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Articles 1 - 5 of 5
Full-Text Articles in Business
Spotify: You Have A Hit!, Christopher E. Dawson Jr., Steve Mann, Edward Roske, Gauthier Vasseur
Spotify: You Have A Hit!, Christopher E. Dawson Jr., Steve Mann, Edward Roske, Gauthier Vasseur
SMU Data Science Review
Abstract. Over 87% of the streaming music is owned by four major record labels (Jones, 2018). Yet, the songs owned by those labels account for <1% of the total amount of music created each year. These labels are historically better at identifying talent (though this talent identification is becoming more difficult). Even though Spotify has 36% of the streaming marketing share (T4, 2021), Spotify has not been profitable because of the large licensing costs paid to the large music labels. If Spotify could identify hit songs & artists before the large labels, they would sign those artists and dramatically reduce their licensing costs. Using the Spotify API, this paper will use Spotify data on over 400K songs over the last three years for exploratory data analysis, provide descriptive statistics, perform feature selection, and develop models using LASSO and XGBOOST Classification. The research determined multiple key features and predicted with over 60% accuracy songs which were going to be a hit (defined as >90% popularity).
Regulating New Tech: Problems, Pathways, And People, Cary Coglianese
Regulating New Tech: Problems, Pathways, And People, Cary Coglianese
All Faculty Scholarship
New technologies bring with them many promises, but also a series of new problems. Even though these problems are new, they are not unlike the types of problems that regulators have long addressed in other contexts. The lessons from regulation in the past can thus guide regulatory efforts today. Regulators must focus on understanding the problems they seek to address and the causal pathways that lead to these problems. Then they must undertake efforts to shape the behavior of those in industry so that private sector managers focus on their technologies’ problems and take actions to interrupt the causal pathways. …
Stock Trend Prediction Using Candlestick Charting And Ensemble Machine Learning Techniques With A Novelty Feature Engineering Scheme, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu
Stock Trend Prediction Using Candlestick Charting And Ensemble Machine Learning Techniques With A Novelty Feature Engineering Scheme, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu
Information Technology & Decision Sciences Faculty Publications
Stock market forecasting is a knotty challenging task due to the highly noisy, nonparametric, complex and chaotic nature of the stock price time series. With a simple eight-trigram feature engineering scheme of the inter-day candlestick patterns, we construct a novel ensemble machine learning framework for daily stock pattern prediction, combining traditional candlestick charting with the latest artificial intelligence methods. Several machine learning techniques, including deep learning methods, are applied to stock data to predict the direction of the closing price. This framework can give a suitable machine learning prediction method for each pattern based on the trained results. The investment …
An Ant-Based Intelligent Design For Future Self-Driving Commercial Car Service Strategy, Jian Denny Lin, Naveed Saleem, Vance Allen Etnyre, Gokhan Gercek, Nanfei Sun
An Ant-Based Intelligent Design For Future Self-Driving Commercial Car Service Strategy, Jian Denny Lin, Naveed Saleem, Vance Allen Etnyre, Gokhan Gercek, Nanfei Sun
Journal of International Technology and Information Management
The technology of self-driving cars will inevitably change the industry of taxis and ride-sharing cars that provide important commercial ground transportation services to travelers, tourists and local residents. There is no doubt that new techniques, business models and strategies will be needed to follow the use of self-driving cars. This paper focuses on a forward-looking research topic that route commercial, vacant self-driving vehicles so that the values to both businesses and passengers are improved. Importance of solutions to the new problem is discussed. We also propose a novel design which simulates behaviors of ants in nature to the vehicles. The …
Deterring Algorithmic Manipulation, Gina-Gail S. Fletcher
Deterring Algorithmic Manipulation, Gina-Gail S. Fletcher
Faculty Scholarship
Does the existing anti-manipulation framework effectively deter algorithmic manipulation? With the dual increase of algorithmic trading and the occurrence of “mini-flash crashes” in the market linked to manipulation, this question has become more pressing in recent years. In the past thirty years, the financial markets have undergone a sea change as technological advancements and innovations have fundamentally altered the structure and operation of the markets. Key to this change is the introduction and dominance of trading algorithms. Whereas initial algorithmic trading relied on preset electronic instructions to execute trading strategies, new technology is introducing artificially intelligent (“AI”) trading algorithms that …