Civil unrest is a powerful form of collective human dynamics, which has led to major transitions of societies in modern history. The study of collective human dynamics, including collective aggression, has been the focus of much discussion in the context of modeling and identification of...

Can textual analysis improve statistical prediction of risky geopolitical events? North Korea has been the most important source of geopolitical risk for South Korea due to the former's unpredictable and secretive military actions against the latter. We find that the tone of English language...

Momentum and Reversion have always been seen as independent of each other and never as a composite. This study explains how the two behaviors are not only connected but also get transformed into each other. This dynamics drives not only stock market systems but all natural systems. One reason...

It is a common understanding that bankruptcy is not a sudden occurrence for any organizations. Macro and micro economic studies have suggested numerous influential factors, which have substantial evidence toward firm's performance (Bekeris, 2012) and survivability (Nehrebecka & Dzik, 2013). With...

This paper conducts surveys that document CFO perspectives on corporate planning, corporate investment, capital structure, payout, and the goal of the firm. Current policy choices are compared to CFO survey data from two decades prior, which allows me to identify decision-making themes that are...

Nearly all nontrivial real-world systems are nonlinear dynamical systems. Chaos describes certain nonlinear dynamical systems that have a very sensitive dependence on initial conditions. Chaotic systems are always deterministic and may be very simple, yet they produce completely unpredictable...

In recent years, river floods in Sarawak River seemed to occur more frequently and had been causing more and more economic and social damages. One of the greatest deficiencies of the current flood management system for Sarawak River basin is its inadequate optimization of the existing structural...

Stock price prediction is a challenging task, but machine learning methods have recently been used successfully for this purpose. In this paper, we extract over 270 hand-crafted features (factors) inspired by technical and quantitative analysis and tested their validity on short-term mid-price...

This paper considers sampling proportional to expected size from a partly unknown distribution. The applied context is the exploration for undiscovered resources, like oil accumulations in different deposits, where the most promising deposits are likely to be drilled first, based on some...