Realizing Sustainability

The fall COMPAS conference explored the value trade-offs that are involved in pursuing competing visions of a sustainable future. The spring COMPAS conference takes a turn toward the practical: the challenge of realizing sustainability. Who bears responsibility for this challenge and how can we motivate the necessary shifts in public policy and personal behavior? If the Paris meetings represent a moment, as President Obama has stated, when "nations embrace their responsibility to assure a world worthy of our children," what policy implications follow from that change in moral viewpoint? The conference will bring together an interdisciplinary group of experts from communications, decision sciences, economics, law, philosophy, and political science, among other fields, to address these issues.Ohio State University. Mershon Center for International Security StudiesEvent web page, Event photo

Neural networks for estimating Macro Asset Pricing model in football clubs

The recent crisis caused by COVID-19 directly affected consumption habits and thestability sof financial markets. In particular, the football industry has been hit hard bythis pandemic and therefore has more volatile stock prices. Given this new scenario,further research is needed to accurately estimate the value of the shares of footballclubs. In this paper, we estimate an asset pricing model in football clubs with differentcompositions of risk nature using non-linear techniques of artificial neural networks.Usually, asset pricing models have been estimated with linear methods such as ordi-nary least squares (...

Forecasting Stock Market Crashes via Real-Time Recession Probabilities: A Quantum Computing Approach

A fast and precise prediction of stock market crashes is an important aspect of economic growth, fiscal and monetary system because it facilitates the government the application of suitable policies. Many works have examined the behaviour of the fall of stock markets and have built models to predict them. Nevertheless, there are limitations to the available research, and the literature calls for more investigation on the topic, as currently the accuracy of the models remains low and they have only been extended for the largest economies. This study provides a comparison of Quantum forecast methods stock market declines and, therefore, a new prediction model of stock market crashes via real-time recession probabilities with the power to accurately estimate future global stock market downturn scenarios. A 104-country sample has been used, allowing the sample compositions to take into account the regional diversity of the alert warning indicators. To obtain a robust model, several alternative techniques have been employed on the sample under study, being Quantum Boltzmann Machines, which have obtained very good prediction results due to their ability to remember features and develop long-term dependencies from time series and sequential data. Our model has large policy implications for the appropriate macroeconomic policy response to downside risks, offering tools to help achieve financial stability at the international level

Quantum Monte Carlo simulations for estimating FOREX markets: A speculative attacks experience

The foreign exchange markets, renowned as the largest financial markets globally, also stand out as one of the most intricate due to their substantial volatility, nonlinearity, and irregular nature. Owing to these challenging attributes, various research endeavors have been undertaken to effectively forecast future currency prices in foreign exchange with precision. The studies performed have built models utilizing statistical methods, being the Monte Carlo algorithm the most popular. In this study, we propose to apply Auxiliary-Field Quantum Monte Carlo to increase the precision of the FOREX markets models from different sample sizes to test simulations in different stress contexts. Our findings reveal that the implementation of Auxiliary-Field Quantum Monte Carlo significantly enhances the accuracy of these models, as evidenced by the minimal error and consistent estimations achieved in the FOREX market. This research holds valuable implications for both the general public and financial institutions, empowering them to effectively anticipate significant volatility in exchange rate trends and the associated risks. These insights provide crucial guidance for future decision-making processes

Testing the Waters: A Demonstration of a Novel Water Quality Mapping System for Citizen Science Groups

Citizen science initiatives are increasingly using new devices, smartphone apps, and interactive websites to improve data quality and collection procedures, better visualize trends and changes, and increase volunteer engagement and retention. This methods paper reports on the development and demonstration of a prototype water quality instrument array and website to modernize volunteer water quality sampling. Using open source software and off-the-shelf components, our device measures GPS location, dissolved oxygen, temperature, conductivity, and pH at a high sampling rate. Combined with a smartphone app and website, the system provides real-time maps and visualization of water quality data. We demonstrated the device on an 11-day public expedition called “Testing the Waters: A Paddle and Probe Adventure” down the Rock River in Wisconsin. The event was successful in collecting 30,000 GPS-tagged water samples across 324 km providing a unique profile of the river’s water, identifying potential water quality issues, and establishing a baseline for comparison. Through the project and additional volunteer feedback, we learned lessons about a broader-scale adoption including: 1) need to simplify setup and calibration; 2) need for further development of online tools to better communicate with a non-technical audience; and 3) need for a flexible device that works in a variety of situations, e.g., static deployment. The pilot demonstrated the potential of new technology and a low-cost device to expand the types and amount of water quality data collected by citizen monitors