not meet parametric assumptions. Understanding the foundation of these methods, as well as ...

Summary 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 ...

Quantiles underpin widely used tools in finance, insurance, and economic inequality—yet building statistical inference for quantiles can be challenging because empirical quantiles are order statistics ...

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.

This is a preview. Log in through your library . Abstract In this paper Pitman's method of constructing and comparing tests based on statistics which are asymptotically normal under the null ...

Explain why and when a non-parametric test should be used or may be preferred for simple comparison over a parametric method Explain the general principles and process of performing a non-parametric ...