Rauterberg & Talley (2017) develop a data set of “corporate opportunity waivers” (COWs) — significant contractual modifications of fiduciary duties — sampled from SEC filings. Part of their analysis utilizes a machine learning (ML) classifier to extend their data set beyond the...

Die Informationsflut, die dem Entscheidungsträger im Internet aber auch in internen Quellen begegnet, lässt sich nur schwer bewältigen, Daher ist die verfügbare Menge der Informationen zunächst in interessante und uninteressante Informationen zu unterteilen. Dem Entscheidungsträger sind...

We have analyzed the risks of possible development of bubbles in Switzerland's residential real estate market. The data employed in this work has been collected by comparis.ch, and carefully cleaned from duplicate records through a procedure based on supervised machine learning methods. The...

In recent years, the government, of African Countries has assumed major responsibilities for economic reforms and growth. In attempting to describe their economies, economists (policymakers) in many African Countries have applied certain models that are by now widely known: Linear programming...

In the real world, the theory of economic faces many obstacles in its analyses and interpretations. One of these problems is overlapping relationships between specific variables and difficulty of determining perfect formulation which contain all possible effect. Traditional statistics tools like...

Energy companies with commitments to meet customers' daily electricity demands face the problem of hedging load and price risk. We propose a joint model for load and price dynamics, which is motivated by the goal of facilitating optimal hedging decisions, while also intuitively capturing the key...

We address the inverse problem of local volatility surface calibration from market given option prices. We integrate the ever-increasing ow of option price information into the well-accepted local volatility model of Dupire. This leads to considering both the local volatility surfaces and their...

A new method to construct a distributed, highly scalable and computationally efficient block chain is proposed. The primary focus is on designing a network that can scale efficiently to any number of nodes and add blocks at a very high rate, while still ensuring that the information stored in...