The complexity of the world oil market has increased dramatically in recent years and new approaches are needed to understand, model, and forecast oil prices today. Many models have been explored and most of the papers and modeling projects referenced in this paper identify their own...

Bayesian inference requires an analyst to set priors. Setting the right prior is crucial for precise forecasts. This paper analyzes how optimal prior changes when an economy is hit by a recession. For this task, an autoregressive distributed lag model is chosen. The results show that a sharp...

This chapter describes the main impact evaluation methods, both experimental and quasi-experimental, and the statistical model underlying them. Some of the most important methodological advances to have recently been put forward in this field of research are presented. We focus not only on the...

As a unified discipline, econometrics is still relatively young and has been transforming and expanding very rapidly over the past few decades. Major advances have taken place in the analysis of cross sectional data by means of semi-parametric and non-parametric techniques. Heterogeneity of...

This paper attempts to introduce the uses of integrals in the Megasfinity Coordinate Space. The main objective of this paper is to present a new mathematical methodology to use for it. This is based on the application of integrals in different Dimensions levels (D) that there are interacting in...

e-Business development has become a key factor for the sustainable economic growth and development of any nation in this new era of digital revolution. This is a macro level study based on the hypothesis that the e-business development of a nation can be predicted on the basis of four...

We present a simple rational approximation to the solution of the rough Heston Riccati equation valid in a region of its domain relevant to option valuation. Pricing under rough Heston using this approximation is both fast and very accurate

We develop a fundamental law of active management based on cross-section factor models for residual returns where the latter have unconditional mean zero and the factor exposures have zero mean and unit variance. Under our model framework the factor returns are cross-sectional information...