A new approach to leveraging neural networks to value financial derivatives is suggested. Rather than using neural networks to approximate a derivative's net present value (NPV) or sensitivities (risk) thereof as is commonly done in the literature, it is suggested to use them to approximate the...

As the year 2020 marks the 60th anniversary of the landmark paper in the Law & Economics (L&E) field by Ronald Coase – The Problem of Social Cost – we provide a systematic bibliometric analysis of the development of this field over the years. We look at the output and input side of knowledge...

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation...

Responding to the growing importance of economic reasoning in legal scholarship, this innovative work provides an essential introduction to the economic tools which can usefully be employed in legal reasoning. It is geared specifically towards those without a great deal of exposure to economic...

Academia faces a challenge, as activism replaces inquiry as the primary goal of the university. In particular, the growing dominance of activist academics, who explicitly reject objective inquiry, has started and will continue to constrain what information researchers can report and what ideas...