This project showcases a spectrum of technical skills in a nontraditional actuarial setting. Many methods are known for analyzing and predicting movement in a financial market and quantifying risk. We seek to give similar treatment in the case of Spotify's Top Charts, where popularity "drives up" the ranking (price) of a given index (song). In particular, we draw special attention to Queen's "Bohemian Rhapsody". Put concisely, in all of Spotify's . . .
AbstractThe identification of factors that predict the cross-section of stock returns has been a focus of asset pricing theory for decades. We address this challenging problem for both equity performance and risk, the latter through the maximum drawdown measure. We test a variety of regression-based models used in the field of supervised learning including penalized linear regression, tree-based models, and neural networks. Using empirical data in the US market from . . .