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 ...

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 ...

The loudspeaker on your home entertainment equipment is designed to project audio around the space in which it operates, if it’s not omnidirectional as such it can feel that way as the surroundings ...

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.

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 ...

We all know and love OpenSCAD for its sweet sweet parametrical goodness. However, it’s possible to get some of that same goodness out of Fusion 360. To do this we will be making a mathematical model ...

Nonparametric estimation and U-statistics have emerged as vital tools in modern statistical analysis, offering robust alternatives to traditional parametric methods. Nonparametric techniques bypass ...

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 ...