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Full-Text Articles in Business
Investigation Into A Practical Application Of Reinforcement Learning For The Stock Market, Philip Traxler, Sadik Aman, Will Rogers, Allyn Okun
Investigation Into A Practical Application Of Reinforcement Learning For The Stock Market, Philip Traxler, Sadik Aman, Will Rogers, Allyn Okun
SMU Data Science Review
A major problem of the financial industry is the ability to adapt their trading strategies at the same rate the market evolves. This paper proposes a solution using existing Reinforcement Learning libraries to help find new strategies at a practical scale. Using a wide domain of ticker symbols, an algorithm is trained in an environment that better represents reality. The supplied decision-making algorithm is tested using recorded data from the U.S stock market from 2000 through 2022. The results of this research show that existing techniques are statistically better than making decisions at random. With this result, this research shows …
Application Of Business Analytics Approaches To Address Climate-Change-Related Challenges, Donald J. Jenkins
Application Of Business Analytics Approaches To Address Climate-Change-Related Challenges, Donald J. Jenkins
Graduate Doctoral Dissertations
Climate change is an existential threat facing humanity, civilization, and the natural world. It poses many multi-layered challenges that call for enhanced data-driven decision support methods to help inform society of ways to address the deep uncertainty and incomplete knowledge on climate change issues. This research primarily aims to apply management, decision, information, and data science theories and techniques to propose, build, and evaluate novel data-driven methodologies to improve understanding of climate-change-related challenges. Given that we pursue this work in the College of Management, each essay applies one or more of the three distinct business analytics approaches (i.e., descriptive, prescriptive, …
A Probabilistic Exploration Of Food Supplementation And Assistance, Logan Mattingly
A Probabilistic Exploration Of Food Supplementation And Assistance, Logan Mattingly
Honors College Theses
Food insecurity is a stark threat that grips our country and affects households throughout our country. Dietary insufficiency manifests itself in ways that affect health and public safety. According to researchers, individuals who suffer from food insecurity have a higher risk of aggression, anxiety, suicide ideation and depression. These problems tend to occur unequally distributed among those households with lower income. In this work, an exploratory analysis within these data sets will be performed to examine the socio-economic, biographical, nutritional, and geographical principal components of food insecurity among survey participants and how the US Supplemental Nutrition Assistance Program (SNAP) effects …
Bridging The Chasm Between Fundamental, Momentum, And Quantitative Investing, Allen Hoskins, Jeff Reed, Robert Slater
Bridging The Chasm Between Fundamental, Momentum, And Quantitative Investing, Allen Hoskins, Jeff Reed, Robert Slater
SMU Data Science Review
A chasm exists between the active public equity investment management industry's fundamental, momentum, and quantitative styles. In this study, the researchers explore ways to bridge this gap by leveraging domain knowledge, fundamental analysis, momentum, crowdsourcing, and data science methods. This research also seeks to test the developed tools and strategies during the volatile time period of 2020 and 2021.