The first ever explicit formulation of the concept of the option's probability density functions has been introduced in our publications “Breakthrough in Understanding Derivatives and Option Based Hedging - Marginal and Joint Probability Density Functions of Vanilla Options - True...

The study empirically examines the causes of poor academic performance of the students in the native area, Ward 6, enrolled at Gokomere High School, Matova Secondary School, St Stanslous Secondary School and Chidzikwe Secondary School using Ordinary Least Squares approach for a sample of 200...

This is a course material for an introductory course in Probability and Statistics for Engineering and Management. It is part of some course notes for my courses in Spanish on that subject. The draft of the book is Apuntes de Probabilidad y Estadiacute;stica para Ingenieriacute;a y...

• It is not widely emphasized in the literature that derivatives are complex random quantities which should, by custom, be characterized by their probability density functions. • It is understood that Black-Scholes style of derivatives pricing represents an expected value, i.e. the...

This paper proves that the mean independence of the error term from the covariates in a linear regression model is equivalent to, rather than just a sufficient condition for, the error term being uncorrelated with any function of the covariates. Therefore, correct functional form specification...

In 1959, Ragnar Frisch prompted Georg Rasch to formalise a separability theorem that continues today to serve as the basis of a wide range of theoretical and applied developments in psychological and social measurement. Previously unnoted are the influences on Rasch exerted by Frisch’s...

There are many economic parameters that depend on nonparametric first steps. Examples include games, dynamic discrete choice, average exact consumer surplus, and treatment effects. Often estimators of these parameters are asymptotically equivalent to a sample average of an object referred to as...

High breakdown-point regression estimators protect against large errors and data contamination. We adapt and generalize the concept of trimming used by many of these robust estimators so that it can be employed in the context of the generalized method of moments. The proposed generalized method...

In the present paper we propose a new method, the Penalized Adaptive Method (PAM), for a data driven detection of structure changes in sparse linear models. The method is able to allocate the longest homogeneous intervals over the data sample and simultaneously choose the most proper variables...