Developing State-Based Recommendation Systems for Golf Training; Evaluating the Demand for Regulation of High-Frequency Trading
Jimenez, Orlando, School of Engineering and Applied Science, University of Virginia
Scherer, William, EN-Eng Sys and Environment, University of Virginia
Jacques, Richard, EN-Engineering and Society, University of Virginia
As scientists, engineers and technologists we have found the tools and technologies available around the world continue to rapidly evolve as our society advances toward a more data driven society all the while further enhancing our capabilities. The effects of these advances in tools and technologies over the past few decades have made sweeping changes in our society shaping entire industries and even created completely new ones. Within this portfolio both my Capstone Project and STS Research Paper share this commonality of being shaped by relatively recent technological advances in their respective industries. Although the Capstone Project and STS Research are loosely coupled being based on entirely different topics both are subjects of interest on how technology has been applied in their respective industries.
The Capstone Project was a collaborative effort between the UVA Systems and Information Engineering Department and GameForge, an up-and-coming golf analytics company looking to bring analytics to the forefront of the golf industry. Utilizing PGA and LPGA Tour data collected by GameForge we embarked on developing a data-driven recommendation system based on statistical analysis and empirical research which would enable users with data to better equip them with the knowledge to make informed decisions to augment their practice regime to increase performance. By first determining the statistical relationships between these datasets we were able to develop a framework capable of modeling these relationships that GameForge can use in the future despite the limitations of the current data. Overcoming the limitations of the data in the future with more robust data will help identify the more noteworthy relationships and factors that rest within the dataset. Secondly, we were able to identify the factors which significantly contributed to the improvement or decline in performance amongst the world’s top professional male and female players. Understanding the statistical inferences gained from this research will aid GameForge in creating a recommendation system for both professional and recreational golf players alike looking to improve performance. Finally, the process, results and insights derived from these methodologies and processes are described within the Technical Report.
The topic of my STS Research Paper is based on the impact of high frequency trading and evaluating the need for regulation. Computer algorithms are playing an ever more important role within our society and even more so within our financial markets. With the electronification of the financial markets long gone are the days of trading pits of the past. Machines and algorithms are now left to facilitate majority of the market transactions with significantly less interaction between people all within fractions of a second. Enormous investments have been made in creating high frequency technology and optimizing transmission technologies all in an effort to cut milliseconds to reduce latency or order travel time and increase profits. With the rise of high frequency trading over the past 20 years while providing benefits to the market microstructure it also has been a target of controversy. My focus of this STS research is to elucidate on the technology and help explore the benefits and detriments of this technology from a sociotechnical perspective using an actor-network framework in considering the need for further regulation. Ultimately, the goal of my STS work is to shed light on the current impacts this technology has on the markets and its participants while discussing potential recommendations of how social and technological efforts can be made to curb the negative impacts of this technology that are sustainable for the industry.
While working simultaneously on my STS Research Paper and Capstone Project, as an engineer I gained a deeper insight not only into how the systems approach to problem solving can lead to innovation and deeper understanding of a system but also the awareness of the responsibility engineers must assume when developing technology and the broader implications they have on society. Partnering with GameForge provided an invaluable educational and hands-on experience to learn about an industry while trying to innovate within a sport steeped in elitist and old-fashioned traditions. On the other hand, my STS research provided a means to better understand the discussion on how high frequency technology impacts actors within its network and the role this particular technology plays within industry and society as a whole through the STS framework. Working concurrently on both the STS Research Paper and Capstone Project provided the opportunity as an engineer to further enhance my understanding and practice of systems thinking and STS frameworks in a manner I wouldn’t have otherwise thought of before.
BS (Bachelor of Science)
Markov Model, Golf, HFT, Finance
School of Engineering and Applied Science
Bachelor of Science in Systems and Information Engineering
Technical Advisor: William Scherer
STS Advisor: Richard Jacques
Technical Team Members: Alanna Flores, Christopher Kaylor, Kelly Rohrer, Jacob Ziller